Article

Impact of urbanization and land-use/land-cover change on diurnal temperature range: A case study of tropical urban airshed of India using remote sensing data

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... Many studies have disclosed that urban expansion and the UGS change of the city are governed by a combination of geographical, environmental and socio-economic factors [3,85,86]. Rapid economic development is the primary cause for rapid urbanization, as economic opportunities in the city fuel rural to urban migration on a massive scale [87]. This process is similar to those that have occurred in Ho Chi Minh [86], Dhaka [3,86], Delhi [87], Hanoi and Anson [88]. ...
... Rapid economic development is the primary cause for rapid urbanization, as economic opportunities in the city fuel rural to urban migration on a massive scale [87]. This process is similar to those that have occurred in Ho Chi Minh [86], Dhaka [3,86], Delhi [87], Hanoi and Anson [88]. ...
... Although the forest area has barely changed, the number and density of its patches increased. This shows that the relatively natural state was intensively interfered with by human activities and then changed into an artificial form, as many developing cities did [3,[85][86][87][88]. The fluctuating tendency of the UGS patch shapes was evidently influenced by the changing awareness of local government regarding the priority of balance between economic development and environmental protection. ...
Article
Full-text available
Rapid urbanization and population growth impact enormous pressures on urban natural, economic and social environments. The quantitative analysis of urban green space (UGS) landscape dynamics and their impact on the urban eco-environment is of great significance for urban planning and eco-environment protection. Taking Shenzhen as an example, the UGS landscape changes and their impact on urban heat islands (UHI), surface wetness, air pollution and carbon storage were comprehensively investigated with Landsat and MODIS images. Results showed a large number of lands transferring from UGS to non-UGS from 1978 to 2018, especially for cropland. Built-up regions have adverse influences on eco-environment factors, and then they suffer high SUHI and AOD and low humidity and carbon storage. The growth of built-up areas not only enlarges the area of SUHI, but also enhances the intensity of heat islands. On the contrary, UGS patches have beneficial influences on all eco-environment factors and then enjoy a better eco-environment, including low SUHII, high surface wetness, high carbon storage and low AOD. It is expected that this study could provide scientific support for UGS plans and for conserving and sustainable urban development for developing cities.
... Along with population growth and economic prosperity, urbanization also led to considerable changes in the local environment . Rapid land use land cover (LULC) transformation are considered key elements of such changes (Mohan and Kandya 2015;Gumma et al. 2017;Liou et al. 2017;Sannigrahi et al. 2020). It steered several accompanying effects like air pollution (Chowdhury et al. 2019), soil pollution (Hu et al. 2013), urban heat island (UHI) (Shastri et al. 2017), modification of bio-geochemical cycle (Seto et al. 2013) and local and regional climate changes (Grimm et al. 2008). ...
... Several studies (Sannigrahi et al. 2018;Chakraborti et al. 2019;Punia 2019a, 2019b) have used LST to capturing the UHI. But, as most Indian cities experienced negative UHI during the day and positive UHI during the night (Shastri et al. 2017); thus DTR could be the best option for capturing the UHI effects for Indian cities (Mohan and Kandya 2015). However, the spatial resolution issues of selective variables (i.e. ...
Article
Full-text available
Rapid urbanization is often responsible for the degradation of urban eco-environmental quality (UEQ), which comprised of ecological, environmental, and anthropogenic components. Hence, frequently monitoring and tracking UEQ for sustainable cities and communities is recommendable. The present study, attempted to compare UEQ of three rapidly growing Indian metros/megacities – Ahmedabad, Hyderabad, and Bangalore. A remote sensing-based composite index, namely ‘urban eco-environmental quality index (UEQI), was constructed by utilizing Landsat 5 (TM), 8 (OLI-TIRS) satellite imageries, and MODIS LST products of 1999/2000-01 and 2018. Five vegetation indices (i.e., NDVI, SAVI, GVI, NDMI, and TcWet) and four urban indices (i.e., BI, NDBI, UI, and DTR) were categorized as per pressure-state- response (PSR) framework and integrated through spatial principal component analysis (SPCA) for constructing the UEQI. The sensitivity and elasticity of UEQI had been tested with respect to population density (PD) and the percentage of impervious surface (IS). Subsequently, the spatio-temporal pattern (i.e., (non)sequential transition – from excellent to very poor) and spatial heterogeneity of UEQ were investigated using Moran’s I, and local indicator of spatial auto-correlation (LISA). Result indicated overall UEQI value for selected cities during studied periods ranged from 0.20 to 2.20, where lower and higher value referred very poor and excellent UEQ, respectively. The most degraded UEQ was found in Bangalore (average UEQI values were 1.08 and 0.80 in 2001 and 2019, respectively); and, the degradation rate was also quite inflated than other cities (i.e., UEQI 1.64 per year). Additionally, the spatio-temporal pattern of UEQI demonstrated that very poor and poor UEQ were primarily clustered in the city’s center and spilling out toward the outskirts of all cities during the studied period. The proportional area under very poor UEQ category was 7.94%, 7.03% and 5.24% for Bangalore, Ahmedabad and Hyderabad, respectively. The non-sequential transition (i.e., excellent to poor or very poor) was prominent in Bangalore, which implied that rapid and abrupt degradation of UEQ. Whereas, Ahmedabad and Hyderabad followed mostly sequential transition. Besides, significant global (Moran’s I = >0.80) and LISA confirmed the non-randomness pattern of UEQ for three cities. The analysis of sensitivity ensured both PD and IS were strongly influenced poor UEQI (as R2 ≥ 0.50). Elasticity of UEQI revealed 1% increase of IS would lead to declining of 0.64%, 0.46%, and 0.21% of UEQI in Ahmedabad, Hyderabad, and Bangalore, respectively. Moreover, the study's observation and findings could also be used for possible area intervention for ‘area-based development’ and ‘greenfield development’ plan, as recommended by ‘climate-resilient smart city mission’.
... Micrometeorological observations, remote sensing data analysis, and improved LULC classification are few of the methods adopted for analyzing surface and canopy layer UHI impacts on Indian cities (Mohan et al., 2012;Ramachandra & Kumar, 2010;Mohan et al., 2011;Pandey et al., 2012;Mohan et al., 2013;Mallick et al., 2013;Borbora & Das, 2014;Thomas et al., 2014;Mohan & Kandya, 2015;Joshi et al., 2015;Kikon et al.;Mathew et al., 2016;Kotharkar & Surawar, 2016;Singh et al., 2017;Mathew et al., 2018;Kotharkar & Bagade, 2018). Dimri (2019) well-documented the regional changes in daily surface temperature extremes over India. ...
... The National Capital Region (NCR) is more extensively studied than other regions in India. Professor Manju Mohan and her research group (at Indian Institute of Technology, Delhi) carefully observed the diurnal temperature range, LULC specific UHI, and temperature trends using in situ as well as satellite observations (Mohan et al., 2011;Mohan et al., 2012;Mohan et al., 2013;Mohan & Kandya, 2015). Pandey et al. (2012) studied the association of particulate matter with UHI over Delhi. ...
Chapter
Urban transition is an unstoppable process. Globally, several planning measures are taken by the city and country administration to control the sprawling process. Despite all the planning, most of the cities experience appreciable impact of urbanization on the localized weather parameters. This chapter summarizes the understanding relating to urban modification of localized weather, that is, changes in precipitation, temperature, and wind speed in the form of increase or decrease, their spatio-temportal distribution, urban heat island (UHI), and urban wind island (UWI). The impacts of the urbanization are primarily because of changes in land-surface characteristics due to the alteration of land use in a city. The urbanization effects on local or mesoscale weather could be studied both through observations and/or numerical modeling. The purpose of this chapter is to provide a review of most of the relevant studies carried out globally and with a special emphasis on India.
... Most of the above studies investigated the LULC change impact on the climate at decadal to multidecadal scales over different regions. However, studies on the impact of LULC changes over Indian regions are limited (Niyogi et al. 2011, Mohan & Kandya 2015, Unnikrishnan et al. 2016, Gogoi et al. 2019. Nayak & Mandal (2012) documented that LULC changes contributed towards warming over western regions of India by ~0.06°C decade −1 . ...
... Several other studies also highlighted qualitatively similar warming and/or cooling characteristics over different regions of India (e.g. Mohan & Kandya 2015, Gogoi et al. 2019. ...
Article
The changes in land use and land cover (LULC) in recent decades are among the responsible factors for the recent climate changes. In this study, the impact of LULC changes on the climate over India was assessed through multi-decade simulations (3 decades) by using the Regional Climate Modeling system (RegCM4) with fixed and changed LULC. Difference between the two simulations was considered as the impact of LULC changes on the regional climate. The main focus was given on the decadal climatology of temperature, precipitation and other several important climatic variables including specific humidity, moisture content, sensible heat, evapotranspiration over Indian regions and their response to the LULC change. The study found a decreasing trend in annual precipitation and increasing trend in annual temperature over India during 1981-2010. The LULC changes over northwest, south peninsular and west central regions of India contributed towards warming during 1991-2010, while that over central north and north eastern regions resulted cooling during this period. The LULC change also indicated wet effect over south peninsular and west central regions of India and dry effect over northwest India in 1991-2010. The analysis indicated that the LULC changes resulted a decrease of evapotranspiration, moisture content and specific humidity that led to decreased precipitation. On the other hand, the changes in LULC resulted significant increase of sensible heat flux and albedo which led to the temperature rise. Our overall modeling results has an implication towards understanding the processes associated with LULC change feedback to the climate over Indian regions.
... Such changes influence the local climate due to the modifications in the interactive mechanism between the lower atmosphere and the land surface [13]. As mentioned before, many studies have highlighted the impacts of LULC change on the Indian climate [35][36][37], and it is noticed that the effect of the LULC change on the climate in terms of the temperature is not uniform over Indian regions. The LULC changes result in warming over Western India [38], Central India [39,40], and Northern India [41], while they result in cooling over Northwest India [42], Northeast India [41], and Eastern India [43]. ...
... For example, LULC changes over Northeastern Indian regions contribute to cooling [40,42], while those over Northern Indian regions contribute to warming [41]. The impacts of LULC changes over urban areas and non-urban areas are also not the same [35][36][37]40]. To examine such differences over Southern Indian regions, the OMR trends were analyzed over five different categories. ...
Article
Full-text available
This study performed a land use and land cover (LULC) change analysis over Southern India for the period 1981–2006 from the normalized difference vegetation index (NDVI) images of AVHRR data and applied the “observation minus reanalysis” (OMR) method to investigate the impact of the LULC change on the temperature of the region. The LULC change analysis indicated that the areas under agriculture/fallow land were significantly increased while the areas under shrubs/small vegetation were decreased during the period 1981–2006. The areas under forest cover and barren land were also decreased but relatively low compared to the other LULC types. The OMR results showed that the LULC changes over urban areas contributed to warming with a temperature of 0.02 °C during this period, while that over non-urban areas showed a cooling effect with a temperature reduction of 0.29 °C and that over the whole Southern India (looked at an average) indicated a cooling effect with a temperature reduction of 0.063 °C. The comparative analysis between the two (LULC change analysis and OMR) results showed that the cooling over Southern India was mostly due to the expansion of agriculture/fallow land and the decline of shrubs/small vegetation. The study suggests that the OMR method reasonably demonstrates the effect of LULC changes on the temperature over Southern India.
... Additionally, the regional parameters, such as urban growth, change in land use, irrigation, and desertification, affect the DTR (Karl et al., 1993); also, increased aerosol concentration in the atmosphere has a direct impact on the local urban climate and subsequently on DTR reduction (Mohan & Kandya, 2015). The cities are mostly warmer than the neighboring rural areas (Oke, 1973); this is due to the urban heat island effect that occurs particularly at night when the absorbed daytime heat released from large impervious surfaces gets trapped within the urban canopy due to the lower sky-view factor and thus increases nighttime temperatures (Mohan & Kandya, 2015). ...
... Additionally, the regional parameters, such as urban growth, change in land use, irrigation, and desertification, affect the DTR (Karl et al., 1993); also, increased aerosol concentration in the atmosphere has a direct impact on the local urban climate and subsequently on DTR reduction (Mohan & Kandya, 2015). The cities are mostly warmer than the neighboring rural areas (Oke, 1973); this is due to the urban heat island effect that occurs particularly at night when the absorbed daytime heat released from large impervious surfaces gets trapped within the urban canopy due to the lower sky-view factor and thus increases nighttime temperatures (Mohan & Kandya, 2015). It is broadly perceived that changes in the climate and urbanization (Makowski et al., 2009;Braganza et al., 2004;Gallo & Owen, 1999;Kueh et al., 2017) to a great extent influence the DTR. ...
Article
Full-text available
Urbanization plays a crucial role in the urban landscape dynamics, contributing to numerous ecosystems and urban climate changes. Diurnal variation of land surface temperature (LST) is a significant index for estimating local climate change as a response to urbanization. This research analyzes the impact of urbanization on the LST-based diurnal temperature range (DTR) for Pune, India, in three steps: (a) detection of spatiotemporal variation in DTR, (b) assessment of DTR behavior in different land use and land cover (LULC) classes, and (C) examining the interrelationship between urban density and DTR. The study utilizes a time series LST estimates from the MODIS satellite for 12 years (2003–2014). The preliminary spatiotemporal assessment shows a decrease in annual averaged DTR across Pune, from 25.79 °C in 2003 to 21.82 °C in 2014. Further investigation in LULC classes revealed a similar downward non-monotonic DTR trend in all classes except for the Built-up class, exhibiting a significant monotonous downtrend with a decrease of 5.67 °C, and the DTR anomalies are also consistent with this trend. The Mann–Kendall test confirms a significant trend with a p-value of 0.029, and Sen's slope analysis with − 0.167 establishes a decreasing DTR trend with a negative slope. The evaluation of urban density in Pune Metropolitan Region (PMR) for DTR variation shows a rise in area under DTR (below 17 °C) in the Dense Built-up class from 0.1 to 7.52% across 2003–2014. Whereas DTR (above 25 °C) in Less Dense Built-up saw a sharp decrease in the area from 16.37 to 0.05% during the same period. Thus the DTR trend in varying urban densities signifies the role of intense urbanization on DTR behavior. These findings are alarming and provide insight into the local climate issues that should help policymakers and urban planners to make informed decisions toward sustainable development in the Pune Metropolitan Region.
... Previous studies have documented that cities located in dry tropical climates often experience negative UHI effects during the day time (Mohan and Kandya, 2015;Shastri et al., 2017) due to the hydro-thermal properties of the ambient surface materials. Thus, the daytime LST is comparatively higher for non-built-up tracts than over built-up areas (Pramanik and Punia, 2019). ...
... Contrastingly, there exists a nocturnal positive UHI effect in the same area (Mallick and Rahman, 2012). Furthermore, a low diurnal range of temperature in the central location of the NCT of Delhi indicates that both the day and nighttime LST are relatively high (Mohan and Kandya, 2015) and that LST analysis outside the extreme temperature seasons (i.e. extreme summer and winter) is more suitable/prudent as thermal anomalies can be avoided (Mallick and Rahman, 2012;Rahman et al., 2011). ...
Article
Full-text available
Urban form is generally accepted to be the most significant aspect controlling LST. This study analyzes the spatio-temporal urban growth pattern in India's rapidly urbanizing National Capital Region (NCR) to discern its dominant urban form based on urban sprawl metrics (USM-a neighborhood based built-up density approach) and traces its spatio-temporal growth patterns. It then gauges the relations between the landscape composition and various development modes of this dominant urban form with the ascertained nighttime LST distribution. The results of the USM based analysis show that the NCR's dominant urban form is constituted by the urban core, which has expanded markedly during the study period of 2000-2018. Within the urban core, nighttime LST increased, particularly during the fall months. Linear regression models (both non-spatial and spatial) reveal a positive relation between the nighttime LST and the built-up area and infilling growth mode. Contrarily, nighttime LST is negatively correlated with the edge-expansion and the respective areas under urbanized green and non-green open spaces. New planning approaches are thus required to restrict infilling based densification and promote well-planned edge-expansion with the designation of new green spaces as well as the greening existing non-green open spaces, particularly in areas underprovided with greenery.
... Similar studies over India are limited. Mohan and Kandya (2015) have studied spatial and temporal variations of satellite-based estimates of the annually-averaged diurnal temperature range (DTR) over the megacity New Delhi for a period of eleven years from 2001 to 2011. Their study shows that areas that are rapidly urbanizing registered a significant decreasing trend in the DTR in the background of the converging DTR, which was primarily due to the increase in the minimum temperatures (Mohan and Kandya 2015). ...
... Mohan and Kandya (2015) have studied spatial and temporal variations of satellite-based estimates of the annually-averaged diurnal temperature range (DTR) over the megacity New Delhi for a period of eleven years from 2001 to 2011. Their study shows that areas that are rapidly urbanizing registered a significant decreasing trend in the DTR in the background of the converging DTR, which was primarily due to the increase in the minimum temperatures (Mohan and Kandya 2015). Sati and Mohan (2018) studied five representative years of each decade-1972, 1981, 1993, 2003, and 2014 model and by focusing on particularly changing urban class land use from other land use types, such as cropland, open areas, and water bodies, over Delhi. ...
Article
The development of the Delhi Mumbai Industrial Corridor (DMIC) region is India’s most ambitious project that is witnessing rapid urbanization growth. Another critical environmental issue faced by this region is climate change. This article investigates the possible impacts of urbanization and climate change in the DMIC region on near-surface air temperatures in the month of May, which is typically the hottest month of the year with the highest heat stress. Numerical experiments were carried out using the Weather Research and Forecasting (WRF) model to estimate the impacts of three urbanization scenarios and four future climate scenarios (Representative Concentrative Pathway [RCP] 4.5 and RCP8.5 mid- and end-century). This allows for a quantitative evaluation of the impacts of urbanization relative to the impacts of climate change as well as a preliminary estimate of impacts of urbanization under future climate conditions. Results of the numerical experiments show that urbanization can increase the minimum temperature by more than 3°C, but the effect on maximum temperature is small. This impact is mainly due to changes in the surface energy budget, where increased heat capacity and reduced evaporation lead to a 20 to 30 W/m2 increase in sensible heat flux and a 12 to 18 W/m2 reduction in latent heat flux. Climate change increases both maximum and minimum temperature by up to 4°C. The combined impact of urbanization and climate change is found to be severe, with the minimum temperature showing an increase of approximately 4 to 7°C and the maximum temperature showing an increase of approximately 1.5 to 3.5°C. Overall, urbanization is likely to exacerbate the adverse effects of climate change in the DMIC region.
... Besides, compact buildings and high urban density, as well as urban impervious surfaces, affect fresh air circulation of the environment (Schwarz, 2010;Schwarz & Manceur, 2015). These finally change the thermal property of land by changing the energy budget (Mohan & Kandya, 2015). Furthermore, very compact buildings and associated paved surfaces in a very cluster of the city block ventilation and affect air cooling time (Wong & Lau, 2013). ...
Article
Full-text available
Land-use and land-cover (LULC) change as a result of rapid urban expansion cause land surface temperature (LST) variations. The study aims to analyze urban LULC change and its impact on the seasonal, spatial and temporal Surface Urban Heat Islands (SUHI) of Addis Ababa city and its surrounding from 1987 to 2019 using Landsat images. The result indicates that the Impervious Surface (IS) of Addis Ababa city and the surroundings have expanded from 81.49 km2 in 1987 to 591.85 km2 in 2019 with a 6.2% rate of change. On the other hand, vegetation cover which has a high thermal cooling effect has been degraded from 217.66 km2 in 1987 to 157.8 km2 in 2019. The spatial pattern of LST increased from northern highlands towards southern lowlands. The mean temperature for January and February 1987 was 26.22 °C and 27.76 °C, respectively. On 25 January 2002, the study area exhibited the mean LST of 28.25 °C, whereas on 26 February 2002, the mean temperature was increased to 31.26 °C. On 16 January 2019, the mean LST was 31.14 °C, whereas on 1 February declined to 30.62 °C. The study area exhibited a high mean LST on 21 March 2019 which was 36.1 °C, whereas on 15 October 2019 the mean LST was 25.41 °C. The study shows that very high LST exhibited on fallow land (27.78, 30.39 and 33.38 °C), crop (26.5, 28.66 and 30.83 °C), grassland (26.52, 28.53 and 31.15 °C) and IS (26.58, 28.38 and 31.39 °C) while low LST found on vegetation cover (22.76, 21.64 and 24.44 °C in 1987, 2002 and 2019, respectively). The mean LST has a positive correlation with fraction of IS (R2 = 0.5152, 0.5855, 0.7184), CL (R2 = 0.716, 0.6294, 0.7089), FL (R2 = 0.6373, 0.6138, 0.8667) and GL (R2 = 0.6513, 0.6073, 0.6442) while negative with VC (R2 = 0.6295, 0.5601, 0.6357 in 1987, 2002 and 2019, respectively). The mean LST that exhibited in Z1 and Z2 was 25.47 and 26.91 °C, 26.06 and 28.88 °C, and 29.43 and 32.33 °C in 1987, 2002, and 2019, respectively. The IS declined when moving from the center to the peripheral area and the mean LST increased towards the rural area along urban–rural zones (URZs). In the north–south direction along URZs, the minimum and maximum mean LST in January increased from 15.83 °C in 1987 to 18.57 °C in 2019 and 33.64 °C in 1987 to 35.58 °C in 2019, respectively. Besides, the minimum and maximum mean LST for February in 1987 and 2019 was 17.57 °C and 18.97 °C and 32.82 °C and 35.21 °C, respectively. The minimum mean temperature also increased from 18.24 °C to 23.4 °C, and maximum mean LST from 32.84 °C to 41.9 °C from October to March 2019. Along east–west direction, the minimum and maximum mean LST in January was found 18.48 °C and 30.8 °C in 1987 while it was increased to 23.66 °C and 35.69 °C in 2019, respectively. The minimum and maximum mean LST in February was also increased from 20.17 to 23.57 °C and 30.81 to 34.91 °C from 1987 to 2019, respectively. Along northeast–southwest direction, the minimum mean LST in January 1987 was 16.17 °C and increased to 18.16 °C in 2019, whereas the maximum mean temperature increased from 32.1 °C in 1987 to 36.06 °C in 2019. The minimum mean LST in February 1987 was 19.43 °C and decreased to 18.5 ℃ in 2019, whereas the maximum value raised from 32.07 °C in 1987 to 36.85 °C in 2019. The pattern of LST decreased when moving to URZ60 to URZ90 in the northwest direction of the city center and increased city center to URZ47 and city center to URZ165 in the southeast direction. The study revealed that SUHII was highly concentrated in the urban area than the peripheral area. Therefore, to reduce SUHI and to have a sound environment, vegetation cover with dense trees canopy and greenery areas covered with grasses and trees are very important for the city and the surrounding.
... The average surface temperature of the world's land and sea in 2019 was about 1.1 C higher than the preindustrial level (NCC 2020). Meanwhile, with the acceleration of urbanization, the scale of urban construction land and population density has increased dramatically, the intensity and scope of human activities have gradually expanded, and the urban system has become increasingly complex, which has had a significant impact on urban climate (Kalnay and Cai 2003;Mohan and Kandya 2015;Oleson et al. 2015). Under the background of global warming and urbanization, extreme heatwave events frequently occur worldwide and have evolved into severe meteorological disasters. ...
Article
Full-text available
The continuous advancement of urbanization and the acceleration of global climate warming have severely aggravated the heatwave vulnerability of the urban complex human–land system. Therefore, the scientific assessment of urban heatwave vulnerability (UHV) is particularly critical. We used Xiamen City, one of the representative heatwave disaster-prone cities, as a case study area. We then constructed a UHV index system that coupled adaptability and selected 12 indicators from the three dimensions: exposure, susceptibility, and adaptability. The back propagation neural network (BPNN) model was used to composite each indicator layer and produce UHV results. Finally, we analyzed the spatial distribution characteristics of UHV. We found that the BPNN model had good training performance, with an overall accuracy of 0.92986. The value of UHV ranged from 0 to 1 and was divided into five grades, from low to high were 18.45%, 18.72%, 17.16%, 28.76%, and 16.91. In terms of spatial characteristics, high adaptability significantly improved UHV. The high value of UHV presented specific agglomeration characteristics, and the extremely vulnerable and disordered areas were mainly located in Huli District and the junction of Siming District and Huli District. The research will provide a new theoretical perspective and framework for urban heatwave assessment and help for disaster management and sustainable development in a high-risk area.
... Meanwhile, the urban environment shifts itself through landscape changes. Temperature increase is known as the urban heat island (UHI) effect (Kafy et al., 2021a;US EPA, 2008), and has been broadly investigated in association with urban expansion in the last few years (Can et al., 2019;Mohan and Kandya, 2015;Son et al., 2017;Tran et al., 2017;Xinmin et al., 2017). ...
Article
Urban development is dominated by various factors ranging from natural and social factors to accessibility to urban infrastructures. Urbanization in an unfavorable location in terms of the above factors can create difficulties with connecting to the city center, adjacent urban areas, and wastage of land resources. In the context of Can Tho city, a newly developing city, its urban expansion process and factors affecting urbanized possibility were explored by applying multiple logistic regression (MLR) on Landsat imagery and accessible geospatial data sources. The analyses confirmed a significant urban expansion in the entire city between 2003 and 2017, mostly in central districts and along the Hau river. The primary dynamics of urban expansion were explained by an efficient MLR (Area Under Receiver Operating Characteristic – AUROC = 0.803), based on six factors related to accessibility to transportation, developed urban areas, industrial zone, elevation, soil type, and population. A simulation of urbanization probability revealed that most remote areas with low accessibility to urban infrastructures are difficult to urbanize with a probability of less than 40%. In contrast, the high potentially urbanized regions expanded the already built-up areas in riverside districts. Our findings facilitate the understanding of urbanized driven factors in the newly developing delta cities for long-term planning when urbanization remains under control.
... It has been also used for the evaluation of the impact of soil and water conservation measures in order to combat LD (Nyamekye et al. 2021). Land use land cover (LULC) dynamics have a direct influence on the spatial and temporal variability of LST (Ding and Shi 2013;Mohan and Kandya 2015;Ogunjobi et al. 2018;Mustafa et al. 2019). Consequently, LST has been found to provide vital and useful information on the surface of the land and is widely used as one of the indicators in the assessment of LD (Karnieli et al. 2010;Gantumur et al. 2018). ...
Article
Full-text available
Land degradation and desertification have recently become a critical problem in Ethiopia. Accordingly, identification of land degradation vulnerable zonation and mapping was conducted in Wabe Shebele River Basin, Ethiopia. Precipitation derived from Global Precipitation Measurement Mission (GMP), the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized difference vegetation index (NDVI) and land surface temperature (LST), topography (slope), and pedological properties (i.e., soil depth, soil pH, soil texture, and soil drainage) were used in the current study. NDVI has been considered as the most significant parameter followed by the slope, precipitation and temperature. Geospatial techniques and the Analytical Hierarchy Process (AHP) approach were used to model the land degradation vulnerable index. Validation of the results with google earth image shows the applicability of the model in the study. The result is classified into very highly vulnerable (17.06%), highly vulnerable (15.01%), moderately vulnerable (32.72%), slightly vulnerable (16.40%), and very slightly vulnerable (18.81%) to land degradation. Due to the small rate of precipitation which is vulnerable to evaporation by high temperature in the region, the downstream section of the basis is categorized as highly vulnerable to Land Degradation (LD) and vice versa in the upstream section of the basin. Moreover, the validation using the Receiver Operating Characteristic (ROC) curve analysis shows an area under the ROC curve value of 80.92% which approves the prediction accuracy of the AHP method in assessing and modelling LD vulnerability zone in the study area. The study provides a substantial understanding of the effect of land degradation on sustainable land use management and development in the basin.
... The use of remote sensing data in conjunction with Geographic Information Systems (GIS) is effective in mapping urban areas, modeling urban growth, monitoring LULC's dynamic changes; estimating LST (Bhagyanagar et al., 2012;Kimuku et al., 2017) and extracting biophysical components (Subrata et al., 2018;Firozjaei et al., 2019). In many studies estimating land surface temperature (LST) and urban heat island (UHI) phenomena over urban ecosystems, remote sensing methods have been shown to be fruitful (Asgarian et al., 2015;Guo et al., 2015;Mohan and Kandya, 2015;Carleton et al., 2016;Das et al., 2020). Several research have been published to study the relationship between LST / LULC in which an increase in land surface temperatures (LST) is considered one of the main effects of LULC changes) especially in urban centers (Aboelnour and Engel, 2018;Pal and Ziaul, 2017;Weng et al., 2004). ...
Article
Full-text available
Urbanization is a phenomenon that is driven by humans. It has significantly influenced biodiversity, ecosystem processes and regional climate. This work explores the relationship between seven biophysical variables (NDVI, SAVI, Greenness, Albedo, DBI, NDBI, and NDBaI indices), and LST over a period of 30 years (1990-2020), based on remote sensing & GIS. A time-series of Landsat images TM, ETM+ and OLI/TIRS data as well as various geospatial approaches were used to facilitate the analysis. The findings have revealed that urban/built-up areas of Guelma city have increased by (20.76 km 2), in contrast to the agricultural and forest areas, which have been reduced by (138.26 km 2 and 2.7 km 2). The average temperature of urban setting was (31,43 C°) in 1990, whereas it reached (41,90 C°) in 2020. The lowest temperature values were observed in forest bodies with (26,55 C°) in 1990 and (37,78 C°) in 2020. There is a possible rise in LST over time scale owing to the substitution of green cover by urban soil areas. Generally, there was a noticeable increase in mean LST of 10,47 C° for urban areas. The coefficient of correlation between the biophysical indices and LST shows that a strong negative correlation exists between vegetation biophysical indices (NDVI, SAVI and Greenness) and LST. In addition to this, the urban biophysical indices (Albedo, DBI, NDBI, and NDBaI) can effectively retrieve the LST. They were positively correlated in all years. DBI and LST have the highest consistently rising positive relationship (R = 0,62). This investigation provides us with clear understanding of the impacts that the urbanization and biophysical indices have on LST.
... Remote-sensing is a powerful and cost-effective data source for assessing the spatial and temporal changes on the earth surface [34][35][36][37][38][39]. Remote sensing techniques have been used to determine the area usage changes between 1995-2020 in Fethiye-Göcek SEPA. ...
Preprint
Increasing population and urbanization are affecting human health and comfort. In order to get rid of these affects, mankind is changing its enviroment and looking for new life areas. This study investigates the influence of Land Cover Change (LCC) and Normalisied Densly Vegetation Index (NDVI) on Land Surface Temperature (LST) of Fethiye-Göcek Specially Protected Area (SEPA) in easterm mediterranean basin. In the study LCC, NDVI and LST were drived from landsat 5, 7 and 8 satellite image of resolation at 30x30 m acquired between 1995-2020. LST were computed based on Land Use/Land Cover (LULC) types. The Corine Index were used for determination of land uses. The results indicated that water, forest and maquia lands decreasing while urban fabric and bare lands are increasing depend upon the urbanization and forest fires in the basin. These changes in LULC widened the temperature differences between the urban and rural areas. The change in LST is associated with changes in constructional materials in urban land and in vegetation abundance both in the urban and rural areas. Vegetation has an important factor in the temperature of different land covers. That produces warming trend in temperetaure in built-up areas it causes to keep other lands warmer in cold weather. Another important result is affective Urban Heat Island (UHI) on climate change based on the impact of urbanization and land cover changes. Significantly possitive correlation were found between the urbanization rate, population and built-up area and warming rate of average air temperature and so the LST.
... The rising trend of minimum temperature is higher than that of maximum temperature, which leads to a decline in the global DTR (Sun et al., 2019). The intensification of urbanization across the globe has also contributed to the decline in DTR since the 1950s (Gallo et al., 1996;Kalnay and Cai, 2003;Feddema 2005;Mohan and Kandya, 2015). This is mainly because the underlying impervious surfaces of cities increases the nighttime temperature by absorbing a large amount of energy in the daytime and releasing it at night (Forster and Solomon, 2003;Zhou et al., 2007;Yang et al., 2020a;Zong et al., 2021). ...
Article
Full-text available
Previous studies on the impact of urbanization on the diurnal temperature range (DTR) have mainly concentrated on the intra-seasonal and interannual–decadal scales, while relatively fewer studies have considered synoptic scales. In particular, the modulation of DTR by different synoptic weather patterns (SWPs) is not yet fully understood. Taking the urban agglomeration of the Yangtze River Delta region (YRDUA) in eastern China as an example, and by using random forest machine learning and objective weather classification methods, this paper analyzes the characteristics of DTR and its urban–rural differences (DTRU–R) in summer from 2013 to 2016, based on surface meteorological observations, satellite remote sensing, and reanalysis data. Ultimately, the influences of urbanization-related factors and different large-scale SWPs on DTR and DTRU–R are explored. Results show that YRDUA is controlled by four SWPs in the 850-hPa geopotential height field in summer, and the DTRs in three sub-regions are significantly different under the four SWPs, indicating that they play a role in regulating the DTR in YRDUA. In terms of the average DTR for each SWP, the southern sub-region of the YRDUA is the highest, followed by the northern sub-region, and the middle sub-region is the lowest, which is most significantly affected by high-level urbanization and high anthropogenic heat emission. The DTRU–R is negative and differs under the four different SWPs with variation in sunshine and rainfall. The difference in anthropogenic heat flux between urban and rural areas is one of the potentially important urbanization-related drivers for DTRU–R. Our findings help towards furthering our understanding of the response of DTR in urban agglomerations to different SWPs via the modulation of local meteorological conditions.
... The negative trend over Indo-Gangetic plains is due to the intensive anthropogenic agricultural irrigation (Kumar and Mishra, 2019). The positive trend over north India during recent decades might be attributed to an increase in anthropogenic greenhouse emissions and land-use change (Mohan and Kandya, 2015;Basha et al., 2017). The peninsular region exhibits almost no trend during recent decades. ...
Article
Climate change has impacted the nature and the severity of extreme temperatures over India in the recent past. In this study, the characterization in nature and change of hot season (March to May) temperatures across India’s various geographical regions have been analysed over the last 69 years. Using canonical correlation analysis (CCA), we elucidate the relationships between various meteorological parameters from the preceding Indian winter (December to February) and the following hot season. A combination of detrended and raw data for CCA has revealed the asynchronous winter parameter's effects on hot season temperatures. The raw data explained the evolution of the relationship between the variables in the warming climate. In contrast, detrended data explains the predictive relationship between hot season temperature and other predictive variables which are not influenced by the trend in the data. The evolving nature of the global and Indian ocean as well as, El‐Niño Southern Oscillation, zonal circulation, and pressure systems, are evident in effecting Indian hot season temperatures. The post‐1980s warming is also tangible from the increasing strength of El Niño in the last few decades. The cross‐validated and mean square skill scores are moderate except for a few regions having an average correlation of ~0.5 or more for the study periods. The minimum temperature has shown better skill than the maximum temperature, and the southern peninsular region has shown more predictability than the northern regions. Compared to raw data, detrended has a lesser prediction skill. The present study will help to predict the seasonal temperature along with the associated relationship and the warming effect post‐1980s.
... A few studies analyzed the consequences of urban expansion and induced land use changes on extreme rainfall scenarios over tropical Indian cities (Boyaj et al., 2020;Kishtawal et al., 2010;Mohan & Kandya, 2015;Paul et al., 2018). Kumar et al. (2008) showed that the highly localized heavy rainfall event (August 2005) over Mumbai was produced as a result of the interaction of synoptic-scale low-pressure system with the typical mesoscale land surface features of this region. ...
Article
Full-text available
In this study, the impacts of urban land surface processes on the extreme heavy rainfall event on 01 December 2015 over Chennai, located in north coastal Tamil Nadu, India are analyzed using convection permitting WRF simulations. A series of numerical experiments are conducted using different land cover data (USGS‐1992, NRSC‐2004, NRSC‐2015), aerodynamic roughness, and land surface models (LSM) to assess their sensitivity on the predicted rainfall. Results suggest that experiments with NRSC‐2015 with increased urban extent improved the rainfall prediction in terms of rainfall intensity and its distribution. Though temperatures, sensible heat, and Planetary Boundary Layer height (PBLH) increased due to urbanization in both dry and wet phases, the humidity and Convective Available Potential Energy (CAPE) reduced during the dry phase suggesting thermal convection played a secondary role in rainfall. Considerable increase of surface drag, momentum transport, wind shear and Turbulent Kinetic Energy are found in simulations with updated land use and roughness, which determined the location of the cyclonic circulation, convergence and maximum precipitation. LSM sensitivity experiments indicated that while the five‐layer model substantially increased the sensible heat, temperature and PBLH, it reduced the moisture convergence and CAPE relative to Noah and Noah‐MP thus resulting in low rainfall. The simulation with Noah‐MP enhanced the low‐level shear and convergence over other LSMs thus produced a wide spread rainfall along the coast. Our results demonstrated that the momentum transport due to urban drag played a vital role by strengthening the low‐level convergence and moist convection, which caused heavy precipitation over Chennai.
... Existing literature on contemporary urbanization in Delhi showed extensive changes in urban land cover (Jain et al., 2011), socio-economic structure (Dupont, 2004), and the implication of urbanization on the environment (Chakraborty et al., 2013;Mohan and Kandya, 2015). At present, Delhi is both a state and a city. ...
Article
Full-text available
Understanding urban land-use changes and accurately quantifying urban land transitions is essential to global land-change research. The present study aimed to capture non-linear land transitions within urban areas using an automated change detection technique in a satellite image time series. Traditional land-use and cover maps used to map and monitor urban areas assume land change is a linear process and that urbanization is the last stage of land transition. In reality, however, most land transitions are non-linear. The present study focused on Delhi National Capital Territory, in India, and its adjacent major cities. A popular time-series analysis method was applied on MODIS NDVI time-series (2000–2017) data to detect change within the impervious surface area of the region. Overall validation and analysis of the results showed that the method was able to capture the direction and timing of the changes very well within all levels of urban density (except very high-density areas with more than 98% built-up density). The majority of urban areas in the region experienced interrupted, abrupt, and gradual greening. The results show different examples of non-linear land transitions detected from satellite images. Until recently, these land transitions could only be observed via long-term field surveys and/or local knowledge. The results reveal that the land-change trajectories can be different based on the level of built-up density, size of the urban area, physical proximity, and accessibility to relatively bigger urban areas. Knowledge gained from this study can be useful in better understanding the micro-climatic patterns and environmental quality within a city.
... The rapid expansion of urban areas is mainly a product of economic growth and rising populations, especially in megacities. 21 The substantial growth of built-up areas has brought a decrease in the area under water bodies, cultivated land, vegetation, and wetlands. Mohan et al. 22 found major impacts of the rapid expansion of the Delhi metropolitan area from 1997 to 2008. ...
Article
Full-text available
Land use/land cover (LULC) change and climate change are thought to be closely related and mutually influential, especially in contexts where land is converted for urban expansion or agriculture. We represent a first attempt to specify the relationship between LULC change and dryness in a region of Vietnam that is profoundly affected by climate change. Using the temperature–vegetation dryness index (TVDI), we specified the relationships and changes underway in Vietnam’s Ba river basin, one of the largest river systems in the South Central Coast. Using Google Earth Engine, we extracted land use data from Landsat images and calculated TVDI values from Moderate Resolution Imaging Spectroradiometer (MODIS) data for 2000 to 2019. We found, first, that agricultural area and deforestation rose by 7.2% and 2.4% annually, respectively. These changes were driven by economic development, rising crop prices, illegal logging, wildfires, and emergence of new agricultural areas. Second, areas classified in the driest TVDI intervals (dry and very dry) occupied 57% of the basin in 2019, 70% of which was agricultural lands and 20% other (mainly urban and bare lands). These driest land categories expanded at an average rate of 0.08% to 0.1% per year. Moreover, 90% of areas classified as “very wet” and “wet” were forest. We observed a strong relationship between LULC change and TVDI. Climate change and LULC change thus appear to be propelling the basin’s climate toward increasing dryness, suggesting the need for policies to reduce the agricultural area and expand forests while developing more adaptive and sustainable livelihoods.
... The microclimate of a province is defined by its bare soil, air temperature, vegetation cover, weather conditions, wind, elevation, relative humidity, and altitude (Kotchi et al., 2016;Mohan & Kandya, 2015;Pitman et al., 2015;Zhang et al., 2013). Understanding and predicting microclimatic parameters is of great importance for many aspects. ...
Article
Full-text available
Local climate in an area is significantly affected by the extent of urbanization. The microclimatic parameters such as wind speed (W), relative humidity (RH) and temperature (T) are affected due to modifications in natural surfaces and land use. With increasing interest in urban microclimate research, factors such as energy conversation, environmental sustainability, and urban design with thermal comfort are researched extensively. The current study attempts to model T, W and RH in an urban landscape of Nagpur City by solving the microclimate governing equations using python and ArcGIS. Numeral field measurements are carried out during summer and winter seasons for validation of modeled data. The results show a statistically positive and significant correlation between modeled and monitored data (p < 0.001 at CI 95%) for T and RH with R² ranging from 92.5–97.7% and 82.2–88.7%, respectively. However, the model underpredicts T by an average of 4–7% in winter and summer, respectively, while RH is overpredicted by an average of 2% overall. W shows moderate correlation between modeled and monitored data with an average variation of 0.02–0.1 m/s for two seasons. Holistically, the modeled data are significantly correlated with ground data, and variations between surface points are captured well by the model, indicating that python and ArcGIS can be used for the measurement of microclimate parameters, forming the basis of sustainable urban design. Evaluating the urban microclimate parameters for both greenfield and brownfield projects can assist the landscape designers, planners to effectively control the temperature and wind conditions and improve the outdoor thermal conditions in an urban area. Graphic abstract
... As a result, population density has been significantly higher in the areas with high abundance of impervious surface. In tune with the increasing population density and LULC transformation, the congested residential and industrial areas of Delhi NCT have experienced a significant decrease in the trend of diurnal temperature range (DTR) (Mohan and Kandya 2015). The core areas of Delhi megacity, characterized by intense UHI effects are highly vulnerable to heat stress. ...
Article
Spatial changes in urban areas are closely associated with the increasing impervious land and thus, monitoring the spatio-temporal changes in impervious area is crucial for identifying urban growth. The capital city of India, Delhi has become one of the most populated cities of the world for its fast-growing economy and infrastructural development. Although the city is expanding since the last couple of decades, the rate of growth has become significantly high in the previous decade. This study aims to identify the spatio-temporal pattern of impervious surface growth in and around Delhi National Capital Territory (NCT) by using bi-temporal Landsat images of 2003 and 2014. The linear spectral unmixing (LSU) technique was employed for assessing the impervious surface growth over the megacity. To understand the associated changes of such growth, vegetation surface fraction (VSF), land surface temperature (LST) and normalized difference vegetation index (NDVI) were estimated and compared with the impervious surface fraction (ISF). Further, the fractional abundance of impervious surface was validated with built-up density, urban expansion and population density of the area. This study reveals the significant growth of impervious land in the peri-urban centres surrounding Delhi. The fractional abundance of impervious surface was found highly correlated with the vegetation surface fraction, LST and NDVI. The significant (p < 0.005) correlation coefficients prove good agreement among these variables. Strong negative correlation (r² = 0.857) between ISF and urban expansion index (UEI) proves the potentiality for urban expansion in the less developed areas with abundant pervious surface. The study also reveals a significant polynomial relationship (r² = 0.746) between impervious surface fraction and population density indicating high ISF (0.9‐1.0) in the densely populated areas and vice-versa. The expanding impervious surface especially in the peri-urban centres along with the rising intensity of urban heat island (UHI) calling for suitable planning and strategies for sustainable urban growth.
... As well, the global changes in land use are interconnected to the enormous rise in carbon emissions that impact the local or microenvironment in the rural areas. Whereas, the loss of forest cover is even more severe in the urban and metropolitan cities of the world's societies (Mohan & Kandya, 2015), which increasingly disturbs the local and then the global environment. It halts the progress of the societies to achieve, for example, the globally recognized Sustainable Development Goals (SDGs) (SDGs, also called as the Global Goals, are the blueprint to achieve a better and sustainable tomorrow for the humanity. ...
Chapter
This study has analyzed carbon emissions as a result of forestland change due to urbanization in Islamabad, Pakistan, over the time-span of 25 years (1992–2017). Forestland change was determined by analyzing land use/land cover change (LULCC) through remote sensing and GIS imaging. The results have confirmed a 22% abridged in the forest cover for 8 years; 1992–2000, which was followed by 27% reduction from 2000 to 2008 and alarmingly 51% forestland was curtailed between 2008 and 2017. This consistent removal of the forest cover has been leading to an increased level of carbon emissions into the open atmosphere of the capital city. The percentage of forestland changes for the whole study period of 25 years (1992–2017) was 48.11%. The carbon emissions equaled to 344.96 carbon tons year⁻¹. The issue draws prompt attention and actions to halt human-induced disaster in the form of massive urbanization on the cost of forestland degradation. The study calls for reforestation and afforestation to ratify Paris Climate Accord of which Pakistan is a signatory country.
... The diurnal asymmetry of OMR trend is more prominent in the urban agglomerations (Fig. 3c, S4), suggesting that urbanization can enhance asymmetric diurnal warming, consistent with Wang et al. (2017). This can be explained by the well-known "urban heat island" effect which takes place prominently at night because of releasing the absorbed solar heat by buildings and streets in daytime (Zhou et al. 2004;Shiu et al. 2009;Mohan and Kandya 2015), thereby exacerbating already increased temperatures at nighttime in the urban areas. However, the diurnal asymmetry in warming trends could be attributed to cloudiness increase or/and solar radiation dimming (Easterling et al. 1997;Cox et al. 2020). ...
Article
Full-text available
Changes in land use, especially urbanization, alter the biophysical properties of Earth’s surface, which in turn affects local climate and even contributes to global warming. The observation minus reanalysis (OMR) approach has been widely applied to isolate the signal of surface forcing from observed temperature changes (which reflect all the sources of climate forcings, including surface effects), but bias in warming trends induced by surface change and estimation uncertainties still remain. Using the ensemble mean of eight temperature reanalysis datasets as background climate, along with in situ observations from 2353 meteorological stations, here we analyze the warming effects of land use changes in China between 1980 and 2015. Results show that OMR trends from land use changes collectively reached +0.100, +0.098, and +0.146 °C/decade for annual mean, maximum, and minimum temperature, contributing approximately 1/4 to 1/3 of overall observed warming trends, and stronger contributions were observed in the three largest urban agglomerations (i.e., Jing-Jin-Ji, the Yangtze River Delta, and the Pearl River Delta). The spatial distribution of OMR trends shows a great deal of heterogeneity that is closely related to impervious surface (positively) and vegetation cover (negatively). Warming trends induced by land use changes (including urbanization) present evident diurnal asymmetry (stronger for minimum than maximum) and vary with season (greater in winter/spring than in summer/autumn) and generally increase over time. Our results highlight that observed warming trends in China were likely influenced substantially by land use changes, especially in highly urbanized areas.
... These causes are still valid in different parts of the world, as discussed in a meta-analysis by Liu and Niyogi (2019). Several observational studies found that the thermal properties associated with the impervious surface and infrastructure encourage the storage of incoming solar radiation in urban areas resulting in noteworthy changes in the energy budget, surface fluxes, and other meteorological characteristics than rainfall over cities (Bornstein and Lin 2000;Burian and Shepherd 2005;Yang et al. 2011;Mohan and Kandya 2015;Haberlie et al. 2015;Chapman et al. 2017). ...
Article
Full-text available
The Kolkata metropolitan region, located in eastern India, is one of the most densely urbanized areas, with significant thunderstorms reported during the pre-monsoon season. The Weather Research and Forecasting (WRF) model is used to investigate the influence of urban-induced land use and land cover (LULC) change over Kolkata during the pre-monsoon thunderstorms. Multiple thunderstorm events reported during 2014–2017 are simulated using a high (Hurb) and low (Lurb) urban LULC scenario. The presence of higher urban pixels in Hurb case favors the enhancement in precipitation mainly over central and northern parts of the city in the downwind direction. Urban Heat Island (UHI) effect is more evident during the nighttime, with a temperature difference of up to 0.5 °C. However, the UHI impacts the vertical structure of the boundary layer (BL) more during the daytime due to prevailing higher temperatures and dominant surface heating. The analysis reveals positive contributions of the ground and sensible heat fluxes to the near-surface UHI intensity. The surfaces over the urban patch and surrounding areas experience a relatively drier atmosphere than their rural counterparts. Over the identified urban patches, a significant impact on meteorological variables is seen near the surface and within the BL in the case of Hurb compared to Lurb LULC scenario. The urbanization over Kolkata stimulates the BL and the local meteorology encouraging nighttime UHI, afternoon or evening moist convection, and consequent occurrence of thunderstorms to result in enhanced and distinctly distributed rainfall over the city and its neighborhood during pre-monsoon months.
... OANT is the second contributor following GHG, and results in a decrease in DTR by −0.12°C (from −0.03°C to −0.20°C). The negative effect of OANT could be explained by the differential response of daytime and nighttime temperature to land use change (Mohan & Kandya, 2015;Ren & Zhou, 2014). For example, the urban heat island effect on rising temperature is much stronger during nighttime than daytime (Sarangi et al., 2021;Yang et al., 2017). ...
Article
Full-text available
Plain Language Summary Contrary to rising temperatures, the diurnal temperature range has been decreasing over the past several decades. Although the impacts of humans on global warming have been widely demonstrated, formal detection and attribution of the impacts of human‐made greenhouse gases (GHG) and aerosols on the DTR are still lacking. Our results suggest that human impacts on the DTR are clearly detectable, separately from natural changes. Human‐made greenhouse gases are the dominant factor controlling decreases in the DTR worldwide. In contrast, anthropogenic aerosols (AER) are the dominant contributor for Europe and have led to an abnormal increase in the DTR in this region. If human emissions continue, we expect to see further decreases in the DTR in most regions. Our first quantification of human impacts on the global and regional DTR has significant implications for climate change assessments and future climate projections.
... The land cover change index (LCCI ij ) quantifies the transformation intensity of ecosystem types [25,26]. When the value of LCCI ij is positive, it means that the overall ecosystem type of the study area has improved, while the value of LCCI ij is negative, indicating that the overall ecosystem type in this study area has deteriorated [19]. ...
Article
Full-text available
The ecological degradation caused by unreasonable development and prolonged utilization threatens economic development. In response to the development crisis triggered by ecological degradation, the Chinese government launched the National Barrier Zone (NBZ) Construction Program in 2006. However, few in-depth studies on the Loess Plateau Ecological Screen (LPES) have been conducted since the implementation of that program. To address this omission, based on the remote sensing image as the primary data, combined with meteorological, soil, hydrological, social, and economic data, and using GIS spatial analysis technology, this paper analyzes the change characteristics of the ecosystem pattern, quality, and dominant services of the ecosystem in the LPES from 2005 to 2015. The results show that from 2005 to 2015, the ecosystem structure in the study area was relatively stable, and the area of each ecosystem fluctuated slightly. However, the evaluation results based on FVC, LAI, and NPP showed that the quality of the ecosystem improved. The vegetation coverage (FVC) increased significantly at a rate of 0.91% per year, and the net primary productivity (NPP) had increased significantly at a rate of 6.94 gC/(m2∙a) per year. The leaf area index (LAI) in more than 66% of the regions improved, but there were still about 8% of the local regions that were degraded. During these 10 years, the soil erosion situation in LPES improved overall, and the amount of soil conservation (ASC) of the ecosystem in the LPES increased by about 0.18 billion tons. Grassland and forest played important roles in soil conservation in this area. Pearson correlation analysis and redundancy analysis showed that the soil conservation services (SCS) in the LPES were mainly affected by climate change, economic development, and urban construction. The precipitation (P), total solar radiation (SOL), and temperature (T) can explain 52%, 30.1%, and 17% of the change trends of SCS, respectively. Construction land and primary industry were negatively correlated with SCS, accounting for 22% and 8% of the change trends, respectively. Overall, from 2005 to 2015, the ecological environment of LPES showed a gradual improvement trend, but the phenomenon of destroying grass and forests and reclaiming wasteland still existed.
... The concept of the urban heat island (UHI) has attracted the attention of many scholars around the world [2]. The acquisition of the land surface temperature (LST) based on remote sensing images provides firm data support for exploring the UHI [3,4], and spatial analysis technology has provided powerful tools for effectively revealing thermal environment effects of land-use/land-cover change along with urbanization [5][6][7]. ...
Article
Full-text available
Exploring the thermal environment effects of built-up land expansion can lay a firm foundation for urban planning and design. This study revealed the spatiotemporal dynamic characteristics of built-up land and heat island center points in Shijiazhuang using land-use/land-cover data and land surface temperature (LST) products from 1996 to 2019, and the response mechanism between the percentage of built-up land (PLAND) and LST with the grid sampling method and statistical analysis. Results indicated that heat islands are mainly clustered in the downtown, built-up areas of counties and the Hutuo River Basin. The spatiotemporal shift direction of the center point of the urban heat island (UHI) and built-up land in the whole study area varied due to the eco-environmental transformation of the Hutuo River Basin. In areas far from the Hutuo River Basin, the center points of UHI and built-up land were shifted in a similar direction. There is a remarkable linear correlation between the PLAND and LST, the correlation coefficient of which was higher than 0.7 during the study period. Areas with PLAND > 60% are urban regions with stronger heat island effects, and areas with PLAND < 55% are villages and towns where the temperature raised more slowly.
... Remote sensing data is a potentially powerful tool for detecting changes in LULC at higher temporal resolutions, reduced coasts, synoptic views, repetitive coverage and gaining real-time and conventional methods [26]. Numerous studies have validated the successive application of several satellites such as MODIS, Aster, Landsat [27][28][29][30][31][32][33]. The Landsat TM/ETM/OLI data have been broadly utilized for many research as an accessible remotely sensed data [34][35][36][37][38][39][40]. ...
Article
Full-text available
Land Use Land Cover (LULC) detection is a crucial indicator of environmental change since it is associated with the climate, ecosystem procedures, land degradation, biodiversity and increased human actions. The objective of current study is to observe how main LULC class changed in Iraq from 1982 to 2019. Overall,5259 Landsat 4, 5 and 8 images were utilized for land classification. In the study, Random Forest classification method was performed in Google Earth Engine (GGE) platform. The research has established the accuracy assessment of overall accuracy and kappa coefficient of four periods are 95% or higher. The trend of classes demonstrated that built up class increased dramatically by 248.6%. In contrast, bare soil, which covers most territories of Iraqdecreased by 8.4% (30,212 km2) from Period 1(1982-1989) to Period 4 (2010-2019). Likewise, vegetation class decreased by 20.2% (8,151 km2) during the same period.
... Since it has been argued that the UHI intensity based on daytime LST are overestimated (Mohan and Kandya, 2015), we also included an analysis based on nighttime LST in Appendix B.1.2. Due to overall weaker intensities, the dependencies on the city size, fractality, and anisometry are less pronounced. ...
Book
To what extent cities can be made sustainable under the mega-trends of urbanization and climate change remains a matter of unresolved scientific debate. Our inability in answering this question lies partly in the deficient knowledge regarding pivotal humanenvironment interactions. Regarded as the most well documented anthropogenic climate modification, the urban heat island (UHI) effect – the warmth of urban areas relative to the rural hinterland – has raised great public health concerns globally. Worse still, heat waves are being observed and are projected to increase in both frequency and intensity, which further impairs the well-being of urban dwellers. Albeit with a substantial increase in the number of publications on UHI in the recent decades, the diverse urban-rural definitions applied in previous studies have remarkably hampered the general comparability of results achieved. In addition, few studies have attempted to synergize the land use data and thermal remote sensing to systematically assess UHI and its contributing factors. Given these research gaps, this work presents a general framework to systematically quantify the UHI effect based on an automated algorithm, whereby cities are defined as clusters of maximum spatial continuity on the basis of land use data, with their rural hinterland being defined analogously. By combining land use data with spatially explicit surface skin temperatures from satellites, the surface UHI intensity can be calculated in a consistent and robust manner. This facilitates monitoring, benchmarking, and categorizing UHI intensities for cities across scales. In light of this innovation, the relationship between city size and UHI intensity has been investigated, as well as the contributions of urban form indicators to the UHI intensity. This work delivers manifold contributions to the understanding of the UHI, which have complemented and advanced a number of previous studies. Firstly, a log-linear relationship between surface UHI intensity and city size has been confirmed among the 5,000 European cities. The relationship can be extended to a log-logistic one, when taking a wider range of small-sized cities into account. Secondly, this work reveals a complex interplay between UHI intensity and urban form. City size is found to have the strongest influence on the UHI intensity, followed by the fractality and the anisometry. However, their relative contributions to the surface UHI intensity depict a pronounced regional heterogeneity, indicating the importance of considering spatial patterns of UHI while implementing UHI adaptation measures. Lastly, this work presents a novel seasonality of the UHI intensity for individual clusters in the form of hysteresis-like curves, implying a phase shift between the time series of UHI intensity and background temperatures. Combining satellite observation and urban boundary layer simulation, the seasonal variations of UHI are assessed from both screen and skin levels. Taking London as an example, this work ascribes the discrepancies between the seasonality observed at different levels mainly to the peculiarities of surface skin temperatures associated with the incoming solar radiation. In addition, the efforts in classifying cities according to their UHI characteristics highlight the important role of regional climates in determining the UHI. This work serves as one of the first studies conducted to systematically and statistically scrutinize the UHI. The outcomes of this work are of particular relevance for the overall spatial planning and regulation at meso- and macro levels in order to harness the benefits of rapid urbanization, while proactively minimizing its ensuing thermal stress.
... · Strong association of DTs magnitude of urbanerural surface energy flux differences but weak during daytime Hyderabad (Sannigrahi et al., 2017) Landsat and MODIS · Effects of urbanization and biophysical changes on UHI investigated in Hyderabad city for years 2002e15 · LST negatively correlated with NDVI for all LULC classes with highest negative association over the areas occupied by aquatic vegetation class followed by urban green space, urban built-up, farmland) and follow land English Bazar, West Bengal (Pal and Ziaul, 2017) LANDSAT TM and LANDSAT 8 OLI · Seasonal and temporal LST is extracted in three phases : 1991, 2010, and 2014 · LST found to increase at 0.070 C/year and 0.114 C/year during winter and summer periods respectively · Built-up area retains maximum LST in all selected phases Raipur (Guha et al., 2017) Landsat · During 1995 to 2016, the study area experienced a gradual increasing rate in mean LST (<1% per annum) · The UHI developed especially along the north-western industrial area and south-eastern bare land of the city. Mean UHI consistently increased from 2.6 C in 1995 to 3.63 C in 2016 · The urban thermal field variance index (UTFVI) applied to measure the thermal comfort level of the city; inner parts of the city ecologically more comfortable than the outer peripheries MODIS and ERA-Interim remote sensing data · The surface SUHI during the summer months reveals an average heat island effect of 1.5 K during the daytime and 0.4 K in the nighttime Malda, West Bengal (Dutta and Das, 2020) Landsat 5 TM and Landsat 8 · Regional Heat Island (RHI) aggregated in the main urban center as well as in its periurban areas · RHI is not only found in the main urban center but also its impact can be seen in its peri-urban areas · RHI class 2 < RLST 4 is identified as high-risk areas Mansa, Punjab (Kaur and Pandey, 2020) Landsat 8 · The SUHI was higher during September than January, and it was higher in Ludhiana followed by Bathinda and Balachaur, irrespective of the season · The SUCIs were formed in the center of Bathinda city during 1991 and in Ludhiana and Balachaur cities during 2011 Agra (Pathak et al., 2021) Landsat 5 TM and Landsat 8 · The focus was on spatial pattern of LST and land indices (i.e., NDVI, NDBI and EBBI) and their interrelationship dynamics over the city landscape in directional profiling · The results of SUHI reveal that city center had experienced 0.5e3.5 C higher LST than urban periphery Mohan and Kandya (2015) studied the effect of urbanization on the LST-based DTR for Delhi for a period of 11 years during 2001e11. There was a consistent increase in the areas experiencing DTR below 11 C, which typically resembled the "urban class," namely from 26.4% in the year 2001% to 65.3% in the year 2011 and subsequently the DTR of entire Delhi, which was 12.48 C in the year 2001 gradually reduced to 10.34 C in the year 2011, exhibiting a significant decreasing trend. ...
Chapter
Research for urban heat island (UHI) in India has accelerated in past few years covering not only megacities but small towns as well. This chapter presents a discussion on the UHI scenario in India, which is the second largest populated country and one of the top growing economies in the world. It examines UHI quantification across India from multiple assessment methods, possible impacts, mitigation strategies and finally, identifies future research directions. In India, UHI intensities up to 8–10°C have been reported in areas with dense urban and commercial pockets. The varied methods of determination of UHI (such as fixed instruments, mobile surveys, and satellite-derived measurements) at surface and canopy layer are discussed while noting the paucity of research for the boundary layer UHI in India. Measurements alone are not adequate due to limitations of instrumental installation and errors and spatiotemporal continuity. Hence, mathematical tools such as empirical models and numerical mesoscale weather prediction models are used to understand the UHI phenomenon at region of interest, assess major causative factors, and design mitigation strategies. Case studies of such model applications are presented in this chapter. UHI effect has shown significant implications on spatiotemporal rainfall patterns, perceived thermal comfort, and heat-related morbidity and mortality for Indian cities. The review brings out emergence of concepts such as regional heat island and UHI based on local climate zones. Efficacy of various mitigation measures such as increasing green cover/plantation, thermally resistant building materials, reflective coating, etc., on surfaces is discussed in detail. The comprehensive review of different aspects of UHI in this chapter should help the scientific community as well as the regulatory bodies to determine future research focus and action plans with regard to UHI effect, its impact and mitigation in India.
Article
Objectives: Diurnal temperature range (DTR) is an important indicator of global climate change. Many epidemiological studies have reported the associations between high DTR and human health. This study investigated the association between DTR and hospitalisations for ischaemic stroke in Hefei, China. Study design: This is an ecological study. Methods: Data of daily hospital admissions for ischaemic stroke and meteorological variables from 1 January 2009 to 31 December 2017 were collected in Hefei, China. A generalised additive model combined with distributed lag non-linear model was used to quantify the effects of DTR on ischaemic stroke. The interactive effect between DTR and temperature was explored with a non-parametric bivariate response surface model. Results: High DTR was associated with hospitalisations for ischaemic stroke. The adverse effect of extremely high DTR (99th percentile [17.1 °C]) occurred after 8 days (relative risk [RR] = 1.021, 95% confidence interval [CI] = 1.002, 1.041) and the maximum effect appeared after 12 days (RR = 1.029, 95% CI = 1.011, 1.046). The overall trend of the effect of DTR on ischaemic stroke was decreasing. In addition, there was a significant interactive effect of high DTR and low temperature on ischaemic stroke. Conclusions: This study suggests that the impact of high DTR should be considered when formulating targeted measures to prevent ischaemic stroke, especially for those days with high DTR and low mean temperature.
Article
Full-text available
Urbanization has dramatic impacts on natural habitats and such changes may potentially drive local adaptation of urban populations. Behavioral change has been specifically shown to facilitate fast adaptation of birds to changing environments, but few studies have investigated the genetic mechanisms of this process. Such investigations could provide insights into questions about both evolutionary theory and management of urban populations. In this study, we investigated whether local adaptation has occurred in urban populations of a Neotropical bird species, Coereba flaveola, specifically addressing whether observed behavioral adaptations are correlated to genetic signatures of natural selection. To answer this question, we sampled 24 individuals in urban and rural environments, and searched for selected loci through a genome-scan approach based on RADseq genomic data, generated and assembled using a reference genome for the species. We recovered 46 loci as putative selection outliers, and 30 of them were identified as associated to biological processes possibly related to urban adaptation, such as the regulation of energetic metabolism, regulation of genetic expression and changes in the immunological system. Moreover, genes involved in the development of the nervous system showed signatures of selection, suggesting a link between behavioral and genetic adaptations. Our findings, in conjunction with similar results in previous studies, support the idea that cities provide a similar selective pressure on urban populations and that behavioral plasticity may be enhanced through genetic changes in urban populations.
Article
Full-text available
Rapid urban growth has coincided with a substantial change in the environment, including vegetation, soil, and urban climate. The surface urban heat island (UHI) is the temperature in the lowest layers of the urban atmosphere; it is critical to the surface’s energy balance and makes it possible to determine internal climates that affect the livability of urban residents. Therefore, the surface UHI is recognized as one of the crucial global issues in the 21st century. This phenomenon affects sustainable urban planning, the health of urban residents, and the possibility of living in cities. In the context of sustainable landscapes and urban planning, more weight is given to exploring solutions for mitigating and adapting to the surface UHI effect, currently a hot topic in urban thermal environments. This study evaluated the relationship between land use/land cover (LULC) and land surface temperature (LST) formation in the temperate mountain valley city of Kathmandu, Nepal, because it is one of the megacities of South Asia, and the recent population increase has led to the rapid urbanization in the valley. Using Landsat images for 2000, 2013, and 2020, this study employed several approaches, including machine learning techniques, remote sensing (RS)-based parameter analysis, urban-rural gradient analysis, and spatial composition and pattern analysis to explore the surface UHI effect from the urban expansion and green space in the study area. The results revealed that Kathmandu’s surface UHI effect was remarkable. In 2000, the higher mean LST tended to be in the city’s core area, whereas the mean LST tended to move in the east, south, north, and west directions by 2020, which is compatible with urban expansion. Urban periphery expansion showed a continuous enlargement, and the urban core area showed a predominance of impervious surface (IS) on the basis of urban-rural gradient analysis. The city core had a lower density of green space (GS), while away from the city center, a higher density of GS predominated at the three time points, showing a lower surface UHI effect in the periphery compared to the city core area. This study reveals that landscape composition and pattern are significantly correlated with the mean LST in Kathmandu. Therefore, in discussing these findings in order to mitigate and adapt to prominent surface UHI effects, this study provides valuable information for sustainable urban planning and landscape design in mountain valley cities like Kathmandu.
Article
China has experienced an unprecedented rate of urbanization in recent decades. As a city with strong political and economic influences in the southwest of China, Chongqing is a typical example of rapidurban development in this period of time. To study the land cover changes and urban expansion of Chongqing, Landsat images from 1999 to 2018 were selected, processed, and quantitatively analysed The results showed that the built-up area of the city had increased tremendously during these years, yet vegetation still accounted for the vast majority of the city’s land area. Restricted by the local topography including mountains and hills and infrastructure constructions, the urbanization process that occurred in central Chongqing actually showed a dominant expansion direction, an obvious spatial clustering tendency, and significant spatio-temporal differences among various regions.
Article
Full-text available
Air pollution is among the world’s major environmental concerns. It remains a major health threat in India and is the leading environmental cause of morbidity in the country. There is considerable evidence that heavy and prolonged exposure to several air contaminants increases the cancer risk. The prevalence of breast cancer in citified environments with high exposure to air pollution has been seen to be elevated. Among various Indian cities, the Delhi cancer registry is having a high breast cancer incidence (28.6%). Owing to the recent and unprecedented global outbreak of coronavirus infectious disease (COVID-19), India is exploring every possible way of controlling its vigorous human transmission. Work from home culture is adopted so as to maintain social distancing during the lockdown. This momentary stoppage is substantially reducing the level of air pollution in several city areas across India dramatically. This paper (i) Overviews the breast cancer and air pollution association; (ii) Compiles the air quality data of Delhi monitored by CPCB during the COVID-19 pandemic lockdown time and compares it with pre-lockdown air quality data; (iii) Explores the reduced threat of breast cancer in Delhi during the nationwide lockdown. This work concluded that Air pollution serves a significant part in breast cancer occurrence. The countrywide lockdown in an attempt to prevent Covid-19 transmission has greatly improved the air quality of various Indian cities like Delhi. Also, with an unprecedented drop in rates of air pollution over Delhi, breast cancer occurrence may also decrease.
Article
Full-text available
This study explored the land use and land cover changes (LULCC) during 1981–2006 over central India and their impact on the surface temperature over this region. The land use maps were prepared from the Advanced Very High Resolution Radiometer (AVHRR) datasets to investigate the LULCC during 1981–2006 and the impact of LULCC was investigated from the Observation Minus Reanalysis method. The overall analysis indicated a decrease in the small vegetation lands and open forests during 1981–2006 and an increase in the dry lands, agricultural lands and dense forests during this period. As a probable consequence, the temperature trend increased by 0.076 °C per decade due to the LULCC over central India.
Article
Full-text available
Globally, extreme temperatures have severe impacts on the economy, human health, food and water security, and ecosystems. Mortality rates have been increased due to heatwaves in several regions. Specifically, megacities have high impacts with the increasing temperature and ever-expanding urban areas; it is important to understand extreme temperature changes in terms of duration, magnitude, and frequency for future risk management and disaster mitigation. Here we framed a novel Semi-Parametric quantile mapping method to bias-correct the CMIP6 minimum and maximum temperature projections for 199 megacities worldwide. The changes in maximum and minimum temperature are quantified in terms of climate indices (ETCCDI and HDWI) for the four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Cities in northern Asia and northern North America (Kazan, Samara, Heihe, Montréal, Edmonton, and Moscow) are warming at a higher rate compared to the other regions. There is an increasing and decreasing trend for the warm and cold extremes respectively. Heatwaves increase exponentially in the future with the increase in warming, that is, from SSP1-2.6 to SSP5-8.5. Among the CMIP6 models, a huge variability is observed, and this further increased as the warming increases. All climate indices have steep slopes for the far future (2066-2100) compared to the near future (2031-2065). Yet the variability among CMIP6 models in near future is high compared to the far future for cold indices.
Article
Simulation and prediction of land use land cover (LULC) has been presented using Hybrid CA-Markov model for the Mahi River basin. LULC information for the year 2000, 2010, and 2020 have been obtained from classification of Landsat TM, IRS -LISS III, and Sentinel 2 sensors, respectively. Fuzzy membership function and Analytical Hierarchical Process (AHP), a Multi-Criteria Evaluation (MCE) have been used for LULC change suitability map preparation. Population density, distance from road, settlement, streams, and reservoir/lakes, slope, and DEM are used as biophysical and socio-economic LULC change drivers. Model results have been validated for year 2020 and accuracy has been found as satisfactory 2020. Results revealed a significant change in forest, agriculture, barren and built-up LULC classes during different years. Agriculture and the built-up area may increase by 641 and 21 sq.km, respectively in 2030. The predicted LULC information provides necessary data to investigate the future hydrological and climatological scenario.
Article
Full-text available
The earth has been reshaped for millennia. The accelerating pace of anthropogenic activities has generated enormous impacts on the water environment. As one of the main drivers of landscape change, anthropogenic disturbance has brought many negative effects on rivers. Studying the relationship between anthropogenic disturbances and river water quality is of significance for regional conservation and ecosystem management, while the relationship remains poorly understood in the current. In this study, we quantified anthropogenic disturbances by introducing the concept of the hemeroby index and evaluated rivers’ water quality in eight sub-watersheds on the Loess Plateau. The results indicated that 37.5% of the sub-watersheds were in Eutrophic status, and 62.5% were in Marginal water quality index. The river water quality was most poor in the southwestern region near the Yellow River with high-level anthropogenic disturbance. A correlation analysis between water quality indicators and hemeroby suggested that anthropogenic disturbance contributed to a significant water quality deterioration trend (p < 0.01). The river water quality was relatively sensitive to the changes of completely disturbed land-use covers, including urban and industrial land. Our findings provide theoretical guidance for regional water resources conservation and ecosystem management in arid areas.
Article
The increase in urban land surface temperature (LST) has become an environmental challenge to urban dwellers and policymakers. To adopt mitigation plans, prediction, and pattern recognition of future temperature is very essential approaches. Therefore this present study intended to simulate future LST patterns using artificial neural networks (ANN) and recognize its spatio-temporal pattern using three different approaches such as hot and cold spot analysis, spatial autocorrelation, and fragmentation analysis. Simulation results show that the area under a comparatively higher temperature intensity zone is predicted to be increased over time. For example, in April month, 1709.73 ha area of >32.34 °C temperature zone in 2017 is predicted to be enlarged by 4079.97 ha in 2037. Accordingly, the results of pattern recognition reveal that area under significant cold spot of winter season decreased from 1046.24 ha in 2007 to 961.07 ha in 2027 and predicted to further decrease as 794.25 ha and 302 ha in 2027 and 2037 respectively. Similarly, very high spatial adjacency of LST with high Morain's I values (0.74–0.99) has been found both in actual and predicted years in summer season. Besides, the large core of uncomfortable low temperature fragmented into medium and small core over time while opposite result has been found in case of uncomfortable high temperature.
Article
Full-text available
PlanetScope satellite data with a 3-m resolution and near-daily global coverage have been increasingly used for land surface monitoring, ranging from land cover change detection to vegetative biophysics characterization and ecological assessments. Similar to other satellite data, effective screening of clouds and cloud shadows in PlanetScope images is a prerequisite for these applications, yet remains challenging as PlanetScope has 1) fewer spectral bands than other satellites hindering the use of traditional methods, and 2) inconsistent radiometric calibration across satellite sensors making the cloud/shadow detection using fixed thresholds unrealistic. To address these challenges, we developed a SpatioTemporal Integration approach for Automatic Cloud and Shadow Screening (‘STI-ACSS’), including two steps: (1) generating initial masks of clouds/shadows by integrating both spatial (i.e. cloud/shadow indices of an individual PlanetScope image) and temporal (i.e. reflectance outliers in PlanetScope image time series) information with an adaptive threshold approach; (2) a two-step fine-tuning on these initial masks to derive final masks by integrating morphological processing with an object-based cloud and cloud shadow matching. We tested STI-ACSS at six tropical sites representative of different land cover types (e.g. forest, urban, cropland, savannah, and shrubland). For each site, we evaluated the performance of STI-ACSS with reference to the manual masks of clouds/shadows, and compared it with four state-of-the-art methods, namely Function of mask (Fmask), Automatic Time-Series Analysis (ATSA), Iterative Haze Optimized Transformation (IHOT) and the default PlanetScope quality control layer. Our results show that, across all sites, STI-ACSS 1) has the highest average overall accuracy (98.03%), 2) generates an average producer accuracy of 95.53% for clouds and 89.48% for cloud shadows, and 3) is robust across sites and seasons. These results suggest the effectiveness of using STI-ACSS for cloud/shadow detection for PlanetScope satellites in the tropics, with potential to be extended to other satellite sensors with limited spectral bands.
Article
Excessive infrastructural developments, driven by urbanization, have not only brought destruction of forests, but also exacerbated the temperature of cities (or towns) due to formation of urban heat islands. Keeping such an urban system in mind, a nonlinear dynamical model is formulated in the proposed work in terms of system of differential equations. The model, comprising of forest resources, human population, urban infrastructural developments and temperature as system variables, is formulated on the assumption that infrastructural developments, induced through human population, escalate temperature of the region at the cost of deforestation. The derived model is mathematically analyzed for qualitative properties of its equilibrium solutions, extending from their existences to stabilities. Further, to demonstrate the impact of parametric variations on dynamical behavior, the system is also investigated for transcritical and Hopf - bifurcations. Quantitative analysis is also being executed with available numerical data to substantiate qualitative findings and to determine sensitiveness of equilibrium values of model outcomes towards system parameters. The results reveal that any of the parameters, which directly or indirectly, responsible for escalation in temperature of the region can put the system in a state of periodic oscillations, arises through Hopf - bifurcation. Therefore, it is suggested to control urban infrastructural developments through implementation of government strategies, which should include check over illegal encroachment of forested land for infrastructural developments.
Article
Full-text available
A correct and timely land use/land cover (LULC) classification provides indispensable information for the effective management of environmental and natural resources. However, earlier studies mapped the LULC map of Bilate Sub-basin using remote sensing images that were acquired for a single season. Hence, these studies did not consider the seasonal effects on the accuracy of LULC classification. Therefore, the objective of this study was to evaluate changes in classification accuracy for images acquired during wet and dry seasons in the Bilate Sub-basin. LULC of the study area was classified using the Landsat 8 satellite imageries. Based on field observations, we classified the LULC of the study area into 9 dominant classes. The classification for the two seasons resulted in a noticeable difference between the LULC composition of the study area because of seasonal differences in the classification accuracy. The overall accuracy of the LULC maps was 80%for the wet season and 90% for the dry season with Kappa coefficient values of 0.8 and 0.9 respectively. Therefore, the two seasons showed a significant difference in the overall accuracy of the classification. However, we discovered that when the classification accuracy was tested locally, that is for individual pixels, the results were not the same. In Bilate Sub-basin, several pixels (14.71%) were assigned to different LULC classes on the two seasons maps while 85.29% of the LULC classes remained unaltered in the two maps. According to the classification results, the season had a noticeable effect on the accuracy of LULC classification. This suggests that for LULC classification, multi-temporal images should be used rather than a single remote sensing image.
Article
Full-text available
The Diurnal Temperature Range (DTR) profoundly affects human health, agriculture, ecosystem , and socioeconomic systems. In this study, we analyzed past and future changes in DTR using gridded Climate Research Unit (CRU) datasets for the years 1950-2020 and an ensemble means of thirteen bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) models under different Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) scenarios for the rest of the 21st century over the southern slope of Central Himalaya, Nepal. Furthermore, the potential drivers (precipitation and cloud cover) of seasonal and annual DTR were studied using correlation analysis. This study found that the DTR trends generally declined; the highest decrease was observed in the pre-monsoon and winter at a rate of 0.09 °C/decade (p ≤ 0.01). As expected, DTR demonstrated a significant negative correlation with cloudiness and precipitation in all four seasons. Further, the decreased DTR was weakly related to the Sea Surface Temperature variation (SST) in the tropical Pacific and Indian Oceans. We found that the projected DTR changes in the future varied from a marginal increase under the SSP1-2.6 (only pre-monsoon) scenario to continued significant decreases under SSP2-4.5 and SSP5-8.5. Insights based on retrospective and prospective evaluation help to understand the long-term evolution of diurnal temperature variations.
Article
Background: Water consumption (WC) data is critical for managing water crises in water-scarce countries, especially in those countries that are lagging behind technical advancement for collecting accurate WC data at the household level. There is a lack of methods for estimating WC. Method: Here, we introduce a simplified method for estimating WC data based on regression analysis of satellite Land Surface Temperature (LST) data for the Khan-Younis Governorate, Gaza Strip, for the year 2017. We demonstrate the potential for using WC-LST models with and without low-resolution population data to estimate residential WC for two spatial resolutions: Landsat TIR moderate resolution (100 m), and MODIS TIR low resolution (1000 m). Residential WC data is measured based on readings from water meters of 28,000 individual houses. Results: The method performs better without the low-spatial resolution population data. The use of similar spatial resolution data or higher to Landsat 8 TIR (100 m) is a prerequisite for robust WC estimation. Although the method can easily be modified and applied in areas where no estimated water consumption data is available, using the regression equation might result in a poor result due to the use of different water supply sources as demonstrated for the periphery of Khan Younis city.
Article
Understanding how urban heat island (UHI) effect responds to urbanization is of great significance to develop appropriate UHI mitigation measures. However, the dynamic response of thermal environment to urban expansion is still less discussed. In this study, the spatiotemporal variation of thermal characteristics and its dynamic response to urbanization was monitored at the pixel level in 1987, 1996, 2007 and 2016 in Wuhan, China based on multi-temporal remotely sensed images. The results indicate that Wuhan experienced significant thermal deterioration during the 29-year period, which was largely attributed to the rapid urbanization from 1996 to 2007. Due to the high spatial heterogeneity of urban development, the thermal characteristic variation did not always spatially correspond to urbanization process. The urbanization dynamics alone can explain only 14.84% ~ 36.37% of the spatiotemporal variation in thermal environment throughout the study area. Nevertheless, the thermally deteriorated areas had good spatial consistence with the rapidly developed areas in all cases, suggesting that urban development could better explain the dynamic characteristics of thermal environment in more rapidly urbanized areas (with the R² values of 0.7013–0.9989). An obvious “context effect” was detected during the dynamic influence of urban development on thermal environment variation. Urban development based on the increase of construction density only strengthened UHI intensity, but contributed little to the spread of thermal environment deterioration. Urban expansion with amounts of newly expanded construction land should be responsible for thermal environment deterioration. These findings provide detailed information and sound evidence to adjust urban planning options accordingly to improve thermal environment.
Article
Full-text available
Temporal aspects of the urban heat island (UHI) of Vancouver, British Columbia, are demonstrated using differences of screen-level air temperature observed at an urban (downtown) and rural (farmland) site for three years. On an annual basis, the UHI is at its maximum near the middle of the night and its minimum is in mid-afternoon. Growth of the nocturnal UHI is driven by rural cooling rates in the early evening, which are much greater than the almost constant rates in the city. Growth starts earlier in winter. The largest UHI occurs in the fall, and the smallest in the spring. In daytime there is often a “cool island,” especially in summer. There is an approximately inverse square root control of the UHI by wind speed and the effect of cloud type and amount follows the Bolz relation. Combining the two gives a “weather factor” that is linearly related to maximum UHI magnitude. Seasonal variation of the UHI is shown to be inversely related to the thermal admittance of the rural site, which itself is controlled largely by soil moisture status. This is done by calculating a “potential” UHI that is free of weather effects; a value that approximately conforms to that predicted by the SHIM numerical model. Surface wetting caused by recent rain, fog, or melting snow also is found to reduce UHI magnitude. While not quantified, marine advective effects appear to modify the UHI, especially the summer daytime cool island. [Key words: urban heat island (UHI), cooling rates, thermal admittance, Vancouver.]
Article
Full-text available
Based on the 1960-2009 meteorological data from 559 stations across China, the urbanization effect on the diurnal temperature range (DTR) was evaluated in this study. Different roles of urbanization were specially detected under solar dimming and solar brightening. During the solar dimming time, both urban and rural stations showed decreasing trends in maximum temperature (T max) because of decreased radiation, suggesting that the dimming effects are not only evident in urban areas but also in rural areas. However, minimum temperature (T min) increased more substantially in urban areas than in rural areas during the dimming period, resulting in a greater decrease in the DTR in the urban areas. When the radiation reversed from dimming to brightening, the change in the DTR became different. The T max increased faster in rural areas, suggesting that the brightening could be much stronger in rural areas than in urban areas. Similar trends of T min between urban and rural areas appeared during the brightening period. The urban DTR continued to show a decreasing trend because of the urbanization effect, while the rural DTR presented an increasing trend. The remarkable DTRdifference in the urban and rural areas showed a significant urbanization effect in the solar brightening time.
Article
Full-text available
Urban heat island intensities (UHI) have been assessed based on in situ measurements and satellite-derived observations for the megacity Delhi during a selected period in March 2010. A network of micrometeorological observational stations was set up across the city. Site selection for stations was based on dominant land use–land cover (LULC) classification. Observed UHI intensities could be classified into high, medium and low categories which overall correlated well with the LULC categories viz. dense built-up, medium dense built-up and green/open areas, respectively. Dense urban areas and highly commercial areas were observed to have highest UHI with maximum hourly magnitude peaking up to 10.7 °C and average daily maximum UHI reaching 8.3 °C. UHI obtained in the study was also compared with satellite-derived land surface temperatures (LST). UHI based on in situ ambient temperatures and satellite-derived land surface temperatures show reasonable comparison during nighttime in terms of UHI magnitude and hotspots. However, the relation was found to be poor during daytime. Further, MODIS-derived LSTs showed overestimation during daytime and underestimation during nighttime when compared with in situ skin temperature measurements. Impact of LULC was also reflected in the difference between ambient temperature and skin temperature at the observation stations as built-up canopies reported largest gradient between air and skin temperature. Also, a comparison of intra-city spatial temperature variations based UHI vis-à-vis a reference rural site temperature-based UHI indicated that UHI can be computed with respect to the station measuring lowest temperature within the urban area in the absence of a reference station in the rural area close to the study area. Comparison with maximum and average UHI of other cities of the world revealed that UHI in Delhi is comparable to other major cities of the world such as London, Tokyo and Beijing and calls for mitigation action plans.
Article
Full-text available
Analyses of the year-month mean maximum and minimum surface thermometric record have now been updated and expanded to cover three large countries in the Northern Hemisphere (the contiguous United States, the Soviet Union, and the People's Republic of China). They indicate that most of the warming which has occurred in these regions over the past four decades can be attributed to an increase of mean minimum (mostly nighttime) temperatures. Mean maximum (mostly daytime) temperatures display little or no warming. In the USA and the USSR (no access to data in China) similar characteristics are also reflected in the changes of extreme seasonal temperatures, e.g., increase of extreme minimum temperatures and little or no change in extreme maximum temperatures. The continuation of increasing minimum temperatures and little overall change of the maximum leads to a decrease of the mean (and extreme) temperature range, an important measure of climate variability.The cause(s) of the asymmetric diurnal changes are uncertain, but there is some evidence to suggest that changes in cloud cover play a direct role (where increases in cloudiness result in reduced maximum and higher minimum temperatures). Regardless of the exact cause(s), these results imply that either: (1) climate model projections considering the expected change in the diurnal temperature range with increased levels of the greenhouse gases are underestimating (overestimating) the rise of the daily minimum (maximum) relative to the maximum (minimum), or (2) the observed warming in a considerable portion of the Northern Hemisphere landmass is significantly affected by factors unrelated to an enhanced anthropogenically-induced greenhouse effect.
Article
Full-text available
Observations indicate that greenhouse induced twentieth-century warming has been strongly modulated by variations in surface solar radiation. Between the 1950s and 1980s, declining surface solar radiation (“global dimming”) likely caused a dampening of global warming, whereas increasing surface solar radiation (“brightening”) may have contributed to the rapid warming in the last 2 decades, and possibly also in the first half of the twentieth century. This is also reflected in the decadal evolution of diurnal temperature range, which is highly correlated with surface solar radiation, and which shows a distinct transition from a strong decrease between the 1950s and 1980s, toward a leveling off thereafter. The present study investigates to what extent these effects are simulated in the latest generation of global climate models used in the fourth Intergovernmental Panel on Climate Change (IPCC) assessment report (AR4) (phase 3 of the Coupled Model Intercomparison Project (CMIP3) models). While these models reproduce the overall twentieth century warming over global land surfaces well, they underestimate the decadal variations in the warming and particularly also in diurnal temperature range, indicative of a lack of decadal variations in surface solar radiation in the models.
Article
Full-text available
Monthly and seasonal relationships between urban-rural differences in minimum, maximum, and average temperatures measured at surface-based observation stations were compared to satellite-derived Advanced Very High Resolution Radiometer estimates of a normalized difference vegetation index (NDVI) and surface radiant temperature (Tsfc). The relationships between surface- and satellite-derived variables were developed during 1989-91 and tested on data acquired during 1992-93. The urban-rural differences in air temperature were linearly related to urban-rural differences in the NDVI and Tsfc. A statistically significant but relatively small (less than 40%) amount of the variation in these urban-rural differences in air temperature [the urban heat island (UHI) bias] was associated with variation in the urban-rural differences in NDVI and Tsfc. A comparison of the satellite-based estimates of the UHI bias with population-based estimates of the UHI bias indicated similar levels of error. The use of satellite-derived data may contribute to a globally consistent method for analysis of the urban heat island bias.
Article
Full-text available
The diurnal range of surface air temperature (DTR) has decreased worldwide during the last 4-5 decades and changes in cloud cover are often cited as one of the likely causes. To determine how clouds and moisture affect DTR physically on daily bases, the authors analyze the 30-min averaged data of surface meteorological variables and energy fluxes from the the First International Satellite Land Surface Climatology Project Field Experiment and the synoptic weather reports of 1980-1991 from about 6500 stations worldwide. The statistical relationships are also examined more thoroughly in the historical monthly records of DTR, cloud cover, precipitation, and streamflow of this century. It is found that clouds, combined with secondary damping effects from soil moisture and precipitation, can reduce DTR by 25%-50% compared with clear-sky days over most land areas; while atmospheric water vapor increases both nighttime and daytime temperatures and has small effects on DTR. Clouds, which largely determine the geographic patterns of DTR, greatly reduce DTR by sharply decreasing surface solar radiation while soil moisture decreases DTR by increasing daytime surface evaporative cooling. Clouds with low bases are most efficient in reducing the daytime maximum temperature and DTR mainly because they are very effective in reflecting the sunlight, while middle and high clouds have only moderate damping effects on DTR. The DTR reduction by clouds is largest in warm and dry seasons such as autumn over northern midlatitudes when latent heat release is limited by the soil moisture content. The net effects of clouds on the nighttime minimum temperature is small except in the winter high latitudes where the greenhouse warming effect of clouds exceeds their solar cooling effect. The historical records of DTR of the twentieth century covary inversely with cloud cover and precipitation on interannual to multidecadal timescales over the United States, Australia, midlatitude Canada, and former U.S.S.R., and up to 80% of the DTR variance can be explained by the cloud and precipitation records. Given the strong damping effect of clouds on the daytime maximum temperature and DTR, the well-established worldwide asymmetric trends of the daytime and nighttime temperatures and the DTR decreases during the last 4-5 decades are consistent with the reported increasing trends in cloud cover and precipitation over many land areas and support the notion that the hydrologic cycle has intensified.
Article
Full-text available
An appreciable number of nonurban stations in the United States and Canada have been identified with statistically significant (at the 90% level) decreasing trends in the monthly mean diurnal temperature range between 1941-80. The percentage of stations in the network showing the decrease is higher than expected due to chance throughout the year, with a maximum reached during late summer and early autumn and a minimum in December. Monte Carlo tests indicate that during five months the field significance of the decreasing range is above the 99% level, and in 12 months above the 95% level. There is a negligible probability that such a result is due to chance. In contrast, trends of increasing or decreasing monthly mean maximum or minimum temperatures have at most only two months with field significance at or above the 90% level. This is related to the tendency toward increasing temperature in the western portions of North America and decreasing temperature in the east.The physical mechanism responsible for the observed decrease in the diurnal range is not known. Possible explanations include greenhouse effects such as changes in cloudiness, aerosol loading, atmospheric water vapor content, or carbon dioxide. Change in circulation is also a possibility, but it will be difficult to isolate since the patterns of the decreased diurnal temperature range have high field significance throughout much of the year, relatively low spatial coherence, and occur at many stations where individual trends in the maximum and minimum temperature are not statistically significant. Our data show that the trends in the maximum and minimum temperatures may differ considerably from trends in the mean.
Article
Full-text available
We propose a new mechanism that could contribute to The highly interactive nature of general circulation models the observed decrease in the diurnal temperature range (DTR) (GCMs) as well as weaknesses in their parameterizations make it over the last century: the physiological behavior of vegetation in difficult to identify the mechanisms underlying predicted changes response to climate. Using a physiologically based land surface in the DTR. The purpose of this study is to examine how the model, we analyze the influence of vegetation on the response of diurnal temperature cycle of vegetated land surfaces responds to the D TR to perturbations in the state of the climate and changes in external forcing and the biophysical state of the vegetation. Increasing down-welling long wave radiation and vegetation. We use the SiB2 land surface model (Sellers et al., surface air temperature together, conditions that could occur as a 1996a) in an off-line mode with prescribed meteorology for a result of doubling of atmospheric CO2, produced little change in number of scenarios highlighting the impact of vegetation on the DTR. Changes in the state of the vegetation (i.e. amount, DTR. Off-line simulations do not account for feedback between physiological capacity, stress) produce changes in the DTR of the order or larger than observed. Results emphasize that DTR modeling studies need to consider vegetation responses and suggest that recently reported increases in vegetation over the last decade could contribute to the observed decreases in the DTR.
Article
Full-text available
The local temperature is one of the major climatic elements to record the changes in the atmospheric environment brought about by industrialization, increasing population and massive urbanization. The present study deals with the annual and seasonal temperature trends and anomalies for maximum, minimum and mean temperatures of the four meteorological stations of the National Capital Region (NCR) of India namely Safdarjung, Palam, Gurgaon and Rohtak for the past few decades and their association with the development through urbanization processes. The annual mean maximum temperature did not show any specific trend; however a consistent increasing trend was seen in the annual mean minimum temperatures indicating an overall warming trend over the NCR especially after 1990. This warming trend is contrary to the cooling trend observed by earlier studies till 1980's in various other cities of India including Delhi. However, the temperature trends in annual mean minimum temperatures reported in various countries (USA, Turkey, Italy, etc.) across the world showed warming trends to be associated to the urbanization process of the cities also. The current warming trends in temperature in the NCR Delhi based on the annual mean minimum temperatures have thus been supported by the trends in other parts of the world and could be utilized to infer the development proc-ess in this region. The urbanization pattern within Delhi is reflected by the trends of differences in annual mean mini-mum temperature of the two stations within the city namely Safdarjung and Palam. The significance of the warming trends of the annual minimum temperature for the urban heat island effect is also discussed.
Article
Full-text available
There has been paucity of field campaigns in India in past few decades on the urban heat island intensities (UHI). Re-mote sensing observations provide useful information on urban heat island intensities and hotspots as supplement or proxy to in-situ surface based measurements. A case study has been undertaken to assess and compare the UHI and hotspots based on in-situ measurements and remote sensing observations as the later method can be used as a proxy in absence of in-situ measurements both spatially and temporally. Capital of India, megacity Delhi has grown by leaps and bounds during past 2 -3 decades and strongly represents tropical climatic conditions where such studies and field cam-paigns are practically non-existent. Thus, a field campaign was undertaken during summer, 2008 named DELHI-I (Delhi Experiments to Learn Heat Island Intensity-I) in this megacity. Urban heat island effects were found to be most dominant in areas of dense built up infrastructure and at commercial centers. The heat island intensity (UHI) was ob-served to be higher in magnitude both during afternoon hours and night hours (maximum up to 8.3˚C) similar to some recent studies. The three high ranking urban heat island locations in the city are within commercial and/or densely populated areas. The results of this field campaign when compared with MODIS-Terra data of land surface temperature revealed that UHI hotspots are comparable only during nighttime. During daytime, similar comparison was less satis-factory. Further, available relationship of maximum UHI with population data is applied for the current measurements and discussed in the context of maximum UHI of various other countries.
Article
Full-text available
The rapid expansion of urban areas due to rise in population and economic growth is increasing additional demand on natural resources thereby causing land-use changes especially in megacities. Therefore, serious problems associated with rapid development such as additional infrastructure, informal settlements, environmental pollution, destruction of ecological structure and scarcity of natural resources has been studied carefully using remote sensing and GIS tech-nologies for a rapidly grown megacity namely, Delhi. The present work evaluates the land use/land cover (LULC) changes and urban expansion in Mega city Delhi and highlights the major impact of rapid urbanization and population growth on the land cover changes which needs immediate attention. The results indicate that the city is expanding to-wards its peripheral region with the conversion of rural regions in to urban expansions. Built-up area of Delhi wit-nessed an overall increment from 540.7 km² to 791.96 km² or 16.86% of the total city area (1490 km² ) during the study period 1997 to 2008 which mainly came from agriculture land, waste land, scrub-land, sandy areas and water bodies. The increment in forest cover of 0.5 % is very small when considering the increment in built up category to 17%. Total area of waterbodies has reduced by 52.9% in a ten year period (58.26 km² in 1997 to 27.43 km² in 2008) with shallow waterbodies now having a dismal presence. LULC changes are studied with the urban growth parameters such as population, vehicles, gross state domestic product etc. The results lay emphasis on the concepts of urban planning to be applied such that more consideration is towards the preservation and management of natural land use classes which will increase the quality of life in an urban environment.
Article
Full-text available
Analysis of the global mean surface air temperature has shown that its increase is due, at least in part, to differential changes in daily maximum and minimum temperatures, resulting in a narrowing of the diurnal temperature range (DTR). The analysis, using station metadata and improved areal coverage for much of the Southern Hemisphere landmass, indicates that the DTR is continuing to decrease in most parts of the world, that urban effects on globally and hemispherically averaged time series are negligible, and that circulation variations in parts of the Northern Hemisphere appear to be related to the DTR. Atmospheric aerosol loading in the Southern Hemisphere is much less than that in the Northern Hemisphere, suggesting that there are likely a number of factors, such as increases in cloudiness, contributing to the decreases in DTR.
Article
Full-text available
Monthly mean maximum and minimum temperatures for over 50% (10%) of the Northern (Southern) Hemisphere landmass, accounting for 37% of the global landmass, indicate that the rise of the minimum temperature has occurred at a rate three times that of the maximum temperature during the period 1951-90 (0.84°C versus 0.28°C). The decrease of the diurnal temperature range is approximately equal to the increase of mean temperature. The asymmetry is detectable in all seasons and in most of the regions studied.The decrease in the daily temperature range is partially related to increases in cloud cover. Furthermore, a large number of atmospheric and surface boundary conditions are shown to differentially affect the maximum and minimum temperature. Linkages of the observed changes in the diurnal temperature range to large-scale climate forcings, such as anthropogenic increases in sulfate aerosols, greenhouse gases, or biomass burning (smoke), remain tentative. Nonetheless, the observed decrease of the diurnal temperature range is clearly important, both scientifically and practically.
Article
Full-text available
“Global warming” due to the increase of greenhouse gases is a major determinant of climate change, but the major changes in land use, such as urbanization, agriculture, deforestation, would seem to be also very important. Unfortunately, their impacts on climate change have been very difficult to separate because they both tend to produce surface warming. We have used the NCEP/NCAR Reanalysis (insensitive to surface changes) to estimate the surface temperature trends due to changes in the land use. For this purpose we subtracted the Reanalysis surface temperatures from the station observations. The climate trends are different for minimum and maximum temperature: for example minimum temperatures within urban areas increase substantially with time, as the heat accumulated in the buildings during the day is radiated out. Maximum temperatures in urban areas may actually decrease slightly, due to shading or low-level aerosols. As a result, the diurnal temperature range (Tmax minus Tmin) tends to decrease with time. From our estimates, about half of the change in diurnal temperature range would seem to be due to changes in the land use. Our estimate of the impact on the mean temperature is ~0.3C/decade, or twice the previous estimate based on urbanization only.
Article
Full-text available
Background: Most heat-related deaths occur in cities, and future trends in global climate change and urbanization may amplify this trend. Understanding how neighborhoods affect heat mortality fills an important gap between studies of individual susceptibility to heat and broadly comparative studies of temperature–mortality relationships in cities. Objectives: We estimated neighborhood effects of population characteristics and built and natural environments on deaths due to heat exposure in Maricopa County, Arizona (2000–2008). Methods: We used 2000 U.S. Census data and remotely sensed vegetation and land surface temperature to construct indicators of neighborhood vulnerability and a geographic information system to map vulnerability and residential addresses of persons who died from heat exposure in 2,081 census block groups. Binary logistic regression and spatial analysis were used to associate deaths with neighborhoods. Results: Neighborhood scores on three factors—socioeconomic vulnerability, elderly/isolation, and unvegetated area—varied widely throughout the study area. The preferred model (based on fit and parsimony) for predicting the odds of one or more deaths from heat exposure within a census block group included the first two factors and surface temperature in residential neighborhoods, holding population size constant. Spatial analysis identified clusters of neighborhoods with the highest heat vulnerability scores. A large proportion of deaths occurred among people, including homeless persons, who lived in the inner cores of the largest cities and along an industrial corridor. Conclusions: Place-based indicators of vulnerability complement analyses of person-level heat risk factors. Surface temperature might be used in Maricopa County to identify the most heat-vulnerable neighborhoods, but more attention to the socioecological complexities of climate adaptation is needed.
Article
Full-text available
1] Diurnal temperature range (DTR) is an important climate change index. Information on this parameter comes primarily from sparse and unevenly distributed observations of shelter air temperature. In this study, five years of GOES-8 based estimates of land surface temperature (LST) over the United States are used to evaluate DTR at high spatial resolution. The spatial and temporal patterns that emerged show a high degree of consistency with independent satellite estimates of the Normalized Difference Vegetation Index (NDVI). Specifically, the arid regions in the western and central U.S. have larger DTRs than the eastern United States or the northwest coast. When stratified by four major surface types, the western U. S. DTRs over these surface types are larger than over the eastern part. It is also observed that urban areas have the lowest DTRs especially over the polluted eastern U. S. The similarity of the DTR spatial and temporal patterns and variations of the independent satellite based vegetation index are encouraging and suggest that satellite based estimates of DTR carry a strong signal on surface conditions which are responsive to climate change.
Article
Full-text available
New data acquisitions are used to examine recent global trends in maximum temperature, minimum temperature, and the diurnal temperature range (DTR). On average, the analysis covers the equivalent of 71% of the total global land area, 17% more than in previous studies. Consistent with the IPCC Third Assessment Report, minimum temperature increased more rapidly than maximum temperature (0.204 vs. 0.141°C dec-1) from 1950-2004, resulting in a significant DTR decrease (-0.066°C dec-1). In contrast, there were comparable increases in minimum and maximum temperature (0.295 vs. 0.287°C dec-1) from 1979-2004, muting recent DTR trends (-0.001°C dec-1). Minimum and maximum temperature increased in almost all parts of the globe during both periods, whereas a widespread decrease in the DTR was only evident from 1950-1980.
Article
Full-text available
This paper presents an evaluation of the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared bands and the status of land surface temperature (LST) version-3 standard products retrieved from Terra MODIS data. The accuracy of daily MODIS LST products has been validated in more than 20 clear-sky cases with in situ measurement data collected in field campaigns in 2000–2002. The MODIS LST accuracy is better than 1C in the range from 210 to 50C. Refinements and improvements were made to the new version of MODIS LST product generation executive code. Using both Terra and Aqua MODIS data for LST retrieval improves the quality of the LST product and the diurnal feature in the product due to better temporal, spatial and angular coverage of clear-sky observations.
Article
Full-text available
The diurnal temperature range (DTR) at weather observation stations that make up the U.S. Historical Climatology Network was evaluated with respect to the predominant land use/land cover associated with the stations within three radii intervals (100, 1000, and 10000 m) of the stations. Those stations that were associated with predominantly rural land use/land cover (LULC) usually displayed the greatest observed DTR, whereas those associated with urban related land use or land cover displayed the least observed DTR. The results of this study suggest that significant differences in the climatological DTR were observed and could be attributed to the predominant LULC associated with the observation stations. The results also suggest that changes in the pre-dominant LULC conditions, within as great as a 10,000 m radius of an observation station, could significantly influence the climatological DTR. Future changes in the predominant LULC associated with observation sites should be monitored similar to the current practice of monitoring changes in instruments or time of observation at the observations sites. 10 refs., 6 tabs.
Article
Full-text available
High temperature and humidity conditions are associated with short-term elevations in the mortality rate in many United States cities. Previous research has quantified this relationship in an aggregate manner over large metropolitan areas, but within these areas the response may differ based on local-scale variability in climate, population characteristics, and socio-economic factors. We compared the mortality response for 48 Zip Code Tabulation Areas (ZCTAs) comprising Philadelphia County, PA to determine if certain areas are associated with elevated risk during high heat stress conditions. A randomization test was used to identify mortality exceedances for various apparent temperature thresholds at both the city and local scale. We then sought to identify the environmental, demographic, and social factors associated with high-risk areas via principal components regression. Citywide mortality increases by 9.3% on days following those with apparent temperatures over 34°C observed at 7:00 p.m. local time. During these conditions, elevated mortality rates were found for 10 of the 48 ZCTAs concentrated in the west-central portion of the County. Factors related to high heat mortality risk included proximity to locally high surface temperatures, low socioeconomic status, high density residential zoning, and age. Within the larger Philadelphia metropolitan area, there exists statistically significant fine-scale spatial variability in the mortality response to high apparent temperatures. Future heat warning systems and mitigation and intervention measures could target these high risk areas to reduce the burden of extreme weather on summertime morbidity and mortality.
Article
Full-text available
A fundamental determinant of climate and life on our planet is the solar radiation (sunlight) incident at the Earth’s surface. Any change in this precious energy source affects our habitats profoundly. Until recently, for simplicity and lack of better knowledge, the amount of solar radiation received at the Earth surface was assumed to be stable over the years. However, there is increasing observational evidence that this quantity undergoes significant multi-decadal variations, which need to taken into account in discussions of climate change and solar energy generation. Coherent periods and regions with prevailing declines (“dimming”) and inclines (“brightening”) in surface solar radiation have been detected in the worldwide observational networks, often in accord with anthropogenic air pollution patterns. This paper highlights the main characteristics of this phenomenon, and provides a conceptual framework for its causes as well as an overview over potential environmental implications.
Article
Full-text available
Abstract. We review the surface air temperature record of the past 150 years, considering the homogeneity of the basic data and the standard errors of estimation of the average hemispheric and global estimates. We present global fields of surface temperature change over the two 20-year periods of greatest warming this century, 1925–1944 and 1978–1997. Over these periods, global temperatures rose by 0.378 and 0.328C, respectively. The twentieth-century warming has been accompanied by a decrease in those areas of the world affected by exceptionally cool temperatures and to a lesser extent by increases in areas affected by exceptionally warm temperatures. In recent decades there have been much greater increases in night minimum temperatures than in day maximum temperatures, so that over 1950–1993 the diurnal temperature range has decreased by 0.088C per decade. We discuss the recent divergence of surface and satellite temperature measurements of the lower troposphere and consider the last 150 years in the context of the last millennium. We then provide a globally complete absolute surface air temperature climatology on a 18 3 18 grid. This is primarily based on data for 1961–1990. Extensive interpolation had to be undertaken over both polar regions and in a few other regions where basic data are scarce, but we believe the climatology is the most consistent and reliable of absolute surface air temperature conditions over the world. The climatology indicates that the annual average surface temperature of the world is 14.08C (14.68C in the Northern Hemisphere (NH) and 13.48C for the Southern Hemisphere). The annual cycle of global mean temperatures follows that of the land-dominated NH, with a maximum in July of 15.98C and a minimum in January of 12.28C.
Article
Full-text available
It has been widely accepted that diurnal temperature range (DTR) decreased on a global scale during the second half of the twentieth century. Here we show however, that the long-term trend of annual DTR has reversed from a decrease to an increase during the 1970s in Western Europe and during the 1980s in Eastern Europe. The analysis is based on the high-quality dataset of the European Climate Assessment and Dataset Project, from which we selected approximately 200 stations, covering the area from Iceland to Algeria and from Turkey to Russia for 1950 to 2005. We investigate national and regional annual means as well as the pan-European mean with respect to trends and reversal periods. 17 of the 24 investigated regions including the pan-European mean show a statistical significant increase since 1990 at the latest. Of the remaining 7 regions, 2 show a non-significant increase, 3 a significant decrease and the remaining 2 no significant trend. The long-term change in DTR is governed by both surface shortwave and longwave radiation, the former of which has undergone a change from dimming to brightening. Consequently, we discuss the connections between DTR, shortwave radiation and sulfur emissions which are thought to be amongst the most important factors influencing the incoming solar radiation through the primary and secondary aerosol effect. We find reasonable agreement between trends in SO2 emissions, radiation and DTR in areas affected by high pollution. Consequently, we conclude that the long-term trends in DTR are mostly determined by changes in emissions and the associated changes in incoming solar radiation.
Article
Full-text available
Many studies have linked weather to mortality; however, role of such critical factors as regional variation, susceptible populations, and acclimatization remain unresolved. We applied time-series models to 107 US communities allowing a nonlinear relationship between temperature and mortality by using a 14-year dataset. Second-stage analysis was used to relate cold, heat, and heat wave effect estimates to community-specific variables. We considered exposure timeframe, susceptibility, age, cause of death, and confounding from pollutants. Heat waves were modeled with varying intensity and duration. Heat-related mortality was most associated with a shorter lag (average of same day and previous day), with an overall increase of 3.0% (95% posterior interval: 2.4%-3.6%) in mortality risk comparing the 99th and 90th percentile temperatures for the community. Cold-related mortality was most associated with a longer lag (average of current day up to 25 days previous), with a 4.2% (3.2%-5.3%) increase in risk comparing the first and 10th percentile temperatures for the community. Mortality risk increased with the intensity or duration of heat waves. Spatial heterogeneity in effects indicates that weather-mortality relationships from 1 community may not be applicable in another. Larger spatial heterogeneity for absolute temperature estimates (comparing risk at specific temperatures) than for relative temperature estimates (comparing risk at community-specific temperature percentiles) provides evidence for acclimatization. We identified susceptibility based on age, socioeconomic conditions, urbanicity, and central air conditioning. Acclimatization, individual susceptibility, and community characteristics all affect heat-related effects on mortality.
Article
Full-text available
The most important anthropogenic influences on climate are the emission of greenhouse gases and changes in land use, such as urbanization and agriculture. But it has been difficult to separate these two influences because both tend to increase the daily mean surface temperature. The impact of urbanization has been estimated by comparing observations in cities with those in surrounding rural areas, but the results differ significantly depending on whether population data or satellite measurements of night light are used to classify urban and rural areas. Here we use the difference between trends in observed surface temperatures in the continental United States and the corresponding trends in a reconstruction of surface temperatures determined from a reanalysis of global weather over the past 50 years, which is insensitive to surface observations, to estimate the impact of land-use changes on surface warming. Our results suggest that half of the observed decrease in diurnal temperature range is due to urban and other land-use changes. Moreover, our estimate of 0.27 degrees C mean surface warming per century due to land-use changes is at least twice as high as previous estimates based on urbanization alone.
Article
Full-text available
Mortality increases with hot weather, although the extent to which lives are shortened is rarely quantified. We compare the extent to which short-term mortality displacement can explain heat deaths in Delhi, São Paulo, and London given contrasting demographic and health profiles. We examined time-series of daily mortality data in relation to daily ambient temperature using Poisson models and adjusting for season, relative humidity, rainfall, particulate air pollution, day of the week, and public holidays. We used unconstrained distributed lag models to identify the extent to which heat-related excesses were followed by deficits (mortality displacement). For each city, an increase in all-cause mortality was observed with same-day (lag 0) and previous day (lag 1) temperatures greater than a threshold of 20 degrees C. At lag 0, the excess risk was greatest in Delhi and smallest in London. In Delhi, an excess was apparent up to 3 weeks after exposure, after which a deficit was observed that offset just part of the overall excess. In London, the heat excess persisted only 2 days and was followed by deficits, such that the sum of effects was 0 by day 11. The pattern in São Paulo was intermediate between these. The risk summed over the course of 28 days was 2.4% (95% confidence interval = 0.1 to 4.7%) per degree greater than the heat threshold in Delhi, 0.8% (-0.4 to 2.1%) in São Paulo and -1.6% (-3.4 to 0.3%) in London. Excess risks were sustained up to 4 weeks for respiratory deaths in São Paulo and London and for children in Delhi. Heat-related short-term mortality displacement was high in London but less in Delhi, where infectious and childhood mortality still predominate.
Article
Full-text available
A regional coupled climate–chemistry–aerosol model is developed to examine the impacts of anthropogenic aerosols on surface temperature and precipitation over East Asia. Besides their direct and indirect reduction of short-wave solar radiation, the increased cloudiness and cloud liquid water generate a substantial downward positive long-wave surface forcing; consequently, nighttime temperature in winter increases by +0.7°C, and the diurnal temperature range decreases by −0.7°C averaged over the industrialized parts of China. Confidence in the simulated results is limited by uncertainties in model cloud physics. However, they are broadly consistent with the observed diurnal temperature range decrease as reported in China, suggesting that changes in downward long-wave radiation at the surface are important in understanding temperature changes from aerosols. • anthropogenic aerosols • diurnal temperature range • long-wave radiative forcing • regional climate change • second indirect effect
Article