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Urbanization induced changes in land use dynamics and its nexus to ecosystem service values: A spatiotemporal investigation to promote sustainable urban growth
Abstract
Proper knowledge regarding the spatial dependence of ecosystem service values (ESVs) on the changes in land use dynamics is essential for environmental management as well as sustainable urban development. To investigate this complex association concerning a fast-growing secondary city, this study estimated the integrated land use dynamic degree (ILUDD), uniform annual land use transition intensity (Wtn), and entropy index of land use mix (LUM), and the ESVs for Raiganj urban agglomeration (UA). The overall association between the three indices and the ESVs is explored using the spatial lag and spatial error model. For the local level association, the geographically weighted regression (GWR) is applied. The output showed that changes in ILUDD and LUM indicate over −20 unit and −2 unit changes in the ESVs of built-up with 1 unit increase in ILUDD and LUM, respectively. However, the ILUDD coefficient score concerning vegetation ESV was observed around +25. The Wtn also represented a significant loss of natural vegetation from every administrative unit of Raiganj UA. The relation between urban growth type and landscape patches is analyzed using Getis-Ord-Gi. It is found that the promotion of compact growth can be the best possible solution to preserve the environmental quality in this region.
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To analyse and characterise land use-land cover (LULC) change, remote sensing (RS) data and geographic information system (GIS) approaches are required. The landscape metrics are also extensively used to explain the structure and pattern of the spatial landscape. This case study has been conducted in the area of the Bhagirathi-Hugli River banks in West Bengal. The study area’s satellite image data from various periods (1989-2017) were used to analyse the spatiotemporal variation of LULC change. The LULC fragmentation was analysed using a total of six landscape measures. Landscape metrics such as Number of Patches (NP), Largest Patch Index (LPI), Landscape Shape Index (LSI), Mean Shape Index (MSI), Contagion (CONTAG), and Shannon’s Diversity Index were used to determine the changes over four different periods. The main features of land use change were the continuous expansion of built-up area (9.30 km ² ), vegetation (189.14 km ² ), and the decrease in agricultural fallow land and water bodies from 1989 to 2017. The landscape pattern in the study area has also changed significantly. The landscape metrics indicate that the studied region had a highly fragmented landscape during the study period. The proposed technique is easy to use and can address more than one metric while selecting the appropriate setting can prove problematic.
The spatial variation of correlation between Cd accumulation and its impact factors plays an important role in precise management of Cd contaminated farmland. Samples of topsoils (n = 247) were collected from suburban farmland located at the junction of the Yellow River Basin and the Huaihe River Basin in China using a 200 m × 200 m grid system. The total and available contents of Cd (T-Cd and A-Cd) in topsoils were analyzed by ICP-MS, and their spatial distribution was analyzed using kriging interpolation with the GIS technique. Geographically weighted regression (GWR) models were applied to explore the spatial variation and their influencing mechanisms of relationships between major environmental factors (pH, organic matter, available phosphorus (A-P)) and Cd accumulation. Spatial distribution showed that T-Cd, A-Cd and their influencing factors had obvious spatial variability, and high value areas primarily cluster near industrial agglomeration areas and irrigation canals. GWR analysis revealed that relationships between T-Cd, A-Cd and their environmental factors presented obvious spatial heterogeneity. Notably, there was a significant negative correlation between soil pH and T-Cd, A-Cd, but with the increase of pH in soil the correlation decreased. A novel finding of a positive correlation between OM and T-Cd, A-Cd was observed, but significant positive correlation only occurred in the high anthropogenic input area due to the complex effects of organic matter on Cd activity. The influence intensity of pH and OM on T-Cd and A-Cd increases under the strong influence of anthropogenic sources. Additionally, T-Cd and A-Cd were totally positively related to soil A-P, but mostly not significantly, which was attributed to the complexity of the available phosphorus source and the differences in Cd contents in chemical fertilizer. Furthermore, clay content might be an important factor affecting the correlation between Cd and soil properties, considering that the correlation between Cd and pH, SOM, A-P was significantly lower in areas with lower clay particles. This study suggested that GWR was an effective tool to reveal spatially varying relationships at field scale, which provided a new idea to further explore the related influencing factors on spatial distribution of contaminants and to realize precise management of a farmland environment.
When validating Land Use Cover (LUC) products, pattern analysis can be used to assess the agreement between the patterns of two maps. It therefore complements other methods and techniques that focus exclusively on the quantity (proportions) and allocation agreement between the categories. Spatial metrics are the first step for any analysis of the patterns of categorical maps. With the wide range of spatial metrics available, it is possible to fully characterize the pattern of any map. It can also be characterized in greater detail using other more complex techniques, as explained in the next chapter of this book (Chap. “Advanced Pattern Analysis to Validate Land Use Cover Maps”). This chapter provides an introduction to the essentials of pattern analysis by explaining the theory behind the calculations of spatial metrics. To this end, we offer examples of how to use spatial metrics to validate LUC maps (either single maps or series) and Land Use Cover Change (LUCC) simulations from modelling exercises. We also include two example exercises illustrating how spatial metrics can be used for general purposes of pattern characterization without validation. Despite all the spatial metrics currently available, in this chapter we will be focusing exclusively on the most common and most suitable metrics for carrying out the type of analyses being performed here. Most of the spatial metrics proposed in the literature are closely related. This means that users must select the metrics that provide most information for their specific cases, so as to avoid reiteration and make sure that clear conclusions are reached. The example exercises were drawn up with maps (CORINE, SIOSE) and modelling exercises from the Asturias Central Area and Ariège Valley databases.
Efficient implementation of remote sensing image classification can facilitate the extraction of spatiotemporal information for land use and land cover (LULC) classification. Mapping LULC change can pave the way to investigate the impacts of different socioeconomic and environmental factors on the Earth’s surface. This study presents an algorithm that uses Landsat time-series data to analyze LULC change. We applied the Random Forest (RF) classifier, a robust classification method, in the Google Earth Engine (GEE) using imagery from Landsat 5, 7, and 8 as inputs for the 1985 to 2019 period. We also explored the performance of the pan-sharpening algorithm on Landsat bands besides the impact of different image compositions to produce a high-quality LULC map. We used a statistical pan-sharpening algorithm to increase multispectral Landsat bands’ (Landsat 7–9) spatial resolution from 30 m to 15 m. In addition, we checked the impact of different image compositions based on several spectral indices and other auxiliary data such as digital elevation model (DEM) and land surface temperature (LST) on final classification accuracy based on several spectral indices and other auxiliary data on final classification accuracy. We compared the classification result of our proposed method and the Copernicus Global Land Cover Layers (CGLCL) map to verify the algorithm. The results show that: (1) Using pan-sharpened top-of-atmosphere (TOA) Landsat products can produce more accurate results for classification instead of using surface reflectance (SR) alone; (2) LST and DEM are essential features in classification, and using them can increase final accuracy; (3) the proposed algorithm produced higher accuracy (94.438% overall accuracy (OA), 0.93 for Kappa, and 0.93 for F1-score) than CGLCL map (84.4% OA, 0.79 for Kappa, and 0.50 for F1-score) in 2019; (4) the total agreement between the classification results and the test data exceeds 90% (93.37–97.6%), 0.9 (0.91–0.96), and 0.85 (0.86–0.95) for OA, Kappa values, and F1-score, respectively, which is acceptable in both overall and Kappa accuracy. Moreover, we provide a code repository that allows classifying Landsat 4, 5, 7, and 8 within GEE. This method can be quickly and easily applied to other regions of interest for LULC mapping.
Background
Understanding the dependence of ecological land and dynamics of the human-nature-coupled landscape is crucial for urban ecosystem resilience. In this study, we characterized and compared the Spatio-temporal responses of ecological land to urban landscape dynamics in Bahir Dar, Addis Ababa, Adama, and Hawassa cities in Ethiopia for the last three decades (1990–2020). Three sets of Landsat satellite images, field observations, and urban land indexes were used to produce landscape maps and geo-spatial data analysis.
Results
The results showed that in all cities ecological land has had changed intensely during 1990–2020 regarding its quantity, and spatial pattern. Besides, the substantial expansion of built-up ecosystems was manifested at the cost of ecological land. The built-up ecosystem was augmented by 17,341.0 ha (32.16%), 2151.27 ha (19.64%), 2715.21 ha (12.21%), and 2599.65 ha (15.71%) for Addis Ababa, Adama, Bahir Dar, and Hawassa cities respectively from 1990 to 2020 periods. A total of 40.97% of the prolonged built-up area was obtained from urban agricultural land alone. Moreover, urban sprawl is likely to continue, which will be outweighed by the loss of the open space ecosystem. The finding also confirmed the value of land-use intensity (LUI) of Addis Ababa (3.31), Bahir Dar (3.56), Hawassa (4.82), Adama (5.04) was augmented parallel with accelerated growth in the built-up ecosystems. Besides, the Integrated land-use dynamics degree (ILUDD) analysis confirmed that the spatial pattern of ecological land loss significantly consistent with LUI in all cities.
Conclusion
Land-use intensity (LUI) dynamics pattern was followed by urban ecological land to the multi-complex human-dominance ecosystem with a substantial influence on urban greenery and ecosystem services provides. Thus, in all cities, the implementation of effective ecological land management and urban planning policies are required to ensure economic development and ecosystem resilience.
ContextThe building landscape greatly affects the urban heat island (UHI), especially in three-dimensional (3D) space, by changing the energy flow between the land surface, the building surface and the lower atmosphere.Objectives
This study quantitatively analyzed the relationship between the 3D spatial pattern of buildings and UHI in China’s 30 provincial capitals/municipalities and discussed them at grid-cell scale and city scale, respectively.Methods
In consideration of the spatial heterogeneity of the urban environment, Geographically Weighted Regression Model (GWR) was selected to identify the effects of 3D building landscape pattern on summer UHI among 30 megacities of China at both micro grid-cell scale and macro city scale. Nine landscape metrics that used to describe the 3D structure of buildings and the UHI that calculated by hot-spot analysis were collected as input variables.ResultsThe floor area ratio (FAR), the average height (AH), and the space congestion degree (SCD) are the most influential factors affecting UHI. AH and SCD are negatively correlated with UHI, while FAR is the opposite. However, these relationships are not static, and they will change when interfered with other factors. The relationship between FAR and UHI becomes negative in the case of relatively low FAR value. In areas with low building coverage ratio, AH is positively correlated with UHI.Conclusions
The results of this study revealed the complicated association between the 3D building spatial pattern and UHI at micro and macro urban contexts, which was significant for decision-makers to formulate policies based on local conditions.
Land-use/cover is one of the major factors that affects the ecosystem and the services it provides. The impact of land-use change on ecosystem service value is a hotspot in developing countries, especially China—a region with rapid economic development and rapid population growth. As the leading area of China’s reform and opening-up, Guangdong province in southern China is subjected to land-use conversion that significantly alters the capacity of natural ecosystem to provide ecosystem services supporting human well-being. We analyzed the characteristics of land-use changes from 1990 to 2018 using the four-phase land-use data interpreted from Landsat satellite images. We estimated the ecosystem service value through a well-established benefit transfer method using modified local value coefficients, analyzed the trade-offs and synergies among ecosystem services through ecosystem service trade-off degree, and compared the relationship between ecosystem services value, economic development, and population in Guangdong province. The results indicated that the following: (1) Built-Up Area drastically expanded from 6783.1 km2 in 1990 to 13,142.0 km2 in 2018 (93.7%), especially in the Pearl River Delta, where the growth rate of Built-Up Area expansion was up to 169.0%. The other land-use types were all contracted as Cropland (−10.9%), Forestland (−1.0%), Grassland (−4.0%), Water Body (−2.1%), and Unused Land (−24.4%). (2) Total ecosystem service value decreased from US116,432 billion in 2018 (−4.3%). Cropland, Forestland, and Water Body played the most important roles for the total ecosystem service value. Water supply experienced the largest declines in ecosystem services value (US$ −1866.3 million, −10.1%), followed by waste treatment (7.6%) and gas regulation (−4.9%). (3) Synergy was the dominant relationship among ecosystem services. The above results can not only serve as reference cases for other provinces/regions/countries/ to carry out relevant research work but also provide much focus on land-use planning to manage the impacts of land-use change on regional ecosystem services function.
The loss of peri-urban wetlands is a major side effect of urbanization in India in recent days. Timely and proper assessment of wetland area change is essential for the conservation of wetlands. This study follows the integrated way of the peri-urban wetland degradation assessment in the case of medium and small-size urban agglomerations with a special focus on Chatra Wetland. Analysis of land-use and land cover (LULC) maps of the past 28 years shows a decrease of 60% area of the wetland including marshy land. This has reduced the ecosystem services value by about 71.90% over the period 1991–2018. From this end, The Land Change Modeler of IDRISI TerrSet using the combination of MLPNN and Markov Chain has been used to predict the LULC map of this region. The scenario-based modeling following the LULC conversion and nine explanatory variables suggests the complete loss of this wetland by 2045. However, the authors have also tried to present a future LULC pattern of this region based on an environmental perspective. This proposed map suggests possible areas for built-up expansion on the western side of the city without significantly affecting the environment.
Understanding the complex relationships among ecosystem services (ESs) is a prerequisite for optimized management and is of great significance to China’s current implementation of an eco-civilization. However, it is always difficult to simultaneously reveal the relationships among multiple ESs from a local perspective. We proposed an assessment framework that can quantify and conveniently display the intensities of relationships (tradeoffs, synergies, and losses) among multiple ESs, permitting the spatial heterogeneity and gradient effects of these relationships to be revealed. Using township as the study unit, a case study was conducted and nine ESs were evaluated in a transitional area, the Beijing Bay Area (BBA), where the conflict between conservation and development has been prominent. The results suggested that nine ESs were clumped and showed either a high-low (ecosystem-dominated ESs) or a low-high (human-dominated ESs) spatial pattern from northwest to southeast in the BBA. In addition, the relationships among multiple ESs showed significant spatial heterogeneity across townships. In general, tradeoff intensity was mainly related to the supply of human-dominated ESs (especially food supply or water quality regulation), and synergy intensity and loss intensity were mainly related to the supply of ecosystem-dominated ESs. Moreover, all relationships among multiple ESs showed gradient effects along influencing factors. The tradeoff intensity largely exhibited V-shaped patterns, first decreasing and then increasing. Synergy intensity and loss intensity were mainly characterized by monotonically increasing or decreasing patterns. Overall, we found that the process of formation of ESs and their dominating factors largely determined their spatial patterns, spatial heterogeneity, and the gradient effects along influencing factors within the BBA. Based on these results, we propose optimized management suggestions for different townships, combining new plans for development of the BBA. The results of our study will provide information for policy makers to alleviate conflict between conservation and development and will promote sustainable development in the area.
Based on satellite remote sensing image, GIS and Fragstats, this study modeled and calculated the dynamic changes of land use, land cover and landscape patterns in Guizhou Province, China, and calculated the changes of ecosystem service values (ESVs). The impacts of the evolution of landscape patterns on the ESVs were analyzed, and reasonable policy recommendations were made. The findings are as follows: (1) In the past two decades, the area of cropland and grassland has decreased; the area of water bodies, urban and rural, industrial and mining, and residential areas has increased; the area of forestland has increased first and then decreased. (2) The two major types of landscapes, cropland and grassland, are clearly being replaced by two land types, forest land and water bodies. (3) Overall, the degree of landscape aggregation and adjacency has decreased, and the landscape heterogeneity has increased. (4) The total amount of ESV in 2000, 2008, 2013 and 2017 was 2574 × 108 Yuan RMB, 2605 × 108 Yuan RMB, 2618 × 108 Yuan RMB and 2612 × 108 Yuan RMB, respectively. The changes of landscape patterns had important impacts on the ESVs. In order to solve the problems caused by the increasingly prominent changes in the landscape patterns and improve the ESVs, it is necessary to rationally plan and allocate land resources, optimize the industrial structures, and develop effective regulatory policies.
In this study, land use/cover change was systematically investigated in the Qeshm Island to understand how human and nature interact in the largest island of Persian Gulf. Land-use maps were prepared for 1996, 2002, 2008, and 2014 using Landsat satellite imagery in six classes including agriculture, bare-land, built-up, dense-vegetation, mangrove, and water-body, and then dynamic of changes in the classes was evaluated using intensity analysis at three levels: interval, category, and transition. Results illustrated that, while the land changes were fast over the first and third time intervals (1996–2002 and 2008–2014), the trend of changes was slow in the second period (2002–2008). Driven by high demand for construction and population growth, the built-up class was identified as an active gainer in all the three time intervals. The class of bare-land was the main supplier of the land for other classes especially for built-up area, while built-up did not act as the active supplier of the land for other classes. The dense-vegetation class was active in all three time intervals. As for the mangrove class, drought and cutting by residents had negative effects, while setting up protected areas can effectively maintain this valuable ecosystem. High demands were observed for land change in relation to built-up and agriculture classes among other classes. The findings of this study can advance our understanding of the relationship and behavior of land use/cover classes among each other over 18 years in a coastal island with arid climate.
Systems of secondary cities play a vital intermediary role as economic, administrative and logistics hubs within national and global systems of cities. They have three basic spatial typologies: regional hubs, metropolitan clusters, and corridors. The pattern, rate of development, and role of systems of secondary cities are changing rapidly in response to urbanisation, globalisation, structural economic change, new technologies, and the rapid development of transport and communications systems. These changes have resulted in a growing gap and inequities in sub-national regional economic development, income, wealth, investment, and employment opportunities within systems of secondary cities. Closing the gap has become a significant challenge for governments. Much of the literature on the development of secondary cities has tended to focus on enhancing the competitiveness of infrastructure, industry clusters, and enabling environments; however, there has been a tendency to overlook the importance of external factors: connectivity, networks, and collaboration, which significantly affect the performance of systems of secondary cities. This book seeks to address this knowledge gap. It examines ways secondary cities can work more collaboratively to improve their development prospects, lift prosperity, and leverage public resources to support equitable and sustainable sub-national economic growth and development. It outlines ways governments and other stakeholders within systems of secondary cities can invest strategically in public goods and services, improve connectivity, develop networks, and leverage common user facilities, infrastructure, and resources at different geographic levels to support inclusive, equitable, and sustainable development.
The continuous urban expansion changes the urban ecological landscape pattern and urban ecosystem functions that possess serious challenge before urban environmental and ecological management. In this context, assessing the relationship between rapid urban expansion and ecosystem services play an important role for the urban sustainability and development related to planning and policies. This study mainly focuses on the assessment of the dynamic nature of urbanization and its impact on urban ecosystem services through land use and land cover (LULC) changes of Old Malda Municipal town, Eastern India. The ecosystem service values (ESVs) are analyzed using Remote Sensing data and GIS techniques corresponding with the global Value Coefficient (VC) for four-time periods (1990, 2000, 2010 and 2017) to estimate total ecosystem service values (ESVt) and individual ecosystem service function change. Coefficient of Sensitivity (CS) is also applied to test the reliability of the estimated VC used as proxies for each LULC categories. The result of the study landscape reveals that the ecosystem service values (ESVs) decreased by 25% from US 1.07 million because of losing cropland and vegetation cover by 34% and 35% respectively during 1990–2017. In case of individual ecosystem service functions, regulating services increased by 12% since 1990–2017 with highest contributing services of water regulation (57%), water supply (22%) and waste treatment (8%) respectively while maximum decline is recorded in soil formation (33.33%) followed by climatic regulation (31.82%) and nutrient cycling (31.25%). The decline in total and some individual ESV in the study landscape requires for urgent measures to be taken to enhance the urban ecosystem sustainability through effective planning and policies.
Urbanisation has been a main cause of land use land cover (LULC) change worldwide, often with irreparable consequences to the provision of ecosystem services. Despite an increase in quantitative assessments of ecosystem service values (ESV) related to LULC changes, data are scarce for ecotones, such as the agreste in northeast Brazil (a transitional area between the Atlantic Forest and the Caatinga biomes). The benefit transfer method was used to quantify changes in ESV between 1989, 2007 and 2014 due to urbanisation in the microwatershed Riacho das Piabas (3660 ha) in the agreste of Paraíba. Remote sensing techniques and a geographic information system were used to quantify LULC changes. Loss of arboreal vegetation (covering 46% of the study area in 1989 and 5% in 2014) was the key factor driving the 73.2% decline in the total ESV (from US 3.7 million in 2017 values). LULC changes resulted in losses of 89% in the estimated value of eight ecosystem services, including climate regulation, water flow regulation, moderation of disturbance, nutrient cycling and biological control, which are critical locally when considering the regional trend towards aridification and the existing pressures on water resources. Ecosystem functions loss and climate change impacts may lead to a shift in ecotone boundaries favouring the semiarid Caatinga vegetation. These results urge the implementation of ecosystem-based spatial planning, focusing on urban green infrastructure and restoration of natural habitats and their connectivity, to prevent further ecosystem service losses. Local estimates of ESV required to inform the suggested policy actions are identified.
Increasingly, the geographically weighted regression (GWR) model is being used for spatial prediction rather than for inference.
Our study compares GWR as a predictor to (a)its global counterpart of multiple linear regression (MLR); (b)traditional geostatistical
models such as ordinary kriging (OK) and universal kriging (UK), with MLR as a mean component; and (c)hybrids, where kriging
models are specified with GWR as a mean component. For this purpose, we test the performance of each model on data simulated
with differing levels of spatial heterogeneity (with respect to data relationships in the mean process) and spatial autocorrelation
(in the residual process). Our results demonstrate that kriging (in a UK form) should be the preferred predictor, reflecting
its optimal statistical properties. However the GWR-kriging hybrids perform with merit and, as such, a predictor of this form
may provide a worthy alternative to UK for particular (non-stationary relationship) situations when UK models cannot be reliably
calibrated. GWR predictors tend to perform more poorly than their more complex GWR-kriging counterparts, but both GWR-based
models are useful in that they provide extra information on the spatial processes generating the data that are being predicted.
KeywordsRelationship nonstationarity–Relationship heterogeneity–GWR–Kriging–Spatial interpolation
This study evaluated the geographically weighted regression (GWR) model for landslide susceptibility mapping in Xing Guo County, China. In this study, 16 conditioning factors, such as slope, aspect, altitude, topographic wetness index, stream power index, sediment transport index, soil, lithology, normalized difference vegetation index (NDVI), landuse, rainfall, distance to road, distance to river, distance to fault, plan curvature, and profile curvature, were analyzed. Chi-square feature selection method was adopted to compare the significance of each factor with landslide occurence. The GWR model was compared with two well-known models, namely, logistic regression (LR) and support vcector machine (SVM). Results of chi-square feature selection indicated that lithology and slope are the most influencial factors, whereas SPI was found statistically insignificant. Four landslide susceptibility maps were generated by GWR, SGD-LR, SGD-SVM, and SVM models. The GWR model exhibited the highest performance in terms of success rate and prediction accuracy, with values of 0.789 and 0.819, respectively. The SVM model exhibited slightly lower AUC values than that of the GWR model. Validation result of the four models indicates that GWR is a better model than other widely used models.
ContextWidespread loss of wetland ecosystems resulting from human land use highlights the need for a reclamation strategy that can sustain wetland ecosystem services. Since wetland function partly depends on landscape structure, reclamation and monitoring can be aided by knowing the differences in wetland configuration between undisturbed and disturbed landscapes. Objectives
Identify a parsimonious set of landscape metrics for quantifying wetland configuration and land-cover composition, and quantify how these metrics vary with anthropogenic disturbance. MethodsA large suite of landscape metrics quantifying area/edge, shape, aggregation, and diversity were calculated for landscapes in the Grassland, Parkland, and Boreal Natural Regions of Alberta. Variable reduction techniques were applied to identify representative metrics. These representative metrics were related to anthropogenic disturbance using non-parametric tests. ResultsThe spatial configuration of wetlands in low-disturbance and high-disturbance landscapes were significantly different from other landscapes. Aggregation metrics were the most commonly identified measures of wetland configuration independent of wetland-proportion in the landscape. Conclusions
Our findings provide insight for reclamation and monitoring by showing that some aspects of wetland configuration vary independently of composition, and therefore both need to be considered when parameterizing the design of reclaimed landscapes. We suggest that using landscape metrics in a reference condition approach is appropriate for evaluating landscape degradation and for setting landscape reclamation targets and monitoring programs.
The prevalence of non-communicable chronic diseases (NCDs) worldwide poses an alarming threat to public health. Recent literature has embraced the opinion that incorporating the social factors should advance the understanding of NCDs prevalence. In this context, examining the NCDs prevalence in association with area social deprivation should provide critical implications for coping with public health risks. However, few empirical studies have examined this specific issue, especially in the developing countries. Using the principal component analysis, an area social deprivation index (ASDI) is established for the Shenzhen city (China) by integrating ten indicators from four dimensions: education, housing, socially disadvantaged population, and economically disadvantaged population. The geographically weighted regression (GWR) is employed to analyze the associations between ASDI and the incidence rate of three prevalent NCDs at district scale. Spatial non-stationary relationships are identified for the three diseases. More specifically, prevalence of the three diseases is all positively correlated with the ASDI. Strength of the associations presents the geography that it generally decreases from the central city to the suburb. These findings suggest that greater possibility of NCDs prevalence would be expected in districts with higher social deprivation. Besides, the impact of social deprivation on NCDs prevalence is much stronger in the central city. The spatial stationarity can facilitate the formulation of location-specific preventive measurements. This paper is believed to provide an innovative insight for social indicators research.
This paper examines the relationship between economic growth and environmental degradation in Ecuador from 1971 to 2010. We estimate this relationship in a country with a heavy reliance on revenue from the exploitation of natural resources, the depletion of vegetation cover in recent decades and a low level of participation of industry in GDP. We show the existence of an inverse relationship between real GDP and vegetation cover, indicating that the output of this country is based on environmental degradation. Through Johansen co-integration tests, we check that there is a relationship of long-term equilibrium between the first differences of real GDP, vegetal cover and the urbanization rate. The ECM shows that there is a short-term relationship between vegetation cover, the GDP and the rate of urbanization. Finally, we did not found Granger causality between the variables. A policy implication based on our findings is that policies to protect the environment should not jeopardize economic growth and not limit the rapid urbanization in the country.
One solution to mitigate conservation threats is to harness the collective impact of individuals changing their behavior. Due to limited resources, it is necessary to identify high impact behaviors to target in future advocacy campaigns. In this article, we followed a systematic process and asked environmental specialists and zoo visitors to list the top three global and local wildlife conservation threats and the corresponding behaviors to mitigate the threats. Visitor perceptions, unlike those of experts, were biased toward global threats with less awareness of local threats. For addressing global threats, both visitors and experts listed individual-based actions. At the local scale, experts focused on behaviors implemented by government and large organizations while visitors listed individual-based actions. Future research and advocacy campaigns will need to address the expert bias toward government and large organization-based behaviors at the local scale and visitor bias toward global threats and behaviors.
The rapid increase of human population is putting an incredible strain on our environment. While developed countries continue to pollute the environment and deplete its resources, developing countries are under increasing pressure to compete economically and their industrial advancements are damaging as well. The demands that this growth places on our global environment are threatening the future of sustainable life on earth. One of the largest environmental effects of human population growth is the problem of global warming. Some scientists fear that global warming will lead to rising sea levels and extreme weather conditions in the future. In order to support the growing population, forests are being destroyed at an alarming rate. Humans also continue to put a great demand on the natural resources of our planet. Many non-renewable resources are being depleted due to the unrestrained use of fuel and energy. Many parts of the world also suffer from a shortage of food and water. The growth of population puts larger demands on our already limited resources. The environment on earth is suffering from the growth of global population. The depletion of resources and biodiversity, the production of waste, and the destroying of natural habitat are serious problems that must be addressed in order to ensure that life on earth will be sustainable throughout the next century.
Keywords: Industrial advancements, Land and soil degradation, global warming, Climate change, Air and water pollution, Deforestation, Physical environment.
a b s t r a c t This paper gives an overview of the value of ecosystem services of 10 main biomes expressed in monetary units. In total, over 320 publications were screened covering over 300 case study locations. Approximately 1350 value estimates were coded and stored in a searchable Ecosystem Service Value Database (ESVD). A selection of 665 value estimates was used for the analysis. Acknowledging the uncertainties and contextual nature of any valuation, the analysis shows that the total value of ecosystem services is considerable and ranges between 490 int/year for the potential services of an 'average' hectare of coral reefs. More importantly, our results show that most of this value is outside the market and best considered as non-tradable public benefits. The continued over-exploitation of ecosystems thus comes at the expense of the livelihood of the poor and future generations. Given that many of the positive externalities of ecosystems are lost or strongly reduced after land use conversion better accounting for the public goods and services provided by ecosystems is crucial to improve decision making and institutions for biodiversity conservation and sustainable ecosystem management.
Several cities in the world have been subjected to urban sprawl. For instance, in India, this process is responsible for environmental degradation. The case of Siliguri Municipal Corporation (SMC) is a good example. Therefore, a proper investigation of the urban expansion characteristics of SMC is required to provide a basis for sustainable urban environmental management. This study analysed the changes in land use and land cover (LULC), future scenarios prediction, and ecosystem services values (ESVs) estimation loss. LULC analysis showed that the built-up area increased from 17.26 sq. km to 36.98 sq. km between 2001 and 2015. As a result, the ESVs from natural vegetation decreased by 9.18 million US$/hectare/year during the same period. The urban growth prediction model was generated based using the Multi-Layer Perceptron Neural Network and Markov Chain. Four scenarios were designed to predict future LULC. The model has predicted a maximum urban expansion (66.46 sq. km) in the business-as-usual scenario. The lowest urban expansion (58.81 sq. km) was identified in the planning scenario. The lowest vegetation degradation was observed in the planning scenario. This study highlights the need for an urgent sustainable urban management plan.
A few recent studies revealed that the intensity of UHI is increasing in medium-class cities due to the rapid degradation of natural vegetation covers. This study explores the patch-level association between green space and LST on a spatial-temporal basis to reflect how green space concentration can influence the LST intensity. A total of 12 landscape metrics are incorporated to evaluate green space fragmentation and isolation in Raiganj City. Further, six metrics are included to show the LST patch compactness, and the complex relationship between these two is analyzed using multi-scale geographically weighted regression. It showed that a high proportion of green spaces with low fragmentation and isolation, particularly in 2000, was the source of sink areas in Raiganj. However, with the rapid removal of green spaces, fragmentation and isolation in the green spaces increased significantly in the subsequent years. It reduces the potentiality of green space as a cooling mechanism and strengthens the UHI effect over the city. This study suggests the requirement of a proper action plan, including a future land use & land cover planning map for the preservation and the net area increase of the compact green spaces. It will help to minimize the effect of UHI.
Urban growth, which caused spatial land use and land cover changes has affected various physical environment, social, and economic activities. Thus, in order to understand the dynamic process of urban spatial growth, researchers throughout the world have implemented diverse approaches, where spatial models have been developed to predict and simulate future urban growth. Those models were developed based on the driving forces that stimulate urban spatial growth. Therefore, in ensuring reliable models to be developed will be able to forecast future changes and their potential environmental effects, the driving forces must be identified. The objective of this paper is to identify possible driving forces that promote urban spatial growth of the George Town Conurbation. The study was conducted based on reviewing recent publications in journals and an on-line survey. An on-line survey was generated and distributed to academicians and urban planners to identify factors influencing urban spatial growth and their weights. The findings indicated that distance to public amenities, cheap housing price, and distance to the workplace are among factors that are important determinants of urban development. The results provide valuable insights in modelling urban growth in future research.
An important non-structural solution in flood management is susceptibility mapping, which identifies the likelihood of flood occurrence in an area. Although various models have been applied in flood susceptibility mapping with different successes, Geographically Weighted Regression [GWR] has not been sufficiently tested despite its effective advantages in interpreting spatially heterogeneous relationships. To test GWR's effectiveness in flood susceptibility modelling, this study included 16 morphometric parameters as the explanatory variables, and historical flood occurrence as the dependent. Multicollinearity was eliminated based on Variance Inflation Factor [VIF], which resulted in six screened parameters: stream order, drainage texture, relief ratio, bifurcation ratio, topographic wetness index, and topographic position index. Five tests were carried out, with the first involving direct inputs of the VIF-screened variables into the GWR modelling process. The other four tests incorporated morphometric parameter normalisation into 1-to-5 ranking scores according to Ordinary Least Square [OLS] coefficients or literature using all or only the VIF-screened parameters. The best-performing model was the first test, indicating that direct input of the screened parameters was the ideal modelling process. This test had the lowest corrected Akaike Information Criterion (160.01), the highest percentage of deviance explained (46.18%), lowest spatial autocorrelation of residuals (0.1122) and transformed residuals (0.2827), highest success accuracy (91.24%), and second-best prediction accuracy (75.15%). These findings show that accounting for spatial variation improved global flood model performance. The results also show that GWR may have the potential for better flood susceptibility mapping when compared with other traditional models such as non-spatial logistic regression and frequency ratio.
In recent times, the role of secondary cities is growing rapidly. It is observed that secondary cities in Latin America contribute nearly 25% of the country's GDP. Rapid urbanization in secondary cities is also noticed in developing South Asian countries. However, the investigations on the theme of urbanization and its associated facts largely remained concentrated to the large cities in these countries. Therefore, more studies are needed to perform on the urbanization character in secondary cities to address their immediate challenges and also to formulate adequate policies for sustainable development. This study selected a fast-growing ordinary city of Eastern India i.e. Raiganj City to highlight the different aspects of an ordinary city. This study revealed that the population has grown more than 10 times since the independence of the country. The existence of poor infrastructure mainly in the slum areas is a major challenge in this city. Besides, unplanned growth, a huge increase in traffic, and encroachment of part of the roads by illegal shops created several infrastructural problems. The infrastructural conditions at the household level are also not uniform. This study suggests an effective future spatial planning involving a future city planning map, Self Help Groups, and micro-enterprises.
Understanding the dependence of ecosystem services (ESs) on the dynamics of human-semi nature-coupled ecosystems is crucial for urban ecosystem resilience. In the present study, the responses of ESs to land use land cover transitions were explored and compared, selecting Addis Ababa, Adama, Hawassa, and Bahir Dar cities in Ethiopia. The geospatial data and benefit transfer approach was used to estimate the nexus over a three-decade period (1990–2020). Moreover, the bivariate Moran's I and spatial regression models were employed to analyze the spatial dependence of ESV on urbanization. The findings showed that the built-up increased by 17,341.0 ha (32.2%), 2151.3 ha (19.6%), 2715.2 ha (12.2%), and 2599.7 ha (15.7%) for Addis Ababa, Adama, Bahir Dar, and Hawassa cities, respectively over the investigated periods. Besides, the total ESV weighed by 24.8%, 8.9%, 0.7%, and 3.9% from the US$ 277.9, 55.5, 100.3, and 90.9 million for Addis Ababa, Adama, Bahir Dar, and Hawassa cities, respectively from1990 to 2020. Synergies occurred among local climate regulation and recreation services, and trade-offs existed among other services. A persistent rising trend in the ESVt was found for all cities the upsurge in Addis Ababa being much sturdier than in others. However, the elasticity of ecosystem of land use (EEL) showed that 1% of the LULC transformation was caused by 8.9% changes in ESV. Besides, the results from the global bivariate Moran's I show substantial positive spatial correlations between ESV, and Integrated Land use Dynamic Degree (ILUDD), Land-Use Intensity (LUI), and Land Use Diversity (LUD) (p < 0.001). Spatial lag model and special error model were shown to be fitting more than the Ordinary Least Square in establishing relationships among the spatial dependence of ESV on urbanization. In contrast, the aggregated ESV is significantly influenced not only by LULC dynamics but also by the spatial spillover effect. Thus, overall findings suggested an antagonistic nexus between the aggregated ESV and ESVf, since 98% of individual ESs were negatively declined as the built-up ecosystem expanded.
Does socioeconomic development result in exacerbation of urban thermal environment? The answer to this question is extremely critical for mitigating and adapting urban heat island effect (UHI). However, such question has not yet been fully understood the details. The aim of this study was to measure the magnitudes and marginal effect of socioeconomic drivers on UHI dynamics in major Chinese cities. We utilized generalized additive model (GAM) for modelling non-linear/linear relations between economic output, population, industrial structure, geographical features and UHI at seasonal and climate-zones level. The results demonstrate socioeconomic factors explain 12%∼20% of UHI intensity variations. Urban economic scale generally has a higher contribution rate than variables of population and industrial structure. Urban economic growth raised the heat stress in hot summer. Moreover, a negative linear nexus was observed between the UHI intensity and per capita GDP, indicating that the empirical results supported a post-environmental Kuznets curve (EKC) relationship during the sample period. We suggest both controlling population size and increasing per capita GDP may contribute to mitigate the summer UHI in the tropical cities. Our study highlights macro socioeconomic policy design and urban planning should be combined to counteract or mitigate the UHI.
Changes in land use and ecosystem services influence each other and such changes have consequences for human wellbeing. In this paper, we review the research literature on how different types of ecosystem services are affected by LUC, and the consequences for human well-being. We begin with a review of the different types of ecosystem services. We examine the influence of LUC on provisioning ecosystem services due to mismatches between agricultural production and hydrological systems. We continue with a review of the impacts of LUC on supporting ecosystem services through the conversion of an ecosystem to cultivated land, and the resulting changes in soil properties and the hydrological balance. Next, We also discuss the regulating ecosystem services which are affected by LUC and alters water purification processes, as well as the effects on cultural ecosystem services. We conclude with a review of the valuation and quantification of the effects of LUC on the management of ecosystem services, and propose future research directions. Most of the research reveals a negative impact of LUC on ecosystem services, despite research gaps related to methods for valuing ecosystem services more accurately and for collecting social responses to the impacts of LUC on different ecosystem services.
Land use/cover change (LUCC) in the Bohai Rim coastal zone has accelerated as a result of rampant economic development, which has directly caused many negative effects on ecosystem functions and services. Based on multi-temporal land use data (2000, 2005, 2010 and 2015), the benefit transfer method was used to assess the ecosystem service value (ESV) of the Bohai Rim coastal zone, and the impact of LUCC on ecosystem services was studied. Multi-scenario simulations for 2025 were conducted using the future land use simulation model. The result of the analysis showed that during the period from 2000 to 2015, the total ESV lost was 22.09 billion yuan, representing a decrease of 3.80%. The spatial distribution of the ESV showed a certain regularity, with obvious characteristics of a land-sea gradient change. As the distance from the coastline increased, the ESV per unit area gradually declined. Compared with those in 2015, the total ESVs of the socio-economic development scenario and the business-as-usual scenario in 2025 showed a declining trend, while they increased under the ecological protection priority scenario. Under the ecological protection priority scenario, regulating services and support services increased significantly, but those declined dramatically under the socio-economic development scenario. The patterns of LUCC are the main reasons for the decrease in ESV. This research provides a theoretical basis and support for the development and utilization of coastal space and the improvement of “ecological-economic-social” benefits; additionally, the results provide support for scientific decision-making services for the sustainable use of resources in the coastal zone and for the sustainable management of ecosystems.
Application of importance-performance analysis (IPA) has received wide applicability to reveal resident’s satisfaction with the performance of ecological services. In recent days, researchers have expanded the horizon of IPA through the implication of this technique in case of different ecosystem services to find out the satisfaction of local people with ecosystem services. However, a little contribution has been made in the field of wetland study through IPA. This study has tried to apply IPA in this field by taking into consideration of 10 common ecosystem services. The study unit is Chatra Wetland, which is a peri-urban wetland of the English Bazar city. Analysis of LULC of the past 18 years suggests that the net area of Chatra Wetland got reduced by >50 percent during this time. Besides this, decreasing the value of LPI, PLAND, cohesion, and CONTAG represents the fragmentation of the landscape of Chatra Wetland. The predicted LULC shows that this wetland will disappear by 2040 if the LULC conversion rate remains the same. In this regard, IPA is performed to understand the satisfaction level of the citizen of English Bazar city and the people of surrounding villages with the performance of Chatra Wetland. The output of IPA reveals that people are dissatisfied with the performance of five ecosystem services. These are biodiversity, flood control, water supply, identity, and cooling effect. All of them require the urgent need of attention to restoring the ecological condition in the study area. Overall, the performance rate of Chatra Wetland at present is perceived by the urban people as only 55.14 percent. However, the rate of perceived performance varies ward-wise and village-wise. It is observed that place attachment and proximity to Wetland have made a vital role in the perception of people. The perceived performance of Chatra Wetland is increasing gradually with increasing distance from the Chatra Wetland. The output of this study helps to reveal the importance of this wetland to the urban people as well as to the local villagers by identifying their satisfaction level and their enjoyment with the urban blue space. It also serves as a basis of the bottom-up approach of environmental management to the decision-makers by displaying the demand of people in case of ecological restoration.
The ecosystems provide a range of material as well as non-material services that contribute to human well-being as well as supply necessary resources for the organisms. The land use/ land cover (LU/ LC) changes have been taken place due to several natural and anthropogenic reasons, which significantly influence the ecosystem services. Therefore, the present study aimed to explore the minor variations of ecosystem services provided by the particular land use types of the study area. Therefore, we have divided the study area into nine grids. The land use land cover classifications have been performed using support vector machine techniques (SVM) for 1999–2019. Based on the multi-temporal land use land cover maps, we have used the global coefficient value of 1997 and 2003 for valuation of ecosystem services for different land use types. Then we have employed elasticity techniques to analyse the response of land use land cover changes over the ecosystem service valuation. The findings showed that the overall built-up area has increased by 29.14% since 1999, while the overall water-body has decreased by 15.81%. Therefore, the ecosystem services provided by water-body have been decreased correspondingly and the 29.14% areas that converted to built-up area from others land use types do not able to provide any ecosystem services and the ecosystem service values become nil, which is not suitable for good health ecosystem. Therefore, the study can be the foundation to the planners and scientists to prepare sustainable plans for the management of local ecosystem based on minorly study on the impact of LULC changes on the ecosystem services.
Every year, gully erosion causes substantial damage to agricultural land, residential areas and infrastructure, such as roads. Gully erosion assessment and mapping can facilitate decision making in environmental management and soil conservation. Thus, this research aims to propose a new model by combining the geographically weighted regression GWR) technique with the certainty factor (CF) and random forest (RF) models to produce gully erosion zonation mapping. The proposed model was implemented in the Mahabia watershed of Iran, which is highly sensitive to gully erosion. Firstly, dependent and independent variables, including a gully erosion inventory map (GEIM) and gully-related causal factors (GRCFs), were prepared using several data sources. Secondly, the GEIM was randomly divided into two groups: training (70%) and validation (30%) datasets.
Thirdly, tolerance and variance inflation factor indicators were used for multicollinearity analysis. The results of the analysis corroborated that no collinearity exists amongst GRCFs. A total of 12 topographic, hydrologic, geologic, climatologic, environmental and soil-related GRCFs and 150 gully locations were used for modelling. The watershed was divided into eight homogeneous units because the importance level of the parameters in different parts of the watershed is not the same. For this purpose, coefficients of levation, distance to stream and distance to road parameters were used. These coefficients were obtained by extracting bi-square kernel and AIC via the GWR method. Subsequently, the RF-CF integrated model was applied in each unit. Finally, with the units combined, the final gully erosion susceptibility map was obtained. On the basis of the RF
model, distance to stream, distance to road and land use/land cover exhibited a high influence on gully formation. Validation results using area under curve indicated that new GWReCFeRF approach has a higher predictive accuracy 0.967 (96.7%) than the individual models of CF 0.763 (76.3%) and RF 0.776 (77.6%) and the CF-RF integrated model 0.897 (89.7%). Thus, the results of this research can be used by local managers and planners for environmental management.
Land cover change monitoring in rapidly urbanizing environments based on spaceborne remotely sensed data and measurable indicators is essential for quantifying and evaluating the spatial patterns of urban landscape change dynamics and for sustainable urban ecosystems management. The objectives of the study are to analyse the spatio-temporal evolution of urbanization patterns of Kigali, Rwanda over the last three decades (from 1984 to 2016) using multi-temporal Landsat data and to assess the associated environmental impact using landscape metrics and ecosystem services. Visible and infrared bands of Landsat images were combined with derived Normalized Difference Vegetation Index (NDVI), Gray Level Co-occurrence Matrix (GLCM) variance texture and digital elevation model (DEM) data for pixel-based classification using a support vector machine (SVM) classifier. Seven land cover classes were derived with an overall accuracy exceeding 87% with Kappa coefficients around 0.8. As most prominent changes, cropland was reduced considerably in favour of built-up areas that increased from 2.13 km² to 100.17 km² between 1984 and 2016. During those 32 years, landscape fragmentation could be observed, especially for forest and cropland. The landscape configuration indices demonstrate that in general the land cover pattern remained stable for cropland, but that it was highly changed for built-up areas. Ecosystem services considered include regulating, provisioning and support services. Estimated changes in ecosystem services amount to a loss of 69 million US dollars (USD) as a result of cropland degradation in favour of urban areas and in a gain of 52.5 million USD within urban areas. Multi-temporal remote sensing is found as a cost-effective method for analysis and quantification of urbanization and its effects using landscape metrics and ecosystem services.
Research works related to public health, transportation and urban planning have called for indices of land use mix (LUM) to support their spatial models. We propose a fishnet-based LUM calculation algorithm that works with the National Land Cover Database (NLCD) land cover data, a high-level product of Landsat satellite images. Comparing to the traditional LUM calculation, the fishnet structure can work at various spatial scales if aggregating to the administrative boundaries. Test results from regression models showed that our method was able to solve the scale problem identified as modifiable area unit problem that caused an unexpected positive correlation of obesity rate with LUM at the county scale. This is due to the fact that the existing methods do not limit the distance of LUM. The fishnet method provides a feasible way to calculate LUM indices across multiple scales. The NLCD data are the state-of-the art land use and land cover data for the contiguous United States. Our research provides a working example of the application of NLCD data or similar remote sensing products in public health-related research.
Introduced in this paper is a family of statistics, G, that can be used as a measure of spatial association in a number of circumstances. The basic statistic is derived, its properties are identified, and its advantages explained. Several of the G statistics make it possible to evaluate the spatial association of a variable within a specified distance of a single point. A comparison is made between a general G statistic andMoran’s I for similar hypothetical and empirical conditions. The empiricalwork includes studies of sudden infant death syndrome by county in North Carolina and dwelling unit prices in metropolitan San Diego by zip-code districts. Results indicate that G statistics should be used in conjunction with I in order to identify characteristics of patterns not revealed by the I statistic alone and, specifically, the Gi and G∗ i statistics enable us to detect local “pockets” of dependence that may not show up when using global statistics.
The urban expansion process in China from the 1970s to 2013 was retrieved based on remote sensing and GIS technology. With the latest zoning method used as reference, annual expansion area per city, urban expansion type, and fractal dimension index were employed to analyze the Chinese urban expansion characteristics and its spatial difference from the aspects of urban expansion process, influence of urban expansion on land use, and urban spatial morphological evolutions. Results indicate that 1) under the powerful guidance of policies, urban expansion in China went through six different stages, and cities in the eastern region entered the rapid expansion period the earliest, followed by cities in the central, northeastern and western regions; 2) cultivated lands and rural settlements and industrial traffic lands were the important land sources for urban expansion in China; the influence of urban expansion on land use in the eastern region was the strongest, followed by the central, northeastern and western regions; 3) urban spatial morphology tended to be complex and was directly related to the adopted spatial expansion mode. Infilling expansion became the main urban expansion mode in the western region first, then in the central and northeastern regions, and finally in the eastern region. This study establishes the foundation for an in-depth recognition of urban expansion in China and optimization of future urban planning.
Elevation is a strong determinant of local climate and may therefore be an important factor to consider when examining the association between climate and tree growth. In this study, we developed a set of tree-ring width records for Abies spectablis (D.Don Spach) in the Manang Valley of central Nepal Himalaya and tested how tree growth and the relationship between tree growth and climate varied across a 450-m elevation transect. The sampled trees had a median age of 115 years, and the oldest individual specimen, which was located at 3775. m, had more than 212 rings. The common signal shared across the tree-ring series was relatively weak, which is typical for ring-width chronologies from the Himalayas. Even though these forests are located within a semi-arid climate, temperature had a stronger and more consistent influence on Abies growth than precipitation. All three chronologies across the transect exhibited a negative relationship with mean March-June temperatures, which could reflect the impact of warm weather during the early part of the growing season, possibly mediated through its influence on evapotranspiration and soil moisture. While interannual fluctuations in tree growth were synchronous across sites, longer-term trends in growth varied across the transect, with high-elevation trees showing elevated growth during the last two or three decades and lower-elevation trees behaving just the opposite. These disparate trends suggest the factors that control longer-term trends in forest productivity vary substantially with elevation. For studies intending to use tree-ring width records in the Trans Himalaya as climate proxies, it may be preferable to collect specimens at lower forest sites, where the agreement across the population of trees is stronger. Because longer-term trends in ring width can differ substantially from one elevation to another in this region, it may also be necessary to collect a greater number of samples from several positions along an elevation gradient.
Land use change is one of the uppermost driving forces of regional ecosystem change, and has a huge impact on the environmental balance. Mining areas with intensive resources exploitation and utilization have undergone different kinds of environmental influences, such as water pollution and land use cover change. The extensive coal mining in China has led to significant regional land use change resulting in major ecological damage. The objective of this study was to form a clearer picture of the regional ecological environmental situation for promoting ecological protection and improvement by ecosystem service valuing. The case study area was selected at Jiawang town, which has undergone extensive coal mine exploitation for many decades. The study investigated the relationship between land use change and ecological environment, and described the ecosystem service value variations in Jiawang, based on remote sensing and GIS technology. After modification of regional ecosystem service value coefficients, the method was used to evaluate the conditions in the study area from 1990 to 2005 based on the land use/cover information interpreted from TM/ETM+ images. The characters and changes of ecosystem service values were then analyzed both quantitatively and spatially.
To enable data collection by remote sensing instruments the Earth's continuously varying surface is regularized into a grid of consistently sized and shaped pixels. Remotely sensed data, as a result, is often highly spatially autocorrelated. The characterization and quantification of spatial autocorrelation can provide a valuable source of information for both theoretical and applied studies in remote sensing. Consequently, various techniques have been developed to assess the spatial dependence characteristics of remotely sensed imagery. Typically such techniques yield summary measures which enable the identification of distinctive regions of spatial dependency within the image. In contrast, local indicators of spatial association (LISA) measures, focus upon variations within the regions of spatial dependence. This letter provides an introduction to one such LISA measure, the Getis statistic, and indicates how it may be used in remote sensing research and applications as a complement to existing approaches. The Getis statistic provides a measure of spatial dependence for each pixel while also indicating the relative magnitudes of the digital numbers in the neighbourhood of the pixel.
The purpose of this paper is to provide a broad overview of the recent patterns and trends of urban growth in developing countries. Over the last 20 years many urban areas have experienced dramatic growth, as a result of rapid population growth and as the world's economy has been transformed by a combination of rapid technological and political change. Around 3 billion people—virtually half of the world's total population-now live in urban settlements. And while cities command an increasingly dominant role in the global economy as centers of both production and consumption, rapid urban growth throughout the developing world is seriously outstripping the capacity of most cities to provide adequate services for their citizens. Over the next 30 years, virtually all of the world's population growth is expected to be concentrated in urban areas in the developing world. While much of the current sustainable cities debate focuses on the formidable problems for the world's largest urban agglomerations, the majority of all urban dwellers continue to reside in far smaller urban settlements. Many international agencies have yet to adequately recognize either the anticipated rapid growth of small and medium cities or the deteriorating living conditions of the urban poor. The challenges of achieving sustainable urban development will be particularly formidable in Africa.