Institute for Global Environmental Strategies
Recent publications
Commons were traditionally associated with rural societies, but socioeconomic changes have triggered new forms of commons linked with urban areas. Despite an emerging literature on these new commons and their connection to landscape management, more knowledge is needed. This study focuses on various forms of commons and their contribution to landscape management in Japan and Slovenia. The aim is to gain insights into the specificities of such commons, explore their evolutionary aspect, and to investigate their governance challenges. Empirical analysis was based on literature, web search and in-depth interviews. The study reveals 1) a great diversity of commons related to landscapes, 2) the evolution of some traditional commons into so-called 'transforming commons', whose main characteristics are the greater involvement of non-owners and the linking of rural-urban areas, 3) new types of commons developed with different resources, mainly in urban areas, and 4) in addition to material benefits these commons also provide non-material aspects and social benefits. The analysis also shows that all commons face governance and social challenges due to ageing of participants, challenging legal procedures, and difficulties in participating in collective actions.
The objective of this paper is to introduce what kind of discussions are happening in the world regarding carbon neutrality when we face devastating and frequent heavy rainfall disaster and to discuss what kind of role building and urban system needs to take by sharing some case studies in Japan and the world.
In general, it is known that extreme climatic conditions such as El Niño and positive Indian Ocean Dipole (IOD+) cause prolonged drought in Indonesia's tropical peatlands so that groundwater levels (GWL) drop and peat is prone to fire. However, 27 years of GWL measurements in Central Kalimantan peat forests show the opposite condition, where the lowest GWL occurs several weeks before El Niño and after IOD+ reaches its peaks. We show that the dropped sea surface temperature anomaly induced by anomalously easterly winds along the southern Java-Sumatra occurs several weeks before the GWL drop to the lowest value. Local rainfall decreased, and GWL dropped sharply by 1.0 to 1.5 m, during the super El Niño events in 1997/98 and 2015, as well as remarkable events of IOD+ in 2019. It is suggested that the tropical peatland ecohydrological system (represented by the GWL), El Niño Southern Oscillation (ENSO), and IOD+ are teleconnected. Hence, monitoring GWL variability of peatland over the IMC is a possibility an alert for extreme climate events associated with El Niño and/or moderate IOD+.
Unlabelled: Coastal cities are under severe threat from the impacts of climate change, such as sea-level rise, extreme weather events, coastal inundation, and ecosystem degradation. It is well known that the ocean, and in particular coastal environments, have been changing at an unprecedented rate, which poses increasing risks to people in small island developing states, such as Fiji. The Greater Suva Urban Area, the capital and largest metropolitan area of Fiji, is expected to be largely impacted by climate-related risks to its socio-economic, cultural, and political positions. In the face of these threats, creating a resilient city that can withstand and adapt to the impacts of climate change and promote sustainable development should be guided by a holistic approach, encompassing stakeholders from the government, the private sector, civil society organizations, and international institutions. This study assesses the risk profile of Suva city using an innovative risk information tool, the climate and ocean risk vulnerability index (CORVI), which applies structured expert judgment to quantify climate-related risks in data-sparse environments. Through comparative quantification of diverse risk factors and narrative analysis, this study identifies three priority areas for Suva's future climate-resilient actions: development of climate risk-informed urban planning, harmonized urban development and natural restoration, and enhancing the climate resilience to the tourism sector. Supplementary information: The online version contains supplementary material available at 10.1007/s11027-022-10043-4.
In recent times, environmental stewardship of mangroves has provided the impetus to protect and restore these ecosystems for their inherent ability to protect coastal regions from climate change, sequester carbon dioxide as rich blue carbon, and support human well-being through a multitude of ecosystem services. Participatory stakeholder assessment, as a part of the present study, integrated local stakeholder perspectives in assessing drivers of mangrove loss in Bhitarkanika and Mahanadi delta, Odisha, providing empirical evidence through a mixed-method approach. The use of a Likert scale provided the methodology to develop a single composite variable as the best measure of central tendency. In total, 27.5% of the respondents were locals and were living close to the study area for generations, whereas the other 72.5% represented researchers, academics, and forest department officials. Stakeholder responses at the ground level indicated that Bhitarkanika and Mahanadi delta were facing increased frequency of extreme climatic events followed, by aquaculture and other land-use changes, which can be considered potential drivers causing mangrove loss. Co-development of future scenarios by integrating concerns of all the stakeholders emerged as a potential solution to effectively address the trade-offs arising from local anthropogenic interferences, as well as large-scale developmental activities. This study highlights the need for convergence of multi-disciplinary knowledge from diverse stakeholder groups, including traditional and indigenous knowledge, for the purpose of developing accurate plausible alternative scenarios. Interactive governance and incentivization approaches, along with alternative livelihood opportunities, are proposed as the means to improve conservation and restoration in the region based on the present study. Understanding of the coupled socio-ecological system and its relevance is found to be critical to improve bi-directional linkages of ecosystem health and human well-being.
In contrast to other natural disasters, droughts may develop gradually and last for extended periods of time. The World Meteorological Organization advises using the Standardized Precipitation Index (SPI) for the early identification of drought and understanding of its characteristics over various geographical areas. In this study, we use long-term rainfall data from 14 rain gauge stations in the Vietnamese Mekong Delta (1979-2020) to examine correlations with changes in rice yields. Results indicate that in the winter-spring rice cropping season in both 2016 and 2017, yields declined, corresponding with high humidity levels. Excessive rainfall during these years may have contributed to waterlogging, which in turn adversely affected yields. The results highlight that not only drought, but also humidity has the potential to adversely affect rice yield.
The Kaziranga Eco-Sensitive Zone is located on the edge of the Eastern Himalayan biodiversity hotspot region. In 1985, the Kaziranga National Park (KNP) was declared a World Heritage Site by UNESCO. Nowadays, anthropogenic interference has created a significant negative impact on this national park. As a result, the area under natural habitat is gradually decreasing. The current study attempted to analyze the land use land cover (LULC) change in the Kaziranga Eco-Sensitive Zone using remote sensing data with CA-Markov models. Satellite remote sensing and the geographic information system (GIS) are widely used for monitoring, mapping, and change detection of LULC change dynamics. The changing rate was assessed using thirty years (1990-2020) of Land-sat data. The study analyses the significant change in LULC, with the decrease in the waterbody, grassland and agricultural land, and the increase of sand or dry river beds, forest, and built-up areas. Between 1990 and 2020, waterbody, grassland, and agricultural land decreased by 18.4, 9.96, and 64.88 %, respectively, while sand or dry river beds, forest, and built-up areas increased by 103.72, 6.96, and 89.03 %, respectively. The result shows that the area covered with waterbodies, grassland, and agricultural land is mostly converted into built-up areas and sand or dry river bed areas. According to this study, by 2050, waterbodies, sand or dry river beds, and forests will decrease by 3.67, 3.91, and 7.11 %, respectively; while grassland and agriculture will increase by up to 16.67 % and 0.37 %, respectively. The built-up areas are expected to slightly decrease during this period (up to 2.4 %). The outcome of this study is expected to be useful for the long-term management of the Kaziranga Eco-Sensitive Zone.
Drought is one of the most frequent and widespread natural hazards in Tien Giang province of Vietnam, which is aggravating under the influence of climate change. As agriculture is the primary economy of the province, it is crucial to understand the influence of climate change on drought severity and how the local farmers perceive and adapt to climate change. Therefore, to examine the impacts of climate change on drought in the Tien Giang province in the Mekong Delta, the present study used three General Circulation Models (GCMs)—ACCESS 1.3, CNRM-CM5, and MRI-CGCM3 under two Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. In addition, the study evaluated household-level adaptation strategies based on structured questionnaire-based household survey data and focus group discussion. This study finds that the drought will be getting more severe in the future in the province based on using three GCMs and two climate change scenarios. The estimated results of the Standardized Precipitation Index (SPI) show that there would be many potential extreme drought years between 2020 and 2050. The results from the questionnaire survey depicted that the household perception of drought is moderate in the Mekong Delta. The current adaptation measures are sufficient to adapt to moderate drought and can be improved to adapt to more potential extreme drought conditions in the future. This study provides important insights for decision-makers to manage future drought situations in the Mekong region.
Despite Bangladesh being one of the leading countries in aquaculture food production worldwide, there is a considerable lack of updated scientific information about aquaculture activities in remote sites, making it difficult to manage sustainably. This study explored the use of geospatial and field data to monitor spatio-temporal changes in aquaculture production sites in the Satkhira district from 2017–2019. We used Shuttle Radar Topographic Mission digital elevation model (SRTM DEM) to locate aquaculture ponds based on the terrain elevation and slope. Radar backscatter information from the Sentinel-1 satellite, and different water indices derived from Sentinel-2 were used to assess the spatio-temporal extents of aquaculture areas. An image segmentation algorithm was applied to detect aquaculture ponds based on backscattering intensity, size and shape characteristics. Our results show that the highest number of aquaculture ponds were observed in January, with a size of more than 30,000 ha. Object-based image classification of Sentinel-1 data showed an overall accuracy above 80%. The key factors responsible for the variation in aquaculture were investigated using field surveys. We noticed that despite a significant number of aquaculture ponds in the study area, shrimp production and export are decreasing because of a lack of infrastructure, poor governance, and lack of awareness in the local communities. The result of this study can provide in-depth information about aquaculture areas, which is vital for policymakers and environmental administrators for successful aquaculture management in Satkhira, Bangladesh and other countries with similar issues.
To monitor the spread of the novel coronavirus (COVID-19), India, during the last week of March 2020, imposed national restrictions on the movement of its citizens (lockdown). Although India’s economy was shut down due to restrictions, the nation observed a sharp decline in particulate matter (PM) concentrations. In recent years, Delhi has experienced rapid economic growth, leading to pollution, especially in urban and industrial areas. In this paper, we explored the linkages between air quality and the nationwide lockdown of the city of Delhi using a geographic information system (GIS)-based approach. Data from 37 stations were monitored from 12 March, 2020 to 2 April, 2020 and it was found that the Air Quality Index for the city was almost reduced by 37% and 46% concerning PM2.5 and PM10, respectively. The study highlights that, in regular conditions, the atmosphere’s natural healing rate against anthropogenic activities is lower, as indicated by a higher AQI. However, during the lockdown, this sudden cessation of anthropogenic activities leads to a period in which the natural healing rate is greater than the induced disturbances, resulting in a lower AQI, and thus proving that this pandemic has given a small window for the environment to breathe and helped the districts of Delhi to recover from serious issues related to bad air quality. If such healing windows are incorporated into policy and decision-making, these can prove to be effective measures for controlling air pollution in heavily polluted regions of the World.
Rapid urbanization has led to the emergence of slums in many developing and industrialized nations. It degrades the quality of life and burdens the urban amenities resulting in the uneven distribution of slums. The majority of people in the developing world live in squatter settlements, and these random gatherings disrupt the economic and social developmental plans of the concerned country. No suitable planning framework has been created for replicability on a considerable scale, despite the fact that slum upgrading is acquiring worldwide importance as a political issue. In recent years Jammu City has witnessed high population growth rates resulting in an uneven provision of urban amenities and a surge in slum areas. This paper focuses on a method-based approach using a Management Information System (MIS) and Geographic Information System (GIS) for upgrading slums and recommends a planning outline using the approach formulated by the Government of India under the scheme named “Rajiv Awas Yojna” (RAY). This study aims to assess the status of slums, propose redevelopment plans, and highlight the roles of different planning agencies in accomplishing the redevelopment goals. The study concludes by postulating several recommendations for upgrading slums and formulating a framework that can be used in other similar areas for development.
Manufacturing and mining sectors are serious pollution sources and risk factors that threaten air quality and human health. We analyzed pollutants at two study sites (Talcher and Brajrajnagar) in Odisha, an area exposed to industrial emissions, in the pre-COVID-19 year (2019) and consecutive pandemic years, including lockdowns (2020 and 2021). We observed that the annual data for pollutant concentration increased at Talcher: PM2.5 (7-10%), CO (29-35%), NO2 and NOx (8-57% at Talcher and 14-19% at Brajrajnagar); while there was slight to substantial increase in PM10 (up to 11%) and a significant increase in O3 (41-88%) at both sites. At Brajrajnagar, there was a decrease in PM2.5 (up to 15%) and CO (around half of pre-lockdown), and a decrease in SO2 concentration was observed (30-86%) at both sites. Substantial premature mortality was recorded, which can be attributed to PM2.5 (16-26%), PM10 (31-43%), NO2 (15-21%), SO2 (4-7%), and O3 (3-6%). This premature mortality caused an economic loss between 86-36 million USD to society. We found that although lockdown periods mitigated the losses, the balance of rest of the year was worse than in 2019. These findings are benchmarks to manage air quality over Asia's largest coalmine fields and similar landscapes.
This study aimed to develop temporal rainfall distribution patterns of 1-day, 3-, 5-, and 7-consecutive rain days for three meteorological stations in Tra Vinh province (Cang Long, Tieu Can, and Tra Cu), using daily rainfall data from 1978 to 2017. The study follows the Vietnamese National Standards (TCVN 10406:2015:Irrigation Works – Calculation of Design Drainage Coefficients) to determine the frequency of events of various rainfall distribution drainage patterns. Thereafter, the probability method was conducted to identify rainfall pattern design according to a 10-year return period. Only Cang Long meteorological station exhibited enough single events of rainfall patterns (>10) for 3 consecutive days to determine a rainfall distribution drainage pattern, fitting in pattern type 1 and distribution types 2 and 3. However, for all distribution types of rainfall patterns, the one with the highest last-day rainfall is the most adverse pattern. Therefore, this study recommends building a 3-consecutive day design rainfall for Cang Long station of pattern type 1 and distribution type 3 for precautionary purposes.
The response of land surface phenology (LSP) to the urban heat island effect (UHI) is a useful biological indicator for understanding how vegetated ecosystems will be affected by future climate warming. However, vegetation cover in rural areas is often dominated by cultivated land, whose phenological timing is considerably influenced by agricultural managements (e.g., timing of sowing and harvesting), leading to biased conclusions derived from the urban-rural LSP differences. To demonstrate this problem, we investigated the crop influence on the phenological response to a warmer environment resulting from the UHI effect. We partitioned cities in the United States into cultivated and non-cultivated categories according to the proportion of crops in rural areas. We then built continuous buffer zones starting from the urban boundary to explore the urban-rural LSP differences considering the UHI effect on them. The results suggest crop inclusion is likely to lead to >14 days of urban-rural differences at both the start of the season (SOS) and the end of the season (EOS) between cultivated and non-cultivated cities. The temperature sensitivity (ST) of SOS is overestimated by approximately 2.7 days/°C, whereas the EOS is underestimated by 3.6 days/°C. Removing crop-dominated pixels (i.e., above 50 %) can minimize the influence of crop planting/harvesting on LSP and derive reliable results. We, therefore, suggest explicit consideration of crop impacts in future studies of phenological differences between urban and rural areas and the UHI effect on LSP in urban domains, as presented by this comprehensive study.
Agriculture in the Global South is innately susceptible to climatic variability and change. In many arid and semi-mountainous regions of the developing world, drought is regularly cited as a significant threat to agricultural systems. The objective of this study is to assess the impacts of climate change on drought and land use and land cover (LULC) change in a semi-mountainous region of the Vietnamese Mekong Delta. We assessed previous drought trends (1980-2020) and future drought in the context of climate change, in accordance with three selected scenarios from the Coupled Model Intercomparison Project Phase 6 global climate models which have recently been released by the Intergovernmental Panel on Climate Change (IPCC) (2021-2060) using the Standardized Precipitation Index (SPI). The change of land use for the period 2010-2020 was then assessed and the associated climatic variability explored. The results show that for the period 1980-2019, SPI 3 responds quickly to changes in precipitation, whereas SPI 9 showed a clear trend of precipitation over time. The first longest duration occurrence of drought for SPI 3, SPI 6, and SPI 9 patterns were respectively 15-16, 21, and 25 months at Chau Doc station, and respectively 11, 14-15, and 16-17 months at Tri Ton station. Future precipitation and both maximum/minimum temperatures are projected to increase in both the wet and dry seasons. In addition, for all-time series scales and climate change scenarios, the levels of drought were slight, followed by moderate. In the future, the humidity at Chau Doc station is expected to decrease, while the occurrence of drought events is expected to increase at Tri Ton station, particularly in SPI 6 patterns (110 drought events in 1980-2020, and up to 198 drought events in the future). Moreover, between 2010-2020, the agricultural land area was seen to decrease, replaced by non-agricultural land uses that were found to increase by 22.4%. Among the agricultural land area, forestry, rice crops, and upland rice were found to reduce by 7.5, 16.0, and 21.2%, respectively, while cash crops and perennial crops increased by 26.4% and 170.6%, respectively. Amongst other factors, it is concluded that the variability of climate has led to drought and thus impacted on the conversion of LULC in the study area. Due to low economic efficiency, changing climate conditions, and a lack of irrigated water, the area of rice crops, forestry, aquaculture , and upland rice decreased, replaced by land for orchards for fruit production and other cash crops.
Globally, hydrometeorological hazards have large impacts to agriculture output, as well as human well-being. With climate change derived increasing frequency of extreme weather conditions, the situation has becoming more severe. This study strives to evaluate both dry and wet conditions in the Vietnamese Mekong Delta (VMD), also known as the rice basket of the Southeast Asian region. Different meteorological parameters from the last three decades were used to develop drought indices for Ca Mau province to investigate their impact on agricultural output. For this purpose, the standard precipitation index (SPI), the agricultural rainfall index (ARI), and the standardized precipitation evapotranspiration index (SPEI) were used in this study. Results highlight that Ca Mau has a peculiar characteristic of the whole VMD in that dry periods persist well into the wet season extending the duration of drought events. The role of storms, including tropical storms, and El Niño cannot be ignored as extreme events, which both change humidity, as well as rainfall. It is also found that the drought situation has caused significant damage to both rice and shrimp outputs in almost 6000 hectares. The assessment contributes to an improved understanding of the pattern of unpredictable rainfall and meteorological anomaly conditions in Ca Mau. The findings of this paper are important for both policymakers and practitioners in designing more robust plans for water resource management.
Satellite remote sensing and geographic information system (GIS) have revolutionalized the mapping, quantifying, and assessing the land surface processes, particularly analyzing the past and future land use-land cover (LULC) change patterns. Worldwide river basins have observed enormous changes in the land system dynamics as a result of anthropogenic factors such as population, urbanization, development, and agriculture. As is the scenario of various other river basins, the Brahmaputra basin, which falls in China, Bhutan, India, and Bangladesh, is also witnessing the same environmental issues. The present study has been conducted on the Brahmaputra Valley in Assam, India (a sub-basin of the larger Brahmaputra basin) and assessed its LULC changes using a maximum likelihood classification algorithm. The study also simulated the changing LULC pattern for the years 2030, 2040, and 2050 using the GIS-based cellular automata Markov model (CA-Markov) to understand the implications of the ongoing trends in the LULC change for future land system dynamics. The current rate of change of the LULC in the region was assessed using the 48 years of earth observation satellite data from 1973 to 2021. It was observed that from 1973 to 2021, the area under vegetation cover and water body decreased by 19.48 and 47.13%, respectively. In contrast, cultivated land, barren land, and built-up area increased by 7.60, 20.28, and 384.99%, respectively. It was found that the area covered by vegetation and water body has largely been transitioned to cultivated land and built-up classes. The research predicted that, by the end of 2050, the area covered by vegetation, cultivated land, and water would remain at 39.75, 32.31, and 4.91%, respectively, while the area covered by built-up areas will increase by up to 18.09%. Using the kappa index (ki) as an accuracy indicator of the simulated future LULCs, the predicted LULC of 2021 was validated against the observed LULC of 2021, and the very high ki observed validated the generated simulation LULC products. The research concludes that significant LULC changes are taking place in the study area with a decrease in vegetation cover and water body and an increase of area under built-up. Such trends will continue in the future and shall have disastrous environmental consequences unless necessary land resource management strategies are not implemented. The main factors responsible for the changing dynamics of LULC in the study area are urbanization, population growth, climate change, river bank erosion and sedimentation, and intensive agriculture. This study aims to provide the region's policy and decision-makers with the necessary what-if scenarios for better decision-making. It shall also be useful in other countries of the Brahmaputra basin for the whole region's transboundary integrated river basin management.
The southwestern coastal part of Bangladesh is highly vulnerable to different kinds of disasters due to the changing climatic conditions. With the lenses of rural communities here an approach to examine how were the different disasters experiences, what lesson they learnt and what are their present disaster associated problems and stakeholder’s networks they rely on to enhance their resilience. Qualitative data were collected through participatory rapid rural appraisal (100–150 persons), field observation, 12 focus group discussions (25–40 people/FGD), and key informant interviews (25 people) in four southwestern coastal districts and nine coastal villages of Bangladesh. Results showed that since long back to date drinking water crisis, poor roads, poverty, poor sanitation, and health problems are the main identified disaster-associated problems. After learning lessons from previous disaster experiences, the community people have improved and changed their practices mainly by storing emergency foods, house construction, and increasing disaster awareness. However, the coastal communities are combating with the problems that have both direct and indirect association with poor infrastructures. Therefore, the coastal communities urge and sketched for a better stakeholders’ supports and networks to minimize their problems and thus to enhance communities’ disaster resilience.
The impact of changing land use and land cover (LULC) on regional habitat quality have attracted extensive attention. The Loess Plateau is an ecologically fragile area; LULC changes in this region have complex impacts on habitat quality at multiple spatiotemporal scales. This study developed an integrated assessment method based on multi-source data to assess habitat quality changes in the Loess Plateau during recent years (2000–2015) and in the future (2015–2050) under four typical scenarios. A significant increase in urban land use was observed on the Loess Plateau from 2000 to 2050, which resulted in a continuous decrease in the cropland area. The area of forest and grassland landscapes was also reduced by both urban and cropland expansion, with the most significant loss in the grasslands. A future overall decreasing trend in overall habitat quality is predicted, but the SSP1–2.6 scenario is significantly better than the SSP5–8.5 scenario. Urban expansion contributes a rapidly increasing proportion of habitat quality decline on the Loess Plateau; urban land will become the most significant threat to regional habitat quality by 2030. Policies for socio-ecological protection with clear, high-level objectives can effectively promote habitat quality. It is recommended that national nature reserves be delineated and ecological functions in the study area be continuously monitored. This research provides a potential socio-ecological baseline and implementation strategy for the habitat conservation-oriented management of large and fragile ecological regions.
Detailed Land-Use and Land-Cover (LULC) information is of pivotal importance in, e.g., urban/rural planning, disaster management, and climate change adaptation. Recently, Deep Learning (DL) has emerged as a paradigm shift for LULC classification. To date, little research has focused on using DL methods for LULC mapping in semi-arid regions, and none that we are aware of have compared the use of different Sentinel-2 image band combinations for mapping LULC in semi-arid landscapes with deep Convolutional Neural Network (CNN) models. Sentinel-2 multispectral image bands have varying spatial resolutions, and there is often high spectral similarity of different LULC features in semi-arid regions; therefore, selection of suitable Sentinel-2 bands could be an important factor for LULC mapping in these areas. Our study contributes to the remote sensing literature by testing different Sentinel-2 bands, as well as the transferability of well-optimized CNNs, for semi-arid LULC classification in semi-arid regions. We first trained a CNN model in one semi-arid study site (Gujranwala city, Gujranwala Saddar and Wazirabadtownships, Pakistan), and then applied the pre-trained model to map LULC in two additional semi-arid study sites (Lahore and Faisalabad city, Pakistan). Two different composite images were compared: (i) a four-band composite with 10 m spatial resolution image bands (Near-Infrared (NIR), green, blue, and red bands), and (ii) a ten-band composite made by adding two Short Wave Infrared (SWIR) bands and four vegetation red-edge bands to the four-band composite. Experimental results corroborate the validity of the proposed CNN architecture. Notably, the four-band CNN model has shown robustness in semi-arid regions, where spatially and spectrally confusing land-covers are present.
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79 members
Premakumara Dickella
  • IGES Centre Collaborating with UNEP on Environmental Technologies (CCET)
Xianbing Liu
  • Climate and Energy Area
Pankaj Kumar
  • Adaptation and Water
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