Abstract Urbanisation significantly modifies land surfaces and amplifies local temperatures and heat stress. This study investigates Surface Urban Heat Island Intensity (SUHII) across the Mumbai Metropolitan Region (MMR) from 2003 to 2023 using Google Earth Engine (GEE) database and mapping. It integrates surface imperviousness from the Global Human Settlement Layer (GHSL), Land Use Land Cover (LULC), and the Local Climate Zone (LCZ) classification (2019) to explore spatial patterns in SUHII. Daily Land Surface Temperature (LST) data from MODIS was further analysed for details across 852 spatially sampled points, categorised by land cover types. Findings reveal a consistent urban–rural SUHII of ~2 °C, with mean LSTs of 35.63 °C in urban and 33.67 °C in rural zones. Urban cores exhibit greater seasonal variability, with LSTs peaking above 51 °C in some areas. Auto Regressive Integrated Moving Average - ARIMA (2,1,1) time-series modelling indicates persistent warming trends, with 2023 pre-monsoon LSTs projected to exceed 44 °C in central MMR with an average of existing 51 °C in urban MMR and about 49 °C in rural MMR. A weak negative Pearson correlation (r = -0.19) between impervious surface intensity and SUHII suggests that built-up extent alone does not explain thermal intensity. LCZ-based profiling shows that Compact High-Rise and Industrial zones have the highest LSTs, while vegetated zones maintain cooler profiles (<31 °C). Zones with >70 % impervious surfaces record disproportionately higher temperatures. Importantly, a review of existing studies shows that no published research has yet combined ARIMA forecasting with LOESS (Locally Estimated Scatterplot Smoothing) for MMR. This study uniquely combines remote sensing, statistical modelling (ARIMA, Pearson correlation), and urban climate zoning via cloud computing for the region. Deep Learning derived spatial datasets (GHSL, LCZ) enhance the spatial resolution of SUHII analysis. The results offer vital insights for climate-adaptive urban planning, emphasising zoning-based interventions, and landscape strategies to mitigate urban heat risks in expansive cities like Mumbai and its surroundings.

Abstract This study investigates the ecological risk of Halti Beel, one of the significant parts of the largest wetland ecosystem of Bangladesh, following the US Environmental Protection Agency (EPA) ecological risk assessment (ERA) guidelines. Physicochemical parameters of water and sediment were analyzed in reference to Environmental Conservation Rules (ECR) and EPA standards. Socio-economic data from local communities and species data from wetland authorities were integrated through questionnaire surveys. Multispectral satellite imageries were used to evaluate the ecological risks associated with LULC changes from 2000 to 2023. ENVI Thematic Change Workflow (TCW) tool was used for LULC change dynamics analysis over 2000-2010, 2010-2023, and 2000-2023. An ecological risk model was developed using Landscape Ecological Risk Indexes (LERI) in Fragstats 4.2; risk zones were mapped, and risk levels were categorized from minimal to severe. A linear regression analysis in SPSS was done to reveal significant relationships between ecological risk and different stressors. The results indicate that the collected samples’ DO, turbidity and electric conductivity exceed the ECR, 1997, and EPA, 2012 standards. The socio-economic prospects of the area largely depend on fishing, farming, and wetland resources, which support local livelihoods despite growing environmental pressure. However, low education levels, poor sanitation, and unregulated land use challenge the local people’s socioeconomic condition. Most of the environmental and anthropogenic factors have strong connections with ecological risk and leave the current status of species highly vulnerable. The significant LULC transformation: from 2000 to 2023, 55.63 % of deep water was converted into shallow water, 11.68 % to agricultural land, and 19.52% of agricultural land was converted to rural settlements, indicating increasing anthropogenic pressure. Between 2000 and 2010, notable changes are that 60.86 % of deep water was converted into shallow water and 18.54 % shifted to agricultural land. From 2010 to 2023, a major transformation of almost half of the deep water area was converted into shallow water and 9.09 % to agricultural land. Ecological risk fluctuated over time; in 2023 ecological risk spread all over the area and middle, highest, and higher risk areas increased synchronously. Major ecological risk areas shifted to the southwest part of the area. The overall results indicate that ecological risk is increasing evidently.

Abstract Climate change and variability have significantly impacted smallholder and subsistence farmers in Ethiopia. The effectiveness of adaptation measures largely depends on how farmers perceive climate change and variability. Hence, understanding their perception and comparing it with long-term trends is crucial for designing appropriate responses. Thus, this study examined climate parameters and smallholder farmers’ awareness of climate change in the Jemma sub-basin. A total of 366 households were randomly selected from highland, midland, and lowland kebeles. Quantitative and qualitative data were collected through household surveys, focus group discussions, and key informant interviews. Grided monthly precipitation and temperature data were obtained from the Ethiopian Meteorology Institute. The Mann–Kendall test and Sen’s slope estimator were employed to examine the time series trends of rainfall and temperature. The MK trend test results revealed that yearly and summer season rainfall exhibit a non-significant increasing trend, while spring season rainfall shows a decreasing trend. The coefficient of variance shows that the monthly and spring season rainfall shows the highest variability (CV>30 %), while the annual rainfall shows less variability. Similarly, the mean annual, maximum, and minimum temperatures show an increasing trend. Consequently, about 83.47 % of highland, 91.54 % of midland, and 100 % of lowland respondents feel the temperature rise, and 44.62 %, 66.2 %, and 100 % of highland, midland, and lowland respondents recognized the decreasing rainfall trend, respectively. The analysis result reveals that age, gender, access to climate information, education, farming experience, and market access significantly influence perceptions of temperature and rainfall trends. Therefore, farmers’ perceptions should be integrated into meteorological data analysis, and policymakers should consider these disparities when developing climate adaptation strategies.

Abstract Sacred groves (SGs) are community-protected forest patches dedicated to local deities, crucial for biodiversity conservation but threatened by habitat loss and weakening traditions. This study provides the first inventory of SGs in Western Haryana, documenting 108 groves across 107 Gram Panchayats, covering 5,888 acres. The Bhiwani division contained 43 % of groves and 50 % of total area, with clustering in Loharu, Charkhi Dadri, and Bhiwani ranges. Sizes varied from <50 acres (48 %) to >100 acres (17 %), and eight grove types were identified, dominated by Temple/Mandir groves (58.3 %). In total, 69 deities were recorded, with 48 % of groves linked to village-based deities. Notably, over 90 % showed ecological degradation due to boundary erosion, biomass removal, and encroachment, while most lacked formal recognition. These findings affirm SGs as biocultural “mini-biospheres” shaped by rituals and land-use legacies, highlighting the urgent need for strengthened governance through People’s Biodiversity Registers, panchayat bylaws, and cultural incentives. The study provides a quantitative baseline for conservation strategies that integrate ecological and cultural sustainability.

Abstract Urban areas are very dynamic places that are changing rapidly due to population growth and urbanization.This study aimed to assess the spatio-temporal dynamics of UGS under land use/land cover change (LULCC) from 1991 to 2024 in Gondar city. To do this, a combination of spatial and non-spatial data sources, including ArcGIS (Ver. 10.8), ERDAS Imagine 2015 and thematic analysis, were employed. A supervised image classification method was employed to create LULCC maps. The results showed that a decrease in the area of water bodies (WB) and croplands (CL) by 1 422.87 and 4,076.93 ha, respectively, while built-up areas (BUA), bare lands (BL) and UGS increased by 4,051.99, 863.66 and 584.15 ha, respectively. The findings revealed that urban expansion, rural-urban migration, population growth, land grabbing and illegal settlements were the main drivers of LULCC. Moreover the rate of UGS change increased by 17.7 ha annually, with a total gain, net change, and net persistence of 1,758.46, 584.15 and 0.82 ha, respectively. The highest area of UGS converted to CL and BUA. To enhance UGS development and a sustainable urban environment, it is crucial to implement effective land use development and management strategies, manage urban expansion and population growth and regulate illegal settlements and land grabbing. These results provide valuable insights for policymakers in the field of urban green infrastructure planning and environmental management and contribute to the existing literature while enhancing knowledge on UGS.

Abstract This study evaluates the impact of a participatory forest management (PFM) program on forest structure and cover change in the Guangua Elala Natural Forest, Ethiopia. A comparison of current vegetation data with baseline information collected by Guangua Woreda agricultural experts was conducted to assess structural and coverage changes. Vegetation data were gathered from 44 plots, each measuring 20 m × 20 m, to capture tree and shrub density, height, and diameter distributions. Additionally, cloud-free Landsat-7 and Landsat-8 images from 2012 and 2021 were analyzed to determine forest cover change over time. Data analysis included computation of vegetation metrics such as stem density, height, and diameter classes, with t-tests applied to compare these variables before and after PFM implementation. Results indicate that the forest displays a healthy, inverted ‘J’ shape population structure, which signifies robust regeneration with higher densities in lower diameter and height classes. Forest and shrub land cover expanded slightly after the PFM program, with increases of 0.69 % and 0.27 %, respectively. This suggests that PFM positively impacts both the structural health and coverage of the forest by promoting regeneration and conserving existing cover. Overall, this study concludes that PFM contributes to the stability and improvement of forest ecosystems in the region. Expanding PFM initiatives to neighboring forests could further enhance forest conservation and provide sustainable benefits to local communities. This research underscores the effectiveness of participatory approaches in managing forest resources for both ecological and social benefits.

Abstract In East Africa, Ethiopia’s rangelands constitute about 64 % of lowland areas, serving as primary feed resources for pastoral communities. However, these rangelands face severe degradation due to overgrazing, climate variability, human disturbance, and invasive species, threatening both productivity and biodiversity. This study assessed the impact of grazing and rangeland exclosures on vegetation dynamics, species diversity, biomass, and pastoral livelihoods in Chifra district, Afar Region, Ethiopia. Stratified random sampling compared enclosed and communally grazed areas through vegetation surveys and household interviews (n=195). Results revealed significantly higher species richness, diversity (H’=2.59 vs 1.46), and herbaceous biomass in enclosed areas compared to open communal grazing lands. Exclosures promoted the regeneration of highly desirable grasses and woody species while reducing invasive and less palatable plants. Pastoralists identified low rainfall and overgrazing as major causes of rangeland decline, impacting livestock productivity and food security. Indigenous management practices such as stock mobility, exclosures establishment, and de-stocking ranked highest for restoring rangeland health. The study highlights the effectiveness of grazing exclusion in rehabilitating degraded rangelands and sustaining pastoral livelihoods. Integrating traditional knowledge with scientific approaches and supporting exclosures management can improve vegetation recovery, biomass production, and resilience against environmental stressors. These findings provide key insights for sustainable rangeland management and conservation strategies in arid and semi-arid pastoral systems.

Abstract Fruit tree-based agroforestry practice in Moret and Jiru was developed by the farmers themselves over time. However, their distribution had remained to certain localities. Thus, this research answers determinants of adoption and the management practices of fruit tree-based agroforestry practice in the study area. Therefore, this research aims to (i) assess management practices of FTBAFPs; ii) identify the determinants of smallholder farmers’ adoption of FTBAFPs in the Moret and Jiru District, North Shewa Zone, Ethiopia. Data were collected in three purposively selected Kebeles using household survey (149 households), key informants (18), focus group discussion (3) and field observation due to the high potential of fruit production and accessibility to data collection. The collected data were analysed using descriptive statics and binary logistic regression methods. The result revealed that common management practices employed by respondents for fruit trees included thinning, hoeing, fencing, pest and disease control, watering, weeding, and fertilizing. However, adoption of FTBAFP was positively and significantly influenced by age (p =0.006), and education (p = 0.004)) at 1 % significance level; landholding (p = 0.017), labour (p = 0.030), and wealth status of households (0.042) at 5 % significance level. Therefore, due emphasis has to be given towards strengthening rural education for adults to increase number of agroforestry adopters by increasing awareness and an appropriate intervention such as variety improvement through research to reduce susceptibility by disease and pest of fruit tree–based agroforestry practice.

Abstract This study examines the application of Geographic Information Systems (GIS) for property tax assessment within the Shillong Municipal Board (SMB), India, highlighting the transformative potential of geospatial technology in improving urban governance for smaller municipalities. A total of 26,611 built-up plots across 27 wards were digitized and categorized into six zones based on economic value. The study employed the Unit Area Value (UAV) method, integrated with GIS, incorporating factors such as construction type, building age, ownership, usage, and location to calculate property taxes. The results revealed notable variations in tax revenue between wards and zones, with central areas generating significantly higher revenue than peripheral regions. The GIS-based system enhanced accuracy in property identification, standardized valuation methods, and improved data management. However, challenges in maintaining up-to-date data and addressing socio-economic disparities in tax burdens were observed. The study proposes improvements, including refining UAV values, adding new assessment factors, and utilizing machine learning for property classification. This research offers a scalable model for small and medium-sized municipalities, providing insights into more efficient, equitable, and transparent property tax systems. The findings have important implications for urban planning, revenue generation, and policy-making, supporting data-driven approaches to sustainable urban development in India and beyond.

Abstract This study aims to assess the spatio-temporal dynamics of vegetation in the Zouagha Forest, located in northeastern Algeria, over the period 2000-2020, taking into account the degradation induced by the complex interactions between biotic, abiotic, and anthropogenic factors. The analysis of vegetation indices, notably the NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), and SAVI (Soil-Adjusted Vegetation Index), for the years 2000, 2010, and 2020 reveals divergent trends. The NDVI shows a slight increase, rising from 0.20 in 2000 to 0.33 in 2020, suggesting a moderate regeneration of the vegetation cover. In contrast, the EVI records a notable decline, dropping from 0.38 in 2000 to 0.30 in 2020, indicating a continuous degradation in vegetation quality. Additionally, the SAVI shifts from −0.10 to 0.07, reflecting a modest improvement, yet the vegetation remains weak in terms of density and quality. This divergence between the indices suggests a spatial variation in vegetation conditions, indicating a growing heterogeneity in vegetation distribution across the forest. This phenomenon is exacerbated by unfavorable climatic conditions, such as reduced rainfall and rising temperatures. These changes, combined with anthropogenic pressures such as deforestation, greatly limit the forest’s natural regeneration capacity. Moreover, pest attacks, particularly by ( Lymantria dispar ) and ( Tortrix viridana ), contribute to uneven degradation of the forest ecosystem. These findings highlight the urgency of developing sustainable management strategies, incorporating soil restoration and water resource management, to strengthen the ecological resilience of the Zouagha Forest in the face of growing challenges posed by climate change and human pressures.