Abstract

Aim: Deforestation due to unplanned developmental activities leading to the loss of carbon sequestration capability and the release of stored carbon to the atmosphere has been a prime mover of global warming, with changes in the climate evident from the spatio-temporal changes in the rainfall, increase in temperature, and higher instances of vector-borne diseases. Unregulated land cover changes have necessitated prioritizing ecologically sensitive regions to develop location-specific management strategies. This entails estimating spatio temporal LULC changes using multi-resolution spatial data to understand landscape dynamics, which helps in the prudent management of natural resources. Methodology: The current communication accounts for land use transitions in the Belgaum district, part of central Western Ghats, through classifying spatial data over a temporal scale using a supervised classifier. Ecologically sensitive regions are prioritized by integrating bo-geo-climatic, ecological, hydrologic, and social parameters. Results: Temporal land use analyses reveal a loss of forest cover by 2.99% (90.29 sq km) with an increase in the built-up area during two decades (1989 to 2019 and a decline of contiguous interior forests from 16.26% to 6.77%. Geo-visualisation of likely land uses through a hybrid Fuzzy MCE AHP MCA modeling indicates a further decrease of forest cover of 5.6% by 2029. Hence, it necessitates the conservation of ecologically sensitive regions (ESR) at disaggregated levels. Interpretation: Regions with exceptionally high sensitivity (ESR1) cover 15% of the spatial extent of the district, 27% (52 grids) cover higher sensitivity (ESR2), 52% (99 grids) are high to moderate sensitive (ESR3), and the rest 6% (12 grids) are minimal sensitive (ESR4). Prioritization of the region based on its ecological sensitiveness would facilitate decision-makers in the implementation of effective conservation policies focusing on maintaining the ecological integrity through prudent management of natural resources to support livelihood with the sustenance of natural resources. Key words: Forest fragmentation, Hybrid modeling, Livelihood of people, Land use Land cover, Natural Resource Management

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