Indian Sundarban Biosphere Reserve (SBR), a fragile ecosystem, is susceptible to frequent cyclones, floods, and storm surge. The study impeccably analyzed the socio-economic vulnerability in SBR using pragmatic approach. Average storm surge height, slope amount, flood inundation, drainage proximity, and drainage density were used for assessing exposure while sensitivity and adaptation were examined from the data derived through a comprehensive field survey of 570 households in SBR. The revelation of the study manifested very high vulnerability in Basanti, Gosaba, Kultali, Namkhana, and Patharpratima blocks and high vulnerability in Kakdwip, Sagar, and Hingalganj blocks of SBR. Constant exposure to cyclones and storm surges, frivolous infrastructural setup, impoverish social structure, and lamentation of losses are major barriers to overall socio-economic upliftment of communities. Consolidated infrastructural setup, proper early warning system, disaster monitoring centres, better transport connectivity within remote islands, better livelihood opportunities, education, and awareness may help in improving the socio-economic conditions of the communities. Pragmatic approach assisted in the cogent understanding of climate change impacts and indicated adaptive and mitigation measures to improve coastal society in SBR. Thus, the approach has proven to be effective for analyzing the impact of climate change-induced hazards on socio-economic condition on the communities in coastal areas.

Land transformation as a result of unprecedented urbanization has introduced changes in local climate and surface energy budget. Land surface temperature (LST) is an important factor influencing local climate and ecology. Mumbai being second largest populated city is experiencing significant changes in land use/land cover (LULC) and surface energy fluxes. Hence, the main objective of the study is to assess the spatial variation in land surface temperature due to land use/land cover change. Several indices like; Normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), modified normalized difference water index (MNDWI) and normalized difference built up index (NDBI) were derived to validate the spatial variability of LST in different land use/land cover classes. The study utilized Landsat5/TM and Landsat8/TIRS data for assessing land transformation and its relation with LST in Mumbai city. January, June and October months of three time series 1990, 2000 and 2015 were chosen as representative of three seasons to analyze variation in LST. Pixel to pixel overlay analysis for different indices and LST was carried out to examine the relation of LST with different indices. The study revealed the maximum change in LST was recorded during the month of June over the study period. Land transformation from vegetation and agricultural land to urban built up has been found to be the main cause of increased LST in the study area. The finding of the study may help in promulgating sustainable urban land use policies and avoiding the effect of urban heat island.