Browsing by Author "Kaushalendra Prakash Goswami"

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Evaluating the influence of biophysical factors in explaining spatial heterogeneity of LST: Insights from Brahmani-Dwarka interfluve leveraging Geodetector, GWR, and MGWR models
(Elsevier Ltd, 2025) Bhaskar Mandal; Kaushalendra Prakash Goswami
The present study aims to investigate variations in land use and land cover (LULC) while examining how land surface temperature (LST) and biophysical parameters in the Brahmani-Dwarka Interfluve zone change over time. It also tries to discover LST clusters and outliers and investigate how biophysical variables influence the spatially stratified heterogeneity of LST. This study introduces an innovative perspective by concentrating on the Brahmani-Dwarka Interfluve, an area characterized by stone crushing and mining operations. It employs Geodetector, Geographically Weighted Regression (GWR), and Multiscale Geographically Weighted Regression (MGWR) to thoroughly evaluate the LST heterogeneity, thereby enhancing its uniqueness. Our analysis revealed LST saw a substantial rise of 7.05 °C, equivalent to an average yearly increase of around 0.235 °C between 1991-2021. The regions primarily occupied by stone crushing and mining activities showed elevated LST values compared to other LULC categories in the years 2001, 2011, and 2021. The factor detector findings suggested that the Normalized Difference Latent Heat Index (NDLI) had the most influence in 2001 (q-value 0.39) and 2021 (q-value 0.50), whereas the Normalized Difference Moisture Index (NDMI) had the highest influence in 1991 (q-value 0.39) and 2011 (q-value 0.29). Soil-adjusted Vegetation Index (SAVI) had the most negligible influence (q-value between 0.09-0.15). The Interaction detector findings identified NDLI with NDMI (q-value 0.42) and Modified Normalized Difference Water Index (MNDWI) (q-value 0.42) in 1991, NDLI with Normalized Difference Bareness Index (NDBaI) (q-value 0.41) and MNDWI (q-value 0.41) in 2001, and NDLI with Normalized Difference Vegetation Index (NDVI) (q-value 0.56) and SAVI (q-value 0.56) in 2021 as the most influential interacting variable. In 2011, significant interactions were identified between MNDWI and NDVI (q-value 0.31), NDMI, and SAVI (q-value 0.31), among others. A comparative assessment between regression models using AICc, R2, and adjusted R2 revealed that all MGWR models performed (R2 between 0.92-0.94 & adj. R2 between 0.89-0.92) much better than GWR and Ordinary Least Square (OLS) models during the research period. The results will undoubtedly assist policymakers, environmentalists, and stakeholders by providing valuable insights for enhancing environmental management and policies. © 2024 Elsevier Ltd
GIS-based suitability assessment of stone crushing site selection using AHP, Fuzzy-AHP, and Fuzzy-TOPSIS models: Navigating towards sustainable environmental management in Brahmani-Dwarka interfluve
(Elsevier B.V., 2025) Bhaskar Mandal; Kaushalendra Prakash Goswami; Sharmistha Mondal
The primary objective of this present study is to carry out the suitability assessment for establishing prospective and existing stone-crushing units in Brahmani-Dwarka Interfluve, which has 764 operational units. The significance of this present study lies in its pioneering effort to identify appropriate locations for such a polluting industry that has not been explored in existing literature. The study utilized the AHP and Fuzzy-AHP to determine the weight of various criteria and sub-criteria. Fuzzy-TOPSIS was employed to identify suitable alternatives for new units, while a sensitivity analysis examined how changes in criteria weight affected those alternatives. The ROC-AUC curve was used to validate the robustness of the models. The findings indicated that 144.22 km2 and 154.44 km2 areas were classified as low to very low suitable according to AHP and FAHP, respectively, while 144.45 km2 and 113.36 km2 areas were deemed very highly suitable. The assessment of existing units revealed that 577 units (AHP) and 493 units (FAHP) were located in low to very low suitable zones, with 12 (AHP) and 24 (FAHP) units in highly suitable areas. FTOPSIS identified 10 potential sites, with Site 1 being the most suitable. Sensitivity analysis indicated Site 5 was most responsive to changes in criteria weight. The AHP and FAHP models achieved AUC values of 0.719 and 0.815, respectively, demonstrating good prediction accuracy and confirming the model's robustness. The findings of the study will help policymakers, planners, and stakeholders develop environmentally friendly site selection strategies and policies in the study region or analogous region. © 2025 The Author(s)
POVERTY AND STATUS OF WOMEN IN HOOGHLY DISTRICT OF WEST BENGAL: A GEOGRAPHICAL PERSPECTIVE
(Institute For Spatial Planning And Environment Research, 2022) Saheli Kumar; Soumyabrata Mondal; Kaushalendra Prakash Goswami
Poverty is a severe and multi-dimensional deprivation. The extent of poverty and its associated deprivation significantly affect the development of any region. Women are one of the most vulnerable and deprived section of society and suffer a lot from the curse of poverty. Therefore, enhancement of the status of women is very essential to overcome poverty in a geographical region. Keeping this in mind, an attempt has been made, in this study, to identify the spatial pattern of poverty and status of women in Hooghly district of West Bengal. To reveal this fact, twelve determinants of poverty and seven indicators of status of women have been taken up for quantitative analysis. The study depicts widespread disparity in the levels of poverty ranging from standard score value of 1.94 for Arambag block to-1.51 for Chanditala-I block. Similarly, in respect to status of women, the disparity varies from the highest standard score of 2.51 recorded by Chanditala-II to the lowest of-1.54 witnessed by Goghat-I block. The study further reveals that intensity of poverty is inversely associated with the status of women and vice versa. © 2022, Institute For Spatial Planning And Environment Research. All rights reserved.