Nilanjana Das Chatterjee
@vidyasagar.ac.in
PROFESSOR,DEPARTMENT OF GEOGRAPHY
VIDYASAGAR UNIVERSITY
Dr Nilanjana Das Chatterjee is Professor and Head of the Department in the Department of Geography Vidyasagar University, Midnapore, West principal area of interest is Bio-Geographical issues, Forest landscape Ecology, Urban Landuse and planning,Social and Cultural Geography , Environment, Folk and indigenous culture and women related issues. She has completed a major project funded by ICSSR on Nature of Human Elephant Conflict and a research programme on GIS Application based analysis of Crime Against women.
Disciplines
Soil ScienceGeographyQuantitative Social Research
Skills and expertise
Environmental Management SystemLandscape EcologyUrban GeographyUrban Ecology
Languages
EnglishHindiBengali; Bangla
Contact information
nilanjana_vu@
EDUCATION
M.A PhD in Geography
RESEARCH, TEACHING, or OTHER INTERESTS
Environmental Science, Urban Studies, Geography, Planning and Development, Ecology
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Raj Kumar Bhattacharya, Nilanjana Das Chatterjee, and Kousik Das
Elsevier BV
Dipankar Bera, Nilanjana Das Chatterjee, Sudip Bera, Subrata Ghosh, and Santanu Dinda
Elsevier BV
Kousik Das, Nilanjana Das Chatterjee, Debarati Jana, and Raj Kumar Bhattacharya
Elsevier BV
S. Pahari, N. Das Chatterjee, and N. K. Barman
Springer Science and Business Media LLC
Subrata Ghosh, Santanu Dinda, Nilanjana Das Chatterjee, and Dipankar Bera
Springer Science and Business Media LLC
Priyanka Biswas and Nilanjana Das Chatterjee
SAGE Publications
In this present study, the focus has been given to excavating the generalities of domestic abuse against women in the Indian state of West Bengal and understanding the possible determinants. The study findings revealed that 69.68% of study respondents throughout Bengal often experienced any form of domestic violence in their lifetime. Mostly the traditional patriarchal structure that governs Bengal’s society endorses vulnerability among the ever-married women in the family environment, yet some other determinants viz. socio-demographic, socio-cultural as well as situational factors are significantly associated with the victimization of domestic abuse among women in Bengal’s society. This study aims to contribute to society and might help policymakers to address this societal issue more efficiently.
Sudip Bera, Riya Samanta, and Nilanjana Das Chatterjee
Springer International Publishing
Dipankar Bera, Nilanjana Das Chatterjee, Subrata Ghosh, Santanu Dinda, and Sudip Bera
Elsevier BV
Raj Kumar Bhattacharya, Nilanjana Das Chatterjee, and Kousik Das
Springer Science and Business Media LLC
Dipankar Bera, Nilanjana Das Chatterjee, Faisal Mumtaz, Santanu Dinda, Subrata Ghosh, Na Zhao, Sudip Bera, and Aqil Tariq
MDPI AG
Increasing land surface temperature (LST) is one of the major anthropogenic issues and is significantly threatening the urban areas of the world. Therefore, this study was designed to examine the spatial variations and patterns of LST during the different seasons in relation to influencing factors in Kolkata Municipality Corporation (KMC), a city of India. The spatial distribution of LST was analyzed regarding the different surface types and used 25 influencing factors from 6 categories of variables to explain the variability of LST during the different seasons. All-subset regression and hierarchical partitioning analyses were used to estimate the explanatory potential and independent effects of influencing factors. The results show that high and low LST corresponded to the artificial lands and bodies of water for all seasons. In the individual category regression model, surface properties gave the highest explanatory rate for all seasons. The explanatory rates and the combination of influencing factors with their independent effects on the LST were changed for the different seasons. The explanatory rates of integration of all influencing factors were 89.4%, 81.4%, and 88.7% in the summer, transition, and winter season, respectively. With the decreasing of LST (summer to transition, then to winter) more influencing factors were required to explain the LST. In the integrated regression model, surface properties were the most important factor in summer and winter, and landscape configuration was the most important factor in the transition season. LST is not the result of single categories of influencing factors. Along with the effects of surface properties, socio-economic parameters, landscape compositions and configurations, topographic parameters and pollutant parameters mostly explained the variability of LST in the transition (11.22%) and summer season (15.22%), respectively. These findings can help to take management strategies to reduce urban LST based on local planning.
Dipankar Bera, Nilanjana Das Chatterjee, Subrata Ghosh, Santanu Dinda, Sudip Bera, and Mrinmay Mandal
Elsevier BV
Subrata Ghosh, Santanu Dinda, Nilanjana Das Chatterjee, Shrabanti Dutta, and Dipankar Bera
Elsevier BV
Raj Kumar Bhattacharya, Nilanjana Das Chatterjee, and Kousik Das
Informa UK Limited
Abstract Despite the stable stratigraphic setup in plateau basin, several anthropogenic interventions triggered geomorphic sensitivity by hydrodynamic metamorphosis. Present research focussed to evaluate the hydrogeomorphic evolution for anthropogenic interventions in Kangsabati River as measured by channel migration rate (CMR), bankline shifting, and erosion-accretion of last thirty years (1990–2020) in 454 mouza using Digital shoreline analysis system (DSAS). Acoustic Doppler Current Profiler (ADCP) was used to directly estimate bank scouring or erosion measuring of hydraulic variables during bankfull discharge across the DSAS transects. DSAS denoted that decaying CMR (64–46 km) decreased accretion area (4.08–1.44 km2) but increased erosion area (2.12–2.44 km2). ADCP revealed that sand mining induced super-critical flow, bridge and embankment generated maximum boundary shear, and mining bed slope increased hydraulic action for channel widening and bank erosion especially middle and lower segments. This study has provided information about channel instability, and bank erosion hazard planning and management.
Santanu Dinda, Nilanjana Das Chatterjee, and Subrata Ghosh
Informa UK Limited
Abstract Changes in land-use and land-cover (LULC) in urban areas affect the natural environment, especially urban green spaces (UGS). The present study examines the loss of UGS due to LULC transformation at different periods to predict the future vulnerable zone of UGS, based on the 'Pressure-State-Response’ framework. To calculate the weight of each factor, a combined Analytical Hierarchical Process and Fuzzy Comprehensive Evaluation method have been used. An integrated multilayer perceptron based artificial neural network and Markov chain (MLP-ANN-MC) model has been employed to predict the UGS vulnerable area in Kolkata. Results indicated that growth rates of built-up area, land-use dynamic degree, change intensity index, and proximity factors are the major responsible for UGS vulnerability. Applying the MLP-ANN-MC model, future vulnerable zones were identified for management and conservation of UGS. The methodology developed and demonstrated in this study expands LULC change analysis and provide a new dimension for UGS vulnerability assessment.
Mrinmay Mandal and Nilanjana Das Chatterjee
Springer Science and Business Media LLC
Raj Kumar Bhattacharya, Nilanjana Das Chatterjee, and Kousik Das
Elsevier BV
Bismay Ranjan Tripathy, Xuehua Liu, Melissa Songer, Lalit Kumar, Senipandi Kaliraj, Nilanjana Das Chatterjee, W. M. S. Wickramasinghe, and Kirti Kumar Mahanta
Frontiers Media SA
Escalation of human-elephant conflict (HEC) in India threatens its Asian elephant (Elephas maximus) population and victimizes local communities. India supports 60% of the total Asian elephant population in the world. Understanding HEC spatial patterns will ensure targeted mitigation efforts and efficient resource allocation to high-risk regions. This study deals with the spatial aspects of HEC in Keonjhar forest division, where 345 people were killed and 5,145 hectares of croplands were destroyed by elephant attacks during 2001–2018. We classified the data into three temporal phases (HEC1: 2001–2006, HEC2: 2007–2012, and HEC3: 2013–2018), in order to (1) derive spatial patterns of HEC; (2) identify the hotspots of HEC and its different types along with the number of people living in the high-risk zones; and (3) assess the temporal change in the spatial risk of HEC. Significantly dense clusters of HEC were identified in Keonjhar and Ghatgaon forest ranges throughout the 18 years, whereas Champua forest range became a prominent hotspot since HEC2. The number of people under HEC risk escalated from 14,724 during HEC1 and 34,288 in HEC2, to 65,444 people during HEC3. Crop damage was the most frequent form of HEC in the study area followed by house damage and loss of human lives. Risk mapping of HEC types and high priority regions that are vulnerable to HEC, provides a contextual background for researchers, policy makers and managers.
Priyanka Biswas, Kousik Das, and Nilanjana Das Chatterjee
Springer Science and Business Media LLC
Subrata Ghosh, Nilanjana Das Chatterjee, and Santanu Dinda
Elsevier BV
Mrinmay Mandal and Nilanjana Das Chatterjee
Elsevier BV
Dipankar Bera, Nilanjana Das Chatterjee, and Sudip Bera
Elsevier BV
Raj Kumar Bhattacharya, Nilanjana Das Chatterjee, Prasenjit Acharya, and Kousik Das
Springer Science and Business Media LLC
Santanu Dinda, Nilanjana Das Chatterjee, and Subrata Ghosh
Elsevier BV
Raj Kumar Bhattacharya, Nilanjana Das Chatterjee, and Kousik Das
Springer Science and Business Media LLC
Priyanka Biswas and Nilanjana Das Chatterjee
Springer Singapore