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Artikel: Ecosystem services change in response to land use land cover dynamics in Paschim Bardhaman District of West Bengal, India

Chatterjee, Soumen / Dutta, Shyamal / Dutta, Ipsita / Das, Arijit

Remote sensing applications. 2022 Aug., v. 27

2022

Abstract: Ecosystem is the basic structural and functional unit of ecology which provides various unique and fundamental services for the people right from the providing of food and shelter to regulating the climate and environment of any region either directly or ...

Abstract	Ecosystem is the basic structural and functional unit of ecology which provides various unique and fundamental services for the people right from the providing of food and shelter to regulating the climate and environment of any region either directly or indirectly. However, the rise of urban industrial society witnessed the uncontrolled resource exploitation, manifold increase of pollution, loss of biodiversity, unprecedented population growth, climate change etc. All these leads to ecological crises as the ecosystem services are facing a gradual decrease. In the light of that the present study has been carried on the Paschim Barddhaman district of West Bengal, India where there is a long history of industrialization and urbanization to examine the present status of ecosystem service in reference with the land use change. The study shows that land use and land cover are the crucial driver of loss of ecosystem services. Overall, ESV values fluctuated massively for the built-up area and agricultural land and remain static to some extent for vegetation. Similarly ESV, its response to land use and finally elasticity value also analyzed for the sub district level to understand the spatial variation.
Schlagwörter	agricultural land ; biodiversity ; climate ; climate change ; ecosystem services ; ecosystems ; industrial society ; industrialization ; land use and land cover maps ; land use change ; pollution ; population growth ; urbanization ; vegetation ; India
Sprache	Englisch
Erscheinungsverlauf	2022-08
Erscheinungsort	Elsevier B.V.
Dokumenttyp	Artikel
ISSN	2352-9385
DOI	10.1016/j.rsase.2022.100793
Datenquelle	NAL Katalog (AGRICOLA)

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Artikel ; Online: Spatial analysis of COVID-19 incidence and its determinants using spatial modeling: A study on India.

Dutta, Ipsita / Basu, Tirthankar / Das, Arijit

Environmental challenges (Amsterdam, Netherlands)

2021 Band 4, Seite(n) 100096

Abstract: The first incident of COVID-19 case in India was recorded on 30th January, 2020 which turns to 100,000 marks on May 19th and by June 3rd it was over 200,000 active cases and 5,800 deaths. Geographic Information System (GIS) based spatial models can be ... ...

Abstract	The first incident of COVID-19 case in India was recorded on 30th January, 2020 which turns to 100,000 marks on May 19th and by June 3rd it was over 200,000 active cases and 5,800 deaths. Geographic Information System (GIS) based spatial models can be helpful for better understanding of different factors that have triggered COVID-19 spread at district level in India. In the present study, 19 variables were considered that can explain the variability of the disease. Different spatial statistical techniques were used to describe the spatial distribution of COVID-19 and identify significant clusters. Spatial lag and error models (SLM and SEM) were employed to examine spatial dependency, geographical weighted regression (GWR) and multi-scale GWR (MGWR) were employed to examine at local level. The results show that the global models perform poorly in explaining the factors for COVID-19 incidences. MGWR shows the best-fit-model to explain the variables affecting COVID-19 (R2= 0.75) with lowest AICc value. Population density, urbanization and bank facility were found to be most susceptible for COVID-19 cases. These indicate the necessity of effective policies related to social distancing, low mobility. Mapping of different significant variables using MGWR can provide significant insights for policy makers for taking necessary actions.
Sprache	Englisch
Erscheinungsdatum	2021-04-10
Erscheinungsland	Netherlands
Dokumenttyp	Journal Article
ISSN	2667-0100
ISSN (online)	2667-0100
DOI	10.1016/j.envc.2021.100096
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Exploring the dynamics of spatial inequality through the development of sub-city typologies in English Bazar Urban Agglomeration and its peri urban areas

Dutta, Ipsita / Das, Arijit

GeoJournal. 2019 Aug., v. 84, no. 4

2019

Abstract: The term peri-urban can be defined as the settlements beyond, about or around core cities. It has often observed that the areas congested with the core city are enjoying some basic facilities/amenities as urban entity whereas the areas beyond the city ... ...

Abstract	The term peri-urban can be defined as the settlements beyond, about or around core cities. It has often observed that the areas congested with the core city are enjoying some basic facilities/amenities as urban entity whereas the areas beyond the city are lagging behind. Thus the uneven distribution of amenities increases the inequality from core to peripheries. These heterogeneous characteristics within a city and around its periphery increase the inequalities which are characterized by the formation of sub-city typologies within the city and its peripheral settlements. The goal of this study is to explore extent and magnitude of spatial inequality in levels of living and the resultant sub-city typologies of English Bazar city and its peri-urban settlements, one of the most dynamic urban agglomerations of West Bengal. Village level House listing and housing data from the 2011 census are used here to find out the magnitude of inequality and construct sub-city typologies. 19 variables from the census are selected to represent three broad class of attributes such as housing quality, access to amenities and availability of household assets through different standardize indices for developing sub-city typology. Hierarchical and non-hierarchical cluster analysis methods are then used to identify empirical typologies considering relevant principal factors from PCA analysis. It identifies a five cluster solution corresponds to five spatial typological categories (High SE-Area, Average SE-Area, Good SE-Area, Average Area, Low socio-economic area). Identification of five spatial typological categories helps to explore the urban inequality at micro level for English Bazar Urban Agglomeration and its peri-urban settlements. The result also shows that settlements lying contiguous to the Old Malda city are deprived in asset holding and household quality whereas the peripheral settlements lying along English Bazar city have better standard of living conditions.
Schlagwörter	assets ; cities ; cluster analysis ; socioeconomics ; urban areas ; villages ; India
Sprache	Englisch
Erscheinungsverlauf	2019-08
Umfang	p. 829-849.
Erscheinungsort	Springer Netherlands
Dokumenttyp	Artikel
ZDB-ID	715360-0
ISSN	1572-9893 ; 0343-2521
ISSN (online)	1572-9893
ISSN	0343-2521
DOI	10.1007/s10708-018-9895-y
Datenquelle	NAL Katalog (AGRICOLA)

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Artikel ; Online: Application of geo-spatial indices for detection of growth dynamics and forms of expansion in English Bazar Urban Agglomeration, West Bengal

Dutta, Ipsita / Das, Arijit

2019

Abstract: In India, urban sprawl of metropolitan cities and other large cities is a widespread concern for planners and policy makers. Modeling urban sprawl of small and medium size towns is completely bypassed urban research of India. This study attempted to fill- ...

Abstract	In India, urban sprawl of metropolitan cities and other large cities is a widespread concern for planners and policy makers. Modeling urban sprawl of small and medium size towns is completely bypassed urban research of India. This study attempted to fill-up the gap by addressing the three urban growth types of infilling growth, outlying growth and edge-expansion growth of EBM which is a medium size town of West Bengal. In this study, an integrated approach of remote sensing and GIS along with spatial landscape matrices have employed to identify and distinguish between three urban growth types of EBM which helps planners to better identify, understand and address the sprawl of small and medium size towns of developing countries. Result shows that the proposed methods successfully identifies and visualize different urban growth types of EBM. Infilling growth is the dominant expansion type. Edge-expansion is concentrated at suburban areas. Outlying growth mainly occurs relatively far from the urban core. The analysis shows that initially the urban area expands mainly as edge-expanding growth during the different temporal periods. Next, growth shows gradual increasing of the area under outlying growth from phase 1 (1991-2001) to phase 3 (2011-2016) with area cover of 2.04km2-3.25km2. Growth filled in vacant non-urban area inwards, resulting into a more compact and aggregated urban pattern. The study shows an improved understanding of urban growth, and helps to provide an effective way for urban planning.
Schlagwörter	ddc:710 ; Land use/ land cover ; Peri-urban ; Remote sensing ; Spatial metrics ; Urban sprawl
Thema/Rubrik (Code)	710
Sprache	Englisch
Verlag	Amsterdam: Elsevier
Erscheinungsland	de
Dokumenttyp	Artikel ; Online
Datenquelle	BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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Artikel: Quantification and mapping of fragmented forest landscape in dry deciduous forest of Burdwan Forest Division, West Bengal, India

Dutta, Shyamal / Dutta, Ipsita / Das, Arijit / Guchhait, Sanat Kumar

Trees, forests and people. 2020 Dec., v. 2

2020

Abstract: Structural pattern of a forest landscape may affect the habitat quality directly. Therefore, monitoring and assessing the changes of forest cover is important for a biodiversity as well as the local ecosystem. Forest fragmentation in unprotected land ... ...

Abstract	Structural pattern of a forest landscape may affect the habitat quality directly. Therefore, monitoring and assessing the changes of forest cover is important for a biodiversity as well as the local ecosystem. Forest fragmentation in unprotected land rapidly changes the forest shape and size in an entire landscape. The present study addresses the issues related to the changing pattern of Burdwan Forest Division (BFD) landscape during the past 29 years (1990–2019) using satellite images. The entire forest area was categorized into 38 forest patches. Supervised image classification using ArcGIS software was used to detect the temporal changes of the forest cover in BFD. Different landscape indices have also been calculated to consider fragmentation with the help of FragStat 4.2 software. The result of the forest cover changes shows that though there is a less variation of forest changes from 1990 (80.66% forest cover) to 2019 (80%) forest cover, patch level variation is striking. Result from different landscape indices shows that, the patches with larger size (ID-1, 6, 15, 17) are more fragmented and complex than the smaller (ID- 5, 9, 18). This result is also supported and validated by regression method. This study may be helpful for the forest division and planners for policy makers to mitigate the factors affecting the fragmentation of this protected forest and to adopt suitable strategies for maintain ecological balance.
Schlagwörter	area ; biodiversity ; classification ; computer software ; deciduous forests ; ecological balance ; ecosystems ; exhibitions ; forest reserves ; habitat fragmentation ; habitats ; issues and policy ; land ; landscapes ; monitoring ; people ; regression analysis ; remote sensing ; shape ; temporal variation ; trees ; India
Sprache	Englisch
Erscheinungsverlauf	2020-12
Erscheinungsort	Elsevier B.V.
Dokumenttyp	Artikel
Anmerkung	NAL-light
ISSN	2666-7193
DOI	10.1016/j.tfp.2020.100012
Datenquelle	NAL Katalog (AGRICOLA)

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Artikel ; Online: Living environment matters: Unravelling the spatial clustering of COVID-19 hotspots in Kolkata megacity, India.

Das, Arijit / Ghosh, Sasanka / Das, Kalikinkar / Basu, Tirthankar / Dutta, Ipsita / Das, Manob

Sustainable cities and society

2020 Band 65, Seite(n) 102577

Abstract: The emergence of COVID-19 has brought a serious global public health threats especially for most of the cities across the world even in India more than 50 % of the total cases were reported from large ten cities. Kolkata Megacity became one of the major ... ...

Abstract	The emergence of COVID-19 has brought a serious global public health threats especially for most of the cities across the world even in India more than 50 % of the total cases were reported from large ten cities. Kolkata Megacity became one of the major COVID-19 hotspot cities in India. Living environment deprivation is one of the significant risk factor of infectious diseases transmissions like COVID-19. The paper aims to examine the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. COVID-19 hotspot maps were prepared using Getis-Ord-Gi* statistic and index of multiple deprivations (IMD) across the wards were assessed using Geographically Weighted Principal Component Analysis (GWPCA).Five count data regression models such as Poisson regression (PR), negative binomial regression (NBR), hurdle regression (HR), zero-inflated Poisson regression (ZIPR), and zero-inflated negative binomial regression (ZINBR) were used to understand the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. The findings of the study revealed that living environment deprivation was an important determinant of spatial clustering of COVID-19 hotspots in Kolkata megacity and zero-inflated negative binomial regression (ZINBR) better explains this relationship with highest variations (adj. R2: 71.3 %) and lowest BIC and AIC as compared to the others.
Schlagwörter	covid19
Sprache	Englisch
Erscheinungsdatum	2020-10-31
Erscheinungsland	Netherlands
Dokumenttyp	Journal Article
ISSN	2210-6715
ISSN (online)	2210-6715
DOI	10.1016/j.scs.2020.102577
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Modelling the Effect of Area-deprivation on COVID-19 Incidences: A Study of Chennai Megacity, India

Das, Arijit / Ghosh, Sasanka / Das, Kalikinkar / Basu, Tirthankar / Das, Manob / Dutta, Ipsita

Public Health

Abstract: Abstract Objectives Socioeconomic inequalities may affect COVID-19 incidence. The goal of the research was to explore the association between deprivation of socioeconomic status (SES) and spatial patterns of COVID-19 incidence in Chennai megacity for ... ...

Abstract	Abstract Objectives Socioeconomic inequalities may affect COVID-19 incidence. The goal of the research was to explore the association between deprivation of socioeconomic status (SES) and spatial patterns of COVID-19 incidence in Chennai megacity for unfolding the disease epidemiology. Study design Ecological (or contextual) study for electoral wards (sub-cities) of Chennai megacity. Methods Using data of confirmed COVID-19 cases from May 15, 2020, to May 21, 2020, for 155 electoral wards obtained from the official website of the Chennai municipal corporation, we examined the incidence of COVID-19 diseases using two count regression models namely, Poisson Regression (PR) and Negative Binomial Regression (NBR). As explanatory factors, we considered area-deprivation that represented the deprivation of socioeconomic status (SES). An index of multiple deprivations (IMD) developed to measure the area-deprivation using an advanced local statistic, Geographically Weighted Principal Component Analysis (GWPCA). Based on the availability of appropriately scaled data, five domains (i.e. poor housing condition, low asset possession, poor availability of WaSH services, lack of household amenities and services, and gender disparity) were selected as components of the IMD in this study. Results The Hot-spot analysis revealed that area-deprivation was significantly associated with higher incidences of COVID-19 in Chennai megacity. The high variations (adj. R2: 72.2%) with the lower BIC (124.34) and AIC (112.12) for the NBR compared to PR suggests that the NBR model better explains the relationship between area-deprivation and COVID-19 incidences in Chennai megacity. NBR with two-sided tests, and p<0.05 was considered statistically significant. The outcome of the PR and NBR suggests that when all other variables were constant, according to NBR, the relative risk (RR) of COVID-19 incidences was 2.19 for the wards with high housing deprivation or in other words, the wards with high housing deprivation having 119% higher probability (RR= e0.786=2.19, 95% CI=1.98 to 2.40) compared to areas with low deprivation. Similarly, in the wards with poor availability of WaSH services, chances of having COVID-19 incidence was 90% higher compared to the wards with good WaSH services (RR= e0.642=1.90, 95% CI=1.79 to 2.00). Spatial risks of COVID-19 infections were predominantly concentrated in the wards with higher levels of area-deprivation which were mostly located in the north-eastern parts of Chennai megacity. Conclusions We formulated an area-based IMD, which was substantially related to COVID-19 incidences in the Chennai megacity. This study highlights that the risks of COVID-19 infections tend to be higher in more deprived areas of SES and the north-eastern part of Chennai megacity was predominantly high-risk areas. Our results can guide measures of COVID-19 control and prevention by considering spatial risks and area-deprivation.
Schlagwörter	covid19
Verlag	Elsevier; PMC; WHO
Dokumenttyp	Artikel ; Online
Anmerkung	WHO #Covidence: #597641
DOI	10.1016/j.puhe.2020.06.011
Datenquelle	COVID19

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Artikel: Living environment matters: Unravelling the spatial clustering of COVID-19 hotspots in Kolkata megacity, India

Das, Arijit / Ghosh, Sasanka / Das, Kalikinkar / Basu, Tirthankar / Dutta, Ipsita / Das, Manob

Sustain Cities Soc

Abstract	The emergence of COVID-19 has brought a serious global public health threats especially for most of the cities across the world even in India more than 50 % of the total cases were reported from large ten cities. Kolkata Megacity became one of the major COVID-19 hotspot cities in India. Living environment deprivation is one of the significant risk factor of infectious diseases transmissions like COVID-19. The paper aims to examine the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. COVID-19 hotspot maps were prepared using Getis-Ord-Gi* statistic and index of multiple deprivations (IMD) across the wards were assessed using Geographically Weighted Principal Component Analysis (GWPCA).Five count data regression models such as Poisson regression (PR), negative binomial regression (NBR), hurdle regression (HR), zero-inflated Poisson regression (ZIPR), and zero-inflated negative binomial regression (ZINBR) were used to understand the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. The findings of the study revealed that living environment deprivation was an important determinant of spatial clustering of COVID-19 hotspots in Kolkata megacity and zero-inflated negative binomial regression (ZINBR) better explains this relationship with highest variations (adj. R2: 71.3 %) and lowest BIC and AIC as compared to the others.
Schlagwörter	covid19
Verlag	WHO
Dokumenttyp	Artikel
Anmerkung	WHO #Covidence: #894214
Datenquelle	COVID19

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Artikel ; Online: Living environment matters

Das, Arijit / Ghosh, Sasanka / Das, Kalikinkar / Basu, Tirthankar / Dutta, Ipsita / Das, Manob

Sustainable Cities and Society

Unravelling the spatial clustering of COVID-19 hotspots in Kolkata megacity, India

2020 , Seite(n) 102577

Schlagwörter	Renewable Energy, Sustainability and the Environment ; Geography, Planning and Development ; Civil and Structural Engineering ; Transportation ; covid19
Sprache	Englisch
Verlag	Elsevier BV
Erscheinungsland	us
Dokumenttyp	Artikel ; Online
ZDB-ID	2573417-9
ISSN	2210-6707
ISSN	2210-6707
DOI	10.1016/j.scs.2020.102577
Datenquelle	BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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