Spatio-temporal pattern of urban eco-environmental quality of Indian megacities using geo-spatial techniques. Issue 17 (2nd September 2022)

• Record Type: Journal Article
• Authors: Pramanik, Suvamoy; Areendran, G.; Punia, Milap; Sahoo, Sourav
• Is Part Of: Geocarto international. Volume 37:Issue 17(2022)
• Page Start: 5067
• Page End: 5090
• Publication Date: 2022-09-02
• Subjects: Urban eco-environmental quality index (UEQI) -- urban environmental health -- climate-resilient city -- sustainable development goal -- SPCA -- spatial autocorrelation indices; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2021.1903578
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract: Rapid urbanization is often responsible for the degradation of urban eco-environmental quality (UEQ), which is comprised of ecological, environmental and anthropogenic components. Hence, frequently monitoring and tracking UEQ for sustainable cities and communities is recommendable. This study, attempted to compare UEQ of three rapidly growing Indian metros/megacities – Ahmedabad, Hyderabad and Bangalore. A remote sensing-based composite index, namely 'urban eco-environmental quality index' (UEQI), was constructed by utilizing Landsat 5 (TM), 8 (OLI-TIRS) satellite imageries and MODIS LST products of 1999/2000–2001 and 2018. Five vegetation indices (i.e. NDVI, SAVI, GVI, NDMI and TcWet) and four urban indices (i.e. BI, NDBI, UI and DTR) were categorized as per pressure-state-response (PSR) framework and integrated through spatial principal component analysis (SPCA) to construct the UEQI. The sensitivity and elasticity of UEQI had been tested with respect to population density (PD) and the percentage of impervious surface (IS). Subsequently, the spatio-temporal pattern (i.e. (non)sequential transition – from excellent to very poor) and spatial heterogeneity of UEQ were investigated using Moran's I, and local indicator of spatial auto-correlation (LISA). Result indicated overall UEQI value for selected cities during studied periods ranged from 0.20 to 2.20, where lower and higher value referred very poor and excellent UEQ, respectively. The most degraded UEQ was found in Bangalore (average UEQI values were 1.08 and 0.80 in 2001 and 2019, respectively); and the degradation rate was also quite inflated than other cities (i.e. UEQI 1.64 per year). Additionally, the spatio-temporal pattern of UEQI demonstrated that very poor and poor UEQ were primarily clustered in the city's centre and spilling out towards the outskirts of all cities during the studied periods. Overall, the proportional area under very poor UEQ category was increased i.e., 7.94%, 7.03% and 5.24% for Bangalore, Ahmedabad and Hyderabad, respectively. The non-sequential transition (i.e. excellent to poor or very poor) was prominent in Bangalore, which implied that rapid and abrupt degradation of UEQ. Whereas, Ahmedabad and Hyderabad followed mostly sequential transition. Besides, significant global (Moran's I = > 0.80) and LISA confirmed the non-randomness pattern of UEQ for three cities. The analysis of sensitivity ensured both PD and IS were strongly influenced poor UEQI (as R 2 ≥ 0.50). Elasticity of UEQI revealed 1% increase of IS would lead to declining of 0.64%, 0.46% and 0.21% of UEQI in Ahmedabad, Hyderabad and Bangalore, respectively. Moreover, the study's observation and findings could also be used for possible area intervention for 'area-based development' (ADB) and 'greenfield development' (GFD) plan, as recommended by 'climate-resilient smart city mission'.