Spatial heterogeneity of ecological footprint of production: a district-level study of Bangladesh

Ishrar Sameen () and Tasnim Feroze
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Ishrar Sameen: Bangladesh University of Engineering and Technology (BUET)
Tasnim Feroze: Bangladesh University of Engineering and Technology (BUET)

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2021, vol. 23, issue 6, No 44, 8949-8973

Abstract: Abstract In an era of environmental degradation, resource extraction needs to be restricted in proportion to natural capital’s regenerative capacity to nullify ecological overshoot. An investigation into spatial heterogeneity of ‘Ecological Footprint of Production’ (EFp) helps to examine spatial variation of human demand on nature due to production purposes. This study focuses on spatial variation in environmental impact of resource extraction by estimating EFp values for all 64 districts of Bangladesh. EFp is spatially varied across six land types in the following ranges 0.016–0.502 gha/capita for cropland; 0.016–0.637 gha/capita for grazing land; 0.004–0.194 gha/capita for fishing ground; 0.000–0.187 gha/capita for forest land; 0.00009–0.011 gha/capita for built-up land; and 0.000–1.192 gha/capita for carbon uptake land. Moreover, in this study, regions are delineated based on EFp values of six land types using ArcGIS-based standard deviation classification method. The region having the highest total EFp is located at the central-east part of Bangladesh. Among six types of land uses, cropland, grazing land and carbon uptake land contributed most in total EFp. Multiple linear regression modeling showed that population employed in service sector drives total EFp (gha) in negative direction and district population drives it in positive direction. Spatially segregated policy directions are recommended for restricting EFp to ensure reduced environmental degradation and increased production-based sustainability. Therefore, to promote sustainable sectoral enhancement plans and policies, this investigation facilitates regional policy guidelines based on sectoral magnitude of resource extraction.

Keywords: Spatial analysis; Production; Environmental pressure; Regionalization; Multiple linear regression (MLR) (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10668-020-01006-3

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