Synergizing remote sensing and ecological indicators (RSEIs) for evaluating ecological environmental quality (EEQ) in Asansol Municipal Corporation: an integrated approach

• Published in: Environmental monitoring and assessment Vol. 196; no. 7; p. 631
• Main Authors: Sarkar, Sanjit, Manna, Harekrishna, Roy, Sujit Kumar, Dolui, Mriganka, Hossain, Moslem
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.07.2024; Springer Nature B.V
• Subjects: Atmospheric Protection/Air Quality Control/Air Pollution; Cities; Conservation of Natural Resources - methods; Decision making; Earth and Environmental Science; Ecology; Ecosystem; Ecotoxicology; Environment; Environmental assessment; Environmental conditions; Environmental Management; Environmental Monitoring - methods; Environmental quality; Global ecology; heat; Human influences; humans; Indicators; industrialization; Landsat; Moisture content; Monitoring/Environmental Analysis; Principal Component Analysis; Principal components analysis; quantitative analysis; Remote sensing; Remote Sensing Technology; Satellite imagery; Urban sprawl; urbanization; India; Remote sensing–based ecological indicators; Asansol Municipality; Receiving operating characteristics; Ecological environmental quality; Principal component analysis
• ISSN: 0167-6369; 1573-2959; 1573-2959
• DOI: 10.1007/s10661-024-12793-x

Human activities have dramatically affected global ecology over the past few decades. Geospatial technologies provide quick, efficient, and quantitative evaluation of spatiotemporal changes in eco-environmental quality (EEQ). This study focuses on a novel approach called remote sensing–based ecological indicators (RSEIs), which has used Landsat imagery data to assess environmental conditions and their changing trends. Four ecological indicators, mainly heatness, dryness, wetness, and greenness, have been used to assess the EEQ in Asansol Municipal Corporation Region (AMCR). Assembling all the indicators to generate RSEI, the principal component analysis (PCA) approach was applied. Our findings show that wetness and greenness favorably impact the province’s EEQ, whereas dryness and heat create a negative impact. The RSEI assessment revealed that 24.53 to 28.83% of the area was poor and very poor, whereas the areas with very good decreased from 18.80 to 4.01% from 2001 to 2021 due to urban expansion and industrialization. The relative importance analysis indicates that greenness has a positive relation with RSEI, and dryness and heatness have a negative relation with RSEI. Finally, the receiving operating characteristic (ROC) was used for validation (AUC-0.885) of the RSEI. This study offers valuable insights for ecological management decision-making, guiding planners, and policymakers.