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

Sarkar, S ; Manna, H ; et al.

In: Environmental monitoring and assessment, Jg. 196 (2024-06-19), Heft 7, S. 631

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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.

Titel:	Synergizing remote sensing and ecological indicators (RSEIs) for evaluating ecological environmental quality (EEQ) in Asansol Municipal Corporation: an integrated approach.
Autor/in / Beteiligte Person:	Sarkar, S ; Manna, H ; Roy, SK ; Dolui, M ; Hossain, M
Link:	Full Text Finder (Volltext)
Zeitschrift:	Environmental monitoring and assessment, Jg. 196 (2024-06-19), Heft 7, S. 631
Veröffentlichung:	1998- : Dordrecht : Springer ; <i>Original Publication</i>: Dordrecht, Holland ; Boston : D. Reidel Pub. Co., c1981-, 2024
Medientyp:	academicJournal
ISSN:	1573-2959 (electronic)
DOI:	10.1007/s10661-024-12793-x
Schlagwort:	Ecology Principal Component Analysis Conservation of Natural Resources methods Ecosystem Cities Environmental Monitoring methods Remote Sensing Technology
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article Language: English [Environ Monit Assess] 2024 Jun 19; Vol. 196 (7), pp. 631. <i>Date of Electronic Publication: </i>2024 Jun 19. MeSH Terms: Environmental Monitoring* / methods ; Remote Sensing Technology* ; Ecology ; Principal Component Analysis ; Conservation of Natural Resources / methods ; Ecosystem ; Cities References: Abulibdeh, A. (2021). Analysis of urban heat island characteristics and mitigation strategies for eight arid and semi-arid gulf region cities. Environmental Earth Sciences, 80(7), 1–26. https://doi.org/10.1007/S12665-021-09540-7/TABLES/8. (PMID: 10.1007/S12665-021-09540-7/TABLES/8) ; Adams, M., & P. S. (2014). A systematic approach to model the influence of the type and density of vegetation cover on urban heat using remote sensing. Landsc Urban Plan, 132, 47–54. (PMID: 10.1016/j.landurbplan.2014.08.008) ; Al Faisal, A., Kafy, A. A., Al Rakib, A., Akter, K. S., Jahir, D. M. 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International Journal of Remote Sensing, 41(2), 683–703. https://doi.org/10.1080/01431161.2019.1646939. (PMID: 10.1080/01431161.2019.1646939) Contributed Indexing: Keywords: Asansol Municipality; Ecological environmental quality; Principal component analysis; Receiving operating characteristics; Remote sensing–based ecological indicators Entry Date(s): Date Created: 20240619 Date Completed: 20240619 Latest Revision: 20240619 Update Code: 20240619

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