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JOURNALS // Computer Optics // Archive

Computer Optics, 2022 Volume 46, Issue 4, Pages 634–642 (Mi co1055)

This article is cited in 2 papers

IMAGE PROCESSING, PATTERN RECOGNITION

Spatiotemporal ecosystem health assessment comparison under the pressure-state-response framework

M. Booria, K. Choudharyab, R. A. Paringerac, A. V. Kupriyanovac

a Scientific Research Laboratory of Automated Syatem of Scientific Research (SRL-35), Samara National Research University, Samara, Russia
b Department of Land Surveying and Geo-informatics, Smart Cities Research Institute, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
c Image Processing Systems Institute of the RAS - Branch of the FSRC "Crystallography and Photonics" RAS, Samara, Russia, Samara

Abstract: A spatiotemporal ecosystem health (EH) assessment study is necessary for sustainable development and proper management of natural resources. At present higher rate of human-socio-economic activities, industrialization, and misuse of land are major factors for ecosystem degradation. Therefore this research work used remote sensing (RS) and geographical information system (GIS) technology, under pressure-state-response (PSR) framework with analytic hierarchy process (AHP) weight method based on 29 indicators were analyzed for spatiotemporal EH assessment in Tatarstan and Samara states in Russia from 2010 to 2020. Results indicate continuous degradation of EH in Tatarstan state while in Samara state first decreased and later on an improved ecosystem health condition. This is one of the most innovative analyses work for real-time accurate ecosystem health assessment, mapping, and monitoring as well as protect fragile eco-environment with sustainable development, proper policy-making, and management at any scale and region.

Keywords: spatiotemporal ecosystem health, PSR, remote sensing and GIS, AHP, indicators

Received: 07.09.2016
Accepted: 11.11.2016

Language: English

DOI: 10.18287/2412-6179-CO-1067



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