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Proceedings Paper

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach
Author(s): Yuriy V. Kostyuchenko; Yulia Sztoyka; Ivan Kopachevsky; Igor Artemenko; Maxim Yuschenko
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Paper Abstract

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

Paper Details

Date Published: 2 November 2017
PDF: 19 pages
Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 1042105 (2 November 2017);
Show Author Affiliations
Yuriy V. Kostyuchenko, Scientific Ctr. for Aerospace Research of the Earth (Ukraine)
Yulia Sztoyka, Institute of Hydrobiology (Ukraine)
Ivan Kopachevsky, Scientific Ctr. for Aerospace Research of the Earth (Ukraine)
Igor Artemenko, Scientific Ctr. for Aerospace Research of the Earth (Ukraine)
Maxim Yuschenko, Scientific Ctr. for Aerospace Research of the Earth (Ukraine)

Published in SPIE Proceedings Vol. 10421:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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