Evaluation of remote sensing techniques-based water quality monitoring for sustainable hydrological applications: an integrated FWZIC-VIKOR modelling approach

Alamoodi, Abdullah Hussein

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Type :	article
Subject :	T Technology (General)
ISSN :	1387-585X
Main Author :	Alamoodi, Abdullah Hussein
Title :	Evaluation of remote sensing techniques-based water quality monitoring for sustainable hydrological applications: an integrated FWZIC-VIKOR modelling approach

Place of Production :	Tanjung Malim
Publisher :	Fakulti Komputeran dan Meta Teknologi
Year of Publication :	2023
Notes :	Environment, Development and Sustainability
Corporate Name :	Universiti Pendidikan Sultan Idris
HTTP Link :	Click to view web link

Abstract : Universiti Pendidikan Sultan Idris

Evaluating remote sensing techniques (RST)-based water quality monitoring systems in hydrological applications is a complex multi-attribute decision-making (MADM) problem due to several integrated issues. These issues include the need to consider 15 evaluation criteria, the importance of these criteria in relation to their application and network infrastructure, data variation, and trade-offs and conflicts between them. Therefore, this study proposes an MADM integrated modelling approach to weight these criteria and rank the selected RSTs using the Fuzzy Weighted with Zero Inconsistency (FWZIC) method coupled with the Vlse-kriterijumska Optimizcija I Kaompromisno Resenje (VIKOR) method. First, a decision matrix was developed for the evaluation criteria and their intersection with various RSTs in different network categories. Next, the assessment criteria were weighted using FWZIC, followed by ranking the RSTs for each category using VIKOR. The findings reveal that the criteria weighting varied across categories, as assigned by specialists-based FWZIC. For example, the data acquisition system complexity criterion received the maximum weight (w = 0.081) for mesh-based sensing and the lowest (w = 0.057) for cellular-based sensing. Using the obtained weights and based on the ascending order of the performance score value (Q), various RSTs were benchmarked using VIKOR. This includes (n = 22) RSTs in fixed star, (n = 8) RSTs in mesh sensing, (n = 6) RSTs in cellular sensing, (n = 3) RSTs in fixed cable sensing, and (n = 2) RSTs in movable sensing. Finally, the evaluation process for the benchmarked RSTs involved systematic ranking, sensitivity analysis, and comparison analysis, which confirmed the robustness of the proposed approach across all RST categories. 2023, The Author(s), under exclusive licence to Springer Nature B.V.

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