Monitoring ecological status of wetlands using linked fuzzy inference system- remote sensing analysis

Sedighkia, Mahdi, and Datta, Bithin (2023) Monitoring ecological status of wetlands using linked fuzzy inference system- remote sensing analysis. Ecological Informatics, 74. 101971.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website:


The present study develops an applicable model to simulate the ecological status of saltwater lakes in which depth and total dissolved solids are selected as the effective factors on aquatic habitats. First, spectral images of the operational land imager of Landsat 8 were used to simulate distribution of depth and total dissolved solids by applying two feed forward neural networks. Next, a Mamdani fuzzy inference system was used to develop habitat suitability rules of Artemia and Flamingo as the selected target species in which expert opinions were considered. Finally, habitat suitability maps of target species were generated by linking distribution maps of selected effective parameters and fuzzy inference system. Based on the results in the Urmia lake as a case study, the Nash-Sutcliffe efficiency coefficients of depth and total dissolved solids are 0.88 and 0.5 which indicates the proposed method for simulating distribution of these parameters is reliable. Average depth in the simulated date is 227 cm, while average simulated total dissolved solids is 264 g per litre. Simulation of habitat suitability maps demonstrated that average habitat suitability of Artemia is less than 30% in the most areas of the lake. Moreover, average habitat suitability of the Flamingo is less than 10% which implies the ecological status of the lake is critical and ecological restoration is necessary. The main advantage of the proposed method is to develop a framework for combining the expert opinions with remote sensing data processing to generate habitat suitability maps in lakes.

Item ID: 77774
Item Type: Article (Research - C1)
ISSN: 1878-0512
Keywords: Ecological modelling, Remote sensing, Feed-forward neural network, Expert system, Fuzzy inference system
Copyright Information: © 2022 Elsevier B.V. All rights reserved.
Date Deposited: 22 Feb 2023 07:48
FoR Codes: 40 ENGINEERING > 4005 Civil engineering > 400513 Water resources engineering @ 100%
SEO Codes: 18 ENVIRONMENTAL MANAGEMENT > 1803 Fresh, ground and surface water systems and management > 180301 Assessment and management of freshwater ecosystems @ 100%
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page