Four decades of spatio-temporal trends in Miankaleh Wetland´s water body and vegetation as revealed by remote sensing time series

Coastal wetlands offer essential ecosystem services, but are increasingly threatened by anthropogenic activities and climate change. These disrupt regional patterns, necessitating time series analyses to inform their long-term trends. Remote sensing provides cost-effective alternatives to demanding traditional wetland monitoring. Here, we employed a 40-year time series of Landsat data, supplemented by Sentinel-1 SAR imagery and Sentinel-2 multispectral data for enhanced recent-period analysis, and applied non-parametric trend analysis to examine changes in water bodies, vegetation, and climatic conditions in Miankaleh peninsula, encompassing an extensive Ramsar site in Iran. We utilized spectral indices and random forest classification to derive the area of water bodies and vegetation, followed by identifying significant trends using various trend analysis methods: Mann-Kendall (MK), Modified Mann-Kendall (MMK), Sequential Mann-Kendall (SeqMK), Seasonal Mann-Kendall (SMK), Sen’s Slope (SS), and LOcally Estimated Scatterplot Smoothing (LOESS). Findings showed a significant reduction in water area (30,700 ha, SS = -1.074) and an increase in vegetation cover (31,400 ha, SS = 1.365) from baseline levels. Among climatic factors, groundwater levels (SS = -0.214) and evaporation (SS = -0.312) were most influential on the wetland. The MMK, accounting for data autocorrelation, provided more accurate results compared to MK, while SeqMK detected important trend change points that were mostly missed by MMK. LOESS visualized local, nonlinear changes and identify subtle trend shifts. The results underscore significant ecological shifts, particularly the reduction of water bodies, which threaten the wetland's functionality. We provide general and case-specific considerations on the sole and complementary application of non-parametric trend analysis approaches, expanding insights into ecological processes in coastal wetlands with broader implications for similar ecosystems. • We compare trend analysis approaches of water bodies and vegetation cover in coastal wetlands. • Non-parametric trend analysis approaches complement each other to achieve accurate results, where using single methods is not recommended. • Advanced trend analysis methods, including MMK, SEQMK, and SMK, enhanced the accuracy and identified critical trend changes. • LOESS visualization highlighted subtle and nonlinear ecological changes essential for wetland management.

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Publication Details

Journal
Ecological Informatics
Published
2025-08-08
DOI
https://doi.org/10.1016/j.ecoinf.2025.103374
Citations
1
Primary Topic
Soil and Environmental Studies
Type
article
Field-Weighted Citation Impact
1.19
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article

Four decades of spatio-temporal trends in Miankaleh Wetland´s water body and vegetation as revealed by remote sensing time series

Hooman Latifi, Rohollah Esmaili, Arvin Fakhri, Nima Arij
1 citations
Ecological Informatics
Soil and Environmental Studies
1.19
article

Four decades of spatio-temporal trends in Miankaleh Wetland´s water body and vegetation as revealed by remote sensing time series

Hooman Latifi, Rohollah Esmaili, Arvin Fakhri, Nima Arij
article en
1 citations

Abstract

Coastal wetlands offer essential ecosystem services, but are increasingly threatened by anthropogenic activities and climate change. These disrupt regional patterns, necessitating time series analyses to inform their long-term trends. Remote sensing provides cost-effective alternatives to demanding traditional wetland monitoring. Here, we employed a 40-year time series of Landsat data, supplemented by Sentinel-1 SAR imagery and Sentinel-2 multispectral data for enhanced recent-period analysis, and applied non-parametric trend analysis to examine changes in water bodies, vegetation, and climatic conditions in Miankaleh peninsula, encompassing an extensive Ramsar site in Iran. We utilized spectral indices and random forest classification to derive the area of water bodies and vegetation, followed by identifying significant trends using various trend analysis methods: Mann-Kendall (MK), Modified Mann-Kendall (MMK), Sequential Mann-Kendall (SeqMK), Seasonal Mann-Kendall (SMK), Sen’s Slope (SS), and LOcally Estimated Scatterplot Smoothing (LOESS). Findings showed a significant reduction in water area (30,700 ha, SS = -1.074) and an increase in vegetation cover (31,400 ha, SS = 1.365) from baseline levels. Among climatic factors, groundwater levels (SS = -0.214) and evaporation (SS = -0.312) were most influential on the wetland. The MMK, accounting for data autocorrelation, provided more accurate results compared to MK, while SeqMK detected important trend change points that were mostly missed by MMK. LOESS visualized local, nonlinear changes and identify subtle trend shifts. The results underscore significant ecological shifts, particularly the reduction of water bodies, which threaten the wetland's functionality. We provide general and case-specific considerations on the sole and complementary application of non-parametric trend analysis approaches, expanding insights into ecological processes in coastal wetlands with broader implications for similar ecosystems. • We compare trend analysis approaches of water bodies and vegetation cover in coastal wetlands. • Non-parametric trend analysis approaches complement each other to achieve accurate results, where using single methods is not recommended. • Advanced trend analysis methods, including MMK, SEQMK, and SMK, enhanced the accuracy and identified critical trend changes. • LOESS visualization highlighted subtle and nonlinear ecological changes essential for wetland management.

Ecological InformaticsVol. 91
Department of the Environment (GB), K. N. Toosi University of Technology (IR), Mazandaran University of Medical Sciences (IR)
Clean water and sanitation
Openalex Percentile: Top 18%
Soil and Environmental Studies
1.19
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