High-Accuracy Mangrove Extraction and Degradation Diagnosis Using Time-Series Remote Sensing and Deep Learning: A Case Study of the Largest Delta in the Northern Beibu Gulf, China

Mangrove extent has increased in many regions under strengthened conservation policies and large-scale restoration programs. Nevertheless, mangrove ecosystems continue to face multiple pressures, including limited total area, habitat degradation, biodiversity decline, and biological invasion, and localized deterioration in ecosystem structure and function has been increasingly reported. Despite extensive mapping efforts, the spatiotemporal dynamics of mangrove degradation—particularly in tidally influenced environments—remain insufficiently understood. Focusing on the Nanliu River Delta, the largest deltaic mangrove system in the Northern Beibu Gulf of China, this study integrates long-term Landsat time-series imagery (1990–2025) with deep learning to quantify both mangrove extent change and canopy degradation. To mitigate tidal inundation effects, a NDVI Pseudo-P75 compositing strategy was applied using Google Earth Engine (GEE), enabling consistent observation of mangrove canopies across tidal stages. Global Mangrove Watch v4 (GMW-V4) and HGMF2020 mangrove dataset for China were used as reference labels to train a ResNet34–UNet segmentation framework incorporating Digital Elevation Model (DEM) constraints. The model achieved high classification performance, with an IoU of 0.822 for mangroves and 0.981 for background, yielding a mean IoU of 0.902. The resulting maps, following manual verification, provided a robust basis for spatiotemporal and degradation analyses. Canopy condition was further assessed using the Enhanced Vegetation Index (EVI), which is less prone to saturation in high-biomass mangrove stands. Results show that mangrove area in the Nanliu River Delta expanded from 266 ha in 1990 to 1414 ha in 2025, with the annual expansion rate after 2005 being nearly seven times higher than that before 2005. Despite this net gain, a cumulative loss of 347.45 ha was recorded, primarily during 1990–2000, with approximately 70% converted to aquaculture and coastal engineering. Spatial analysis revealed that mangrove expansion occurred predominantly seaward, whereas both mangrove loss and canopy degradation exhibited an inverse J-shaped relationship with seawall proximity. More than 80% of mangrove loss occurred within 200 m of seawalls, indicating concentrated anthropogenic encroachment, while 75.6% of canopy degradation was observed within 350 m, potentially reflecting landward forest senescence. These results indicate a transition in dominant threats from permanent land conversion in the late 20th century to more subtle, internal functional degradation in recent decades, underscoring the need to complement extent-based assessments with canopy condition monitoring in mangrove conservation and management.

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Journal
Water
Published
2026-03-04
DOI
https://doi.org/10.3390/w18050617
Primary Topic
Coastal wetland ecosystem dynamics
Type
article
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article

High-Accuracy Mangrove Extraction and Degradation Diagnosis Using Time-Series Remote Sensing and Deep Learning: A Case Study of the Largest Delta in the Northern Beibu Gulf, China

Riming Wang, Xi Liu, Xiaokui Xie, Zhijun Dai
Water
Coastal wetland ecosystem dynamics
article

High-Accuracy Mangrove Extraction and Degradation Diagnosis Using Time-Series Remote Sensing and Deep Learning: A Case Study of the Largest Delta in the Northern Beibu Gulf, China

Riming Wang, Xi Liu, Xiaokui Xie, Zhijun Dai
article en

Abstract

Mangrove extent has increased in many regions under strengthened conservation policies and large-scale restoration programs. Nevertheless, mangrove ecosystems continue to face multiple pressures, including limited total area, habitat degradation, biodiversity decline, and biological invasion, and localized deterioration in ecosystem structure and function has been increasingly reported. Despite extensive mapping efforts, the spatiotemporal dynamics of mangrove degradation—particularly in tidally influenced environments—remain insufficiently understood. Focusing on the Nanliu River Delta, the largest deltaic mangrove system in the Northern Beibu Gulf of China, this study integrates long-term Landsat time-series imagery (1990–2025) with deep learning to quantify both mangrove extent change and canopy degradation. To mitigate tidal inundation effects, a NDVI Pseudo-P75 compositing strategy was applied using Google Earth Engine (GEE), enabling consistent observation of mangrove canopies across tidal stages. Global Mangrove Watch v4 (GMW-V4) and HGMF2020 mangrove dataset for China were used as reference labels to train a ResNet34–UNet segmentation framework incorporating Digital Elevation Model (DEM) constraints. The model achieved high classification performance, with an IoU of 0.822 for mangroves and 0.981 for background, yielding a mean IoU of 0.902. The resulting maps, following manual verification, provided a robust basis for spatiotemporal and degradation analyses. Canopy condition was further assessed using the Enhanced Vegetation Index (EVI), which is less prone to saturation in high-biomass mangrove stands. Results show that mangrove area in the Nanliu River Delta expanded from 266 ha in 1990 to 1414 ha in 2025, with the annual expansion rate after 2005 being nearly seven times higher than that before 2005. Despite this net gain, a cumulative loss of 347.45 ha was recorded, primarily during 1990–2000, with approximately 70% converted to aquaculture and coastal engineering. Spatial analysis revealed that mangrove expansion occurred predominantly seaward, whereas both mangrove loss and canopy degradation exhibited an inverse J-shaped relationship with seawall proximity. More than 80% of mangrove loss occurred within 200 m of seawalls, indicating concentrated anthropogenic encroachment, while 75.6% of canopy degradation was observed within 350 m, potentially reflecting landward forest senescence. These results indicate a transition in dominant threats from permanent land conversion in the late 20th century to more subtle, internal functional degradation in recent decades, underscoring the need to complement extent-based assessments with canopy condition monitoring in mangrove conservation and management.

WaterVol. 18(5)
Guangxi University (CN), Beibu Gulf University (CN), East China Normal University (CN)
Life below water
Openalex Percentile: Top 44%
Coastal wetland ecosystem dynamics
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