Spatiotemporal Dynamics and Drivers of Wetland Change on Chongming Island (2000–2020) Using Deep Learning and Remote Sensing

Using Landsat series imagery and the deep learning model CITNet, this study conducted high-accuracy classification and spatiotemporal change analysis of wetlands on Chongming Island from 2000–2020 and explored the driving mechanisms by integrating climatic and anthropogenic factors. The results demonstrate that the total wetland area decreased by approximately 125.5 km2 over the two decades. Among natural wetlands, tidal mudflats and shallow seawater zones continuously shrank, while herbaceous marshes exhibited a “decline recovery” trajectory. Artificial wetlands expanded before 2005 but contracted significantly thereafter, mainly due to aquaculture pond reduction. Wetland transformation was dominated by wetland-to-non-wetland conversions, peaking during 2005–2010. Driving factor analysis revealed a “human pressure dominated, climate modulated” pattern: nighttime light index (NTL) and GDP demonstrated strong negative correlations with wetland extent, while minimum temperature and the Palmer Drought Severity Index (PDSI) promoted herbaceous marsh expansion and accelerated artificial wetland contraction, respectively. The findings indicate that wetland changes on Chongming Island result from the combined effects of policy, economic growth, and ecological processes. Sustainable management should focus on restricting urban expansion in ecologically sensitive zones, optimizing water resource allocation under drought conditions, and incorporating climate adaptation and invasive species control into restoration programs to maintain both the extent and ecological quality of wetlands.

• Publication year

  2025

• Venue

  Journal of Marine Science and Engineering

• Publication date

  2025-09-23

• Fields of study

  Not labeled

• Identifiers
  DOI 10.3390/jmse13101837
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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