Abstract
This dataset provides annual 10‑meter wetland maps for the Mobile‑Tensaw‑Apalachee (MTA) River Delta from 2019 to 2024, generated by integrating Sentinel‑2 optical imagery and Sentinel‑1 time‑series SAR data. A 1D‑CNN deep learning model was used to classify four wetland types: Forested Wetland, Marsh, Unconsolidated Shore, and Open Water, along with three non‑wetland classes. Classification accuracy ranged from 93% to 96%, supported by field verification and comparison with existing regional products. The dataset captures year-to-year changes in wetland extent and transitions, enabling the detection of subtle hydrological and ecological shifts within one of the largest freshwater wetland complexes in the United States.
Purpose
To examine wetland extent changes of different wetland types in the MTA River Delta from 2019 to 2024.
DOI: 10.57778/979a-nf32
Suggested Citation
Yang, Zutao. Annual Wetland Maps (2019-2024) of Mobile-Tensaw-Apalachee (MTA) River Delta . Dauphin Island Sea Lab, 2026, doi:10.57778/979A-NF32.
Related Publication Citation
Attribution
This project was paid for [in part] with federal funding for the Alabama Center of Excellence from the Department of the Treasury under the Resources and Ecosystems Sustainability, Tourist Opportunities, and Revived Economies of the Gulf Coast States Act of 2012 (RESTORE Act) in cooperation with the State of Alabama Department of Conservation and Natural Resources under the Alabama Center of Excellence Program at the MESC/Dauphin Island Sea Lab.
