Annual Wetland Maps (2019-2024) of Mobile-Tensaw-Apalachee (MTA) river delta
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.
Fields of Study & Subjects
Remote-Sensing Image Classification
Wetland Management and Conservation
Coastal wetland ecosystem dynamics
Publication details
- Journal / source
- Dauphin Island Sea Lab Repository
- Publication date
- 3 February 2026
- Language
- EN
- Document type
- Dataset