Imaging Spectroscopy for Enhancing Regional Coastal Wetland Extent Monitoring

Abstract Coastal wetland habitats contribute to important ecosystem services, including improved water quality, carbon sequestration, and flood mitigation, but they are difficult to be monitored in situ due to their inaccessibility. This research aims to explore the potential and limitation of monitoring coastal wetland habitats in the Greater Cape Floristic Region (GCFR), South Africa, with the NASA Earth Mineral Dust Source Investigation (EMIT). High‐resolution habitat extent derived from PlanetScope imagery was used to train random forest regression algorithms with EMIT data. We estimate the subpixel extent of three wetland habitats (salt marshes, reeds and sedges, and submerged aquatic vegetation (SAV)). We validate model performance using a testing estuary unseen by the model. The best‐performing model achieved a root mean square error (RMSE) of 7.8% (281 m 2 ) for salt marsh, 11.4% (410 m 2 ) for reeds and sedges, and 5.6% (202 m 2 ) for SAV. At higher tidal stages, model performance decreased with RMSE of 23.6% for salt marsh and 12.2% for SAV, underscoring the influence of tidal inundation on mapping accuracy of these habitats. These findings illustrate the need to select tidal stages when mapping these habitats, particularly the importance of imagery acquired at low tidal stages during the growing season. This study shows that when medium‐resolution imaging spectroscopy is combined with machine learning, we can estimate subpixel habitat extent, addressing the spatial limitations of the EMIT imaging spectrometer. With more data, our approach could provide information on long‐term trends and changes in these ecosystems. EMIT‐based subpixel monitoring of coastal wetlands is possible and can provide important information on the extent and change of these ecosystems.