Multi-sensor remote sensing for land cover mapping in the Can Gio mangrove ecosystem, Ho Chi Minh City
DOI:
https://doi.org/10.5281/zenodo.19766444Keywords:
Multi-sensor remote sensing, linear spectral mixture model, land use/land cover, hyperspectralAbstract
This study presents an integrated approach utilizing multispectral Sentinel-2, hyperspectral PRISMA, and Synthetic Aperture Radar (SAR) COSMO-SkyMed (CSK) data to map land use/land cover (LULC) patterns in the Can Gio mangrove ecosystem. The analysis is supplemented with biophysical variables (LAI, FAPAR) and an in-situ spectral library to enhance the spectral discriminability of vegetation and spectrally similar surfaces. A Linear Spectral Mixture Model (LSMM) is applied to the PRISMA data to address the severe spectral mixing commonly encountered in coastal environments. Furthermore, CSK data are exploited to delineate urban settlements and aquaculture ponds. The classification results yielded an overall accuracy of 88% (Kappa = 0.83), demonstrating the efficacy of the multisensor approach in characterizing heterogeneous landscapes. This methodology exhibits significant potential for application in next-generation hyperspectral missions.
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