Development of a Rapid Mangrove Zonation Mapping Workflow Using Sentinel 2-Derived Indices and Biophysical Dataset

Moderate to high resolution satellite imageries are commonly used in mapping mangrove cover from local global scales. In addition extent information, studies such as composition, ecology, and distribution analysis require further information on zonation. Mangrove zonation refers unique sections within a forest being dominated by similar family, genus, or species. This can be observed both natural planted forests. this study, workflow was developed detect test sites Katunggan-It Ibajay (KII) Ecopark (Aklan), Bintuan (Coron), Bogtong, Sagrada (Busuanga) the Philippines Fukido Park (Ishigaki, Japan) using Sentinel-2 imagery. The methodology then applied generate nationwide map of for year 2020. Combination biophysical products, water, vegetation indices were classification inputs including leaf area index (LAI), fractional (FVC), fraction photosynthetically-active radiation (FAPAR), Canopy chlorophyll content (C ab ), canopy water w Normalized Difference Vegetation Index (NDVI), modified normalized difference (MNDWI), absorption reflectance (MCARI), red-edge inflection point (REIP). extents first mapped either Maximum Likelihood Classification (MLC) algorithm (MVI)-based methodology. these areas stacked transformed through Principal Component Analysis (PCA). Regions Interest (ROIs) selected PCA bands training input MLC. Results show that maps highlight major zones study sites, limited up genera level only except with one known species thriving area. Four detected KII Ecopark: Avicennia zone, Nypa mixed mangroves zones. For Coron Busuanga, mangroves, Rhizophora zone sparse/damaged Three site: stylosa -dominant Bruguiera gymnorrhiza validated field plot data orthophotos generated Unmanned Aerial System (UAS) surveys, accuracies ranging 75 100%.