Post-Disaster Recovery Assessment of Mangrove Forests in Leyte Island, Philippines using Sentinel-2 Imagery

The research investigated the synergy of different vegetation indices, biophysical variables, and landscape metrics in assessing the post-disaster recovery of the mangrove forests in Maasin City and Matalom in Leyte Island, Philippines after Super Typhoon Odette (International Name: Rai). These data show the monthly mean vegetation indices, monthly mean biophysical variables, and four-month landscape metrics values in the study area from 2019 to 2022, which spans three years before and one year after Super Typhoon Odette hit the area. The data were gathered using Google Earth Engine, SNAP Biophysical Processor, and QGIS Landscape Ecology Statistics Plug-In. Time series analysis was used to interpret the data, which includes the Theil-Sen Estimator and Mann-Kendall Test. Notable finding includes decline across all post-disaster parameters which reveal substantial damage to the functional, structural, and landscape configuration characteristics of the mangrove forest. Contrasting recovery and resiliency profiles were observed between vegetation indices and biophysical variables, which indicate that previous post-disaster studies that only employed NDVI may have reported underestimd recovery values.