A-PoRM SIPLAS: Assessing The Post-Disaster Recovery Of Mangrove Forest In Siargao Island Protected Landscape And Seascape (SIPLAS) Area Using Sentinel-1 SAR Data

Abstract

Tropical cyclones and typhoons pose significant threats to coastal ecosystems, particularly mangrove forests. Assessing the extent of mangrove damage and monitoring recovery post-disaster is vital for effective conservation and management strategies. Space-based observations have become increasingly common in monitoring forest damage in tropical regions. However, the predominant methods for change detection rely on satellite optical imagery, which faces challenges in humid tropical zones. Technological advancements have led to the development of detection techniques utilizing synthetic aperture radar (SAR) to address cloud cover issues. The study specifically targets Siargao Island Protected Landscape and Seascape (SIPLAS), the largest contiguous forest in the Philippines, from destruction caused by Super typhoon Rai (Odette). The study utilized SAR time-series data, unsupervised log ratio change detection method and Cumulative Sum (CuSum) analysis via Google Earth Engine (GEE). Analysis of Sentinel-1 GRD images found VV polarization had the highest accuracy at 92% and an F-measure of 0.92. VH polarization had 87.5% accuracy and an F-measure of 0.87, while combining VV and VH and VV/VH achieved the same results of 80.5% overall accuracy with an F-measure of 0.82. With that, results indicated that 53% of mangroves in SIPLAS area were damaged, with 38.05% regenerating by 2022 and 56.75% by 2023, notably after September 16, 2022 detected from CuSum analysis using the VV polarization. These findings substantiate the robustness of the data and methodologies employed in monitoring mangrove resilience and supporting conservation initiatives within the SIPLAS area.