MAPPING MANGROVE GREEN BELTS IN AQUACULTURE PONDS USING GOOGLE EARTH ENGINE

Abstract

Mangrove ecosystems function as vital biophysical buffers, attenuating wave energy, reducing coastal erosion, and stabilizing shorelines. Historically, they have been employed as natural barriers to protect coastal aquaculture, including fish ponds. This study examines the temporal dynamics of mangroves safeguarding the Unhas Bojo educational fish ponds using cloud-based geospatial analysis via Google Earth Engine (GEE). Field data were collected from June 2–5, 2023, across 27 sampling points within three stations, complemented by Sentinel-2A imagery (474 scenes, from 2016 to 2023). Equipment included GPS logger, quadrat, compass, ImageJ, timestamp camera, protractor, Google My Maps, GPX Viewer, QGIS, and GEE. Species identified were Rhizophora mucronata, Rhizophora apiculata, and Sonneratia alba. Average canopy cover was 76.2 ± 5.8%, indicating good ecological condition. NDVI values ranged from -0.12 to 0.65, with a model coefficient of determination (R²) of 0.835 and RMSE of 1.69. Despite overall resilience, seasonal NDVI dynamics revealed consistent patterns: higher productivity during the dry season and reduced values in the rainy season. These intra-annual fluctuations demonstrate that mangrove vigor is strongly coupled with climatic drivers, particularly rainfall intensity and hydrological regimes. Persistent canopy cover underscores ecological resilience, yet sensitivity to seasonal stressors highlights the importance of monitoring mangrove health under variable climatic conditions.