Integrating Sentinel-2 NDVI and Web GIS for Rice Vegetation Monitoring
DOI:
https://doi.org/10.47709/brilliance.v6i4.9878Keywords:
Agricultural Monitoring, Geographic Information System, Normalized Difference Vegetation Index, Remote Sensing, Sentinel-2Abstract
Monitoring rice vegetation across agricultural plots requires accessible spatial information. Satellite-derived vegetation indices provide periodic observations, while Web Geographic Information Systems (Web GIS) present spatial data through interactive maps. This study develops a Web GIS integrating Sentinel-2-derived Normalized Difference Vegetation Index (NDVI) data to support rice vegetation monitoring in Negarajati Village, Cimanggu District, Cilacap Regency, Indonesia. The study used processed monthly NDVI values from ten sampling locations (P1–P10) covering May–September 2026. Descriptive statistics were calculated to summarise monthly NDVI values and their variation. The Web GIS was developed using Laravel, PostgreSQL with PostGIS for spatial data management, and LeafletJS for map visualisation. The application was deployed in a web-hosting environment to provide browser-based access. The monthly mean NDVI values were 0.159538 in May, 0.270014 in June, 0.491593 in July, 0.621865 in August, and 0.571092 in September. The mean increased from May to August before declining in September. The Web GIS presents monthly NDVI information and sampling-point attributes through an interactive map, enabling users to explore the processed spatial dataset. The developed Web GIS provides an integrated platform for presenting Sentinel-2-derived NDVI information for village-scale rice vegetation monitoring. The monthly values describe variation in the processed dataset but do not independently confirm crop growth stages or field health. Further work should document image-processing procedures and include field validation to strengthen interpretation.
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Copyright (c) 2026 Beny Riswanto, Kusnana, Nursetianti, Agus Sudarmanto, Syaiful Akbar Rizy Mubarok
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