Analisis Kesehatan Vegetasi Multi-Temporal Berbasis WebGIS Menggunakan NDVI Sentinel-2 dan Penilaian Multi-Kriteria SAW

Akner Yosha Ade Saputra (Universitas Dian Nuswantoro)
Nurul Anisa Sri Winarsih (Universitas Dian Nuswantoro)
Muhammad Syaifur Rohman (Universitas Dian Nuswantoro)
Danny Oka Ratmana (Universitas Dian Nuswantoro)

Infotekmesin
Vol 17 No 2 (2026): Infotekmesin: Juli 2026

This study integrates Sentinel-2 NDVI, the Simple Additive Weighting (SAW) method, and WebGIS to analyze vegetation health dynamics across 19 sub-districts in Grobogan Regency (±1,975.87 km²). Data were sourced from four Sentinel-2 Level-2A images (September 14–October 9, 2025) and supporting meteorological parameters. Results indicate NDVI values ranging from 0.2424 to 0.6297. On September 14, 42.1% of the areas were classified as High. However, by September 19, 12 sub-districts experienced a significant decline anomaly (), leaving only 21.1% in the High category. The SAW assessment yielded scores between 0.2793 and 0.4918. Spearman's validation demonstrated a perfect correlation () between NDVI and SAW rankings. The observed temporal fluctuations correlated with rainfall and humidity. In conclusion, this integrated approach effectively evaluates vegetation anomalies to support precise land management decisions.