ACCURACY EVALUATION OF SATELLITE-BASED LAND COVER DATA TO SUPPORT WATER RESOURCE MANAGEMENT IN MANGGARAI REGENCY

Abstract

To support sustainable water resource management in Manggarai Regency, the availability of accurate land cover data is essential. However, the limited availability of local data necessitates the use of satellite imagery-based data, such as ESRI and Landsat 8 imagery. This study aims to evaluate the accuracy of both datasets before they are used in land cover analysis. The 2024 ESRI imagery, which has been pre-classified into eight land cover classes, was compared with 2024 Landsat 8 imagery, which was classified using the Maximum Likelihood Classification (MLC) method in ArcGIS into ten land cover classes. Accuracy assessment was conducted using the Accatama plugin in QGIS, with Google Earth Pro serving as the reference data. The number of samples was determined using Slovin’s formula, resulting in 488 samples for the ESRI imagery and 951 for Landsat 8. The evaluation results show that ESRI imagery achieved a higher accuracy (0.72) compared to Landsat 8 (0.19). These findings suggest that ESRI imagery is more appropriate for land cover analysis aimed at enhancing water resource management efforts in Manggarai Regency. Although some classification errors still occurred, the ESRI imagery generally provides a more accurate representation of land cover conditions in the study area.