Sentinel-2 NDVI Analysis Using GEE and QGIS for Green Open Space Sustainability Assessment in Kendari City - Sufrianto, Sufrianto; Yaacob Zubir, Siti Sara; Jassin, Andi Makkawaru Isazarni; Brata, Joko Tri; Danggi, Erni; Sallu, Sulfikar (Informatika, Universitas Jenderal Soedirman, 2025)
Rapid urbanization has profoundly transformed land cover in many growing cities, leading to a substantial decline in Green Open Space (GOS) and a progressive deterioration of ecological functions. The continuous conversion of vegetated zones into impervious and built-up surfaces has reduced the city’s ability to absorb carbon, regulate local microclimates, and maintain overall ecological resilience. Consequently, assessing the sustainability and spatial distribution of GOS is crucial for ensuring environmentally balanced urban development and resilience to future land-use pressures. This study aims to evaluate the sustainability of urban green spaces in Kendari City through an integrated geospatial approach that combines remote sensing and open-source cloud computing technologies. Sentinel-2 Level-2A imagery was analyzed in Google Earth Engine (GEE) using the QA60 band for cloud masking and spatial clipping to accurately define the study boundaries. Normalized Difference Vegetation Index (NDVI) values were subsequently processed and classified in QGIS using a reclassification technique to distinguish vegetation density categories. The results indicate that 56.7% of the total land area, equivalent to 15,213 hectares, exhibits high greenness, reflecting dense and healthy vegetation, whereas 32.3% consists of low or non-vegetated surfaces dominated by built-up and barren lands. These findings reveal substantial spatial disparities in vegetation coverage and underscore the importance of sustainable land management and green infrastructure policies. Furthermore, this research contributes to the advancement of geospatial informatics by developing an open, reproducible workflow that integrates cloud-based computation and open-source GIS for urban ecological monitoring and sustainability assessment.