AI-Assisted NDVI Monitoring of Vegetation Change in Merapi National Park Using Google Earth Engine - Monika Ruwaimana; Subyantoro Tri Pradopo; Ruky Umaya; Diah Arianti; Vincentius Tri Setyobudi; Indah Murwani Yulianti; Wibowo Nugroho Jati; Pramana Yuda (Biota : Jurnal Ilmiah Ilmu-Ilmu Hayati, 2026)
Vegetation mapping is essential for monitoring conservation efforts in national parks and can be performed remotely using remote sensing and GIS technologies. However, the process is often complex and requires technical expertise. This study explores the use of AI, specifically ChatGPT, to simplify and support vegetation mapping workflows. We monitored monthly vegetation changes in Merapi Mountain National Park (TNGM) from 2017 to 2023 using the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 satellite data. The workflow combined Google Earth Engine (GEE) for satellite image processing and Python in Jupyter Notebook for time series analysis, with ChatGPT assisting in code editing. Our results show NDVI patterns are significantly influenced by volcanic activity, particularly eruptions and pyroclastic clouds, and about one-third of images were affected by cloud cover, especially during the rainy season. ChatGPT performed well in non-coding queries with a 79% satisfaction rate, but only 53% of generated code prompts were correct without modification. We conclude that while AI tools like ChatGPT have strong potential to enhance accessibility and efficiency in remote vegetation mapping, human oversight and foundational knowledge in geospatial analysis remain essential for accurate results.