The Classification of Land Use and Land Cover was conducted using the Manual Method in ArcGIS and using AI/ML in the Google Earth Engine for Salem District, Tamilnadu, India.

This study examines the land use and land cover (LULC) classification in Salem District, Tamil Nadu, India, using both a manual method in ArcGIS and an AI-driven approach in the Google Earth Engine (GEE). The manual method offers high accuracy but is labor intensive, while GEE uses cloud computing and machine learning for greater efficiency and scalability. The study compares the accuracy, efficiency, and applicability of both methods across different scales and temporal resolutions. The results showed that ArcGIS is better for detailed, small-scale work, while GEE excels in large-scale and dynamic analyses. This study identifies the strengths and limitations of each approach and suggests future research directions for environmental monitoring, urban planning, and emerging technologies.