Current Research in Next Generation Materials Engineering
The Classification of Land Use and Land Cover Conducted Using the Manual Method in Arcgis and Using AI / Ml in Google Earth Engine for Salem District, Tamil Nadu, India
Abstract
S. Mohammed Junaid
This study compares two methods for Land Use and Land Cover (LULC) change detection in Salem District, Tamil Nadu using manual mapping with ArcGIS and automated analysis using Google Earth Engine (GEE). ArcGIS provides high spatial accuracy, making it suitable for small-scale, detailed studies, but is resource-intensive and time-consuming. GEE leverages cloud computing for efficient, scalable analysis, enabling broader regional and temporal assessments. The comparison reveals ArcGIS is better suited for localized, precision studies, while GEE excels in rapid processing of large datasets. The study highlights each method’s strengths and limitations, offering insights for applications in environmental monitoring and urban planning.
