Time Series Analysis of Surface Water Areas Using Sentinel Imagery on Google Earth Engine: A Spatial Approach

The study aimed to map exterior water areas employing time-series sentinel data through GEE platform it utilized series with regard to techniques including image pre-processing water index calculation cloud and shadow masking to be able to precisely locate and map surface bodies of surface water the outcomes demonstrated that Google earth engine is a practical tool for processing substantial volumes of satellite data for mapping surface water offering a quick and effective way to monitor alterations in bodies of water over time at the regional and global scale surface water body where spatial and temporal methods can be used to map surface water body dynamics sets and became accessible using remote sensing methods. The NDWI and ML models such as SVM and nave Bayes using sentinel-8 data were used in the ongoing project to track both the geographical analysis and temporal changes. Implementation of these models were performed to figure out the volume and density changes in water in light of prior rise in the coverage surface region of water bodies after the monsoon season in Vijayawada. India based on sentinel time series photos of earth utilizing the Google earth engine remote computing infrastructure information collected from observations that were processed in a platform and compared to live groundwater levels.