This paper is based on data analysis by python programming language on Google collaborator platform, data analysis for Google-Earth sentinel imagery, for the area of ‘SUNDARBANS’, situated in West Bengal, India, the world’s largest mangrove forest, the UNESCO heritage property. The file for python code of analysis is linked with the ‘Google Earth Engine’, data pulled from this interface, using the coordinates of the area of interest, here which is the area of ‘SUNDARBANS’, the delta. In Google Earth Engine, there is to have a log-in credential and during the execution of this python programming to fetch data from this interface, it was required to create some project in ‘Google Earth Engine’, with a newly created project id, which was to incorporate in the programming file to initialize and authenticate the execution and also for pulling of data from that interface. In this way by ‘Google Earth’ initialization and providing project id, enabled with authentication from Google id, obtained the imagery data for sentinel-1 for visualization of VH(vertical-horizontal) backscatter and VV (vertical-vertical) backscatter on folium map for the area of interest. Then obtained result of NDVI value from sentinel-2 imagery along with visualization of NDVI value for a particular date range, incorporated in the program. VV is reflected wave received vertically to the radar sensor and VH is reflected wave received horizontally to the radar sensor. High VV back scatter indicates rough surface on earth such as structures etc and low VV back scatter indicates smooth surfaces like water. NDVI value, B4, B5 surface reflectance band are related for understanding vegetation on the earth surface. VV, VH values as well as visualization of backscatter time series graph and also NDVI values and visualization of NDVI help to understand changes in different geo-physical properties such as surface roughness, soil moisture, vegetation and other. From this type of data analysis obtaining result as well as visualization regarding change of such parameters, can provide valuable information to monitor the environment, natural resources, impact on human activity on earth’s surface.