BHOO-MI – BHOONIDHI META INTELLIGENCE

Presently satellite data products are supplied to the users in various formats and with required meta data associated to it. In general, this Meta data contains the latitude/longitude information of the area covered. The utilization of satellite imagery in diverse fields necessities efficient methods to add value to the core images. In this research work, we designed a comprehensive methodology to design a system which provides the intelligence to the basic data product by adding various geographic features over that area. Both natural and manmade geographic features were considered in study. The features include post offices, monuments, airports, museums, hospitals, educational institutes (NITs & IITs) etc. All these features are extracted and preserved as a centralized repository/database. Leveraging a combination of Python programming, web scraping techniques, and advanced geospatial libraries such as Geopandas and Shapely, our system undertakes a multi-step approach. Initially, the system reads the metadata of the satellite image to obtain corner latitude and longitude coordinates. Then the system identifies and extracts relevant feature data. These feature’s meta information is then compiled into a shapefile, providing a comprehensive overview of the features present within the satellite image. This shapefile serves as a valuable resource for further analysis and decision- making in applications such as environmental monitoring, urban planning, and disaster response.