Open-Source Remote Sensing Analysis for E-Governance using Python for NDVI and Vegetation Index Analysis

Urban planning in India increasingly depends on accurate and timely geospatial data for sustainable development.This paper presents the design and implementation of a Tkinter-based Python GUI application that computes vegetation indices from satellite raster data and integrates statistical and graphical analytics.The system is developed to aid E-Governance activities in Chhatrapati Sambhajinagar (Aurangabad) by simplifying raster data handling and automating NDVI, EVI, SAVI, and other vegetation index calculations.Users can interactively select raster bands, compute indices, visualize spatial patterns, analyze statistical metrics, and generate graphical representations using open-source libraries.A case study using Landsat data from 2013 demonstrates the tool's application in urban vegetation monitoring.Results show that the system provides effective spatial and statistical insights, helping planners detect vegetation stress, water bodies, and urban expansion zones with minimal technical overhead.