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Comparative Study of Satellite Imageries for the Vegetation Analysis with Geospatial Artificial Intelligence: Using Python and Scikit-Learn

Vickram A.S, Vidhya Lakshmi S, R. Anand, Veeraraghavan V.P

2024International Journal of Civil Engineering31 citationsDOIOpen Access PDF

Abstract

The datasets were collected for the urban area of Salem, which is located in India. As part of the investigation, four different datasets were gathered. A machine learning process was applied to the satellite imagery, with seventy percent of the area designated as the training set data and the remaining thirty percent utilized as test data. Using the K-means Clustering method, the research primarily concentrated on evaluating the first stage of vegetation in Salem City. A visual representation of the results obtained can be found in pictures 1, 2, 3, and 4. The statistical analysis of the research region reveals that areas with limited vegetation are experiencing consistent annual growth, with an exceptionally substantial rise recorded between February 2019 and February 2024.

Topics & Concepts

Python (programming language)Geospatial analysisComputer scienceSatelliteRemote sensingGeomaticsSatellite imageryArtificial intelligenceCartographyGeographyEngineeringOperating systemAerospace engineeringRemote Sensing in AgricultureRemote Sensing and LiDAR ApplicationsSpecies Distribution and Climate Change