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

International Journal of Civil Engineering

© 2024 by SSRG - IJCE Journal

Volume 11 Issue 2

Year of Publication : 2024

Authors : A.S. Vickram, S. Vidhya Lakshmi, Anand Raju, V.P. Veeraraghavan

10.14445/23488352/IJCE-V11I2P108

How to Cite?

A.S. Vickram, S. Vidhya Lakshmi, Anand Raju, V.P. Veeraraghavan, "Comparative Study of Satellite Imageries for the Vegetation Analysis with Geospatial Artificial Intelligence: Using Python and Scikit-Learn," SSRG International Journal of Civil Engineering, vol. 11,  no. 2, pp. 80-92, 2024. Crossref, https://doi.org/10.14445/23488352/IJCE-V11I2P108

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.

Keywords:

Artificial Intelligence, Scikit-learn, Types of vegetation, Remote sensing, Python.

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