ITM Web Conf.
Volume 56, 2023First International Conference on Data Science and Advanced Computing (ICDSAC 2023)
|Number of page(s)||9|
|Published online||09 August 2023|
Land cover clustering and classification of satellite images
1 Electronics & Telecommunication, MKSSS’s Cummins College of Engineering for Women, Pune, India
2 Hydraulic Instrumentation, Central Water and Power Research Station (CWPRS), Pune, India
* corresponding author: email@example.com
Land cover classification refers to the process of using remote sensing data to categorize different types of land cover like vegetation, water bodies and soil. This is helpful for gaining key information about the surface of the Earth and for the future interactions between human activities and the environment. These predicted interactions lead to the development of sustainable land use practices along with the protection of natural resources. This paper deals with classifying the land cover using unsupervised and supervised methods. The unsupervised method includes land cover detection using a K-means clustering algorithm and the supervised classification is done using random forest classifier. The evaluation parameter values are calculated and compared for the input and output images.
Key words: classification / remote sensing / multiband satellite imagery / rescaling / segmentation
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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