Performance Evaluation Report for LCLU Based on SVM, ANN and MLE Supervised Classification Algorithms Using Machine Learning

Authors

  • G. Nagalakshmi, T. Sarath

Abstract

 The Land Cover/ Land Use (LCLU) are the words used by the researchers who awareof classifying the land of a particular instant. Mainly this LCLU is used interchangeably, their actual meaning is pretty simple land use denotesthe purpose of the land servers, for illusion mining, agriculture, settlement etc. Land cover denotes to the ground which covers the surface, vegetation based on whether,bare soil,wateretc.These LCLU classification is done by exhausting remote sensing and GIS (Geographical Information System). The remote sensing images like multispectral, hyperspectral, LANDSAT, Sentinel, world view etc.,GIS procedures can be used onvector polygon layers,raster images or mixture of both characterizes the land classification or detecting the LCLU. The remote sensing images are taken in the form of the daily basis. This study presents how LCLU classification can be done with the use of machine learning algorithms andanalyzation of results based on various machine learning algorithms.

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Published

2020-05-17

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Section

Articles