Pattern Recognition in Remote Sensing Image Analysis: Theory, Methods, and a Case Study of Rijiyar Donor in Katsina, Nigeria

Thomas U. Omali¹ , Kebiru Umoru²

Section:Research Paper, Product Type: Journal-Paper
Vol.11 , Issue.6 , pp.61-65, Dec-2023

Online published on Dec 31, 2023

Copyright © Thomas U. Omali, Kebiru Umoru . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Remotely sensed data is of great importance in the dynamic assessment of both natural and artificial earth’s resources. The conventional method used for the classification of remote sensing imagery is mainly based on the pixel spectral data of geographical features. This technique depends on pixel spectral data alone, as such, it frequently fail in attaining the desired aim due to the multifarious nature of the environment it is being used to analyse. One important approach that is used to enhance remote sensing data classification and analysis is Pattern recognition. Therefore, the aim of this paper is mainly to discuss the concept of pattern recognition in remotely sensed image analysis with emphasis on its theory, and methods of application. Also, pattern recognition was applied in this study for the classifying LULC of Rijiyar Donor within Katsina State of Nigeria.

Key-Words / Index Term :
Classification, feature extraction, fuzzy, image processing, land cover, preprocessing, postprocessing

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