• P. Penchala Swamy
• Ch. Dileep Chakravarthy

Multi-spectral satellite imagery is a practical, precise and proper strategy for getting data ashore utilize and arrive cover since they give information at consistent interims and is sparing when contrasted with the other customary techniques for ground study and aeronautical photography. Classification of multi spectral remotely detected information is examined with an uncommon spotlight on vulnerability examination in the created land cover maps. Here, we have proposed a proficient strategy for ordering the multi spectral satellite pictures utilizing SVM into arrive cover and land utilize segments. In the proposed classification system at first pre-processing is done where the information picture is subjected to an arrangement of pre-processing steps which incorporates Gaussian filtering and RGB to Lab shading space picture change. In this manner, division utilizing fluffy fused progressive clustering method is done. At that point preparing of the SVM is done in the preparation information determination methodology lastly the classification step, where the cluster centroids are subjected to the prepared SVM to get the land utilize and land cover parts. The experimentation is completed utilizing the multi spectral satellite pictures and the investigation guarantees that the execution of the proposed system is enhanced contrasted and conventional clustering algorithm.

Multispectral satellite image, Clustering, Classification, Support vector machine

"Classification of Spatial Data from Satellite images to distinguish Regions of Land Use", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.369-379, July-2018, Available :http://www.jetir.org/papers/JETIR1806656.pdf

"Classification of Spatial Data from Satellite images to distinguish Regions of Land Use", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp369-379, July-2018, Available at : http://www.jetir.org/papers/JETIR1806656.pdf