• Govindalakshmi T.S.
• Dr C.Kiran Mai
• Dr P.Sammulal

Multispectral satellite images are essential source of information in the Land Usage and Land Cover (LULC) observation which is accomplished by the classification of LULC spatial data. Nevertheless, the mapping of extensive regions with spatial boundaries in spatial data is costly process .The Land Cover (LC) information describes an information source for different kinds of logical research. The classification of LC dependent on satellite information is mostly challenging assignment, and an effective classification technique is required. Most examinations have revealed that the predominant execution of image investigation on various landscape types namely urban regions, water bodies, and forest lands but, these observations have difficulties while choosing the ideal scale of segmentation, which can fall in the under or over segmentation. The different classification techniques in spatial data analysis have their own constraints, advantages, preferences and detriments, and no single strategic technique is ideal for all cases. This paper outlines and examines different soft computing methods and feature extraction strategies which are utilized for LULC spatial data classification. In view of the average error rate, exhibitions of different soft computing strategies are assessed.

Satellite images, Soft computing, Spatial resolution, Feature extraction, Classification Methods

"A Review on spatial data classification on land usage and land cover using feature extraction and classification methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.706-709, February-2019, Available :http://www.jetir.org/papers/JETIRAB06134.pdf

"A Review on spatial data classification on land usage and land cover using feature extraction and classification methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp706-709, February-2019, Available at : http://www.jetir.org/papers/JETIRAB06134.pdf