A Survival Study on Classification Methods with Geospatial Data

Abstract

Data mining is method of determining patterns in large datasets. The spatial information includes position of spatial features, association of geospatial features and measurement values. Spatial data comprises points, lines, polygons, geographic and geometric information primitives that is mapped through location, stored with object as metadata. Spatial data is employed for communication to find user devices. This study compares different existing spatial data classification techniques with geospatial information. Many researchers carried out their research on spatial data classification. However, classification accuracy and time performances were not enhanced. Our objective is to improve the performance of spatial data classification at higher accuracy and lesser time.