Land Cover Classification Schemes Using Remote Sensing Images: A Recent Survey

Abstract

Economic development and growth in population have prompted rapid changes to earth’s land cover over the last few decades, and there is every indication that the pace of these changes will accelerate in the future. Therefore, systematic evaluations of Earth’s land cover must be repeated at a frequency that allows monitoring of both long term trends as well as inter-annual variability, and at a level of spatial detail to allow study of land use patterns. Land cover analysis can be done most effectively through remote sensing images of various spatial, spectral and temporal resolutions to improve the selection of areas designed for agricultural, urban and/or industrial areas of a region. Astute efforts have been made in developing advanced classification algorithms and techniques for improving the accuracy of land cover classification. Recent image classification approaches for land cover pattern analysis have been brought together with their pros and cones by reviewing literatures, books, manuals and other related documents. Suitable classification algorithms may be chosen based on their performance, type of image and application area. Through this survey, various aspects regarding, preprocessing, classification and accuracy assessment, new and unique land cover products may be generated which could not be produced by earlier techniques.