Land Cover Classification Of Satellite Images Using Artificial Neural Network And Support Vector Machine
The excitement and curiosity of viewing our planet from afar has led to the development of artificial satellites into stellar orbit for having live images of earth. Such images falls under the category of satellite imagery, which is a collection of images of earth snapped by artificial satellites. Extracting land cover information from such images is a challenging classification problem in the area of remote sensing. This work deals with a new approach for attempting the land cover classification of satellite images by the integration of Artificial Neural Networks and Support Vector Machine. The proposed technique uses a novel combination of Multi-layer artificial neural network and Multi-class SVM for the classification of land cover information. The experimental results evaluate the feasibility, performance and accuracy of the system by the construction of a confusion matrix.
Index Terms— Land cover classification, Multi-class Support vector machine, Multi-layer Artificial neural network, Remote sensing, Satellite imagery.