JIP_V1_N4_RP1 Muni Rathnam Ramashri Journal on Image Processing 2349-6827 1 4 1 7 Artificial Neural Network (ANN), RBP (Resilient Back Propagation), Remote sensing, Satellite Images, Volcano The explosive growth of remote sensing technology, internet and multimedia systems poses great challenge in handling huge amount of data. Advancement in the field of Remote Sensing has gone to an extent of taking the geospatial accuracy to few centimeters. The use of remote sensing of natural hazards and disasters has become common. Remote sensing plays a vital role because of their pressing need in the analysis of natural hazards. Among the various hazards, the Volcanoes are terrific hazards which may harm the nature as well as the living things. Here, the identification of volcanoes and their hotspot identification are important to protect the living things. Hence, the present investigation is utilized to identify the volcanoes and their hotspot from the satellite images. Therefore to overcome the aforesaid problems, we are going to identify the hotspot of volcano using the Artificial Neural Network (ANN) which uses Resilient Back Propagation (RBP) Algorithm. At first, the color space of the satellite image will be converted to another color space to identify the contents of the image clearly. Then image will be segmented to identify the volcano's hotspot. To improve the accuracy, eight Statistical parameters are extracted from satellite image such as mean, variance, contrast, homogeneity, energy, correlation, standard deviation and entropy. The proposed mechanism will be developed with the aid of the platform MATLAB (version 7.11). October - December 2014 Copyright © 2014 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=3034