Identification of Volcano Hotspots by using Resilient Back Propagation (RBP) Algorithm Via Satellite Images

S. Muni Rathnam*, T. Ramashri**
* H.O.D of Electronics and Communication, Balaji Institute of Engineering And Management Studies, Nellore(D), Andhra Pradesh, India.
** Professor in Electronics and Communication, Sri Venkateswara College of Engineering, SV University, Tirupati, Chittoor (D), Andhra Pradesh, India.
Periodicity:October - December'2014


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).


Artificial Neural Network (ANN), RBP (Resilient Back Propagation), Remote sensing, Satellite Images and Volcano.

How to Cite this Article?

Rathnam, M., and Ramashri, T. (2014). Identification of Volcano Hotspots by using Resilient Back Propagation (RBP) Algorithm Via Satellite Images. i-manager’s Journal on Image Processing, 1(4), 1-7.


[1]. Starks and Kreinovich. (May 2002). “Multi-spectral inverse problems in satellite image processing”. Systems Analysis Modeling Simulation. Vol.42, No.5.
[2]. Mohammad Awad. ( April 2010). “An Unsupervised Artificial Neural Network Method for Satellite Image Segmentation”. The International Arab Journal of Information Technology. Vol.7, No.2, pp.199-207,
[3]. Saheb Karim, Farah Riadh Bassel Solaiman and Ben- Ahmed Mohamed. (July 2008). “Toward a multi-temporal approach for satellite image interpretation”. The International Arab Journal of Information Technology, Vol.5, No.3, pp.281-287.
[4]. Sathiya, Vaidhiyanathan and Victor Rajamanickam. (October 2009). “Assessment of Ocean Parameters through the Satellite Images – AOOPSI”. International Journal of Computer Theory and Engineering. Vol.1, No.4, pp.420-423.
[5]. Nigar Sulthana and Mahesh Chandra. (2010). “Image compression with Adaptive Arithmetic Coding”. International Journal of Computer Applications, Vol.1, No.18, pp.31-34.
[6]. Sadykhov, Dorogush, Pushkin, Podenok and Ganchenko. (July 2007). “Multispectral Satellite Images Processing For Forests And Wetland Regions Monitoring Using Parallel MPI Implementation”. In proceedings of ENVISAT Symposium. Monteux, Switzerland.
[7]. Fleury, Self and Downton. (2005). “Multi-spectral Satellite Image Processing on a Platform FPGA Engine”. In Military and Aeronautics Logic Devices (MAPLD'05).
[8]. Ahmed Rekik, Mourad Zribi, Ahmed Ben Hamida and Mohammed Benjelloun. (2009). “An Optimal Unsupervised Satellite image Segmentation Approach Based on Pearson System and k-Means Clustering Algorithm Initialization”. International Journal of Signal Processing. Vol.5, No.1, pp.38-45.
[9]. Farnood Ahmadi, Valadan Zoej, Ebadi and Mokhtarzade. (2008). “Road Extraction from High Resolution satellite images using Image Processing Algorithms and CAD based Environments Facilities”. Journal of Applied Sciences. Vol.8, No.17, pp.2975-2982.
[10]. Ahmed Rekik, Mourad Zribi, Ahmed Ben Hamida and Mohammed Benjelloun. (October 2007). “Review of satellite image segmentation for an optimal fusion system based on the edge and region approaches”. IJCSNS. Vol.7,No. 10, pp.242-250.
[11]. Joyce, Belliss, Samsonov, McNeill and Glassey. (2009). “A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters”. Progress in Physical Geography. Vol.33, No.2, pp.183-207.
[12]. Mirnalinee Dhinesh, Sukhendu Das, Koshy Varghese. (January 2008). “Automatic Curvilinear Structure detection from Satellite Images using Multi resolution GMM”. International Journal of Imaging Science and Engineering. Vol.2,No.1,pp.154-157.
[13]. Debasish Chakraborty, Gautam Kumar Sen and Sugata Hazra. (October 2009). “High-resolution satellite image segmentation using Holder exponents”. J. Earth Syst. Sci., Vol.,No.5,pp.609-617.
[14]. Shwetank, Jain Kamal and Bhatia. (June 2010). “Review of Rice Crop Identification and Classification using Hyper- Spectral Image Processing System”. International Journal of Computer Science & Communication. Vol.1, No.1, pp.253-258.
[15]. Ashok and Rajan. (Aug 2010). “Multi Spectral Image Enhancement in Satellite Imagery”. ACS-International Journal on Computational Intelligence. Vol.1, No.1, pp.13-20.
[16]. V.V.Joseph Rajapandian and N. Gunaseeli. (Oct 2007). “Modified Standard Back Propagation Algorithm with Optimum Initialization for Feedforword Neural Network”. International Journal of Image Science and Engineering. Vol.1, No.3.
[17]. Jim Y.F Yam and Tommy W.S. Chow. (March 2001). “Feedforward Network Training Speed Enhancement by Optimal Initialization of Synaptic Coefficients”. IEEE Transaction on Neural Networks. Vol.12, No.2.
[18]. Chien Sheng and Szu Lin Su. (2010). “Resilient Back Propagation Neural Network for Approximation 2- DGDOP”, Proceedings of the International Multi Conference of Engineers & Computer Scientists. Vol.II, Hong Kong.
[19]. S. Muni Rathnam and T. Ramashri. (March 2014). “Identification of volcano hotspots by using standard back propagation (SBP) algorithm via satellite images”. Journal of Theoretical and Applied Information Technology. Vol. 61. No.1.
[20]. S. Muni Rathnam and T. Ramashri. (May-Jun. 2014). “Identification of volcano hotspots by using Modified Standard Back propagation (MBP) algorithm via satellite images”. IOSR Journal of VLSI and Signal Processing (IOSRJVSP). Vol. 4, No. 3, Ver. I.
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