International Journal of Management, IT and Engineering
Year : 2016, Volume : 6, Issue : 10
First page : ( 27) Last page : ( 33)
Online ISSN : 2249-0558.

Hybrid algorithm for deforestation detection using satellite data

Babu J. Suresh, Prof. Sudha T.

Online published on 27 February, 2017.

Abstract

The conservation and development of forests are vital to the welfare of human beings. Forests management is essential to maintain social, economic and ecological services. Forrest monitoring allows to track their state of health and productivity, in order to conduct proper management, according to the state of resources, to enhance their functionality and promote conservation. Remote sensors, optical and radar, offer the possibility of locating changes in forest areas using various analysis techniques, ranging from the purely visual interpretation to the implementation of a fully automated algorithm. The main purpose of this work was the development of a tool to detect in real time (daily) deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA sensor and Artificial Neural Networks. The developed tool provides the parameterization of the configuration for the neural network training to enable finding the best neural architecture to address the problem and makes use of confusion matrixes to determine the degree of success of the network. Part of the city of Porto Velho, in Rondônia state, makes up the tile H11V 09 of the MODIS/TERRA sensor, which was used as the study area. A spectrum-temporal analysis of this area was made on 57 images from 20 of May to 15 of July 2003 using the trained neural network. This analysis allowed verifying the quality of the implemented neural network classification as well as helped the understanding of the dynamics of deforestation in the Amazon rainforest. The great potential of neural networks for image classification was perceived with this work. However, the generation of consistent alarms, in other words, detecting predatory actions at the beginning; instead of firing false alarms is a complex task that is not yet solved. Therefore, the major contribution of this paper is to provide a theoretical basis and practical use of neural networks and satellite images to combat illegal deforestation.

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