Early Detection for Forest Illegal Logging at River Basin Area

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Author(s) Syafruddin Syarif | N. Harun | M. Tola | M.W. Tjaronge
Pages 502-507
Volume 3
Issue 5
Date May, 2013
Keywords Illegal logging, SVM, digital image processing, forest area, identification systems.

Abstract

The purpose of this study was to classify the use of multiple methods of expert systems, to determine the optimal model of early detection of illegal logging and changes in a forest area. Illegal logging is one of the ecological concerns related to the forest protection in Indonesia. In some cases, the illegal logging is almost impossible to be early identified by only physical inspection from the forestry staffs due to the field difficulty to reach the location. For this reason, the image processing by means Expert System using Support Vector Machine (SVM) method might be helpful to early identify the illegal logging activity. The sample image used in this research is taken from the Google Earth for one location of river basin area in Indonesia with the size area of 560m x 375m. The procedure of identification system is started by cropping the digital image and then classified for retrieving two-halves of the image in the form of forest and non-forest. These forms will be the input for the support vector machine method. Meanwhile, the testing data consists of five pairs of initial and final data. The simulation result shows that SVM method is able to early identify of illegal logging activity in protected forest areas with a level of accuracy of 80%. The testing process is basically similar to the image processing; only process of saving data sets it apart. The main point is the illegal logging indicator is obtained through the segmentation stage. Further analysis may determine the output whether the area is illegal logging or not.

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