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http://dx.doi.org/10.7780/kjrs.2017.33.6.3.7

Deforestation Analysis Using Unsupervised Change Detection Based on ITPCA  

Choi, Jaewan (School of Civil Engineering, Chungbuk National University)
Park, Honglyun (School of Civil Engineering, Chungbuk National University)
Park, Nyunghee (School of Civil Engineering, Chungbuk National University)
Han, Soohee (Dept. of Geoinformatics Engineering, Kyungil University)
Song, Jungheon (HyperSensing)
Publication Information
Korean Journal of Remote Sensing / v.33, no.6_3, 2017 , pp. 1233-1242 More about this Journal
Abstract
In this study, we tried to analyze deforestation due to forest fire by using KOMPSAT satellite imagery. For deforestation analysis, unsupervised change detection algorithm is applied to multitemporal images. Through ITPCA (ITerative Principal Component Analysis) of NDVI (Normalized Difference Vegetation Index) generated from multitemporal satellite images before and after forest fire, changed areas due to deforestation are extracted. In addition, a post-processing method using SRTM (Shuttle Radar Topographic Mission) data is involved in order to minimize the error of change detection. As a result of the experiment using KOMPSAT-2 and 3 images, it was confirmed that changed areas due to deforestation can be efficiently extracted.
Keywords
Change detection; Deforestation; ITPCA; KOMPSAT; NDVI;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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