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Terrace Fields Classification in North Korea Using MODIS Multi-temporal Image Data
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 Title & Authors
Terrace Fields Classification in North Korea Using MODIS Multi-temporal Image Data
Jeong, Seung Gyu; Park, Jonghoon; Park, Chong Hwa; Lee, Dong Kun;
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 Abstract
Forest degradation reduces ecosystem services provided by forest and could lead to change in composition of species. In North Korea, there has been significant forest degradation due to conversion of forest into terrace fields for food production and cut-down of forest for fuel woods. This study analyzed the phenological changes in North Korea, in terms of vegetation and moisture in soil and vegetation, from March to Octorber 2013, using MODIS (MODerate resolution Imaging Spectroradiometer) images and indexes including NDVI (Normalized Difference Vegetation Index), NDSI (Normalized Difference Soil Index), and NDWI (Normalized Difference Water Index). In addition, marginal farmland was derived using elevation data. Lastly, degraded terrace fields of 16 degree was analyzed using NDVI, NDSI, and NDWI indexes, and marginal farmland characteristics with slope variable. The accuracy value of land cover classification, which shows the difference between the observation and analyzed value, was 84.9% and Kappa value was 0.82. The highest accuracy value was from agricultural (paddy, field) and forest area. Terrace fields were easily identified using slope data form agricultural field. Use of NDVI, NDSI, and NDWI is more effective in distinguishing deforested terrace field from agricultural area. NDVI only shows vegetation difference whereas NDSI classifies soil moisture values and NDWI classifies abandoned agricultural fields based on moisture values. The method used in this study allowed more effective identification of deforested terrace fields, which visually illustrates forest degradation problem in North Korea.
 Keywords
Forest degradation;NDXI;Land cover classification;Phenology;
 Language
Korean
 Cited by
1.
Mapping Deforestation in North Korea Using Phenology-Based Multi-Index and Random Forest, Remote Sensing, 2016, 8, 12, 997  crossref(new windwow)
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