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Position: Home > Articles > Detection of landuse/landcover changes using remotely-sensed data Journal of Forestry Research 2016,27 (6)

Detection of landuse/landcover changes using remotely-sensed data

作者：

Jin-Woo Park;Jungsoo Le

单位：

Department of Forest Management, College of Forest and Environmental Sciences, Kangwon National University, Chunchon, Republic of Korea;Department of Forest Management, College of Forest and Environmental Sciences, Kangwon National University, Chunchon, Republic of Kore

关键词：

Deforestation;Spatial sampling method;Remotely sensed data;Land cover change;Spatial resolution;LAND-COVE

摘要：

We evaluated the use of spatial sampling and satellite images to identify deforested areas in Wonju, South Korea. The changes in land cover were identified using a grid of sample points overlaid onto medium and high-resolution remote sensing (RS) satellite images. Deforestation identified in this way (hereafter, RSD) was compared to administrative data on deforestation. We also compared high-resolution satellite images (HR-RSD) and actual deforestation based on categories which were Intergovernmental Panel on Climate Change data. RSD generated by medium-resolution satellite images overestimated the amount of deforested area by 1.5-2.4 times the actual deforested area, whereas RSD generated by HR-RSD underestimated the amount of deforested area by 0.4-0.9 times the actual area. The highest degree of matching (90 %) was found in HR-RSD with a grid interval of 500 m and the accuracy of HR-RSD was the highest, at 67 %. The results also revealed that the largest cause of deforestation was the establishment of settlements followed by conversion to cropland and grassland. We conclude that for the identification of deforestation using satellite images, HR-RSD with a grid interval of 500 m is most suitable.

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Detection of landuse/landcover changes using remotely-sensed data

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