Journal of The Geomorphological Association of Korea (한국지형학회지)
- Volume 23 Issue 3
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- Pages.67-78
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- 2016
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- 1226-4296(pISSN)
DOI QR Code
Spatial Prediction of Soil Carbon Using Terrain Analysis in a Steep Mountainous Area and the Associated Uncertainties
지형분석을 이용한 산지토양 탄소의 분포 예측과 불확실성
- Jeong, Gwanyong (Department of Geography, Chonnam National University)
- 정관용 (전남대학교 지리학과)
- Received : 2016.09.05
- Accepted : 2016.09.25
- Published : 2016.09.30
Abstract
Soil carbon(C) is an essential property for characterizing soil quality. Understanding spatial patterns of soil C is particularly limited for mountain areas. This study aims to predict the spatial pattern of soil C using terrain analysis in a steep mountainous area. Specifically, model performances and prediction uncertainties were investigated based on the number of resampling repetitions. Further, important predictors for soil C were also identified. Finally, the spatial distribution of uncertainty was analyzed. A total of 91 soil samples were collected via conditioned latin hypercube sampling and a digital soil C map was developed using support vector regression which is one of the powerful machine learning methods. Results showed that there were no distinct differences of model performances depending on the number of repetitions except for 10-fold cross validation. For soil C, elevation and surface curvature were selected as important predictors by recursive feature elimination. Soil C showed higher values in higher elevation and concave slopes. The spatial pattern of soil C might possibly reflect lateral movement of water and materials along the surface configuration of the study area. The higher values of uncertainty in higher elevation and concave slopes might be related to geomorphological characteristics of the research area and the sampling design. This study is believed to provide a better understanding of the relationship between geomorphology and soil C in the mountainous ecosystem.
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