Browse > Article

Building a Model for Estimate the Soil Organic Carbon Using Decision Tree Algorithm  

Yoo, Su-Hong (연세대학교 공과대학 사회환경시스템공학)
Heo, Joon (연세대학교 공과대학 사회환경시스템공학부)
Jung, Jae-Hoon (연세대학교 공과대학 사회환경시스템공학부)
Han, Su-Hee (연세대학교 공과대학 사회환경시스템공학부)
Publication Information
Journal of Korean Society for Geospatial Information Science / v.18, no.3, 2010 , pp. 29-35 More about this Journal
Abstract
Soil organic carbon (SOC), being a help to forest formation and control of carbon dioxide in the air, is found to be an important factor by which global warming is influenced. Excavating the samples by whole area is very inefficient method to discovering the distribution of SOC. So, the development of suitable model for expecting the relative amount of the SOC makes better use of expecting the SOC. In the present study, a model based on a decision tree algorithm is introduced to estimate the amount of SOC along with accessing influencing factors such as altitude, aspect, slope and type of trees. The model was applied to a real site and validated by 10-fold cross validation using two softwares, See 5 and Weka. From the results given by See 5, it can be concluded that the amount of SOC in surface layers is highly related to the type of trees, while it is, in middle depth layers, dominated by both type of trees and altitude. The estimation accuracy was rated as 70.8% in surface layers and 64.7% in middle depth layers. A similar result was, in surface layers, given by Weka, but aspect was, in middle depth layers, found to be a meaningful factor along with types of trees and altitude. The estimation accuracy was rated as 68.87% and 60.65% in surface and middle depth layers. The introduced model is, from the tests, conceived to be useful to estimation of SOC amount and its application to SOC map production for wide areas.
Keywords
SOC(Soil Organic Carbon); Decision Tree Algorithm;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 임영문, 곽준구, 황영섭, 2005, "C4.5 알고리즘을 이용한 산업 재해의 특성 분석", 한국안전학회지, 제20권, 제4호, pp.130-137.   과학기술학회마을
2 Chen, F., Kissel, D. E., West, L. T. and Adkins, W., 2000, "Field-Scale Mapping of Surface Soil Organic Carbon Using Remotely Sensed Imagery", Soil Sci Soc America, Vol.64, pp.746-753.   DOI
3 Hunter, Gary J.와 Goodchild, Michael F., 1997, "Modeling the Uncertainty of Slope and Aspect Estimates Derived from Spatial Databases", Geographical Analysis, Vol.29, No.1, pp.35-49.
4 Ramachandran, A., Jayakumar, S., Haroon, R. M., Bhaskaran, A. and Arockiasamy, D. I., 2007, "Carbon sequestration: estimation of carbon stock in natural forests using geospatial technology in the Eastern Ghats of Tamil Nadu", India, Current Science, Vol.92, pp.323-331.
5 RuleQuest Research, Australia, http://www.rulequest. com/see5-info.html
6 변성호, 강현직, 한정우, 김태웅, 2008, "의사결정나무모형을 이용한 유역내 구조적 홍수방어 대안 도출", 대한 토목학회지, 제 28권 제 1 B 호, pp.33-40.
7 송영석, 채병곤, 2008, "의사결정나무모형을 이용한 편마암 지역에서의 급경사지재해 예측기법 개발", The Journal of Engineering Geology, Vol.18, pp.45-54.   과학기술학회마을
8 이극노, 이홍철, 2003, "이동통신고객 분류를 위한 의사결정나무와 신경망 결합 알고리즘에 관한 연구", 한국지능정보시스템학회논문지, 제9권, 제1호, pp.139-155.   과학기술학회마을
9 Skidmore, A.K., Watford, F., Luckananurug, P. and Ryan, P.J., 1996, "An operational GIS expert system for mapping forest soi",. Photogrammetric Engineering and Remote Sensing, Vol.62, pp.501–511.
10 박수진, 손연규, 홍석영, 박찬원, 장용선, 2010, "한국 주요 토양유형의 공간적 분포와 토양형성요인을 이용한 예측가능성 평가", 대한지리학회지, 제 45권, 제 1호, pp.95-118.   과학기술학회마을
11 The University of Trier, Howard J. Hamilton, http://www2.cs.uregina.ca/~dbd/cs831/course.html
12 The University of Waikato, New Zealand, http://www.cs.waikato.ac.nz/~ml/index.html
13 Scull P., Franklin, J., Chadwick O.A. and McArthur, D., 2003, "Predictive soil mapping - a review", Progress in Physical Geography, Vol.27, pp.171- 197.   DOI   ScienceOn