Integration of GIS and Decision Tree in Land Evaluation for Coconut Trees in Mo Cay Nam District, Ben Tre Province
Main Article Content
Abstract
In this research, the integrated model of GIS and decision tree (DT) was built for land suitability analysis that support the foundation of land use planning. GIS was used to create thematic maps and decision tree shows several factor combinations according to plant average productivity. This study is applied for coconut trees in Mo Cay Nam district, Ben Tre province. The target variable is the productivity and the predictor variables consist of soil types, salinity, acidity, flood and irrigation. The study shows that the interpretation level of the predictive variables is 99.09%. The area of highly suitable is 3,522.22 hectares, suitable is 12,376.21 hectares, moderately suitable is 6,309.37 hectares.
Keywords:
Land evaluation, GIS, decision tree, coconut tree, Mo Cay Nam district.
References
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[3] de la Rosa, D., van Diepen, C.A., 2002. Qualitative and Quantitative Land Evaluation. In Willy H. Verheye. Land Use, Land Cover and Soil Sciences - Volume II: Land Evaluation. EOLSS, pp. 59-77.
[4] Jian Tian, Yueming Hu, Jianmin Liu, Yanling Zhao, Changwei Wang, 2009. The comparative analysis of various classification models on land evaluation. Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74921A, 15 October 2009, Wuhan, China.
[5] Kumar, N., Obi Reddy, G. P., Chatterji, S., 2013. Evaluation of Best First Decision Tree on Categorical Soil Survey Data for Land Capability Classification. International Journal of Computer Applications. 72(4): 5-8.
[6] van Lanen, H.A.J., Hack-ten Broeke, M.J.D., Bouma, J., de Groot, W.J.M., 1992. A mixed qualitative/quantitative physical land evaluation methodology. Geoderma. 55(1-2): 37-54.
[7] Bouma, J., Wagenet, R. J., Hoosbeek, M. R., Hutson, J. L., 1993. Using expert systems and simulation modelling for land evaluation at farm level: a case study from New York State. Soil Use Management. 9(4): 131–139.
[8] Yang JingFeng, Li Ting, Chen ZhiMin, 2010. Land evaluation method based on decision tree produced by C4.5 and fuzzy decision. Agricultural Science & Technology – Hunan. 11(3): 1-3.
[9] Nguyễn Ánh Nga, 2012. Ứng dụng kỹ thuật khai phá dữ liệu cho việc định lượng trong đánh giá đất đai trên địa bàn huyện Định Quán, tỉnh Đồng Nai. Luận văn thạc sĩ khoa học nông nghiệp. Trường Đại học Nông Lâm Thành phố Hồ Chí Minh.
[10] Han, J., Kamper, M., 2006. Data Mining: Concepts and Techniques, Second Edition. Morgan Kaufmann Publishers, Elsevier Inc, 772 pages.