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Open AccessArticle

Mapping the Soil Texture in the Heihe River Basin Based on Fuzzy Logic and Data Fusion

by Ling Lu 1,2, Chao Liu 1,2,3, Xin Li 1,2,4 and Youhua Ran 1,2,*
Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
University of Chinese Academy of Sciences, Beijing 100049, China
Zhuzhou Electric Locomotive Research Institute Co., Ltd., China Railway Rolling Stock Corporation (CRRC), Zhuzhou 412001, China
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
Author to whom correspondence should be addressed.
Sustainability 2017, 9(7), 1246;
Received: 12 June 2017 / Revised: 10 July 2017 / Accepted: 11 July 2017 / Published: 17 July 2017
Mapping soil texture in a river basin is critically important for eco-hydrological studies and water resource management at the watershed scale. However, due to the scarcity of in situ observation of soil texture, it is very difficult to map the soil texture in high resolution using traditional methods. Here, we used an integrated method based on fuzzy logic theory and data fusion to map the soil texture in the Heihe River basin in an arid region of Northwest China, by combining in situ soil texture measurement data, environmental factors, a previous soil texture map, and other thematic maps. Considering the different landscape characteristics over the whole Heihe River basin, different mapping schemes have been used to extract the soil texture in the upstream, middle, and downstream areas of the Heihe River basin, respectively. The validation results indicate that the soil texture map achieved an accuracy of 69% for test data from the midstream area of the Heihe River basin, which represents a much higher accuracy than that of another existing soil map in the Heihe River basin. In addition, compared with the time-consuming and expensive traditional soil mapping method, this new method could ensure greater efficiency and a better representation of the explicitly spatial distribution of soil texture and can, therefore, satisfy the requirements of regional modeling. View Full-Text
Keywords: soil texture; soil land inference model; data fusion; arid region soil texture; soil land inference model; data fusion; arid region
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Lu, L.; Liu, C.; Li, X.; Ran, Y. Mapping the Soil Texture in the Heihe River Basin Based on Fuzzy Logic and Data Fusion. Sustainability 2017, 9, 1246.

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