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

机译:基于模糊逻辑和数据融合的黑河流域土壤质地制图。

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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.
机译:在流域范围内绘制流域土壤质地对于生态水文研究和水资源管理至关重要。然而,由于缺乏对土壤质地的原位观察,使用传统方法很难以高分辨率绘制土壤质地。在这里,我们采用基于模糊逻辑理论和数据融合的集成方法,通过结合原地土壤质地测量数据,环境因素,以前的土壤质地图,绘制了西北干旱地区黑河流域的土壤质地图。 ,以及其他专题图。考虑到整个黑河流域的景观特征不同,分别采用了不同的映射方案来提取黑河流域上游,中部和下游地区的土壤质地。验证结果表明,针对黑河流域中游地区的测试数据,土壤质地图的准确性达到69%,这比黑河流域中现有的另一幅土壤图的准确性要高得多。另外,与费时且昂贵的传统土壤制图方法相比,该新方法可确保更高的效率并更好地表示土壤质地的显式空间分布,因此可以满足区域建模的要求。

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