基于模糊集理论提取土壤—地形定量关系及制图应用

DIGITAL SOIL MAPPING BY EXTRACTING QUANTITATIVE RELATIONSHIPS BETWEEN SOIL PROPERTIES AND TERRAIN FACTORS BASED ON FUZZY SET THEORY

通过对研究区地形因子的模糊聚类,提取了地形因子组合与特定土壤属性的定量隶属度关系,然后对隶属度高值区土壤进行目的性采样为隶属度函数赋值,制作研究区土层厚度连续分布图。通过野外实地验证,将观测值与图中预测值比较,结果显示该方法制图精度在82%左右,具有一定的可靠性。进一步考察认为该模型在地形部位较低,地势较为平坦,土壤发育较好,土层较厚,成土环境相对稳定的地区预测效果更好,适用性更强。该方法能提高土壤制图效率,降低制图成本,提高制图精度,对土壤微域变异的表现更为详细,图面信息负载量更高。应用该方法制作大比例尺土壤详图不失为土壤调查与制图领域一种可行的新方法。

A study was conducted to extract relationships between terrain factors and soil properties by clustering terrain factors based on the fuzzy set theory. Similarity of each pixel to the typical ones was obtained from the classification results, with degrees of similarity referred to as fuzzy membership. Then, a continuous soil horizon thickness distribution map was drawn with the aid of ARC/info software based on samples collected at the area with high value of fuzzy membership and population of the similarity model using the linear and additive weighting function. Comparison of the predicted value set from the map with the independently collected field sample set showed the derived soil map achieved 82 % of accuracy. Further investigation showed that the model worked well in the area of low altitude, well-developed soil, thick soil horizon, stable surrounding for soil formation. The new approach was found to be higher in efficiency and accuracy of soil mapping, lower in mapping cost, and more capable of demonstrating microregional variance and accommodating higher information load for mapping. Hence, it is a feasible new method worth extrapolating in soil survey and mapping.