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Extraction of Quantitative Relationships between Soil Properties and Landscape Factors Based on Fuzzy Set Theory and Its Applications in Digital Soil Mapping

Author: ZhaoLiang
Tutor: ZhangGanLinï¼›ZhouLiXiang
School: Nanjing Agricultural College
Course: Environmental Engineering
Keywords: Fuzzy set theory Soil thickness Topographical factors Soil - landscape model Soil Mapping SoLIM
CLC: S159.2
Type: Master's thesis
Year: 2007
Downloads: 169
Quote: 5
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Abstract


The development of precision agriculture, environmental management and ecological processes simulation produced a large demand for high-precision soil information. However, traditional soil mapping process is completed based on the expression of polygon graphics and hand. Polygon-based soil maps, due to the limitations of the scale, the smaller individual soil can not be reflected in the graph, and the small figure plaque in the cartographic generalization are often integrated out, resulting in soil maps space simplified; and, in most cases, the spatial variation of the soil is continuous, traditional soil map, soil polygons boundary segmentation variants that occurs only at the border, gradient can not express the soil properties and continuous, resulting in simplified attributes. Therefore, how to objectively describe soil spatially continuous distribution law to become a new topic. Modern information acquisition the Ways and processing technology development, in particular the application of \improved. Soil - landscape model extrapolation method, quantitative prediction most mainstream, suitable for regional scale soil mapping methodology. The method is based on the soil of the classic theory, the famous Jenny equations: S = f (Cl, O, R, P, T ...), where S is the soil, Cl, O, R, P, T is called environmental factors affect soil into soil, climate, organisms, topography, parent material and time respectively. The equation indicates that such an assumption: The same soil occurred landscape corresponds to the same type of soil; Once informed of the correspondence between the soil and landscape unit, you can infer soil type by the characteristics of the landscape unit. In this study, a hilly test area in southern Anhui case region by quantitative degree of membership relations of the terrain factor fuzzy clustering combination of topographic factors and soil properties portfolio, and then attached to the high value of the area for the purpose of sampling membership function assignment, the production study area soil thickness continuous maps. Random sampling through the field, the predictive value comparison of observations with the figure, the accuracy of test model accuracy of about 80%, from the accuracy of soil mapping and needs to consider, with a certain reliability. Better predictability relative error for further analysis and found that the prediction model lower parts of the terrain, better soil development, soil-forming environment is relatively stable and strong applicability. On this basis, the introduction of the organic matter content and soil pH of the soil surface two soil properties into the model, to further examine the prediction of the model. The results showed that the same model on the soil surface organic matter greater forecasting accuracy, but the predicted effect on soil pH is poor, is not sensitive enough to show that the model for the variation of minimum data sets, a poor predictor. Overall, on the basis of membership Figure terrain factor clustering, only a few purposeful sampling, a total of 30 soil profiles has been correspondence between soil properties and topographical factors, to meet the mapping requirements, improve sampling efficiency, greatly reducing the workload, thereby reducing mapping costs. Variability of soil properties maps predicted continuous, gradual, and no artificial division of the boundary of the polygons, more in line with the continuous changes in the actual situation of the soil space due to small changes in the space in the computer mapping through small pixel to reflected, so the performance of the soil micro-domain variation in more detail, drawing a higher load, thus drawing more accurate. The mapping method compared with traditional drafting methods, most of the work is done by computer complete mapping cycle is short, fast update. Finally using SOLIM model is also drawing membership diagram of the study area, soil types, as well as \The precision is also higher. In short, the study shows that the fuzzy clustering method is an effective way to extract the relationship of soil properties and topographical factors, the application of the method to produce large-scale soil Detailing is a viable method of soil survey and mapping fields.

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CLC: > Agricultural Sciences > Agriculture as the foundation of science > Soil > Soil geography, soil survey > Chinese soil geography, soil survey
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