Soil Mapping Using GIS, Expert Knowledge, and Fuzzy Logic
Soil Mapping Using GIS, Expert Knowledge, and Fuzzy Logic
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DOI：
10.2136/sssaj2001.6551463x
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发表时间：
2001-09
影响因子：
2.9
通讯作者：
A. Zhu;B. Hudson;J. Burt;K. Lubich;D. Simonson
中科院分区：
文献类型：
--
作者：
A. Zhu;B. Hudson;J. Burt;K. Lubich;D. Simonson
描述了一种基于地理信息系统（GIS）或专家知识的模糊土壤推理方案（土壤-土地推理模型，索利姆）。该计划包括三个主要组成部分：（i）采用土壤的相似性表示的模型，（ii）一套推理技术，用于推导的相似性表示，和（iii）使用的相似性表示。相似性表示允许土壤景观被认为是一个连续体，从而克服了传统土壤制图中土壤的泛化。一套推理技术是基于土壤因子方程和土壤景观模型。土壤-景观概念认为，如果一个人知道一个地区的每种土壤与其环境之间的关系，那么他就能够通过评估该点的环境条件来推断景观上每个位置的土壤。在索利姆下，使用地理信息系统或遥感技术确定一个地区的土壤环境条件。土壤与其形成环境条件之间的关系是从当地土壤专家或使用一套人工智能技术的实地观察中提取的。然后，将所表征的环境条件与所提取的关系相结合，以获得一个区域内土壤的相似性表示。通过两个实例研究表明，索利姆土壤调查有许多优势，比传统的土壤调查方法。通过索利姆获得的土壤信息产品在空间细节水平和属性准确度方面都具有高质量。此外，该计划显示，通过减少进行调查的时间和成本，有希望提高土壤调查和随后更新的效率。然而，索利姆的成功程度在很大程度上取决于环境数据的可用性和质量，以及研究区域土壤-环境关系知识的质量。
A geographical information system (GIS) or expert knowledge-based fuzzy soil inference scheme (soil-land inference model, SoLIM) is described. The scheme consists of three major components: (i) a model employing a similarity representation of soils, (ii) a set of inference techniques for deriving the similarity representation, and (iii) use of the similarity representation. The similarity representation allows the soil landscape to be considered as a continuum, and thereby overcomes the generalization of soils in conventional soil mapping. The set of inference techniques is based on the soil factor equation and the soil-landscape model. The soil-landscape concept contends that if one knows the relationships between each soil and its environment for an area, then one is able to infer what soil might be at each location on the landscape by assessing the environmental conditions at that point. Under the SoLIM, soil environmental conditions over an area are characterized using GIS or remote sensing techniques. The relationships between soils and their formative environmental conditions are extracted from local soil experts or from field observations using a set of artificial intelligence techniques. The characterized environmental conditions are then combined with the extracted relationships to derive a similarity representation of soils over an area. It is demonstrated through two case studies that the SoLIM for soil survey has many advantages over the conventional soil survey approach. Soil information products derived through the SoLIM are of high quality in terms of both level of spatial detail and degree of attribute accuracy. In addition, the scheme shows promise for improving the efficiency of soil survey and subsequent updates through reducing time and costs of conducting a survey. However, the degree of success of the SoLIM highly depends on the availability and quality of environmental data, and the quality of knowledge on soil-environmental relationships over the study area.