摘要
客观给定农田质量分级指标,是实现农田质量等级划定智能化的技术难题之一.以北京市房山区为例,首先建立农田质量参照系;基于GIS,叠加土地利用现状图、土壤图和地形图,生成农田质量评价单元和数据库;采用模糊非对称贴近度算法,计算各评价单元农田质量评分;提出了农田质量分级的模糊稀疏度与模糊贴近度比较算法模型,根据农田质量评分数值的密度分布,自动提取农田质量等级界定指标。
To give an objective criterion for grading farmland quality is one of the difficult technical problems in intelligent realization in the farmland quality gradation. This article attempts to identify and describe the application of Sparseness based Clustering Technique (SBCT) to realize automatic quality classification of farmland. To begin with Fangshan, one district of Beijing's, as an example, the reference frame of farmland quality is established which consists of four criteria including soil fertility, environment, facilities and management of farmland. Subsequently, the evaluation units of farmland quality are generated by overlaying the feature maps of land use, soil type and topography based on GIS technology, and the data base of farmland quality is created. Then the grades of the farmland quality evaluation units are calculated by using the non symmetry fuzzy closeness algorithms. Consequently, according to the value distribution density of the farmland quality grade, the classified indices of farmland quality grade are put forward automatically by a fuzzy algorithmic model which compares sparseness with closeness of farmland quality grades, and the gradation of farmland quality is divided. The calculation result (fig.2) shows that the SBCT can indicate the inner difference of farmland quality classification in Fangshan district. The high quality farmland which is the main cultivation area of Fangshan is distributed in the diluvium plain between Yongding river and Dashi river, the low quality farmland is distributed in the hilly area of western Fangshan. The SBCT may reduce the subjective criterion of classified indices in farmland quality classification, but as one of Algorithms which realizes the automatic quality classification of farmland, the foregoing discussion of the SBCT applied to farmland quality classification in other districts will be demonstrated.
出处
《南京大学学报（自然科学版）》
CAS
CSCD
1999年第6期697-703,共7页
Journal of Nanjing University（Natural Science）
基金
国家自然科学基金!资助项目(编号 :4 980 10 15 )
关键词
农田质量评价
质量参照系
自动分等定级
GIS
Farmland quality evaluation
Reference frame of farmland quality
fuzzy sparseness
Automatic gradation
GIS technology
