CAJ | 학술논문

针对农用地评价因素的复杂性和模糊性，而传统的多因素综合评价法在农用地分等时易对评价因素以及等别进行“硬性划分”的不足。该文以湖北省安陆市为例，首次提出将模糊综合评判法与模糊聚类分析法结合（简称模糊综合分析法），以模糊综合评判的矩阵成果作为模糊 C-均值聚类分析的数据源来对划分农用地等别方法进行探讨，并将模糊综合评判法的分等结果与传统方法分等结果进行比较，得出2种方法分等结果中约有80%相同。采用安陆市各村的粮食平均播面单产对2种方法分等结果存在差异的地区进行独立检验，得到模糊综合评判法和传统方法的分等成果同播面单产的线性相关系数分别为0.87和0.82。研究结果表明：运用模糊综合分析法进行农用地分等具有可行性；将模糊综合分析法运用到农用地分等中比传统方法更能客观准确地说明土地质量的优劣程度。
침대농용지평개인소적복잡성화모호성，이전통적다인소종합평개법재농용지분등시역대평개인소이급등별진행“경성화분”적불족。해문이호북성안륙시위례，수차제출장모호종합평판법여모호취류분석법결합（간칭모호종합분석법），이모호종합평판적구진성과작위모호 C-균치취류분석적수거원래대화분농용지등별방법진행탐토，병장모호종합평판법적분등결과여전통방법분등결과진행비교，득출2충방법분등결과중약유80%상동。채용안륙시각촌적양식평균파면단산대2충방법분등결과존재차이적지구진행독립검험，득도모호종합평판법화전통방법적분등성과동파면단산적선성상관계수분별위0.87화0.82。연구결과표명：운용모호종합분석법진행농용지분등구유가행성；장모호종합분석법운용도농용지분등중비전통방법경능객관준학지설명토지질량적우렬정도。
Rational use of agricultural land is of significant importance to the food safety of our country and the development of social economy. With the introduction of new National Standards, classification of farmland has become an important part of land management. Accurate classification of farmland is the foundation of the management of both land quality and quantity. Classification of agricultural land is a very complex process, which requires a concurrent consideration of the natural quality, the utilized and economic level of land. Up till the present moment, the main method used to classify agricultural land was multi-factor comprehensive evaluation method, which was referenced onThe Farmland Gradation and Classification(GB/T 28407-2012) issued by the Ministry of Land and Resources of China. The classification index of farmland in this method was calculated through a comprehensive assessment and progressive modification of natural, social and economic factors related to the land. The calculation of the index was based on light-temperature potential productivity and the standard farming system of the land. Although traditional methods did well in applying quantum mathematics to farmland grading, it had some drawbacks such as absolute quantity and rigid division, due to the complex process of classification of agricultural land. It was essential to explore a more scientific approach to classify agricultural land. The purpose of this paper was to apply fuzzy mathematics to classification of farmland, and explore the feasibility of combining fuzzy comprehensive evaluation with fuzzy clustering analysis, which was termed as the fuzzy comprehensive analysis method in the study. Take Anlu city as a study case, we employed the fuzzy comprehensive evaluation and fuzzy C-means clustering algorithm as the analysis methods. Besides, we used ArcGIS and Visual Studio2010 as the data processing platforms. The research process was as follow Firstly, we obtained the degree of membership of grading units to each grade through compound operation of decision evaluation matrix and the weights of evaluation factors, based on the fuzzy comprehensive evaluation. And then, we used the membership matrix as a data source to grade agricultural land by fuzzy C-means clustering algorithm, since the method can make up for the information’s loss caused by the principle of maximum membership in the process of classification. The results indicated that the fuzzy comprehensive analysis method can be used to classify agricultural land. Roughly 80% of grading cells of farmland were consistent with the result of traditional method. To further examine/test the accuracy of the method introduced in this study, we adopted the grain yield per unit of sown area in each village in Anlu city to verify the grading result generated by fuzzy comprehensive analysis method and the traditional method. Result showed that linear correlative coefficients were 0.87 and 0.82 respectively, which meant both methods had significant correlations. However, the correlation of fuzzy comprehensive analysis method was slightly higher than that of the traditional method. Thus, we can conclude that the application of the fuzzy comprehensive analysis method in classification of agricultural land can improve the classification of farmlands objectively and accurately, which has practical significance and reference value in quality evaluation of agricultural land.