基于模糊c-均值聚类法的绿洲农田精确管理分区研究

Definition of management zones based on fuzzy c-mean algorithm in oasis farmland

以新疆绿洲棉区为研究对象,将176个土壤耕层属性数据作为变量进行精确管理分区研究。模糊c-均值聚类法被用来进行分区,采用c-φ多次组合法来确定适宜的模糊控制参数。研究区最佳分区数为4,模糊指数为1.5,平均混乱度指数为0.17,不同模糊类别交叠程度小,地理空间上土壤的隶属关系相对明确。为了评价分区结果的合理性,对各管理分区土壤数据进行常规性统计,并用LSR法进行各分区间差异显著性检验,结果表明:各管理分区土壤属性的变异系数都较分区前全研究区有所减小,分区间土壤属性差异显著。通过选取适宜的模糊控制参数,模糊c-均值聚类法可以较好地进行管理分区划分,分区结果可以作为变量施肥的单独作业单元进行耕作管理。

Percent organic matter,total nitrogen,available phosphorus,and salinity were estimated in 176 topsoil samples.These samples were collected from a 9600 hm2 cotton field in northern Xinjiang Province.A fuzzy c-means clustering algorithm was used to assign these samples to management zones.The derivative of the objective function with respect to the fuzziness exponent,（δJ/δφ）c0.5,was used to determine the optimum fuzzy control parameters.The optimum number of the classes and the fuzziness exponent was 4 and 1.5,respectively.The average confusion index was 0.17 in all management zones.Thus,the overlapping of fuzzy classes at points was low and the spatial distribution of membership grades was unambiguous.To estimate the validity of zoning result,the general statistics analysis on the data was carried out.The zoning statistics showed that variation coefficients of soil properties decreased,while the means of the soil properties differed sharply between management zones.These results indicated that fuzzy c-means clustering algorithm can be used to delineate management zones by the optimum fuzzy control parameters.The management zones can then be used to help guide the rate of fertilizer application in an effort to manage soil nutrient levels more efficiently.