摘要
针对传统聚类算法易陷入局部最优、不兼顾地理空间的问题,该研究以湖南省怀化市为例,从生态敏感性、用地适宜性与整治迫切性3个维度建立分区评价指标体系,应用一种基于混合距离,同时具有聚类方案质量识别功能的两级选择性聚类集成方法对怀化市农用地整治进行时空配置。通过聚类运算,将怀化市300个聚类单元划分为:近期重点整治区、近期适度整治区、中期重点整治区、中期适度整治区和远期限制整治区5个类型,面积比例分别为9.05%、30.48%、22.58%、7.33%、30.56%,符合怀化现状条件;相较于传统聚类方法,两级选择性聚类集成方法具有聚类质量识别与兼顾地理空间的优势,且更适用聚类单元较多、属性空间复杂的情况。研究结果在客观上为未来土地整治工作与聚类方法的创新提供了可供借鉴的思路。
Most case studies have been implemented to explore the agricultural land consolidation in the temporal and spatial dimensions. An automated clustering has also been applied for the agricultural land consolidation zoning in recent years.However, the inherent limitations cannot been overcome in the automated clustering, particularly without considering the geographical space. It is very necessary for the rational zoning of clustering in the time and space dimension, especially for the spatial organization of agricultural land consolidation projects. The traditional clustering can also be tended to fall into the local optimality without the geographic space. In this study, a zoning evaluation index system was established in the Huaihua City, Hunan Province, China, according to three dimensions of the ecological sensitivity, land suitability, and urgency of consolidation. The clustering schemes were then evaluated for the spatial and temporal allocation of agricultural land consolidation. A two-level selective clustering ensemble was selected using mixed distances and three kinds of clustering of the hierarchical clustering, SOFM neural network(Self-Organising Feature Map), and the K-means clustering. The generated solution was identified using NMI(Normalized Mutual Information) and quality index, where the abnormal solutions were rejected to test the similarity of the solutions. Firstly, three algorithms were used to generate a library of solutions. Secondly,several clustering schemes with the better clustering were selected to evaluate the quality index using the NMI. Thirdly, the schemes were selected from a library of solutions for the second level of clustering. Finally, the similar cells of a cluster were treated with the same maximum number of clustering cells as a new one. The process was then repeated until all clusters were included in the new clusters. As such, the clusters were merged with the greater similarity, where the smaller clusters included in the clusters to reduce the dispersion between clusters
作者
张雅杰
靳铭
张丰
孔雪松
Zhang Yajie;Jin Ming;Zhang Feng;Kong Xuesong(School of Resource and Environmental Sciences,Wuhan University,Wuhan 430079,China;School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079,China)
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2022年第9期268-276,共9页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家重点研发计划项目(2018YFD1100801)。
关键词
土地利用
整治
分区
聚类分析
聚类集成
农用地整治
land use
consolidation
zoning
cluster analysis
clustering ensemble
agricultural land consolidation
