基于功能分区与多聚类算法集成的耕地细碎化评价及整治  

Evaluation and consolidation of cultivated land fragmentation based on integration of function zoning and multi-cluster algorithms

作　　者：李希明 黄秋昊[1,2,3,5] 吕剑成 李满春 陈振杰[1,2,3] 李飞雪 Li Ximing;Huang Qiuhao;Lyu Jiancheng;Li Manchun;Chen Zhenjie;Li Feixue(School of Geography and Ocean Science,Nanjing University,Nanjing 210023,China;Key Laboratory for Land Satellite Remote Sensing Applications,Ministry of Natural Resources,Nanjing 210023,China;Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology,Nanjing 210023,China;Key Laboratory of the Coastal Zone Exploitation and Protection,Ministry of Natural Resources,Nanjing 210023,China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China;Jiangsu Institute of Land Survey and Planning,Nanjing 210023,China)

机构地区：[1]南京大学地理与海洋科学学院,南京210023 [2]自然资源部国土卫星遥感应用重点实验室,南京210023 [3]江苏省地理信息技术重点实验室,南京210023 [4]自然资源部海岸带开发与保护重点实验室,南京210023 [5]江苏省地理信息资源开发与利用协同创新中心,南京210023 [6]江苏省土地勘测规划院,南京210023

出　　处：《农业工程学报》2022年第6期274-282,共9页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金面上项目(41571082)。

摘　　要：基于图斑尺度的耕地细碎化评价及整治有利于耕地布局优化,促进农业规模化与集约化发展。该研究以耕地图斑为基本评价单元,引入聚合分析来量化图斑间空间位置关系,围绕耕地细碎化内涵选取评价指标;运用热点分析和二步聚类算法来对研究区功能分区,在功能分区基础上,基于带轮廓系数的k-means聚类算法,评价耕地图斑的细碎化程度。结果表明:1)根据功能分区的聚类结果,新北区被划分为不显著区、连片规整区、离散复杂区;2)评价结果将新北区耕地图斑分为3类:类别一,离散破碎类,包含图斑17332块,平均图斑面积过小,连片度低,图斑面积集中在0~10000 m^(2),面积占比21.98%,连片度集中在1~4,主要分布在新北区中心区域;类别二,形状复杂类,包含图斑4535块,图斑形状复杂不规整,面积占比9.65%,形状指数集中在1.5~2.5,均匀分布在全区;类别三,连片规整类,包含图斑4091块,图斑集中连片、形态规整,面积占比68.37%,连片度集中在5~10,形状指数集中在1~1.5,主要分布在外围区域;并基于各类别耕地细碎化属性差异,提出相应的优化模式和整治意见。研究结果可以为耕地细碎化整治提供一定参考。Taking the cultivated land in the Xinbei district of Changzhou City in Jiangsu Province of China as the research object,an evaluation model was constructed for the patch-scale arable land fragmentation using the integrated functional zoning and regional clustering.Taking the cultivated land patch as the basic unit,some indicators were firstly selected,including the patch area,contiguous degree,and shape index.A spatial analysis was conducted to calculate the indicators,such as aggregation in ArcGIS 10.6.Secondly,the area weighting was used to expand the patch index to the area with the administrative village as the unit,where the Getis-Ord Gi*was further used to identify the cold and hot areas of each index for the degree of regional fragmentation.Thirdly,the research area was divided into functional zones using two-step clustering,where the administrative villages with neighboring geographical locations and similar fragmentation attributes were clustered into one zone.Finally,the Python-based Sklearn library was selected to implement the K-means clustering with the silhouette measure.The silhouette measure was introduced to determine the optimal number of clusters and the best clustering.The clustering data was then used to evaluate the degree of fragmentation of the cultivated land.The results showed that:1)There were the insignificant area,continuous regular areas,and discrete complex zone,according to the clustering data of functional zoning.2)The cultivated land patches were classified into three categories:Category 1,the number of patches was 17332,the average area of patches was too small,the degree of continuity was low,the area of patch was concentrated in 0-10000 m^(2),the area accounted for 21.98%,and the contiguous degree was concentrated in 1-4,mainly distributed in the central area;Category 2,the number of patches was 4535,the complex and irregular shape of patches,the area accounts for 9.65%,the shape index was concentrated in 1.5-2.5,evenly distributed in the whole area;Category 3,the number of pa

关 键 词：整治 评价 功能分区 耕地细碎化 热点分析 二步聚类 K-MEANS聚类 常州 

分 类 号：F301.21[经济管理—产业经济]