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	基于空间聚类的平原旱作农区土地平整单元区划分方法
其他题名	Land leveling partitioning of farming area in arid plain based on spatial clustering
	郝星耀 1; 潘瑜春 2; 唐秀美 2; 邱贺 2; 刘玉 2; 任艳敏 2
来源期刊	农业工程学报
ISSN	1002-6819
出版年	2015
卷号	31 期号:5 页码:301-307
中文摘要	平整工程是土地整治项目的重要组成部分,其工程量和投资都占整个项目的很大比例,平整过程中通过合理规划土地平整单元区可以有效降低工程投资,并最大限度地满足农业生产需求。该文提出通过空间聚类划分平整单元区的方法,并基于工程量、平整度和单元区斑块规则度构建了用于确定最佳分区数及其平整单元区分布的目标函数。采用该方法对研究区进行平整单元区划分并计算相应评价参数,结果表明:随着分区数的增加工程量逐渐降低、分区间高程差升高,平整度下降、分区形状指数减小规则度升高,目标函数值随分区数增加呈现先降低后升高的趋势,根据目标函数的低谷可确定最优分区数目;相对于经验法,空间聚类法的工程量下降24%,高程极差下降11%,对于平整后项目区的平整工程量和平整度有较大地改善,但分区斑块形状指数增大11%,分区规则性降低,因此在实践中可将空间聚类法划分结果作为基础,再依靠专家经验对方案进行调整,以充分发挥2种方法各自的优势。
英文摘要	Land leveling accounts for the major part of project quantity and investment of land consolidation. Rational planning and implementation of land leveling project have important practical significance to reducing the project investment. Partitioning of leveling area is beneficial to reducing the project quantity and facilitating project organization. However, the existing empirical partitioning methods are mainly based on farmland irrigation and drainage facilities, and put little concerns on the project quantity and land consolidation efficiency. A partitioning method of land leveling area based on spatial clustering was proposed and tested in this paper. Firstly, the farmland was divided into a regular grid and the grid cells were used as clustering units. The grid cell size followed the present DEM (digital elevation model) resolution, and was 5m * 5m in this paper. Secondly, clustering variables were selected to ensure that the natural and agricultural infrastructure conditions in one partition are as consistent as possible. These clustering variables included elevation, relative position to the road, land ownership, and spatial coordinates. Thirdly, the spatial clustering was achieved by two-step cluster algorithm to adapt to different clustering variables. Result schemes were evaluated through three quantitative indexes: project quantity, elevation range and shape index. The comparison of empirical and spatial clustering partition schemes both with 9 partitions shows that: the scheme using clustering method save 24% project quantity and 11% elevation range; the shape index of the scheme using empirical method was 11% lower than the scheme using clustering method. The empirical method balances the influence of various factors and its partitions get more regular shape, but it lacks the consideration of project quantity. In the clustering method, the project quantity and elevation range can be significantly reduced due to the consideration of elevation. Although the factors of road and land ownership are also considered in the clustering method, they only have limited impacts on the shape of partition boundaries. Various partition schemes using spatial clustering method were obtained by adjusting the number of clusters. The output of each partition scheme included partition number, partition distribution and evaluation indexes. The comparison of spatial clustering partition schemes with different numbers of partitions shows that with the increasing of number of partitions, the project quantity gradually reduced, the elevation range increased; the shape index decreased, the partition patches became smaller and regularized, and the complexity of partition border were reduced. The comprehensive evaluation index was calculated by weighted average of these three indicators, and the three corresponding weights were 0.47, 0.37 and 0.16 that were calculated by Analytic Hierarchy Process in this paper. The comprehensive index declines rapidly at first then slowly increase with number of partitions. When number of partitions is 7, the minimum value of comprehensive index appears, which means the partition scheme has the best performance overall. To sum up, using spatial clustering method to partitioning the leveling area can effectively reduce the project quantity and improve the flatness after land consolidation, which are beneficial to reducing investment and can satisfy the future needs of agricultural production. However, the clustering method performs less rational than empirical method in aspect of the regularity and distribution patterns. Therefore, in practice, the clustering scheme could be used as the preliminary foundation, and then the scheme can be adjusted depending on experts experience to give full play to advantages of both methods.
中文关键词	土地利用 ; 整治 ; 分区 ; 空间聚类 ; 土地平整 ; 平整单元区
英文关键词	land use consolidation zoning spatial clustering land leveling leveling unit
语种	中文
国家	中国
收录类别	CSCD
WOS类目	AGRICULTURAL ECONOMICS POLICY
WOS研究方向	Agriculture
CSCD记录号	CSCD:5395368
来源机构	北京林业大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/233019
作者单位	1.北京林业大学, 国家农业信息化工程技术研究中心;;农业部农业信息技术重点实验室;;北京市农业物联网工程技术研究中心, 北京 100083, 中国; 2.国家农业信息化工程技术研究中心, 国家农业信息化工程技术研究中心;;农业部农业信息技术重点实验室;;北京市农业物联网工程技术研究中心, 北京 100097, 中国
推荐引用方式 GB/T 7714	郝星耀,潘瑜春,唐秀美,等. 基于空间聚类的平原旱作农区土地平整单元区划分方法[J]. 北京林业大学,2015,31(5):301-307.
APA	郝星耀,潘瑜春,唐秀美,邱贺,刘玉,&任艳敏.(2015).基于空间聚类的平原旱作农区土地平整单元区划分方法.农业工程学报,31(5),301-307.
MLA	郝星耀,et al."基于空间聚类的平原旱作农区土地平整单元区划分方法".农业工程学报 31.5(2015):301-307.