摘要
为提升高标准农田监管效能,该文基于空间分异规律,依据相关标准和规划,构建了差别化的高标准农田建设空间特征判别指标体系,在此基础上,使用C#.NET、ArcObject技术,设计和实现了高标准农田建设空间特征判别系统。系统的实证案例表明:用于监测评价场景的黄土高原案例区符合高标准农田空间特征的田块38.33 hm^2,与验收后实际确认的高标准农田相比,总体判别精度为94.38%。2)用于设计评审场景的南方山地丘陵案例区符合高标准农田空间特征的30.07 hm^2,较批复立项的高标准农田多10.34 hm^2,造成该差异的主要因素是部分田块尚未划定为永久基本农田,如扣除永久基本农田划定因素,总体判别精度为100%。从实例结果看,使用该系统可从空间特征方面辅助判别高标准农田,分析高标准农田建设在田块平整、道路和灌排设施配套、农田防护方面的不足,为丰富高标准农田监测手段、提升管理效能提供参考。
Rational construction of a well-facilitated farmland become necessary for food security and modern agriculture in China. In farmland construction, the automatic management of spatial data can benefit to accurately distinguish wellfacilitated farmland from the various land types. Various discriminating ways of well-facilitated farmland are adopted due to the different influence factors of agricultural productionin in different regions, where the spatial distribution and structural features of well-facilitated farmland are quite different from place to place across the country. Most of the previous studies focus mainly on policies, benefit evaluation, preliminary planning and design in the well-facilitated farmland construction.There is still lacking on the studies of the discrimination and analysis for the regional structural features of the well-facilitated farmland. In this paper, a framework of an index system was constructed to identify the spatial distribution and structural features of the well-facilitated farmland using the law of spatial differentiation together with the related national standards and strategic planning, ranging from the scale and shape of farmlands, irrigation and drainage facilities, traffic accessibility, and farmland protection ratio. The identifying system was designed on the basis of the index framework with C#. NET and Arc Object. Subsequently, the proposed system was verified for its availability by taking a case study of a LoessPlateau and a southern mountainous region. The results were as follows:(1) In the Loess Plateau area, the standard rate of the farmland scale, farmland shape, irrigation and drainage facilities, traffic accessibility was 87.01%, 83.12%, 80.52%, 90.91% and83.12%, respectively. The well-facilitated farmlandarea can be identified by the system was 38.33 hm^2 with the total discriminating precision was 94.38%. There were some farmlands that did not meet the requirements of the well-facilitated farmland, such as incomplete irrigation and drainage facilities, the
作者
李少帅
郧文聚
张燕
杨剑
曹文静
李红举
陈元鹏
Li Shaoshuai;Yun Wenju;Zhang Yan;Yang Jian;Cao Wenjing;Li Hongju;Chen Yuanpeng(China University of Geosciences(Beijing),School of Land Science and Technology,Beijing 100083,China;Land Consolidation and Rehabilitation Center,Ministry of Natural Resources,Beijing 100035,China;Center of Engineering and Construction Service,Ministry of Agriculture and Rural Affairs,Beijing 100081,China;Center for Assessment and Development of Real Estate,Shenzhen 518040,China)
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2020年第6期253-261,共9页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家重点研发计划(NQI)项目(2017YFF0206800)
自然资源部土地整治重点实验室开放课题(2018-KF-04)。
关键词
土地利用
农村
空间分异
高标准农田
空间特征判别
系统设计
land use
rural area
spatial differentiation
well-facilitated farmland
spatial features discrimination
system design
