永久基本农田保护片区智能识别系统iZone的建立与应用

永久基本农田划定是当前国土资源管理一项十分重要而紧迫的任务,其对维护粮食安全和控制城镇无序增长具有重要意义。永久基本农田划定不仅要满足耕地质量较高而且还要集中连片,更需要协调城镇化矛盾。因此,如何从土地利用现状数据库中提取永久基本农田保护图斑实际上是一个复杂的空间数据挖掘过程。研究利用农用地分等成果定义保护片区质量,利用元胞自动机模拟分析土地利用矛盾,利用种子扩充算法进行保护片区搜索,利用神经网络进行耕地保护压力预警。基于C#和Arc Engine10.1将多种空间数据挖掘模型进行集成,构成了面向全域永久基本农田识别的智能系统工具包iZone,并在广东省高要区金利镇进行实例应用。研究表明,iZ...

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Published in农业工程学报 Vol. 33; no. 2; pp. 276 - 282
Main Author 马世发 吴楷钊 劳春华 钟远军 张婷 黄韬
Format Journal Article
LanguageChinese
Published 广东省国土资源技术中心,广州,510075%广东工业大学管理学院,广州,510520 2017
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ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2017.02.038

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Summary:永久基本农田划定是当前国土资源管理一项十分重要而紧迫的任务,其对维护粮食安全和控制城镇无序增长具有重要意义。永久基本农田划定不仅要满足耕地质量较高而且还要集中连片,更需要协调城镇化矛盾。因此,如何从土地利用现状数据库中提取永久基本农田保护图斑实际上是一个复杂的空间数据挖掘过程。研究利用农用地分等成果定义保护片区质量,利用元胞自动机模拟分析土地利用矛盾,利用种子扩充算法进行保护片区搜索,利用神经网络进行耕地保护压力预警。基于C#和Arc Engine10.1将多种空间数据挖掘模型进行集成,构成了面向全域永久基本农田识别的智能系统工具包iZone,并在广东省高要区金利镇进行实例应用。研究表明,iZone能按既定规则从土地利用现状数据库中提取保护图斑,有效避免了人为划定的过多主观性,并且能获得与人工方案相当乃至更好的表现。iZone利用复杂地理计算技术进行永久基本农田智能识别,可提高永久基本农田划定工作的科学性。
Bibliography:11-2047/S
Ma Shifa1, Wu Kaizhao1, Lao Chunhua2, Zhong Yuanjun1, Zhang Ting1, Huang Tao1 (1. Land and Resources Technology Center of Guangdong Province, Guangzhou, 510075, China; 2. School of Management Guangdong University of Technology, Guangzhou, 510520, China)
China has fed about 20% of the world population with only 8% of the world land. Actually, the proportion of arable land is much lower than 8% because most of the land is unavailable for agriculture activity, such as mountains, deserts and so on. Since the reform and opening-up policy was proposed in 1978, China has undergone rapid urbanization, which has become a great threat to food security. In this case, Chinese government proposed a new policy about protection of permanent basic farmland in response to the increasing urban growth. It is important and urgent to zone the permanent farmland for restraining the pell-mell urban expansion and improving the protective efficiency, which is of great significance to food security for China. Whether the basic
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2017.02.038