摘要
自然资源调查监测体系构建是实现山水林田湖草沙等自然资源统一监管的必由之路,难点在于多种调查监测体系的地类融合。针对该问题,本文以全域全覆盖的第三次国土调查和地理国情监测数据为例,建立两类数据间交叉矩阵,从语义关联关系和统计关联关系两个角度入手量化不同标准下相似地类的空间关联度;根据关联度差异,将地类间对应关系分为强对应、基本对应、无对应等三种类型,结合差异原因确定地类采用不同的融合方法。以济南市为试验区开展探索与实践,验证了本方法的科学性和可行性,建立了两类数据逐步融合的切实可行的技术路线,为自然资源协同调查监测体系构建提供了有力的支撑。
The construction of natural resources investigation and monitoring system is the only way to realize the unified supervision of natural resources such as mountains,rivers,forests,lakes,grass and sand.The difficulty lies in the land type integration of a variety of investigation and monitoring data.To solve this problem,this paper takes the Third National Land Resource Survey and geographical national condition monitoring data as an example,establishes the cross matrix between the two types of data,and quantifies the spatial correlation degree between similar land types under different standards from the perspectives of semantic correlation and statistical correlation.According to the difference of correlation,the correspondence between land types is divided into three types:strong correspondence,basic correspondence and no correspondence.According to this,different integration methods such as map spot level fusion,statistical convergence and application convergence are chosen.Taking Jinan as the experimental area,the method is proved to be scientific and feasible.The study provides a practical technical route for the gradual integration of the two types of data,and also supplies a strong support for the construction of the collaborative investigation and monitoring system of natural resources.
作者
江娜
郭永亮
祁玉涛
凌晓春
Jiang Na;Guo Yongliang;Qi Yutao;Ling Xiaochun(Shandong Provincial Institute of Land Surveying and Mapping,Jinan 250013,China;Rushan Marine and Fishery Supervision Brigade,Weihai 264500,China;Jinan Instiute of Surveying and Mapping,Jinan 250101,China)
出处
《工程勘察》
2022年第8期63-68,78,共7页
Geotechnical Investigation & Surveying
基金
山东省重点研发计划(2019JZZY020103)
山东省国土测绘院科研项目(SDCHKY-2021-0202).
关键词
国土三调
地理国情
语义关联
统计关联
the Third National Land Resource Survey
geographical national condition
semantic association
statistical association
