基于GNSS轨迹大数据的测绘质量监管关键技术研究  

Research on Key Technologies of Surveying and Mapping Quality Supervision Based on GNSS Trajectory Big Data

作　　者：唐辉 何宗 王岚 袁烽迪 唐亚洲 张成宁 TANG Hui;HE Zong;WANG Lan;YUAN Fengdi;TANG Yazhou;ZHANG Chengning(Chongqing Geomatics and Remote Sensing Center,Chongqing 401147,China)

机构地区：[1]重庆市地理信息和遥感应用中心,重庆401147

出　　处：《地理空间信息》2025年第2期90-93,共4页Geospatial Information

摘　　要：为提升测绘质量监管工作的主动性,提出了一种基于GNSS轨迹大数据的测绘质量监管方法,具体步骤为:首先对已监管的测绘项目范围进行坐标转换和信息融合形成监管现状“一张图”,再通过聚类算法对测绘单位测绘活动产生的GNSS轨迹点按名称属性和空间位置进行聚类,模拟测绘项目实际作业区域“分布图”,然后将现状“一张图”与模拟“分布图”进行叠加分析,得到各区域测绘项目的监管水平,从而发现监管的薄弱区域。该方法有效解决了因测绘单位漏报瞒报、择优报送等造成的项目信息难以获取的问题,通过模拟测绘作业的真实分布和分析被监管项目的占比,主动发现监管的薄弱环节,有效提升了测绘质量主动监管的能力。To enhance the initiative of surveying and mapping quality supervision,we proposed a surveying and mapping quality supervision method based on GNSS trajectory big data.Firstly,we carried out coordinate transformation and information fusion on the projects that had al-ready been supervised and managed to form a“one map”of regulatory status.Then,we classified GNSS trajectory points according to their name attribute and spatial positions using clustering algorithm,and simulated the actual operation area“distribution map”of surveying and map-ping projects.Finally,we overlay analyze the simulated“distribution map”with the current“one map”to obtain the regulatory level of survey-ing and mapping projects in each district and county,discovering weak areas of regulation.This method effectively solves the problem that diffi-cult to obtain the complete information caused by omissions,concealment,and selective reporting those submitted by surveying and mapping units.By simulating the real distribution of surveying and mapping operations and analyzing the proportion of supervised projects,it proactively identifies weak links in supervision and effectively enhances the proactive ability of quality supervision.

关 键 词：GNSS轨迹大数据 测绘质量 聚类算法 主动监管 

分 类 号：P205[天文地球—测绘科学与技术]