Error matching detection and robust estimation adjustment approach for map conflation

作     者：TONG XiaoHua & DENG SuSu Department of Surveying and Geo-informatics,Tongji University,Shanghai 200092,China 

作者机构：Tongji Univ Dept Surveying & Geoinfromat Shanghai 200092 Peoples R China 

出 版 物：《Science China(Technological Sciences)》 (中国科学（技术科学英文版）)

年 卷 期：2008年第51卷第S1期

页      面：48-61页

核心收录：

学科分类：080202[工学-机械电子工程] 08[工学] 0802[工学-机械工程] 

基　　金：the National Natural Science Foundation of China (Grant Nos. 40771174 and 40301043) the Doctoral Program of Higher Education of China (Grant No. 20070247046) the Program for ShuGuang Scholarship of Shanghai (Grant No. 07SG24) Foundation of Shanghai Ris-ing-Star Program (Grant No. 05QMX1456) 

主　　题：map conflation robust estimation error feature matching uncertainty 

摘      要：The conflation of geographic datasets is one of the key technologies in the realm of spatial data capture and integration in geographic information system (GIS). Map conflation is a complex process of matching and merging spatial data. Due to various reasons such as errors in original data related to map data discrepancies,a great amount of uncertainties exists during the process and this will result in errors in featuring matching,especially point feature. Thus,it is vital to develop the method to detect the errors in feature matching and further the conflation results will not be affected. In this paper,error matching detection and robust estimation adjustment methods are proposed for map conflation. The characteristics of errors in feature matching are first analyzed,then a new approach for map conflation based on the least-squares adjustment is presented,and a robust estimation adjustment method is further proposed to detect and process matching errors. The results of the map conflation test show that the proposed method not only determines the errors in feature matching,but also obtains the optimal merging results in map conflation.