Geomatics and Information Science of Wuhan University. 2014, (04) Core

Methods of Crowd Sourcing Geographic Data Processing and AnalysisChinese Full Text

SHAN Jie;QIN Kun;HUANG Changqing;HU Xiangyun;YU Yang;HU Qingwu;LIN Zhiyong;CHEN Jiangping;JIA Tao;School of Remote Sensing and Information Engineering,Wuhan University;School of Civil Engineering,Purdue University;

Abstract: Crowd sourcing geographic data（CSGD）is a new kind of open geospatial data collected and provided to citizens or organizations by non-professional volunteers.Its acquisition differs from conventional methods of surveying and mapping.It has the characteristics of being up-to-date,informative,low cost,and large size.Unique issues of such data are its heterogeneous data quality,redundancy and incompleteness,uneven data coverage,absence of data standards,privacy and safety,etc. It can be employed in a wide range of application fields including emergency cartography,early warning,map and database updating,crime analysis,and epidemiologic studies.Thus,it is important to systematically investigate the key aspects regarding its processing and analysis.The paper reviews the progress and challenges of CSGD processing and analysis.Firstly,the paper summarizes the concept and characteristics of CSGD.Secondly,the paper introduces the acquisition methods and potential data sources of CSGD.Thirdly,the paper discusses some key methods and techniques on the processing and analysis of CSGD,which includes data quality metrics,information extraction and updating,spatial data analysis and mining.Specifically,the paper suggests that firstly data evaluation is a critical prerequisite for CSGD research and application,secondly information extraction and updating via CSGD can complement the conventional methods of geographic database updating,and finally spatial data analysis and mining on CSGD can provide valuable information and knowledge for potential applications using methods like network topological analysis,spatial statistical analysis,and spatial data mining.Lastly,the paper draws some conclusions on the state-of-the-art of CSGD processing and analysis and points out the future research directions.

Keywords：

crowd sourcing geospatial data（CSGD）; quality analysis and evaluation; information ex-traction and updating; spatial analysis; spatial data mining; geographical information service;

DOI：
10.13203/j.whugis20130633
Series：
Subject：
Classification Code：
P208

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Methods of Crowd Sourcing Geographic Data Processing and AnalysisChinese Full Text

SHAN Jie;QIN Kun;HUANG Changqing;HU Xiangyun;YU Yang;HU Qingwu;LIN Zhiyong;CHEN Jiangping;JIA Tao;School of Remote Sensing and Information Engineering,Wuhan University;School of Civil Engineering,Purdue University;

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