Paper
28 October 2006 Spatial data quality concerns for field data collection in mobile GIS
F. Wang, W. Reinhardt
Author Affiliations +
Proceedings Volume 6420, Geoinformatics 2006: Geospatial Information Science; 64201C (2006) https://doi.org/10.1117/12.712733
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China
Abstract
In the domain of GIS, large amounts of geographic data are increasingly shared, interchanged and analyzed in many different applications. Mobile GIS technologies bring lots of advantages for field survey and the datasets acquired by field based data collection in Mobile GIS are often employed for many purposes. Therefore, to ensure the quality of the collected datasets and tell the data users information about how reliable the datasets are, more concerns have to be contributed to spatial data quality issues. This paper will describe the open architecture of field based Mobile GIS and show the importance of spatial data quality issues. Then it explains how the spatial data quality concerns are considered for Mobile GIS aligning with international standards in geoinformatics, like ISO and OGC standards. Geographic data modeling with emphasis of spatial integrity constraints will be introduced here. In order that field users can simultaneously receive the warning of errors when they are entering the data in the field and correct them through seeing the reality, the data quality assurance work should be seamlessly integrated into the Mobile GIS. Therewith, the method of applying the spatial integrity constraints into the data collection work will also be explained.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
F. Wang and W. Reinhardt "Spatial data quality concerns for field data collection in mobile GIS", Proc. SPIE 6420, Geoinformatics 2006: Geospatial Information Science, 64201C (28 October 2006); https://doi.org/10.1117/12.712733
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Geographic information systems

Data modeling

Standards development

Databases

Data acquisition

Process modeling

Geoinformatics

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