Education, Science, Technology, Innovation and Life
Open Access
Sign In

Reviewing Methods for Controlling Spatial Data Quality from Multiple Perspectives

Download as PDF

DOI: 10.23977/geors.2022.050104 | Downloads: 6 | Views: 609


Danling Chen 1


1 Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China

Corresponding Author

Danling Chen


Spatial data is the core and operation object of geographic information system (GIS). The quality of spatial data determines the application of GIS and the effectiveness of decision-making to a great extent. This article introduces two important types of spatial data, vector data and raster data. Then, this paper discusses the uncertainty and sources of errors in spatial data, and discusses the methods of checking and preventing uncertainty and errors from the aspects and processes of digitization, so as to ensure the quality of spatial data. Finally, this paper explores cutting-edge approaches to improving spatial data quality, including the Area preserving method for improved categorical raster resampling, and using hierarchical grid index to detect and correct errors in vector elevation data. By studying effective data quality control methods, the quality of spatial data in GIS can be guaranteed, and the basic guarantee for the wide application and development of geographic information science can be provided.


Spatial Data, Geographic Information System, Uncertainty, Error, GIS


Danling Chen, Reviewing Methods for Controlling Spatial Data Quality from Multiple Perspectives. Geoscience and Remote Sensing (2022) Vol. 5: 22-27. DOI:


[1] Carver, S. J., & Brunsdon, C. F. Vector to raster conversion error and feature complexity: an empirical study using simulated data. International Journal of Geographical Information Systems, 1994, 8(3), 261-270. 10.1080/02693799408901999 
[2] Couclelis, H. The certainty of uncertainty: GIS and the limits of geographic knowledge. Transactions in GIS, 2003, 7(2), 165-175. 
[3] Piwowar, J. M., Ledrew, E. F., & Dudycha, D. J. Integration of spatial data in vector and raster formats in a geographic information system environment. International Journal of Geographical Information Systems, 1990, 4(4), 429-444. 
[4] Peuquet, D. Vector/raster options for digital cartographic data. (1983). 
[5] Kwang-Soo, K., Min-Soo, K., & Kiwon, L. On integrated scheme for vector/raster-based GIS's utilization. IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development, (3-8 Aug. 1997). 
[6] Jian-Jun, C., Cheng-Hu, Z., & Wei-Ming, C. Area error analysis of vector to raster conversion of areal feature in GIS. (2007). 
[7] Oberkampf, W. L., DeLand, S. M., Rutherford, B. M. Error and uncertainty in modeling and simulation. Reliability Engineering & System Safety, (2002). 75(3), 333-357. 10.1016/ S0951-8320(01)00120-X 
[8] Messina, J. P., Evans, T. P., Manson, S. M., Shortridge, A. M., Deadman, P. J., & Verburg, P. H. Complex systems models and the management of error and uncertainty. Journal of Land Use Science, (2008). 3(1), 11-25. 10.1080/17474230802047989 
[9] Wang, G., Gertner, G. Z., Fang, S., & Anderson, A. B. A methodology for spatial uncertainty analysis of remote sensing and GIS products. Photogrammetric Engineering & Remote Sensing, (2005). 71(12), 1423-1432. 
[10] Sun Qing-hui, C. T.-h., Zhao Jun-xi, Zhong Da-wei, Shao Shi-xin. Errors and Uncertainties Analysis of Spatial Data Processing Model. (2007). 
[11] Li Nan, Z. J. Error Analysis and Quality Control of Spatial Data. (2017). 
[12] Li, D., Zhang, J., & Wu, H. Spatial data quality and beyond. International Journal of Geographical Information Science, (2012). 26(12), 2277-2290. 
[13] Yongling, W. (2001). Analysis of Error Sources in Spatial Data and Discussion on Quality Control. 
[14] Johnson, J. M., & Clarke, K. C. An area preserving method for improved categorical raster resampling. Cartography and Geographic Information Science, (2021). 48(4), 292-304.
[15] Kangning, L. Research on error recognition and correction of vector elevation data based on hierarchical grid index. (2021). 

Downloads: 499
Visits: 52230

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.