The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-4/W2-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W2-2021, 119–122, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-119-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W2-2021, 119–122, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W2-2021-119-2021

  19 Aug 2021

19 Aug 2021

APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCE

C. A. Paiva, R. G. Campos, and S. P. Camboim C. A. Paiva et al.
  • Geodetic Science Graduate Program, Department of Geomatics, Federal University of Parana, Curitiba 81531970, Brazil

Keywords: Collective Space Intelligence, Geospatial Data Quality, OpenStreetMap

Abstract. The scarcity of metrics for analysing the quality of Voluntary Geographic Information without direct comparisons with reference data makes it impossible to use this information in many areas of society. Especially in developing countries, where collaborative data can help fill the deficit of official data, studies on intrinsic parameters of quality become an alternative to conventional comparative methods for evaluating spatial data. A recurring parameter in related research is Collective Spatial Intelligence. Seeking to offer researchers on the subject a tool capable of measuring the Collective Spatial Intelligence in predefined areas, we developed a Python application that counts representative values of this intelligence in political-administrative limits. Considering that, in general, the quality of spatial data is inferred on these limits, research that seeks to explain the VGI quality without using official data as a reference can be facilitated.