APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCE

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 officia...

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Bibliographic Details
Main Authors: Paiva, C. A., Campos, R. G., Camboim, S. P.
Format: Conference Proceeding
Language:English
Subjects:
Developing countries
Intelligence
LDCs
Parameters
Spatial data
Online Access:Get full text
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Summary: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.
ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprs-archives-XLVI-4-W2-2021-119-2021