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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Copernicus Publications
2021-08-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-4-W2-2021/119/2021/isprs-archives-XLVI-4-W2-2021-119-2021.pdf |
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doaj-3d7ffc897f4448b397a2c8d1fad1b5312021-08-23T07:04:23ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342021-08-01XLVI-4-W2-202111912210.5194/isprs-archives-XLVI-4-W2-2021-119-2021APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCEC. A. Paiva0R. G. Campos1S. P. Camboim2Geodetic Science Graduate Program, Department of Geomatics, Federal University of Parana, Curitiba 81531970, BrazilGeodetic Science Graduate Program, Department of Geomatics, Federal University of Parana, Curitiba 81531970, BrazilGeodetic Science Graduate Program, Department of Geomatics, Federal University of Parana, Curitiba 81531970, BrazilThe 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.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-4-W2-2021/119/2021/isprs-archives-XLVI-4-W2-2021-119-2021.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
C. A. Paiva R. G. Campos S. P. Camboim |
spellingShingle |
C. A. Paiva R. G. Campos S. P. Camboim APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCE The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
C. A. Paiva R. G. Campos S. P. Camboim |
author_sort |
C. A. Paiva |
title |
APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCE |
title_short |
APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCE |
title_full |
APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCE |
title_fullStr |
APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCE |
title_full_unstemmed |
APPLICATION FOR MEASURING REPRESENTATIVE VARIABLES OF COLLECTIVE SPACE INTELLIGENCE |
title_sort |
application for measuring representative variables of collective space intelligence |
publisher |
Copernicus Publications |
series |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
1682-1750 2194-9034 |
publishDate |
2021-08-01 |
description |
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. |
url |
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-4-W2-2021/119/2021/isprs-archives-XLVI-4-W2-2021-119-2021.pdf |
work_keys_str_mv |
AT capaiva applicationformeasuringrepresentativevariablesofcollectivespaceintelligence AT rgcampos applicationformeasuringrepresentativevariablesofcollectivespaceintelligence AT spcamboim applicationformeasuringrepresentativevariablesofcollectivespaceintelligence |
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1721198736634281984 |