2005
DOI: 10.1559/152304005775194827
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Exploring the Hidden Potential of Common Spatial Data Models to Visualize Uncertainty

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Cited by 4 publications
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“…where: Kardos, Moore, and Benwell (2005) identified three types of uncertainty: attribute uncertainty, which applies to differences existing between the semantic characteristic of a feature and the corresponding data stored; spatial uncertainty, which relates to differences between the actual physical position of a feature and the corresponding data stored; and temporal uncertainty, referring to the time difference between data acquisition and data utilization. Based on a previous study (Manzano-Agugliaro et al, 2013), settlements with lineal error higher than 20 km can be considered as uncertain, and they are removed for further analysis.…”
Section: Methodsmentioning
confidence: 99%
“…where: Kardos, Moore, and Benwell (2005) identified three types of uncertainty: attribute uncertainty, which applies to differences existing between the semantic characteristic of a feature and the corresponding data stored; spatial uncertainty, which relates to differences between the actual physical position of a feature and the corresponding data stored; and temporal uncertainty, referring to the time difference between data acquisition and data utilization. Based on a previous study (Manzano-Agugliaro et al, 2013), settlements with lineal error higher than 20 km can be considered as uncertain, and they are removed for further analysis.…”
Section: Methodsmentioning
confidence: 99%