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Description
  • Digital elevation models (DEM) are models that approximate a topographical surface. These models will contain both random and systematic errors that create uncertainty, or unreliability, in elevation measurements. Uncertainty can be defined as a lack of knowledge about the reliability of a measurement, whereas error is the departure of a measurement from its true value. This error is hardly quantifiable very often and is defined as the difference between reality and a representation of reality. In the other hand, quantifying data uncertainty is an important part of spatial analysis, and researchers are still developing methods to assess, describe and reduce random and systematic DEM uncertainty. The common methods used for the assessment of the accuracy of digital elevation models - DEMs (like root mean square error or mean absolute error) are only global non-spatial measures. Their unquestionable advantages are their easy calculation and interpretation. However, as to environmental applications, the knowledge of spatial error variability is very important. Many authors claim that the extent of errors in a DEM depends on a character of a terrain and is spatially variable. The attempts to express the magnitude of error in a space led to the emergence of different methods for spatial visualization of DEM accuracy. Visualizations bring quick and easy method how to be informed about precision of the model and how to understand the nature of the data. The uncertainty has to be also incorporate for deeper understanding of the model in the light of the previous statement. Several visualization techniques for portrayal uncertainty in DEM have been developed, but there is a gap between transferring knowledge between researchers and final users due to lack of knowledge about the effectiveness of these visualizations. An approach incorporating effectiveness of uncertainty visualization on the decision making processes is still missing.
  • Digital elevation models (DEM) are models that approximate a topographical surface. These models will contain both random and systematic errors that create uncertainty, or unreliability, in elevation measurements. Uncertainty can be defined as a lack of knowledge about the reliability of a measurement, whereas error is the departure of a measurement from its true value. This error is hardly quantifiable very often and is defined as the difference between reality and a representation of reality. In the other hand, quantifying data uncertainty is an important part of spatial analysis, and researchers are still developing methods to assess, describe and reduce random and systematic DEM uncertainty. The common methods used for the assessment of the accuracy of digital elevation models - DEMs (like root mean square error or mean absolute error) are only global non-spatial measures. Their unquestionable advantages are their easy calculation and interpretation. However, as to environmental applications, the knowledge of spatial error variability is very important. Many authors claim that the extent of errors in a DEM depends on a character of a terrain and is spatially variable. The attempts to express the magnitude of error in a space led to the emergence of different methods for spatial visualization of DEM accuracy. Visualizations bring quick and easy method how to be informed about precision of the model and how to understand the nature of the data. The uncertainty has to be also incorporate for deeper understanding of the model in the light of the previous statement. Several visualization techniques for portrayal uncertainty in DEM have been developed, but there is a gap between transferring knowledge between researchers and final users due to lack of knowledge about the effectiveness of these visualizations. An approach incorporating effectiveness of uncertainty visualization on the decision making processes is still missing. (en)
Title
  • The spatial expression of an uncertainty for the quality assessment of the digital elevation models
  • The spatial expression of an uncertainty for the quality assessment of the digital elevation models (en)
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  • The spatial expression of an uncertainty for the quality assessment of the digital elevation models
  • The spatial expression of an uncertainty for the quality assessment of the digital elevation models (en)
skos:notation
  • RIV/61989592:15310/12:33143220!RIV13-MSM-15310___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
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  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 170178
http://linked.open...ai/riv/idVysledku
  • RIV/61989592:15310/12:33143220
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • quality assessment; DEM; spatial visualization; error; uncertainty (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [13194EFAC04A]
http://linked.open...v/mistoKonaniAkce
  • Albena, Bulgaria
http://linked.open...i/riv/mistoVydani
  • Sofia
http://linked.open...i/riv/nazevZdroje
  • Conference proceedings 12th International Multidisciplinary Scientific GeoConference, Volume II
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Brus, Jan
  • Svobodová, Jana
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 1314-2704
number of pages
http://bibframe.org/vocab/doi
  • 10.5593/SGEM2012/S11.V3010
http://purl.org/ne...btex#hasPublisher
  • STEF92 Technology Ltd.
https://schema.org/isbn
  • 978-954-91818-3-8
http://localhost/t...ganizacniJednotka
  • 15310
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