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Quantifying uncertainty in remote sensing-based urban land-use mapping

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MONTE-CARLO-SIMULATION, SPECTRAL MIXTURE ANALYSIS, IMPERVIOUS SURFACES, SENSITIVITY ANALYSIS, ERROR PROPAGATION, SENSED DATA, CLASSIFICATION, COVER, IMAGERY, AREAS, Uncertainty, Land-use mapping, Urban remote sensing, Image, classification, Spectral unmixing, Monte Carlo simulation

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Citation

Please use this url to cite or link to this publication:

MLA
Cockx, Kasper, et al. “Quantifying Uncertainty in Remote Sensing-Based Urban Land-Use Mapping.” INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, vol. 31, 2014, pp. 154–66.
APA
Cockx, K., Van de Voorde, T., & Canters, F. (2014). Quantifying uncertainty in remote sensing-based urban land-use mapping. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 31, 154–166.
Chicago author-date
Cockx, Kasper, Tim Van de Voorde, and Frank Canters. 2014. “Quantifying Uncertainty in Remote Sensing-Based Urban Land-Use Mapping.” INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 31: 154–66.
Chicago author-date (all authors)
Cockx, Kasper, Tim Van de Voorde, and Frank Canters. 2014. “Quantifying Uncertainty in Remote Sensing-Based Urban Land-Use Mapping.” INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 31: 154–166.
Vancouver
1.
Cockx K, Van de Voorde T, Canters F. Quantifying uncertainty in remote sensing-based urban land-use mapping. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION. 2014;31:154–66.
IEEE
[1]
K. Cockx, T. Van de Voorde, and F. Canters, “Quantifying uncertainty in remote sensing-based urban land-use mapping,” INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, vol. 31, pp. 154–166, 2014.
@article{8645336,
  author       = {Cockx, Kasper and Van de Voorde, Tim and Canters, Frank},
  issn         = {0303-2434},
  journal      = {INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION},
  keywords     = {MONTE-CARLO-SIMULATION,SPECTRAL MIXTURE ANALYSIS,IMPERVIOUS SURFACES,SENSITIVITY ANALYSIS,ERROR PROPAGATION,SENSED DATA,CLASSIFICATION,COVER,IMAGERY,AREAS,Uncertainty,Land-use mapping,Urban remote sensing,Image,classification,Spectral unmixing,Monte Carlo simulation},
  language     = {eng},
  pages        = {154--166},
  title        = {Quantifying uncertainty in remote sensing-based urban land-use mapping},
  url          = {http://dx.doi.org/10.1016/j.jag.2014.03.016},
  volume       = {31},
  year         = {2014},
}

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