Ghent University Academic Bibliography

Advanced

Random forests as a tool for estimating uncertainty at pixel-level in SAR image classification

Lien Loosvelt UGent, Jan Peters UGent, Henning Skriver, Hans Lievens UGent, Frieke Vancoillie UGent, Bernard De Baets UGent and Niko Verhoest UGent (2012) INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION. 19. p.173-184
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
Random Forests, Synthetic aperture radar (SAR), Multi-frequency, Multi-date, Land cover, Crop classification, Model uncertainty, Prediction probability, Data fusion, Entropy, LAND-COVER CLASSIFICATION, REMOTE-SENSING DATA, POLARIMETRIC SAR, UNSUPERVISED CLASSIFICATION, DISTRIBUTION MODELS, AGRICULTURAL CROPS, CATEGORICAL-DATA, NEURAL-NETWORK, RADAR DATA, ERROR
journal title
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
Int. J. Appl. Earth Obs. Geoinf.
volume
19
pages
173 - 184
Web of Science type
Article
Web of Science id
000309028500015
JCR category
REMOTE SENSING
JCR impact factor
2.176 (2012)
JCR rank
6/26 (2012)
JCR quartile
1 (2012)
ISSN
0303-2434
DOI
10.1016/j.jag.2012.05.011
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
2974967
handle
http://hdl.handle.net/1854/LU-2974967
date created
2012-08-27 09:44:19
date last changed
2013-07-12 13:36:29
@article{2974967,
  author       = {Loosvelt, Lien and Peters, Jan and Skriver, Henning and Lievens, Hans and Vancoillie, Frieke and De Baets, Bernard and Verhoest, Niko},
  issn         = {0303-2434},
  journal      = {INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION},
  keyword      = {Random Forests,Synthetic aperture radar (SAR),Multi-frequency,Multi-date,Land cover,Crop classification,Model uncertainty,Prediction probability,Data fusion,Entropy,LAND-COVER CLASSIFICATION,REMOTE-SENSING DATA,POLARIMETRIC SAR,UNSUPERVISED CLASSIFICATION,DISTRIBUTION MODELS,AGRICULTURAL CROPS,CATEGORICAL-DATA,NEURAL-NETWORK,RADAR DATA,ERROR},
  language     = {eng},
  pages        = {173--184},
  title        = {Random forests as a tool for estimating uncertainty at pixel-level in SAR image classification},
  url          = {http://dx.doi.org/10.1016/j.jag.2012.05.011},
  volume       = {19},
  year         = {2012},
}

Chicago
Loosvelt, Lien, Jan Peters, Henning Skriver, Hans Lievens, Friedl Vancoillie, Bernard De Baets, and Niko Verhoest. 2012. “Random Forests as a Tool for Estimating Uncertainty at Pixel-level in SAR Image Classification.” International Journal of Applied Earth Observation and Geoinformation 19: 173–184.
APA
Loosvelt, L., Peters, J., Skriver, H., Lievens, H., Vancoillie, F., De Baets, B., & Verhoest, N. (2012). Random forests as a tool for estimating uncertainty at pixel-level in SAR image classification. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 19, 173–184.
Vancouver
1.
Loosvelt L, Peters J, Skriver H, Lievens H, Vancoillie F, De Baets B, et al. Random forests as a tool for estimating uncertainty at pixel-level in SAR image classification. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION. 2012;19:173–84.
MLA
Loosvelt, Lien, Jan Peters, Henning Skriver, et al. “Random Forests as a Tool for Estimating Uncertainty at Pixel-level in SAR Image Classification.” INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 19 (2012): 173–184. Print.