Random forests as a tool for estimating uncertainty at pixel-level in SAR image classification
- Author
- Lien Loosvelt (UGent) , Jan Peters (UGent) , Henning Skriver, Hans Lievens (UGent) , Frieke Vancoillie (UGent) , Bernard De Baets (UGent) and Niko Verhoest (UGent)
- Organization
- Keywords
- 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
Downloads
-
(...).pdf
- full text
- |
- UGent only
- |
- |
- 1.04 MB
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-2974967
- MLA
- Loosvelt, Lien, 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, vol. 19, 2012, pp. 173–84, doi:10.1016/j.jag.2012.05.011.
- 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. https://doi.org/10.1016/j.jag.2012.05.011
- Chicago author-date
- Loosvelt, Lien, Jan Peters, Henning Skriver, Hans Lievens, Frieke 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: 173–84. https://doi.org/10.1016/j.jag.2012.05.011.
- Chicago author-date (all authors)
- Loosvelt, Lien, Jan Peters, Henning Skriver, Hans Lievens, Frieke 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. doi:10.1016/j.jag.2012.05.011.
- 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.
- IEEE
- [1]L. Loosvelt 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, vol. 19, pp. 173–184, 2012.
@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}},
keywords = {{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://doi.org/10.1016/j.jag.2012.05.011}},
volume = {{19}},
year = {{2012}},
}
- Altmetric
- View in Altmetric
- Web of Science
- Times cited: