An advanced classifier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia

P. Ghamisi; D. Wu; G. Cavallaro; J. A. Benediktsson; S. Phinn; Nicola Falco

doi:10.1109/IGARSS.2015.7326281

An advanced classifier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia

P. Ghamisi, D. Wu, G. Cavallaro, J. A. Benediktsson, S. Phinn, Nicola Falco

University of Iceland

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

With respect to the exponential increase in the number of available remote sensors in recent years, the possibility of having different types of data captured over the same scene, has resulted in many research works related to the joint use of passive and active sensors for the accurate classification of different materials. However, until now, there is a small number of research works related to the integration of highly valuable information obtained from the joint use of LiDAR and hyperspectral data. This paper proposes an efficient classification approach in terms of accuracies and demanded CPU processing time for integrating big data sets (e.g., LiDAR and hyperspectral) to provide land cover mapping capabilities at a range of spatial scales. In addition, the proposed approach is fully automatic and is able to efficiently handle big data containing a huge number of features with very limited number of training samples in few seconds.

Original language	English
Title of host publication	2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2354-2357
Number of pages	4
ISBN (Electronic)	9781479979295
DOIs	https://doi.org/10.1109/IGARSS.2015.7326281
Publication status	Published - 10 Nov 2015
Event	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Milan, Italy Duration: 26 Jul 2015 → 31 Jul 2015

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2015-November

Conference

Conference	IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Country/Territory	Italy
City	Milan
Period	26/07/15 → 31/07/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Other keywords

big data processing
Fusion of LiDAR and hyperspectral
random forest classifier
self-dual attribute profile

Access to Document

10.1109/IGARSS.2015.7326281

Cite this

Ghamisi, P., Wu, D., Cavallaro, G., Benediktsson, J. A., Phinn, S., & Falco, N. (2015). An advanced classifier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia. In 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings (pp. 2354-2357). Article 7326281 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2015-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2015.7326281

Ghamisi, P. ; Wu, D. ; Cavallaro, G. et al. / An advanced classifier for the joint use of LiDAR and hyperspectral data : Case study in Queensland, Australia. 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 2354-2357 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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abstract = "With respect to the exponential increase in the number of available remote sensors in recent years, the possibility of having different types of data captured over the same scene, has resulted in many research works related to the joint use of passive and active sensors for the accurate classification of different materials. However, until now, there is a small number of research works related to the integration of highly valuable information obtained from the joint use of LiDAR and hyperspectral data. This paper proposes an efficient classification approach in terms of accuracies and demanded CPU processing time for integrating big data sets (e.g., LiDAR and hyperspectral) to provide land cover mapping capabilities at a range of spatial scales. In addition, the proposed approach is fully automatic and is able to efficiently handle big data containing a huge number of features with very limited number of training samples in few seconds.",

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author = "P. Ghamisi and D. Wu and G. Cavallaro and Benediktsson, {J. A.} and S. Phinn and Nicola Falco",

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doi = "10.1109/IGARSS.2015.7326281",

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Ghamisi, P, Wu, D, Cavallaro, G, Benediktsson, JA, Phinn, S & Falco, N 2015, An advanced classifier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia. in 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings., 7326281, International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2015-November, Institute of Electrical and Electronics Engineers Inc., pp. 2354-2357, IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015, Milan, Italy, 26/07/15. https://doi.org/10.1109/IGARSS.2015.7326281

An advanced classifier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia. / Ghamisi, P.; Wu, D.; Cavallaro, G. et al.
2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 2354-2357 7326281 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2015-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Ghamisi P, Wu D, Cavallaro G, Benediktsson JA, Phinn S, Falco N. An advanced classifier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia. In 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2015. p. 2354-2357. 7326281. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS.2015.7326281

An advanced classifier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia

Abstract

Publication series

Conference

Bibliographical note

Other keywords

Access to Document

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Cite this