This study deals with data fusion of hyperspectral and LiDAR sensors for forest applications. In particular, the added value of different data sources on tree species mapping has been analyzed. A total of seven species have been mapped for a forested area in Belgium: Beech, Ash, Larch, Poplar, Copper beech, Chestnut and Oak. Hyperspectral data is obtained from the APEX sensor in 286 spectral bands. LiDAR data has been acquired with a TopoSys sensor Harrier 56 at full waveform. Conﬁrming previous research , it has been found that airborne LiDAR data, when combined with hyperspectral data, can improve classiﬁcation results. The novelty of this study is in the quantiﬁcation of the contribution of the individual data sources and their derived parameters. LiDAR information was combined with the hyperspectral image in a data fusion approach. Different data fusion techniques were tested, including feature and decision fusion. Decision fucsion produced optimal results, reaching an overall accuracy of 96% (Kappa  of 0:95).
|Number of pages||4|
|Publication status||Published - 18 Jul 2014|
|Event|| 2014 IEEE Geoscience and Remote Sensing Symposium IGARSS - Quebec City, Canada|
Duration: 13 Jul 2014 → 18 Jul 2014
|Conference||2014 IEEE Geoscience and Remote Sensing Symposium IGARSS|
|Abbreviated title||IGARSS 2014|
|Period||13/07/14 → 18/07/14|
- hyperspectral images
- tree species mapping
- image classification
Kempeneers, P., Vancoillie, F., Liao, W., Devriendt, F., Vandekerkhove, K., Bernier, M. (Ed.), Lévesque, J. (Ed.), Garneau, J-M. (Ed.), & LeDrew, E. (Ed.) (2014). Tree species mapping by combining hyperspectral with LiDAR data. Paper presented at 2014 IEEE Geoscience and Remote Sensing Symposium IGARSS , Quebec City, Canada.