Tree species mapping by combining hyperspectral with LiDAR data

Kempeneers, Pieter and Vancoillie, Frieke and Liao, Wenzhi and Devriendt, Flore and Vandekerkhove, Kris; Bernier, Monique and Lévesque, Josée and Garneau, Jean-Marc and LeDrew, Ellsworth, eds. (2014) Tree species mapping by combining hyperspectral with LiDAR data. In: 2014 IEEE Geoscience and Remote Sensing Symposium IGARSS, 2014-07-13 - 2014-07-18.

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    Abstract

    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 [1], 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 [3] of 0:95).