In this paper a system for the fusion of hyperspectral and airborne laser scanning (ALS) data for the estimation of forest attributes is presented. In particular we focused on the classification of tree species, the estimation of stem diameter at breast height (DBH) and the estimation of the stem volume. The results showed that the fusion of hyperspectral and ALS data improve the estimation results respect to the use of only one data source
Dalponte, M.; Frizzera, L.; Gianelle, D. (2014). Fusion of hyperspectral and LIDAR data for forest attributes estimation. In: International Geoscience and Remote Sensing Symposium (IGARSS 2014) / 35th Canadian Symposium on Remote Sensing (35th CSRS): Energy and our Changing Planet, July 13-18, 2014, Quebec City, Canada. url: http://www.igarss2014.org/ handle: http://hdl.handle.net/10449/24546
Fusion of hyperspectral and LIDAR data for forest attributes estimation
Dalponte, Michele;Frizzera, Lorenzo;Gianelle, Damiano
2014-01-01
Abstract
In this paper a system for the fusion of hyperspectral and airborne laser scanning (ALS) data for the estimation of forest attributes is presented. In particular we focused on the classification of tree species, the estimation of stem diameter at breast height (DBH) and the estimation of the stem volume. The results showed that the fusion of hyperspectral and ALS data improve the estimation results respect to the use of only one data source
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