Title :
Fusion of hyperspectral and LiDAR data for forest attributes estimation
Author :
Dalponte, Michele ; Frizzera, Lorenzo ; Gianelle, Damiano
Author_Institution :
Res. & Innovation Centre, Dept. of Sustainable Agro-Ecosyst. & Bioresources, Res. & Innovation Centre, Fondazione E. Mach, San Michele all´Adige, Italy
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.
Keywords :
geophysical image processing; geophysical techniques; image classification; image fusion; optical radar; remote sensing by laser beam; vegetation; airborne laser scanning; breast height; forest attributes estimation; hyperspectral-LiDAR data fusion; stem diameter estimation; tree species classification; Accuracy; Estimation; Hyperspectral imaging; Vegetation; Volume measurement; Airborne laser scanner; classification; estimation; forestry; hyperspectral;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6946542
