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

fYear

2014

fDate

13-18 July 2014

Firstpage

788

Lastpage

791

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International

Conference_Location

Quebec City, QC

Type

conf

DOI

10.1109/IGARSS.2014.6946542

Filename

6946542