Fusion of hyperspectral and lidar remote sensing data for the estimation of tree stem diameters

Author

Dalponte, Michele ; Bruzzone, Lorenzo ; Gianelle, Damiano

Author_Institution

Dept. of Inf. Eng. & Comput. Sci., Univ. of Trento, Trento, Italy

Volume

2

fYear

2009

fDate

12-17 July 2009

Abstract

The estimation of stem diameters can be very useful in the study of forests, as together with height and tree specie, it is one of the most important parameters used in forest inventories. In this paper a system for the estimation of stem diameters with LIDAR and hyperspectral data (both separately and combined in a data fusion framework) is presented. An analysis on the effectiveness of these data in the estimation process and on the accuracy and robustness of different estimation algorithms is presented. Experimental results point out the effectiveness and the properties of the proposed system.

Keywords

forestry; geophysical techniques; optical radar; remote sensing by radar; vegetation; LIDAR remote sensing data; data fusion framework; estimation algorithms; forest inventories; forestry; forests; hyperspectral remote sensing data; stem diameters; tree diameter estimation; tree specie; Algorithm design and analysis; Bonding; Hyperspectral imaging; Hyperspectral sensors; Laser radar; Parameter estimation; Remote sensing; Robustness; Signal processing algorithms; Spatial resolution; LIDAR; data fusion; forestry; hyperspectral images; tree diameter estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009

Conference_Location

Cape Town

Print_ISBN

978-1-4244-3394-0

Electronic_ISBN

978-1-4244-3395-7

Type

conf

DOI

10.1109/IGARSS.2009.5418274

Filename

5418274