Title :
Fusion of High-Resolution Satellite and Lidar Data for Individual Tree Recognition
Author :
Zaremba, Marek B. ; Gougeon, Francois A.
Author_Institution :
Dept. d´´Informatique et d´´Ingenierie, Quebec Univ., Gatineau, Que.
Abstract :
A major shift in the forest inventory and management paradigm toward the use of semi-automated analysis realized on an individual tree crown basis has been made possible by recent developments in high-resolution remote sensing. This paper discusses issues related to the fusion of high-resolution satellite imagery and LIDAR (light detection and ranging) data and their application in the classification of individual trees for precision forest management. The proposed methodological approach consists in the combination of spatial filtering object detection and reconstruction methods with a rule-based individual tree crown (ITC) system. Examples using QuickBird imagery combined with LIDAR data from an Alberta site (both boreal and mixed forest) demonstrate the advantages of the proposed fusion approach
Keywords :
filtering theory; forestry; image classification; image fusion; image reconstruction; image resolution; object detection; optical radar; remote sensing; trees (mathematics); LIDAR data; forest inventory management; high-resolution remote sensing; high-resolution satellite imagery; individual tree recognition; light detection and ranging; object reconstruction methods; rule-based individual tree crown system; semiautomated analysis; spatial filtering object detection; Character recognition; Forestry; Image analysis; Image recognition; Inventory management; Laser radar; Multispectral imaging; Satellite broadcasting; Spatial databases; Spatial resolution; Individual Tree Crown system; Lidar data; Satellite imagery; data fusion;
Conference_Titel :
Electrical and Computer Engineering, 2006. CCECE '06. Canadian Conference on
Conference_Location :
Ottawa, Ont.
Print_ISBN :
1-4244-0038-4
Electronic_ISBN :
1-4244-0038-4
DOI :
10.1109/CCECE.2006.277351
