DocumentCode :
143237
Title :
Optimizing ground return detection through forest canopies with small footprint airborne mapping LiDAR
Author :
Fernandez-Diaz, Juan Carlos ; Heezin Lee ; Glennie, Craig L. ; Carter, William E. ; Shrestha, Ramesh L. ; Singhania, Abhinav ; Sartori, Michael P. ; Hauser, Darren L.
Author_Institution :
Dept. of Civil & Environ. Eng., Univ. of Houston, Houston, TX, USA
fYear :
2014
fDate :
13-18 July 2014
Firstpage :
1963
Lastpage :
1966
Abstract :
The capability of airborne LiDAR scanners (ALS) to record returns from the ground surface and other targets occluded by forest canopies has been of great value for geosciences and military operations. In this paper we present preliminary results from efforts aimed to characterize different types of forest canopies and to assess the quantity and quality of potential ground returns obtained through different configurations of small footprint airborne mapping LiDAR systems. The final goal of this work is to provide a methodology that allows for the quantification of the “openness” of a forest canopy and procedures to determine the best configuration of ALS systems that ensures maximum detection of ground returns independent of the many different system designs currently available.
Keywords :
airborne radar; optical radar; vegetation; ALS capability; airborne LiDAR scanner capability; best ALS system configuration; forest canopy openness quantification; forest canopy type; great geoscience value; ground return detection optimization; ground surface; maximum ground return detection; military operation; potential ground return quality assessment; potential ground return quantity assessment; small footprint airborne mapping LiDAR; small footprint airborne mapping LiDAR system configurations; system design; Atmospheric modeling; Laser beams; Laser modes; Laser radar; Remote sensing; Surface emitting lasers; Vegetation mapping; LiDAR; forest; ground returns; sensor configuration;
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.2014.6946845
Filename :
6946845
Link To Document :
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