DocumentCode :
483971
Title :
Comparison of Aviris and AISA Airborne Hyperspectral Sensing for Above-Ground Forest Carbon Mapping
Author :
Goodenough, David G. ; Niemann, K. Olaf ; Dyk, Andrew ; Hobart, Geordie ; Gordon, Piper ; Loisel, Matthew ; Chen, Hao
Author_Institution :
Pacific Forestry Centre, Natural Resources Canada, Victoria, BC
Volume :
2
fYear :
2008
fDate :
7-11 July 2008
Abstract :
Monitoring of the 418 million ha of forests in Canada is needed to ensure the sustainable development of these forests. Hyperspectral sensing can provide mapping of forest species, forest health, and above-ground biomass. Airborne two-meter AISA hyperspectral and LIDAR data were acquired by the University of Victoria (UVic) over the Greater Victoria Watershed District (GVWD) test site and compared to NASA´s AVIRIS data that had been acquired in the summer of 2002 at 4 m spatial resolution. Tree heights derived from LIDAR data, and allometric equations were used to provide independent ground estimates of biomass. Between-sensor calibration calibrated the AISA data to the same basis as the AVIRIS data. The calibrated reflectance data were used to generate forest species classifications, and biomass estimates for the test site. Average classification accuracies exceeded 89% in mapping major forest species. These products were used to create a map of above-ground carbon for the forested portion of the GVWD test site.
Keywords :
atmospheric boundary layer; atmospheric composition; atmospheric techniques; calibration; carbon; optical radar; remote sensing by radar; sustainable development; vegetation; vegetation mapping; AD 2002; AISA; Aviris; C; Canada; Greater Victoria Watershed District; LIDAR; Victoria University; above ground biomass; above ground forest carbon mapping; airborne hyperspectral sensing; allometric equation; between-sensor calibration; forest health; forest species; sustainable development; Biomass; Calibration; Equations; Hyperspectral imaging; Hyperspectral sensors; Laser radar; Monitoring; Spatial resolution; Sustainable development; Testing; AISA; AVIRIS; Hyperspectral; LIDAR; above-ground carbon; biomass; forest; species;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-2807-6
Electronic_ISBN :
978-1-4244-2808-3
Type :
conf
DOI :
10.1109/IGARSS.2008.4778944
Filename :
4778944
Link To Document :
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