Title
Processing Hyperion and ALI for forest classification
Abstract
Hyperion (a hyperspectral sensor) and the Advanced Land Imager (ALI) (a multispectral sensor) are carried on the National Aeronautics and Space Administration's Earth Observing 1 (EO-1) satellite. The Evaluation and Validation of EO-1 for Sustainable Development (EVEOSD) is our project supporting the EO-1 mission. With 10% of the world's forests and the second largest country by area in the world, Canada has a natural requirement for effective monitoring of its forests. Eight test sites have been selected for EVEOSD, with seven in Canada and one in the United States. Extensive fieldwork has been conducted at four of these sites. A comparison is made of forest classification results from Hyperion, ALI, and the Enhanced Thematic Mapper Plus (ETM+) of Landsat-7 for the Greater Victoria Watershed. The data have been radiometrically corrected and orthorectified. Feature selection and statistical transforms are used to reduce the Hyperion feature space from 198 channels to 11 features. Classes chosen for discrimination included Douglas-fir, hemlock, western redcedar, lodgepole pine, and red alder. Overall classification accuracies obtained for each sensor were Hyperion 90.0%, ALI 84.8%, and ETM+ 75.0%. Hyperspectral remote sensing provides significant advantages and greater accuracies over ETM+ for forest discrimination. The EO-1 sensors, Hyperion and ALI, provide data with excellent discrimination for Pacific Northwest forests in comparison to Landsat-7 ETM+.
Year
DOI
Venue
2003
10.1109/TGRS.2003.813214
Geoscience and Remote Sensing, IEEE Transactions
Keywords
Field
DocType
forestry,geophysical techniques,vegetation mapping,400 to 2500 nm,ALI,Advanced Land Imager,Alnus rubra,Arbutus menziesii,British Columbia,Canada,Douglas fir,EO-1,EVEOSD,Greater Victoria Watershed,Hyperion,IR,Pinus contorta,Pseudotsuga menziesii,Thuja plicata,Tsuga heterophylla,Vancouver Island,forest classification,forestry,geophysical measurement technique,hyperspectral remote sensing,infrared,lodgepole pine,multispectral remote sensing,red alder,satellite remote sensing,tree species,vegetation mapping,visible,western hemlock,western red cedar
Thematic Mapper,Satellite,Vegetation,Pacific ocean,Remote sensing,Multispectral image,Watershed,Hyperspectral imaging,Mathematics,Orthophoto
Journal
Volume
Issue
ISSN
41
6
0196-2892
Citations 
PageRank 
References 
40
4.41
3
Authors
8
Name
Order
Citations
PageRank
david g goodenough17818.64
a dyk28518.72
k o niemann3488.20
J. S. Pearlman430777.90
Hao Chen5457.54
Tian Han6445.64
M. Murdoch7455.43
C. West8455.77