Canadian Forest Service Publications

Monitoring Forests with Hyperion and ALI. 2002. Goodenough, D.G.; Bhogal, A.S. (Pal); Dyk, A.; Hollinger, A.; Mah, Z.; Niemann, O.; Pearlman, J.; Chen, H.; Han, T.; Love, J.; McDonald, S. Pages 882-885 in IGARSS 2002, Proceedings: IEEE International Geoscience and Remote Sensing Symposium and the 24th Canadian Symposium on Remote Sensing. June 24-28, 2002, Toronto, Canada. IEEE, Piscataway, New Jersey.

Year: 2002

Available from: Pacific Forestry Centre

Catalog ID: 20547

Language: English

CFS Availability: PDF (request by e-mail)

Abstract

Hyperion, a hyperspectral sensor, and the Advanced Land Imager (ALI) are carried on NASA’s 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 US. Extensive fieldwork has been conducted at four of these sites.
A comparison is made of forest classification results from Hyperion, ALI, and the ETM+ of Landsat-7 for the Greater Victoria Watershed. The data have been radiometrically corrected and ortho-rectified. Feature selection and statistical transforms are used to reduce the Hyperion feature space from 220 channels to 12 features. Classes chosen for discrimination included Douglas Fir, Hemlock, Western Red Cedar, Lodgepole Pine and Red Alder. Overall classification accuracies obtained for each sensor were: Hyperion 92.9%, 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.

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