Forest stand mapping with data from Hyperion, ALI, and ETM

Bingxiang Tan; Zengyuan Li; Erxue Chen; Yong Pang

doi:10.1117/12.681708

9 June 2006 Forest stand mapping with data from Hyperion, ALI, and ETM

Bingxiang Tan, Zengyuan Li, Erxue Chen, Yong Pang

Proceedings Volume 6200, Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China; 62000H (2006) https://doi.org/10.1117/12.681708
Event: Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, 2005, Guiyan City, China

Abstract

The EO-1 spacecraft, launched November 21, 2000 into a sun synchronous orbit behind Landsat 7, hosts advanced technology demonstration instruments, whose capabilities are currently being assessed by the user community for future missions. A significant part of the EO-1 program is to perform data comparisons between Hyperion, ALI and Landsat 7 ETM+. In this paper, a comparison of forest classification results from Hyperion, ALI, and ETM+ of Landsat-7 are provided for Wangqing Forest Bureau, Jilin Province, and Northeast of China. The data have been radiometrically corrected and geometrically resampled. Feature selection and statistical transforms are used to reduce the Hyperion feature space from 129 channels to 15 features. Classes chosen for discrimination included Larch, Oak, Birch, Popular, Young tree, mixed forest, Grassland and Shrub. Classification accuracies by sensors for classes in the demonstration area were: Hyperion 88.89%, ALI 85.19%, and ETM+ 77.78%. The results shows: Hyperion classification results were the best, ALI's were much better than ETM+. Therefore, we can consider that hyper spectral remote sensing provides significant advantages and greater accuracies over ETM+ for forest discrimination. The EO-1 sensors, Hyperion and ALI, provide data with better discrimination for Northeast forests of China in comparison to Landsat-7 ETM+.

Citation Download Citation

Bingxiang Tan, Zengyuan Li, Erxue Chen, and Yong Pang "Forest stand mapping with data from Hyperion, ALI, and ETM", Proc. SPIE 6200, Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, 62000H (9 June 2006); https://doi.org/10.1117/12.681708

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KEYWORDS

Alternate lighting of surfaces

Sensors

Earth observing sensors

Landsat

Remote sensing

Forestry

Signal to noise ratio

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