Comparison of EO-1 Hyperion to AVIRIS for mapping forest composition in the Appalachian Mountains, USA
- 1 October 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 793-795
- https://doi.org/10.1109/igarss.2002.1025688
Abstract
We used classification and regression trees (CART) to map forest composition with Hyperion and AVIRIS in the Central Appalachian Mountains. Imagery from both sensors exhibited strong topographic effects, with AVIRIS also having a view-angle dependent brightness gradient across the image swath. A DEM-based empirical adjustment to reflectance levels was implemented to reduce apparent topographic effects in the imagery. In general, classification accuracy improved using the topographically normalized imagery, although it is possible that the adjustments to the AVIRIS imagery diminished the superior signal:noise performance of the AVIRIS imagery. Subtle distinctions in forest composition were detectable from both AVIRIS and Hyperion imagery, and despite the superior S:N and spatial resolution of AVIRIS, classification of Hyperion images was as accurate or more accurate than AVIRIS for most species. We therefore demonstrate the utility of Hyperion imagery, but note that further comparisons are still required. In particular, the effects of sensor artifacts (such as striping and "smile") must still be addressed when using Hyperion data.Keywords
This publication has 10 references indexed in Scilit:
- A refined empirical line approach for reflectance factor retrieval from Landsat-5 TM and Landsat-7 ETM+Remote Sensing of Environment, 2001
- Topographic Normalization of Landsat Thematic Mapper Data in Three Mountain EnvironmentsGeocarto International, 2000
- The use of decision tree and multiscale texture for classification of JERS-1 SAR data over tropical forestIEEE Transactions on Geoscience and Remote Sensing, 2000
- Maximizing land cover classification accuracies produced by decision trees at continental to global scalesIEEE Transactions on Geoscience and Remote Sensing, 1999
- Empirical methods to compensate for a view-angle-dependent brightness gradient in AVIRIS imageryRemote Sensing of Environment, 1997
- Decision tree classification of land cover from remotely sensed dataRemote Sensing of Environment, 1997
- Delineation of inundated area and vegetation along the Amazon floodplain with the SIR-C synthetic aperture radarIEEE Transactions on Geoscience and Remote Sensing, 1995
- Modern Applied Statistics with S-PlusPublished by Springer Nature ,1994
- Radiometric corrections of topographically induced effects on Landsat TM data in an alpine environmentISPRS Journal of Photogrammetry and Remote Sensing, 1993
- Derivation of scaled surface reflectances from AVIRIS dataRemote Sensing of Environment, 1993