| Title | Preprocessing of EO-1 Hyperion data |
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| Author | Khurshid, K S; Staenz, K; Sun, L; Neville, R; White, H P ; Bannari, A; Champagne, C M; Hitchcock, R |
| Source | 26th Canadian Symposium on Remote Sensing: managing resources and monitoring the environment; by Hopkinson, C (ed.); White, H P (ed.); Canadian Journal of Remote Sensing vol. 32, no. 2, 2006 p. 84-97, https://doi.org/10.5589/m06-014 |
| Year | 2006 |
| Alt Series | Earth Sciences Sector, Contribution Series 20060108 |
| Publisher | Informa UK Limited |
| Meeting | 26th Canadian Symposium on Remote Sensing: managing resources and monitoring the environment; CA |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf (Adobe Acrobat Reader) |
| Subjects | miscellaneous; remote sensing; spectral analyses; satellites; satellite imagery; spectrometric analyses; infrared surveys; infrared spectral analyses; software; computer graphics; computer mapping;
computer applications; data collections |
| Illustrations | schematic diagrams; formulae; aerial photographs; satellite imagery; satellite images; graphs; tables |
| Program | Geomatics for Sustainable Development of Natural
Resources |
| Program | Sustainable Development Through Knowledge Integration
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| Released | 2014 06 02 |
| Abstract | A procedure for processing hyperspectral data acquired with Hyperion has been developed with an aim to correct for sensor artifacts and atmospheric and geometric effects. Advances in preprocessing of
hyperspectral remote sensing data have enabled more accurate atmospheric correction and have led to the development of new information extraction techniques in the areas of agriculture, forestry, geosciences, and environmental monitoring. These
processing and analysis tools have been incorporated into Imaging Spectrometer Data Analysis Systems (ISDAS), a software package developed at the Canada Centre for Remote Sensing (CCRS). The procedure, as applied for Hyperion data, begins with
geometric corrections to the short-wave infrared (SWIR) component to register the SWIR and visible near-infrared (VNIR) data spatially. This is followed by the removal of stripes and pixel (column) dropouts and noise reduction, using recently
developed automated software tools. The data cube is subsequently analyzed using keystone and spectral smile detection software to characterize these distortions. Included in the smile detection procedure is an optional gain and offset correction
technique. The radiance data are converted to reflectance using a MODTRAN-based atmospheric correction procedure. Only at this point are the data corrected for smile effects. Any artifacts still remaining after these corrections are removed by
post-processing. |
| GEOSCAN ID | 222382 |
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