HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM
Hyperspectral remote sensing is more effective than multispectral remote sensing in many application fields because of having hundreds of observation bands with high spectral resolution. However, hyperspectral remote sensing resources are limited both in temporal and spatial coverage. Therefore, s...
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doaj-52f4771a104548959d9b7aded74109842020-11-24T21:16:06ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342016-06-01XLI-B766166510.5194/isprs-archives-XLI-B7-661-2016HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHMN. T. Hoang0N. T. Hoang1K. Koike2Graduate School of Engineering, Kyoto University, Katsura C1-2-215, Kyoto 615-8540, JapanDepartment of Environmental Science, College of Sciences, Hue University, 77 Nguyen Hue, Hue, VietnamGraduate School of Engineering, Kyoto University, Katsura C1-2-215, Kyoto 615-8540, JapanHyperspectral remote sensing is more effective than multispectral remote sensing in many application fields because of having hundreds of observation bands with high spectral resolution. However, hyperspectral remote sensing resources are limited both in temporal and spatial coverage. Therefore, simulation of hyperspectral imagery from multispectral imagery with a small number of bands must be one of innovative topics. Based on this background, we have recently developed a method, Pseudo-Hyperspectral Image Synthesis Algorithm (PHISA), to transform Landsat imagery into hyperspectral imagery using the correlation of reflectance at the corresponding bands between Landsat and EO-1 Hyperion data. This study extends PHISA to simulate pseudo-hyperspectral imagery from EO-1 ALI imagery. The pseudo-hyperspectral imagery has the same number of bands as that of high-quality Hyperion bands and the same swath width as ALI scene. The hyperspectral reflectance data simulated from the ALI data show stronger correlation with the original Hyperion data than the one simulated from Landsat data. This high correlation originates from the concurrent observation by the ALI and Hyperion sensors that are on-board the same satellite. The accuracy of simulation results are verified by a statistical analysis and a surface mineral mapping. With a combination of the advantages of both ALI and Hyperion image types, the pseudo-hyperspectral imagery is proved to be useful for detailed identification of minerals for the areas outside the Hyperion coverage.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/661/2016/isprs-archives-XLI-B7-661-2016.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
N. T. Hoang N. T. Hoang K. Koike |
spellingShingle |
N. T. Hoang N. T. Hoang K. Koike HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
N. T. Hoang N. T. Hoang K. Koike |
author_sort |
N. T. Hoang |
title |
HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM |
title_short |
HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM |
title_full |
HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM |
title_fullStr |
HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM |
title_full_unstemmed |
HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM |
title_sort |
hyperspectral transformation from eo-1 ali imagery using pseudo-hyperspectral image synthesis algorithm |
publisher |
Copernicus Publications |
series |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
1682-1750 2194-9034 |
publishDate |
2016-06-01 |
description |
Hyperspectral remote sensing is more effective than multispectral remote sensing in many application fields because of having hundreds
of observation bands with high spectral resolution. However, hyperspectral remote sensing resources are limited both in temporal and
spatial coverage. Therefore, simulation of hyperspectral imagery from multispectral imagery with a small number of bands must be
one of innovative topics. Based on this background, we have recently developed a method, Pseudo-Hyperspectral Image Synthesis
Algorithm (PHISA), to transform Landsat imagery into hyperspectral imagery using the correlation of reflectance at the corresponding
bands between Landsat and EO-1 Hyperion data. This study extends PHISA to simulate pseudo-hyperspectral imagery from EO-1
ALI imagery. The pseudo-hyperspectral imagery has the same number of bands as that of high-quality Hyperion bands and the same
swath width as ALI scene. The hyperspectral reflectance data simulated from the ALI data show stronger correlation with the original
Hyperion data than the one simulated from Landsat data. This high correlation originates from the concurrent observation by the ALI
and Hyperion sensors that are on-board the same satellite. The accuracy of simulation results are verified by a statistical analysis and
a surface mineral mapping. With a combination of the advantages of both ALI and Hyperion image types, the pseudo-hyperspectral
imagery is proved to be useful for detailed identification of minerals for the areas outside the Hyperion coverage. |
url |
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/661/2016/isprs-archives-XLI-B7-661-2016.pdf |
work_keys_str_mv |
AT nthoang hyperspectraltransformationfromeo1aliimageryusingpseudohyperspectralimagesynthesisalgorithm AT nthoang hyperspectraltransformationfromeo1aliimageryusingpseudohyperspectralimagesynthesisalgorithm AT kkoike hyperspectraltransformationfromeo1aliimageryusingpseudohyperspectralimagesynthesisalgorithm |
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