High-resolution hyperspectral images of Council, Alaska 2019
Hyperspectral data are gaining popularity in remote sensing and signal processing communities because of the increased spectral information relative to multispectral data. Several airborne and spaceborne hyperspectral datasets are publicly available, facilitating the development of various applicati...
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Arctic Data Center
2021
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dataone:doi:10.18739/A2416T10D 2024-10-03T18:46:23+00:00 High-resolution hyperspectral images of Council, Alaska 2019 Junhwa Chi Jae-In Kim Ali Masjedi John Evan Flatt Melba M. Crawford Ayman F. Habib Joohan Lee Hyun-Cheol Kim Council, Alaska ENVELOPE(-163.7139,-163.7083,64.84444,64.84028) BEGINDATE: 2019-09-23T00:00:00Z ENDDATE: 2019-09-26T00:00:00Z 2021-01-01T00:00:00Z https://doi.org/10.18739/A2416T10D unknown Arctic Data Center Remote sensing Hyperspectral UAV Permafrost Council, Alaska Dataset 2021 dataone:urn:node:ARCTIC https://doi.org/10.18739/A2416T10D 2024-10-03T18:17:32Z Hyperspectral data are gaining popularity in remote sensing and signal processing communities because of the increased spectral information relative to multispectral data. Several airborne and spaceborne hyperspectral datasets are publicly available, facilitating the development of various applications and algorithms. However, hyperspectral data are usually limited by their narrow, highly correlated, and contiguous spectral bands in both processing and analysis. Moreover, the resolution of available hyperspectral datasets is not sufficiently high for the identification of small objects. Nevertheless, with the rapidly advancing technology, hyperspectral imaging systems can now be mounted on small aerial vehicles for detecting small objects at low altitude. To properly handle these high spectral and spatial resolution data, new or redesigned data processing or analysis pipelines must be developed. However, such datasets are currently not publicly available. Therefore, we provide two hyperspectral datasets from GNSS/INS-assisted co-aligned pushbroom hyperspectral scanners on a drone. The hyperspectral datasets consist of raw/post-processed hyperspectral data, raw/post-processed Global Navigation System Satellite/Inertial Measurement Unit (GNSS/IMU) data, and digital surface models, and were radiometrically and geometrically evaluated. These datasets are expected to aid the improvement of UAV-based hyperspectral data processing and analysis algorithms. Dataset permafrost Alaska Arctic Data Center (via DataONE) ENVELOPE(-163.7139,-163.7083,64.84444,64.84028) |
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Open Polar |
collection |
Arctic Data Center (via DataONE) |
op_collection_id |
dataone:urn:node:ARCTIC |
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topic |
Remote sensing Hyperspectral UAV Permafrost Council, Alaska |
spellingShingle |
Remote sensing Hyperspectral UAV Permafrost Council, Alaska Junhwa Chi Jae-In Kim Ali Masjedi John Evan Flatt Melba M. Crawford Ayman F. Habib Joohan Lee Hyun-Cheol Kim High-resolution hyperspectral images of Council, Alaska 2019 |
topic_facet |
Remote sensing Hyperspectral UAV Permafrost Council, Alaska |
description |
Hyperspectral data are gaining popularity in remote sensing and signal processing communities because of the increased spectral information relative to multispectral data. Several airborne and spaceborne hyperspectral datasets are publicly available, facilitating the development of various applications and algorithms. However, hyperspectral data are usually limited by their narrow, highly correlated, and contiguous spectral bands in both processing and analysis. Moreover, the resolution of available hyperspectral datasets is not sufficiently high for the identification of small objects. Nevertheless, with the rapidly advancing technology, hyperspectral imaging systems can now be mounted on small aerial vehicles for detecting small objects at low altitude. To properly handle these high spectral and spatial resolution data, new or redesigned data processing or analysis pipelines must be developed. However, such datasets are currently not publicly available. Therefore, we provide two hyperspectral datasets from GNSS/INS-assisted co-aligned pushbroom hyperspectral scanners on a drone. The hyperspectral datasets consist of raw/post-processed hyperspectral data, raw/post-processed Global Navigation System Satellite/Inertial Measurement Unit (GNSS/IMU) data, and digital surface models, and were radiometrically and geometrically evaluated. These datasets are expected to aid the improvement of UAV-based hyperspectral data processing and analysis algorithms. |
format |
Dataset |
author |
Junhwa Chi Jae-In Kim Ali Masjedi John Evan Flatt Melba M. Crawford Ayman F. Habib Joohan Lee Hyun-Cheol Kim |
author_facet |
Junhwa Chi Jae-In Kim Ali Masjedi John Evan Flatt Melba M. Crawford Ayman F. Habib Joohan Lee Hyun-Cheol Kim |
author_sort |
Junhwa Chi |
title |
High-resolution hyperspectral images of Council, Alaska 2019 |
title_short |
High-resolution hyperspectral images of Council, Alaska 2019 |
title_full |
High-resolution hyperspectral images of Council, Alaska 2019 |
title_fullStr |
High-resolution hyperspectral images of Council, Alaska 2019 |
title_full_unstemmed |
High-resolution hyperspectral images of Council, Alaska 2019 |
title_sort |
high-resolution hyperspectral images of council, alaska 2019 |
publisher |
Arctic Data Center |
publishDate |
2021 |
url |
https://doi.org/10.18739/A2416T10D |
op_coverage |
Council, Alaska ENVELOPE(-163.7139,-163.7083,64.84444,64.84028) BEGINDATE: 2019-09-23T00:00:00Z ENDDATE: 2019-09-26T00:00:00Z |
long_lat |
ENVELOPE(-163.7139,-163.7083,64.84444,64.84028) |
genre |
permafrost Alaska |
genre_facet |
permafrost Alaska |
op_doi |
https://doi.org/10.18739/A2416T10D |
_version_ |
1811927973699256320 |