Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager
An automated ice-mapping algorithm has been developed and evaluated using data from the GOES-13 imager. The approach includes cloud-free image compositing as well as image classification using spectral criteria. The algorithm uses an alternative snow index to the Normalized Difference Snow Index (ND...
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ftdoajarticles:oai:doaj.org/article:759ad8f22a364cd2a429ae505e0e338a 2023-05-15T18:18:34+02:00 Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager Peter Dorofy Rouzbeh Nazari Peter Romanov and Jeffrey Key 2016-12-01T00:00:00Z https://doi.org/10.3390/rs8121015 https://doaj.org/article/759ad8f22a364cd2a429ae505e0e338a EN eng MDPI AG http://www.mdpi.com/2072-4292/8/12/1015 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs8121015 https://doaj.org/article/759ad8f22a364cd2a429ae505e0e338a Remote Sensing, Vol 8, Iss 12, p 1015 (2016) sea ice concentration shortwave infrared GOES imager remote sensing Science Q article 2016 ftdoajarticles https://doi.org/10.3390/rs8121015 2022-12-31T07:31:33Z An automated ice-mapping algorithm has been developed and evaluated using data from the GOES-13 imager. The approach includes cloud-free image compositing as well as image classification using spectral criteria. The algorithm uses an alternative snow index to the Normalized Difference Snow Index (NDSI). The GOES-13 imager does not have a 1.6 µm band, a requirement for NDSI; however, the newly proposed Mid-Infrared Sea and Lake Ice Index (MISI) incorporates the reflective component of the 3.9 µm or mid-infrared (MIR) band, which the GOES-13 imager does operate. Incorporating MISI into a sea or lake ice mapping algorithm allows for mapping of thin or broken ice with no snow cover (nilas, frazil ice) and thicker ice with snow cover to a degree of confidence that is comparable to other ice mapping products. The proposed index has been applied over the Great Lakes region and qualitatively compared to the Interactive Multi-sensor Snow and Ice Mapping System (IMS), the National Ice Center ice concentration maps and MODIS snow cover products. The application of MISI may open additional possibilities in climate research using historical GOES imagery. Furthermore, MISI may be used in addition to the current NDSI in ice identification to build more robust ice-mapping algorithms for the next generation GOES satellites. Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Misi ENVELOPE(26.683,26.683,66.617,66.617) Remote Sensing 8 12 1015 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
sea ice concentration shortwave infrared GOES imager remote sensing Science Q |
spellingShingle |
sea ice concentration shortwave infrared GOES imager remote sensing Science Q Peter Dorofy Rouzbeh Nazari Peter Romanov and Jeffrey Key Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager |
topic_facet |
sea ice concentration shortwave infrared GOES imager remote sensing Science Q |
description |
An automated ice-mapping algorithm has been developed and evaluated using data from the GOES-13 imager. The approach includes cloud-free image compositing as well as image classification using spectral criteria. The algorithm uses an alternative snow index to the Normalized Difference Snow Index (NDSI). The GOES-13 imager does not have a 1.6 µm band, a requirement for NDSI; however, the newly proposed Mid-Infrared Sea and Lake Ice Index (MISI) incorporates the reflective component of the 3.9 µm or mid-infrared (MIR) band, which the GOES-13 imager does operate. Incorporating MISI into a sea or lake ice mapping algorithm allows for mapping of thin or broken ice with no snow cover (nilas, frazil ice) and thicker ice with snow cover to a degree of confidence that is comparable to other ice mapping products. The proposed index has been applied over the Great Lakes region and qualitatively compared to the Interactive Multi-sensor Snow and Ice Mapping System (IMS), the National Ice Center ice concentration maps and MODIS snow cover products. The application of MISI may open additional possibilities in climate research using historical GOES imagery. Furthermore, MISI may be used in addition to the current NDSI in ice identification to build more robust ice-mapping algorithms for the next generation GOES satellites. |
format |
Article in Journal/Newspaper |
author |
Peter Dorofy Rouzbeh Nazari Peter Romanov and Jeffrey Key |
author_facet |
Peter Dorofy Rouzbeh Nazari Peter Romanov and Jeffrey Key |
author_sort |
Peter Dorofy |
title |
Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager |
title_short |
Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager |
title_full |
Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager |
title_fullStr |
Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager |
title_full_unstemmed |
Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager |
title_sort |
development of a mid-infrared sea and lake ice index (misi) using the goes imager |
publisher |
MDPI AG |
publishDate |
2016 |
url |
https://doi.org/10.3390/rs8121015 https://doaj.org/article/759ad8f22a364cd2a429ae505e0e338a |
long_lat |
ENVELOPE(26.683,26.683,66.617,66.617) |
geographic |
Misi |
geographic_facet |
Misi |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Remote Sensing, Vol 8, Iss 12, p 1015 (2016) |
op_relation |
http://www.mdpi.com/2072-4292/8/12/1015 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs8121015 https://doaj.org/article/759ad8f22a364cd2a429ae505e0e338a |
op_doi |
https://doi.org/10.3390/rs8121015 |
container_title |
Remote Sensing |
container_volume |
8 |
container_issue |
12 |
container_start_page |
1015 |
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1766195182822227968 |