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A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017
This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6335612/ https://www.ncbi.nlm.nih.gov/pubmed/30644853 http://dx.doi.org/10.1038/sdata.2018.300 |
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author | Tran, Hoang Nguyen, Phu Ombadi, Mohammed Hsu, Kuo-lin Sorooshian, Soroosh Qing, Xia |
author_facet | Tran, Hoang Nguyen, Phu Ombadi, Mohammed Hsu, Kuo-lin Sorooshian, Soroosh Qing, Xia |
author_sort | Tran, Hoang |
collection | PubMed |
description | This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Area product (MOD10C1) through a series of spatiotemporal filters followed by the Variational Interpolation (VI) algorithm; the filters and VI algorithm were evaluated using bootstrapping test. The dataset was validated over the period with the Landsat 7 ETM+ snow cover maps in the Seattle, Minneapolis, Rocky Mountains, and Sierra Nevada regions. The resulting cloud-free snow cover captured accurately dynamic changes of snow throughout the period in terms of Probability of Detection (POD) and False Alarm Ratio (FAR) with average values of 0.955 and 0.179 for POD and FAR, respectively. The dataset provides continuous inputs of snow cover area for hydrologic studies for almost two decades. The VI algorithm can be applied in other regions given that a proper validation can be performed. |
format | Online Article Text |
id | pubmed-6335612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-63356122019-01-18 A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017 Tran, Hoang Nguyen, Phu Ombadi, Mohammed Hsu, Kuo-lin Sorooshian, Soroosh Qing, Xia Sci Data Data Descriptor This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Area product (MOD10C1) through a series of spatiotemporal filters followed by the Variational Interpolation (VI) algorithm; the filters and VI algorithm were evaluated using bootstrapping test. The dataset was validated over the period with the Landsat 7 ETM+ snow cover maps in the Seattle, Minneapolis, Rocky Mountains, and Sierra Nevada regions. The resulting cloud-free snow cover captured accurately dynamic changes of snow throughout the period in terms of Probability of Detection (POD) and False Alarm Ratio (FAR) with average values of 0.955 and 0.179 for POD and FAR, respectively. The dataset provides continuous inputs of snow cover area for hydrologic studies for almost two decades. The VI algorithm can be applied in other regions given that a proper validation can be performed. Nature Publishing Group 2019-01-15 /pmc/articles/PMC6335612/ /pubmed/30644853 http://dx.doi.org/10.1038/sdata.2018.300 Text en Copyright © 2019, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Tran, Hoang Nguyen, Phu Ombadi, Mohammed Hsu, Kuo-lin Sorooshian, Soroosh Qing, Xia A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017 |
title | A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017 |
title_full | A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017 |
title_fullStr | A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017 |
title_full_unstemmed | A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017 |
title_short | A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017 |
title_sort | cloud-free modis snow cover dataset for the contiguous united states from 2000 to 2017 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6335612/ https://www.ncbi.nlm.nih.gov/pubmed/30644853 http://dx.doi.org/10.1038/sdata.2018.300 |
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