Dataset Open Access

SMAP-HydroBlocks: Hyper-resolution satellite-based soil moisture over the continental United States

Noemi Vergopolan; Nathaniel W. Chaney; Ming Pan; Justin Sheffield; Hylke E. Beck; Craig R. Ferguson; Laura Torres-Rojas; Eric F. Wood


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{
  "description": "<p><a href=\"https://waterai.earth/smaphb/\">SMAP-HydroBlocks (SMAP-HB)</a>&nbsp;is a hyper-resolution satellite-based surface soil moisture product that combines NASA&#39;s Soil Moisture Active-Passive (SMAP) L3 Enhance product, hyper-resolution land surface modeling, radiative transfer modeling, machine learning, and in-situ observations. The dataset was developed over the continental United States at 30-m 6-hourly resolution (2015&ndash;2019), and it reports the top 5-cm surface soil moisture in volumetric units (m3/m3).</p>\n\n<p>This repository contains the following two versions of the SMAP-HydroBlocks dataset:</p>\n\n<ol>\n\t<li><strong>SMAP-HB_hru_6h.zip</strong>: SMAP-HydroBlocks data in the Hydrological Response Unit (HRU) space. Storing the data in the HRU space enables the entire 30-m 6-h dataset to be compressed to 33.8 GB. A python script and instructions to post-process and remap the data from the HRU-space into geographic coordinates (latitude, longitude) is provided at <a href=\"https://github.com/NoemiVergopolan/SMAP-HydroBlocks_postprocessing\">GitHub</a>. After post-processed, files are stored in netCDF4 format with a Plate Carr&eacute;e projection.</li>\n\t<li><strong>SMAP-HB_1km_6h.zip</strong>: SMAP-HydroBlocks data at 1-km 6-h resolution. This aggregated version is already post-processed, and thus it is already in geographic coordinates (latitude, longitude), stored in netCDF4 format, with a Plate Carr&eacute;e projection, and comprising 31.5 GB of data.&nbsp;</li>\n</ol>\n\n<p>Different subsets of the original dataset can be made available on request from Noemi Vergopolan (noemi.v.rocha@gmail.com). Data visualization, updates, and more information is available at <a href=\"http://waterai.earth/smaphb/\">https://waterai.earth/smaphb/</a>&nbsp;</p>\n\n<p>&nbsp;</p>\n\n<p>Please cite the following paper when using the dataset in any publication:</p>\n\n<p>Vergopolan, N., Chaney, N. W., Beck, H. E., Pan, M., Sheffield, J., Chan, S., &amp; Wood, E. F. (2020). Combining hyper-resolution land surface modeling with SMAP brightness temperatures to obtain 30-m soil moisture estimates. Remote Sensing of Environment, 242, 111740. <a href=\"https://doi.org/10.1016/j.rse.2020.111740\">https://doi.org/10.1016/j.rse.2020.111740</a></p>\n\n<p>Vergopolan, N., Chaney, N.W., Pan, M.&nbsp;<em>et al.</em>&nbsp;SMAP-HydroBlocks, a 30-m satellite-based soil moisture dataset for the conterminous US.&nbsp;<em>Sci Data</em>&nbsp;<strong>8,&nbsp;</strong>264 (2021). <a href=\"https://doi.org/10.1038/s41597-021-01050-2\">https://doi.org/10.1038/s41597-021-01050-2</a></p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Department of Civil and Environmental Engineering, Princeton University", 
      "@id": "https://orcid.org/0000-0002-7298-0509", 
      "@type": "Person", 
      "name": "Noemi Vergopolan"
    }, 
    {
      "affiliation": "Department of Civil and Environmental Engineering, Duke University", 
      "@type": "Person", 
      "name": "Nathaniel W. Chaney"
    }, 
    {
      "affiliation": "Department of Civil and Environmental Engineering, Princeton University", 
      "@type": "Person", 
      "name": "Ming Pan"
    }, 
    {
      "affiliation": "School of Geography and Environmental Science, Southampton University", 
      "@type": "Person", 
      "name": "Justin Sheffield"
    }, 
    {
      "affiliation": "Department of Civil and Environmental Engineering, Princeton University", 
      "@type": "Person", 
      "name": "Hylke E. Beck"
    }, 
    {
      "affiliation": "Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany", 
      "@type": "Person", 
      "name": "Craig R. Ferguson"
    }, 
    {
      "affiliation": "Department of Civil and Environmental Engineering, Duke University", 
      "@type": "Person", 
      "name": "Laura Torres-Rojas"
    }, 
    {
      "affiliation": "Department of Civil and Environmental Engineering, Princeton University", 
      "@type": "Person", 
      "name": "Eric F. Wood"
    }
  ], 
  "url": "https://zenodo.org/record/5206725", 
  "datePublished": "2021-08-18", 
  "version": "1.1", 
  "keywords": [
    "SMAP, HydroBlocks, hyper-resolution, soil moisture, hydrology, remote sensing, satellite, machine learning"
  ], 
  "@context": "https://schema.org/", 
  "distribution": [
    {
      "contentUrl": "https://zenodo.org/api/files/4b9f2e78-8b40-44fa-8f9a-c3469cdd9ee9/SMAP-HB_1km_6h.zip", 
      "encodingFormat": "zip", 
      "@type": "DataDownload"
    }, 
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      "contentUrl": "https://zenodo.org/api/files/4b9f2e78-8b40-44fa-8f9a-c3469cdd9ee9/SMAP-HB_hru_6h.zip", 
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  "identifier": "https://doi.org/10.5281/zenodo.5206725", 
  "@id": "https://doi.org/10.5281/zenodo.5206725", 
  "@type": "Dataset", 
  "name": "SMAP-HydroBlocks: Hyper-resolution satellite-based soil moisture over the continental United States"
}
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