There is a newer version of this record available.

Dataset Open Access

Monthly MODIS LST data related to the article: A new fully gap-free time series of land surface temperature from MODIS LST data

Metz, Markus; Andreo, Verónica; Neteler, Markus


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="DOI">10.5281/zenodo.1115666</identifier>
  <creators>
    <creator>
      <creatorName>Metz, Markus</creatorName>
      <givenName>Markus</givenName>
      <familyName>Metz</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-4038-8754</nameIdentifier>
      <affiliation>mundialis GmbH &amp; Co. KG. Bonn, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Andreo, Verónica</creatorName>
      <givenName>Verónica</givenName>
      <familyName>Andreo</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-4633-2161</nameIdentifier>
      <affiliation>Department of Earth Observation Sciences. ITC - Faculty of Geo-Information Science and Earth Observation. University of Twente. Enschede, The Netherlands</affiliation>
    </creator>
    <creator>
      <creatorName>Neteler, Markus</creatorName>
      <givenName>Markus</givenName>
      <familyName>Neteler</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-1916-1966</nameIdentifier>
      <affiliation>mundialis GmbH &amp; Co. KG. Bonn, Germany</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Monthly MODIS LST data related to the article: A new fully gap-free time series of land surface temperature from MODIS LST data</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2017</publicationYear>
  <subjects>
    <subject>land surface temperature</subject>
    <subject>environmental monitoring</subject>
    <subject>urban heat waves</subject>
    <subject>MODIS</subject>
    <subject>reconstruction</subject>
    <subject>time series</subject>
    <subject>dataset</subject>
    <subject>open data</subject>
    <subject>earth observation</subject>
    <subject>remote sensing</subject>
    <subject>temperature</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2017-12-14</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1115666</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsCitedBy">10.3390/rs9121333</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1115665</relatedIdentifier>
  </relatedIdentifiers>
  <version>1.0.0</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Temperature time series with high spatial and temporal resolutions are important for several applications. The new MODIS Land Surface Temperature (LST) collection 6 provides numerous improvements compared to collection 5. However, being remotely sensed data in the thermal range, LST shows gaps in cloud-covered areas. With a novel method [1] we fully reconstructed the&amp;nbsp; daily global MODIS LST products MOD11C1 and MYD11C1 (spatial resolution: 3 arc-min, i.e. approximately 5.6 km at the equator). For this, we combined temporal and spatial interpolation, using emissivity and elevation as covariates for the spatial interpolation. Here we provide a time series of these reconstructed LST data aggregated as monthly average, minimum and maximum LST maps.&lt;/p&gt;

&lt;p&gt;[1]&amp;nbsp; Metz M., Andreo V., Neteler M. (2017): A new fully gap-free time series of Land Surface Temperature from MODIS LST data. Remote Sensing, 9(12):1333. DOI: http://dx.doi.org/10.3390/rs9121333&lt;/p&gt;

&lt;p&gt;LICENSE: Open Data Commons Open Database License (ODbL) http://opendatacommons.org/licenses/odbl/&lt;/p&gt;

&lt;p&gt;Acknowledgments: We are grateful to the NASA Land Processes Distributed Active Archive Center (LP DAAC) for making the MODIS LST data available. The dataset is based on MODIS Collection V006.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;The data available here for download are the reconstructed global MODIS LST products MOD11C1/MYD11C1 at a spatial resolution of 3 arc-min&lt;/strong&gt; (approximately 5.6 km at the equator; see https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table), &lt;strong&gt;aggregated to monthly data&lt;/strong&gt;. The data are provided in GeoTIFF format. The Coordinate Reference System (CRS) is identical to the MOD11C1/MYD11C1 product as provided by NASA. In WKT as reported by GDAL:&lt;br&gt;
&lt;br&gt;
GEOGCS[&amp;quot;Unknown datum based upon the Clarke 1866 ellipsoid&amp;quot;,&lt;br&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp; DATUM[&amp;quot;Not specified (based on Clarke 1866 spheroid)&amp;quot;,&lt;br&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; SPHEROID[&amp;quot;Clarke 1866&amp;quot;,6378206.4,294.9786982138982,&lt;br&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; AUTHORITY[&amp;quot;EPSG&amp;quot;,&amp;quot;7008&amp;quot;]]],&lt;br&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp; PRIMEM[&amp;quot;Greenwich&amp;quot;,0],&lt;br&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp; UNIT[&amp;quot;degree&amp;quot;,0.0174532925199433]]&lt;br&gt;
&amp;nbsp;&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;File name&lt;/strong&gt; abbreviations:&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;avg = average of daily averages&lt;/li&gt;
	&lt;li&gt;min = minimum of daily minima&lt;/li&gt;
	&lt;li&gt;max = maximum of daily maxima&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;Meaning of &lt;strong&gt;pixel values&lt;/strong&gt;:&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;The &lt;strong&gt;pixel values&lt;/strong&gt; are coded in &lt;strong&gt;degree Celsius * 100&lt;/strong&gt; (hence, to obtain &amp;deg;C divide the pixel values by 100.0).&lt;/li&gt;
&lt;/ul&gt;</description>
  </descriptions>
</resource>
1,536
25,247
views
downloads
All versions This version
Views 1,536590
Downloads 25,24712,576
Data volume 5.4 TB2.7 TB
Unique views 1,372543
Unique downloads 1,6251,198

Share

Cite as