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    <identifier>10.57760/sciencedb.43093</identifier>
    <datestamp>2026-07-28T14:38:06Z</datestamp>
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  <dc:date>2026-07-28</dc:date>
  <dc:title>1 km annual daytime surface urban heat island intensity dataset for the Yangtze River Delta, China, 2001&amp;ndash;2024</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.43093</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset provides annual daytime urban heat island intensity data for the Yangtze River Delta region from 2001 to 2024, with a spatial resolution of 1000 meters and a total of 24 annual grids. The research scope adopts the caliber of 16 cities in the Yangtze River Delta Economic Zone in 2010, including Shanghai, Nanjing, Wuxi, Changzhou, Suzhou, Nantong, Yangzhou, Zhenjiang, and Taizhou in Jiangsu Province, as well as Hangzhou, Ningbo, Jiaxing, Huzhou, Shaoxing, Zhoushan, and Taizhou in Zhejiang Province.&amp;nbsp;Data production is based on the original data specifications, using MODIS MCD12Q1 annual land cover products and MOD11A2 8-day surface temperature products to identify urban built-up areas and rural background areas on the Google Earth Engine platform. The urban built-up area adopts the &amp;quot;urban and built-up area&amp;quot; type in the IGBP land cover classification, and constructs a rural reference area with a buffer range of 10-30 kilometers around the city; The intensity of urban heat island on the surface is defined as the difference between the average effective daytime surface temperature of urban built-up areas and rural background areas throughout the year. Positive values indicate that the daytime surface temperature in urban built-up areas is higher than that in rural background areas, while negative values indicate relatively cold islands.&amp;nbsp;The data is stored in single band Float32 GeoTIFF format, with a coordinate system of WGS 84/UTM 46N (EPSG: 32646), a grid size of 503 &amp;times; 588 pixels, invalid values of -9999, and temperature differences in degrees Celsius. The data has undergone surface temperature quality identification screening, removal of invalid pixels such as clouds, ice and snow, outlier detection, and annual grid integrity and spatial reference consistency checks. It can be used for spatiotemporal changes in urban thermal environment, urbanization effects, hot air risk assessment, national land spatial planning, and climate adaptation research in the Yangtze River Delta region.&amp;nbsp;</dc:description>
  <dc:subject>Yangtze River Delta; surface urban heat island intensity; land surface temperature</dc:subject>
  <dc:creator>Song Yilin</dc:creator>
  <dc:creator>jiang he ping</dc:creator>
  <dc:creator>Earth Resource Data Cloud</dc:creator>
  <dc:creator>Tengyue</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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