Dieses Dataset enthält jährliche, sommerliche und winterliche Intensitäten der städtischen Wärmeinsel an der Oberfläche (Surface Urban Heat Island, SUHI) für Tag und Nacht für über 10.000 städtische Cluster weltweit. Der Datensatz wurde mit den MODIS-Produkten (Moderate Resolution Imaging Spectroradiometer) für die Oberflächentemperatur (Land Surface Temperature, LST) von TERRA und AQUA (8 Tage), der Landscan-Datenbank für die städtische Ausdehnung, den globalen Geländehöhendaten mit mehreren Auflösungen von 2010 und den Daten zur Landbedeckung der Climate Change Initiative (CCI) der Europäischen Weltraumorganisation (ESA) mit dem Simplified Urban-Extent Algorithm erstellt. Das Produkt ist sowohl auf Pixelebene (mit einer Auflösung von 300 m nach dem Herunterskalieren) als auch als Mittelwerte für städtische Ballungsräume von 2003 bis 2018 verfügbar. Die monatlichen Composites sind nur als Mittelwerte für städtische Cluster verfügbar.
Das Dataset ist in die folgenden sechs Komponenten unterteilt:
UHI_all_averaged::Bild mit der durchschnittlichen zusammengesetzten SUHI-Intensität für Tag und Nacht für das Jahr, den Sommer und den Winter.
UHI_monthly_averaged::Bild mit monatlichen Composites der SUHI-Intensität (Stadt-Wärmeinsel) für Tag und Nacht, die auf Clusterebene gemittelt wurden.
UHI_yearly_averaged::Bildersammlung von Cluster-Mittelwerten für jährliche Composites der SUHI-Intensität (Surface Urban Heat Island) bei Tag und Nacht von 2003 bis 2018.
UHI_yearly_pixel::Bildersammlung der räumlich disaggregierten (nominaler Maßstab von 300 m) jährlichen SUHI-Intensität für Tag und Nacht von 2003 bis 2018.
Summer_UHI_yearly_pixel::Bildersammlung der räumlich disaggregierten (Nominalskala von 300 m) SUHI-Intensität für Sommer, Tag und Nacht von 2003 bis 2018.
Winter_UHI_yearly_pixel::Bildersammlung mit räumlich disaggregierter (nominaler Maßstab von 300 m) SUHI-Intensität im Winter, tagsüber und nachts, von 2003 bis 2018.
Chakraborty, T., & Lee, X. (2019). Ein vereinfachter Algorithmus zur Bestimmung der Ausdehnung von Städten, um städtische Wärmeinseln an der Oberfläche auf globaler Ebene zu charakterisieren und die Auswirkungen der Vegetation auf ihre räumlich-zeitliche Variabilität zu untersuchen. International Journal of Applied Earth Observation and Geoinformation, 74, 269–280.
doi:10.1016/j.jag.2018.09.015
Dieses Dataset enthält die jährlichen, sommerlichen und winterlichen Intensitäten der städtischen Wärmeinsel an der Oberfläche (Surface Urban Heat Island, SUHI) für Tag und Nacht für über 10.000 städtische Ballungsräume weltweit. Das Dataset wurde mit den 8‑Tages-Produkten zur Oberflächentemperatur (Land Surface Temperature, LST) von TERRA und AQUA des MODIS, der Landscan-Datenbank für städtische Gebiete, dem Global Multi-resolution Terrain …
[null,null,[],[[["\u003cp\u003eThis dataset provides monthly, annual, summertime, and wintertime surface urban heat island (SUHI) intensity data for over 10,000 urban clusters globally from 2003 to 2018.\u003c/p\u003e\n"],["\u003cp\u003eSUHI intensity is provided for both daytime and nighttime, and the dataset includes cluster-mean monthly composites, as well as spatially disaggregated data at a 300m resolution.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset was created using MODIS land surface temperature products, Landscan urban extent data, terrain elevation data, and ESA land cover data using the Simplified Urban-Extent Algorithm.\u003c/p\u003e\n"],["\u003cp\u003eUsers can explore the data further using the Global Surface UHI Explorer web application or access it programmatically via the provided Earth Engine snippet.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is available under a CC-BY-4.0 license and citations for relevant publications are provided.\u003c/p\u003e\n"]]],["This dataset from the Yale Center for Earth Observation (YCEO) provides surface urban heat island (SUHI) intensity data from 2003 to 2018, covering over 10,000 urban clusters globally. The data, derived from MODIS and other sources, includes monthly, annual, summer, and wintertime composites for day and night. It offers cluster-mean values and pixel-level data at 300m resolution, all accessible through Google Earth Engine with specified visualization parameters. The data is licensed under CC-BY-4.0.\n"],null,["# YCEO Surface Urban Heat Islands: Spatially-Averaged Monthly Composites of Daytime and Nighttime Intensity\n\nDataset Availability\n: 2003-01-01T00:00:00Z--2018-12-31T00:00:00Z\n\nDataset Provider\n:\n\n\n [Yale Center for Earth Observation (YCEO)](https://yceo.yale.edu/research/global-surface-uhi-explorer)\n\nTags\n:\n[climate](/earth-engine/datasets/tags/climate) [uhi](/earth-engine/datasets/tags/uhi) [urban](/earth-engine/datasets/tags/urban) [yale](/earth-engine/datasets/tags/yale) \n\n#### Description\n\nThis dataset contains annual, summertime, and wintertime surface urban\nheat island (SUHI) intensities for day and night for over 10,000 urban clusters\nthroughout the world. The dataset was created using the MODIS 8-day TERRA and\nAQUA land surface temperature (LST) products, the Landscan urban extent\ndatabase, the Global Multi-resolution Terrain Elevation Data 2010, and the\nEuropean Space Agency (ESA) Climate Change Initiative (CCI) land cover data\nusing the Simplified Urban-Extent Algorithm. The product is available both at\nthe pixel level (at 300 m resolution after downscaling) and as urban cluster\nmeans from 2003 to 2018. The monthly composites are only available as urban\ncluster means.\n\nA summary of older versions,\nincluding changes from the dataset created and analyzed in the originally\npublished manuscript can be found on the\n[Yale Center for Earth Observation website](https://yceo.yale.edu/research/global-surface-uhi-explorer).\nThe dataset can also be explored using the [Global Surface UHI\nExplorer web application](https://yceo.users.earthengine.app/view/uhimap).\n\nThe dataset is split into the following six components:\n\n1. **UHI_all_averaged:** Image containing cluster-mean\n composite daytime and nighttime SUHI intensity for annual, summer,\n and winter.\n\n2. **UHI_monthly_averaged:** Image containing cluster-mean\n monthly composites of daytime and nighttime SUHI intensity.\n\n3. **UHI_yearly_averaged:** Image collection of cluster-mean\n yearly composites of daytime and nighttime SUHI intensity from 2003.\n to 2018.\n\n4. **UHI_yearly_pixel:** Image collection of spatially\n disaggregated (nominal scale of 300 m) annual daytime and nighttime\n SUHI intensity from 2003 to 2018.\n\n5. **Summer_UHI_yearly_pixel:** Image collection of spatially\n disaggregated (nominal scale of 300 m) summertime daytime and\n nighttime SUHI intensity from 2003 to 2018.\n\n6. **Winter_UHI_yearly_pixel:** Image collection of spatially\n disaggregated (nominal scale of 300 m) wintertime daytime and\n nighttime SUHI intensity from 2003 to 2018.\n\nThis asset is the second component.\n\n### Bands\n\n\n**Pixel Size**\n\n300 meters\n\n**Bands**\n\n| Name | Units | Pixel Size | Description |\n|-----------------|-------|------------|-------------------------|\n| `Jan_day_UHI` | °C | meters | January Daytime UHI |\n| `Jan_night_UHI` | °C | meters | January Nighttime UHI |\n| `Feb_day_UHI` | °C | meters | February Daytime UHI |\n| `Feb_night_UHI` | °C | meters | February Nighttime UHI |\n| `Mar_day_UHI` | °C | meters | March Daytime UHI |\n| `Mar_night_UHI` | °C | meters | March Nighttime UHI |\n| `Apr_day_UHI` | °C | meters | April Daytime UHI |\n| `Apr_night_UHI` | °C | meters | April Nighttime UHI |\n| `May_day_UHI` | °C | meters | May Daytime UHI |\n| `May_night_UHI` | °C | meters | May Nighttime UHI |\n| `Jun_day_UHI` | °C | meters | June Daytime UHI |\n| `Jun_night_UHI` | °C | meters | June Nighttime UHI |\n| `Jul_day_UHI` | °C | meters | July Daytime UHI |\n| `Jul_night_UHI` | °C | meters | July Nighttime UHI |\n| `Aug_day_UHI` | °C | meters | August Daytime UHI |\n| `Aug_night_UHI` | °C | meters | August Nighttime UHI |\n| `Sep_day_UHI` | °C | meters | September Daytime UHI |\n| `Sep_night_UHI` | °C | meters | September Nighttime UHI |\n| `Oct_day_UHI` | °C | meters | October Daytime UHI |\n| `Oct_night_UHI` | °C | meters | October Nighttime UHI |\n| `Nov_day_UHI` | °C | meters | November Daytime UHI |\n| `Nov_night_UHI` | °C | meters | November Nighttime UHI |\n| `Dec_day_UHI` | °C | meters | December Daytime UHI |\n| `Dec_night_UHI` | °C | meters | December Nighttime UHI |\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-4.0](https://spdx.org/licenses/CC-BY-4.0.html)\n\n### Citations\n\nCitations:\n\n- Chakraborty, T., \\& Lee, X. (2019). A simplified urban-extent algorithm\n to characterize surface urban heat islands on a global scale and examine\n vegetation control on their spatiotemporal variability. International\n Journal of Applied Earth Observation and Geoinformation, 74, 269-280.\n [doi:10.1016/j.jag.2018.09.015](https://doi.org/10.1016/j.jag.2018.09.015)\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.Image('YALE/YCEO/UHI/UHI_monthly_averaged/v4');\n\nvar visualization = {\n bands: ['Jan_day_UHI'],\n min: -1.5,\n max: 7.5,\n palette: [\n '313695', '74add1', 'fed976', 'feb24c', 'fd8d3c', 'fc4e2a', 'e31a1c',\n 'b10026']\n};\n\nMap.setCenter(-74.7, 40.6, 7);\n\nMap.addLayer(dataset, visualization, 'January Daytime UHI');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/YALE/YALE_YCEO_UHI_UHI_monthly_averaged_v4) \n[YCEO Surface Urban Heat Islands: Spatially-Averaged Monthly Composites of Daytime and Nighttime Intensity](/earth-engine/datasets/catalog/YALE_YCEO_UHI_UHI_monthly_averaged_v4) \nThis dataset contains annual, summertime, and wintertime surface urban heat island (SUHI) intensities for day and night for over 10,000 urban clusters throughout the world. The dataset was created using the MODIS 8-day TERRA and AQUA land surface temperature (LST) products, the Landscan urban extent database, the Global Multi-resolution Terrain ... \nYALE/YCEO/UHI/UHI_monthly_averaged/v4, climate,uhi,urban,yale \n2003-01-01T00:00:00Z/2018-12-31T00:00:00Z \n-49.98 -180 69.7 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://yceo.yale.edu/research/global-surface-uhi-explorer)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/YALE_YCEO_UHI_UHI_monthly_averaged_v4)"]]
