이 데이터 세트에는 전 세계 10, 000개 이상의 도시 클러스터에 대한 연간, 여름,겨울 주간 및 야간 표면 도시 열섬 (SUHI) 강도가 포함되어 있습니다. 이 데이터 세트는 간소화된 도시 범위 알고리즘을 사용하여 MODIS 8일 TERRA 및 AQUA 지표 온도 (LST) 제품, Landscan 도시 범위 데이터베이스, Global Multi-resolution Terrain Elevation Data 2010, 유럽우주기구 (ESA) 기후 변화 이니셔티브 (CCI) 토지 피복 데이터를 사용하여 생성되었습니다. 이 제품은 픽셀 수준 (다운스케일링 후 300m 해상도)과 2003~2018년의 도시 클러스터 평균으로 제공됩니다. 월별 합성 데이터는 도시 클러스터 평균으로만 제공됩니다.
Chakraborty, T., & Lee, X. (2019). 전 세계적으로 표면 도시 열섬을 특성화하고 시공간적 가변성에 대한 식물 제어를 조사하기 위한 단순화된 도시 범위 알고리즘 International
Journal of Applied Earth Observation and Geoinformation, 74, 269-280.
doi:10.1016/j.jag.2018.09.015
이 데이터 세트에는 전 세계 10, 000개 이상의 도시 클러스터의 연간, 여름,겨울 지표 도시 열섬 (SUHI) 강도가 낮과 밤에 대해 포함되어 있습니다. 이 데이터 세트는 MODIS 8일 TERRA 및 AQUA 지표 온도 (LST) 제품, Landscan 도시 범위 데이터베이스, 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)"]]
