Full Range Heat Anomalies - USA 2021

Notice: this is not the latest Heat Island Anomalies image service. To explore other versions of the data, visit the links below: Full Range Heat Anomalies - USA 2025 Full Range Heat Anomalies - USA 2024 Full Range Heat Anomalies - USA 2023 Full Range Heat Anomalies - USA 2022 Full Range Heat Anomalies - USA 2020 This layer contains the relative degrees Fahrenheit difference between any given pixel and the mean heat value for the city in which it is located, for every city in the contiguous United States. This 30-meter raster was derived from Landsat 8 imagery band 10 (ground-level thermal sensor) from the summer of 2021, with patching from summer of 2020 where necessary. Federal statistics over a 30-year period show extreme heat is the leading cause of weather-related deaths in the United States. Extreme heat exacerbated by urban heat islands can lead to increased respiratory difficulties, heat exhaustion, and heat stroke. These heat impacts significantly affect the most vulnerable—children, the elderly, and those with preexisting conditions. The purpose of this layer is to show where certain areas of cities are hotter or cooler than the average temperature for that same city as a whole. This dataset represents a snapshot in time. It will be updated yearly, but is static between updates. It does not take into account changes in heat during a single day, for example, from building shadows moving. The thermal readings detected by the Landsat 8 sensor are surface-level, whether that surface is the ground or the top of a building. Although there is strong correlation between surface temperature and air temperature, they are not the same. We believe that this is useful at the national level, and for cities that don’t have the ability to conduct their own hyper local temperature survey. Where local data is available, it may be more accurate than this dataset. Dataset Summary This dataset was developed using proprietary Python code developed at The Trust for Public Land, running on the Descartes Labs platform through the Descartes Labs API for Python. The Descartes Labs platform allows for extremely fast retrieval and processing of imagery, which makes it possible to produce heat island data for all cities in the United States in a relatively short amount of time. In order to click on the image service and see the raw pixel values in a map viewer, you must be signed in to ArcGIS Online, then Enable Pop-Ups and Configure Pop-Ups. Using the Urban Heat Island (UHI) Image Services The data is made available as an image service. There is a processing template applied that supplies the yellow-to-red or blue-to-red color ramp, but once this processing template is removed (you can do this in ArcGIS Pro or ArcGIS Desktop, or in QGIS), the actual data values come through the service and can be used directly in a geoprocessing tool (for example, to extract an area of interest). Following are instructions for doing this in Pro. In ArcGIS Pro, in a Map view, in the Catalog window, click on Portal. In the Portal window, click on the far-right icon representing Living Atlas. Search on the acronyms “tpl” and “uhi”. The results returned will be the UHI image services. Right click on a result and select “Add to current map” from the context menu. When the image service is added to the map, right-click on it in the map view, and select Properties. In the Properties window, select Processing Templates. On the drop-down menu at the top of the window, the default Processing Template is either a yellow-to-red ramp or a blue-to-red ramp. Click the drop-down, and select “None”, then “OK”. Now you will have the actual pixel values displayed in the map, and available to any geoprocessing tool that takes a raster as input. Below is a screenshot of ArcGIS Pro with a UHI image service loaded, color ramp removed, and symbology changed back to a yellow-to-red ramp (a classified renderer can also be used): Other Sources of Heat Island Information Please see these websites for valuable information on heat islands and to learn about exciting new heat island research being led by scientists across the country: EPA’s Heat Island Resource Center Dr. Ladd Keith, University of Arizona Dr. Ben McMahan, University of Arizona Dr. Jeremy Hoffman, Science Museum of Virginia Dr. Hunter Jones, NOAA Daphne Lundi, Senior Policy Advisor, NYC Mayor's Office of Recovery and Resiliency Disclaimer/Feedback With nearly 14,000 cities represented, checking each city's heat island raster for quality assurance would be prohibitively time-consuming, so The Trust for Public Land checked a statistically significant sample size for data quality. The sample passed all quality checks, with about 98.5% of the output cities error-free, but there could be instances where the user finds errors in the data. These errors will most likely take the form of a line of discontinuity where there is no city boundary; this type of error is caused by large temperature differences in two adjacent Landsat scenes, so the discontinuity occurs along scene boundaries (see figure below). The Trust for Public Land would appreciate feedback on these errors so that version 2 of the national UHI dataset can be improved. Contact [e-mail] with feedback.注意：本服务并非最新的热岛异常影像服务。若需探索该数据的其他版本，请访问以下链接：全范围热异常-美国2025、全范围热异常-美国2024、全范围热异常-美国2023、全范围热异常-美国2022、全范围热异常-美国2020。 本图层包含美国本土所有城市中，任一像素与其所在城市的平均热值之间的华氏相对温差。该30米分辨率栅格数据源自2021年夏季的Landsat 8影像第10波段（地面热红外传感器），必要时会使用2020年夏季的影像进行补全。 美国30年联邦统计数据显示，极端高温是美国与天气相关死亡的首要诱因。城市热岛效应加剧的极端高温会引发呼吸困难加剧、热衰竭及中暑。此类高温影响会显著波及最脆弱群体——儿童、老年人及存在基础疾病的人群。 本图层的设计目的是展示城市中某些区域相较于该城市整体平均温度的冷热差异。本数据集为某一时间点的快照，将按年度更新，更新周期内数据保持静态。其未考虑单日之内的温度变化，例如建筑阴影移动带来的影响。Landsat 8传感器所探测的热读数为地表温度，无论该表面是地面还是建筑楼顶。尽管地表温度与空气温度之间存在较强相关性，但二者并不等同。我们认为，该数据集在国家层面以及无法开展自主超本地温度勘测的城市中具有应用价值。若当地已有可用的本地数据，其精度可能高于本数据集。 数据集摘要 本数据集由美国公共土地信托基金（The Trust for Public Land）开发的专有Python代码构建，通过Python版Descartes Labs API在Descartes Labs平台上运行。Descartes Labs平台支持极快的影像检索与处理速度，使得在相对较短的时间内生成美国所有城市的热岛数据成为可能。 若要点击影像服务并在地图查看器中查看原始像素值，您需先登录ArcGIS Online，随后启用并配置弹窗功能。 城市热岛（Urban Heat Island, UHI）影像服务使用方法 本数据以影像服务形式发布。服务默认应用了处理模板，用于生成黄-红或蓝-红色阶，但移除该处理模板后（可在ArcGIS Pro、ArcGIS Desktop或QGIS中操作），即可获取服务中的原始数据值，并直接用于地理处理工具（例如提取感兴趣区域）。以下为在ArcGIS Pro中的操作步骤： 在ArcGIS Pro中，打开地图视图，在目录窗口中点击「门户」选项。在门户窗口中，点击最右侧代表「Living Atlas（生活地图集）」的图标。使用缩写“tpl”和“uhi”进行搜索，返回的结果即为UHI影像服务。右键点击任一搜索结果，从右键菜单中选择「添加至当前地图」。将影像服务添加至地图后，在地图视图中右键点击该服务，选择「属性」。在属性窗口中选择「处理模板」。窗口顶部的下拉菜单中，默认处理模板为黄-红色阶或蓝-红色阶。点击下拉菜单并选择「无」，随后点击「确定」。此时地图中将显示原始像素值，且该数据可被所有支持栅格输入的地理处理工具调用。 下图为ArcGIS Pro加载UHI影像服务、移除色阶并将符号系统改回黄-红色阶的截图（也可使用分级渲染器）： 其他热岛信息来源 请访问以下网站获取热岛相关的宝贵信息，并了解全美各地科学家主导的前沿热岛研究：美国环境保护署热岛资源中心、亚利桑那大学拉德·基思博士、亚利桑那大学本·麦克马汉博士、弗吉尼亚科学博物馆杰里米·霍夫曼博士、美国国家海洋和大气管理局亨特·琼斯博士、纽约市市长办公室恢复与韧性办公室高级政策顾问达芙妮·隆迪女士。 免责声明与反馈 本数据集涵盖近14000个城市，若对每个城市的热岛栅格进行质量检查将耗费极高的时间成本，因此美国公共土地信托基金仅对具有统计显著性的样本量进行了数据质量验证。该样本通过了所有质量检查，约98.5%的输出城市数据无错误，但用户仍可能发现部分数据错误。此类错误多表现为无城市边界的不连续线条；该类错误由相邻Landsat影像场景间的巨大温差导致，因此不连续现象会沿场景边界出现（参见下图）。美国公共土地信托基金欢迎用户反馈此类错误，以便优化全国UHI数据集的第二版。如有反馈，请联系[e-mail]。