Wildfire Risk to Communities: Spatial datasets of wildfire risk for populated areas in the United States: 2nd edition

The data included in this publication depict components of wildfire risk specifically for populated areas in the United States. These datasets represent where people live in the United States and the in situ risk from wildfire, i.e., the risk at the location where the adverse effects take place.

National wildfire hazard datasets of annual burn probability and fire intensity, generated by the USDA Forest Service, Rocky Mountain Research Station and Pyrologix LLC, form the foundation of the Wildfire Risk to Communities data. Vegetation and wildland fuels data from LANDFIRE 2020 (version 2.2.0) were used as input to two different but related geospatial fire simulation systems. Annual burn probability was produced with the USFS geospatial fire simulator (FSim) at a relatively coarse cell size of 270 meters (m). To bring the burn probability raster data down to a finer resolution more useful for assessing hazard and risk to communities, we upsampled them to the native 30 m resolution of the LANDFIRE fuel and vegetation data. In this upsampling process, we also spread values of modeled burn probability into developed areas represented in LANDFIRE fuels data as non-burnable. Burn probability rasters represent landscape conditions as of the end of 2020. Fire intensity characteristics were modeled at 30 m resolution using a process that performs a comprehensive set of FlamMap runs spanning the full range of weather-related characteristics that occur during a fire season and then integrates those runs into a variety of results based on the likelihood of those weather types occurring. Before the fire intensity modeling, the LANDFIRE 2020 data were updated to reflect fuels disturbances occurring in 2021 and 2022. As such, the fire intensity datasets represent landscape conditions as of the end of 2022. The data products in this publication that represent where people live, reflect 2021 estimates of housing unit and population counts from the U.S. Census Bureau, combined with building footprint data from Onegeo and USA Structures, both reflecting 2022 conditions.

The specific raster datasets included in this publication include:

Building Count: Building Count is a 30-m raster representing the count of buildings in the building footprint dataset located within each 30-m pixel.

Building Density: Building Density is a 30-m raster representing the density of buildings in the building footprint dataset (buildings per square kilometer [km²]).

Building Coverage: Building Coverage is a 30-m raster depicting the percentage of habitable land area covered by building footprints.

Population Count (PopCount): PopCount is a 30-m raster with pixel values representing residential population count (persons) in each pixel.

Population Density (PopDen): PopDen is a 30-m raster of residential population density (people/km²).

Housing Unit Count (HUCount): HUCount is a 30-m raster representing the number of housing units in each pixel.

Housing Unit Density (HUDen): HUDen is a 30-m raster of housing-unit density (housing units/km²).

Housing Unit Exposure (HUExposure): HUExposure is a 30-m raster that represents the expected number of housing units within a pixel potentially exposed to wildfire in a year. This is a long-term annual average and not intended to represent the actual number of housing units exposed in any specific year.

Housing Unit Impact (HUImpact): HUImpact is a 30-m raster that represents the relative potential impact of fire to housing units at any pixel, if a fire were to occur. It is an index that incorporates the general consequences of fire on a home as a function of fire intensity and uses flame length probabilities from wildfire modeling to capture likely intensity of fire.

Housing Unit Risk (HURisk): HURisk is a 30-m raster that integrates all four primary elements of wildfire risk - likelihood, intensity, susceptibility, and exposure - on pixels where housing unit density is greater than zero.The geospatial data products described and distributed here are part of the Wildfire Risk to Communities project. This project was directed by Congress in the 2018 Consolidated Appropriations Act (i.e., 2018 Omnibus Act, H.R. 1625, Section 210: Wildfire Hazard Severity Mapping) to help U.S. communities understand components of their relative wildfire risk profile, the nature and effects of wildfire risk, and actions communities can take to mitigate risk. The first edition of these data represented the first time wildfire risk to communities had been mapped nationally with consistent methodology. They provided foundational information for comparing the relative wildfire risk among populated communities in the United States. In this version, the 2nd edition, we use improved modeling and mapping methodology and updated input data to generate the current suite of products.See the Wildfire Risk to Communities website at https://www.wildfirerisk.org for complete project information and an interactive web application for exploring some of the datasets published here. We deliver the data here as zip files by U.S. state (including AK and HI), and for the full extent of the continental U.S.

This data publication is a second edition and represents an update to any previous versions of Wildfire Risk to Communities risk datasets published by the USDA Forest Service. There are two companion data publications that are part of the WRC 2.0 data update: one that characterizes landscape-wide wildfire hazard and risk for the nation (Scott et al. 2024, https://doi.org/10.2737/RDS-2020-0016-2), and one that delineates wildfire risk reduction zones and provides tabular summaries of wildfire hazard and risk raster datasets (Dillon et al. 2024, https://doi.org/10.2737/RDS-2024-0030).

本出版物所包含的数据描绘了美国人口密集区域的森林火灾风险组成部分。这些数据集表征了美国人民居住的区域以及火灾现场的现实风险，即不利影响发生的地点风险。国家森林火灾危害数据集，包括年度燃烧概率和火势强度，由美国农业部森林服务局、落基山研究站和Pyrologix LLC生成，构成了社区森林火灾风险数据的基础。LANDFIRE 2020（版本2.2.0）的植被和野外燃料数据被用作两个不同但相关的地理空间火灾模拟系统的输入。年度燃烧概率采用美国森林服务局地理空间火灾模拟器（FSim）在相对粗略的270米（m）单元格尺寸下生成。为了将燃烧概率栅格数据提升到更细的分辨率，以便于评估危害和风险，我们对这些数据进行上采样，以达到LANDFIRE燃料和植被数据的原生30米分辨率。在上采样过程中，我们还把模拟的燃烧概率值分散到LANDFIRE燃料数据中表示的开发区域，作为不可燃区域。燃烧概率栅格表示截至2020年末的景观条件。火势强度特征以30米分辨率通过一个过程进行建模，该过程执行一系列全面的FlamMap运行，涵盖火灾季节中发生的全部与天气相关的特征，并将这些运行综合成多种基于这些天气类型发生可能性的结果。在火势强度建模之前，LANDFIRE 2020数据已更新以反映2021年和2022年发生的燃料扰动。因此，火势强度数据集表示截至2022年末的景观条件。本出版物中代表人们居住位置的数据产品反映了2021年美国人口普查局对住宅单位和人口数量的估计，以及来自Onegeo和USA Structures的建筑足迹数据，两者均反映了2022年的情况。

本出版物包含的具体栅格数据集包括：

建筑数量：建筑数量是一个30米栅格，表示位于每个30米像素内的建筑足迹数据集中的建筑数量。

建筑密度：建筑密度是一个30米栅格，表示建筑足迹数据集中的建筑密度（每平方公里[km²]的建筑数量）。

建筑覆盖率：建筑覆盖率是一个30米栅格，描绘了建筑足迹覆盖的可居住土地面积百分比。

人口数量（PopCount）：PopCount是一个30米栅格，像素值表示每个像素的住宅人口数量。

人口密度（PopDen）：PopDen是一个30米栅格，表示住宅人口密度（人/km²）。

住宅单位数量（HUCount）：HUCount是一个30米栅格，表示每个像素的住宅单位数量。

住宅单位密度（HUDen）：HUDen是一个30米栅格，表示住宅单位密度（住宅单位/km²）。

住宅单位暴露度（HUExposure）：HUExposure是一个30米栅格，表示每年像素内预期可能暴露于森林火灾的住宅单位数量。这是一个长期年度平均值，并不旨在代表任何特定年份中实际暴露的住宅单位数量。

住宅单位影响（HUImpact）：HUImpact是一个30米栅格，表示任何像素上住宅单位在发生火灾时相对潜在的火灾影响。这是一个综合指标，将火灾对家庭的总体影响作为火势强度和火焰长度概率的函数，以捕捉火灾模拟中可能强度的可能性。

住宅单位风险（HURisk）：HURisk是一个30米栅格，综合了四个主要的风险要素——可能性、强度、易损性和暴露性——在住宅单位密度大于零的像素上。此处描述和分发的地方地理空间数据产品是森林火灾风险对社区项目的一部分。该项目由2018年综合拨款法案（即2018年综合法案，H.R. 1625，第210节：森林火灾危害严重性制图）指导，旨在帮助美国社区了解其相对森林火灾风险特征组成部分、森林火灾风险的性质和影响，以及社区可以采取的措施来减轻风险。这些数据的第一版代表了首次使用一致的方法在全国范围内制图社区森林火灾风险。它们为比较美国人口密集社区之间的相对森林火灾风险提供了基础信息。在本版中，第二版，我们使用了改进的建模和制图方法，并更新了输入数据，以生成当前的产品套件。有关完整的项目信息和交互式网络应用程序，请访问森林火灾风险对社区网站https://www.wildfirerisk.org。我们以美国各州（包括阿拉斯加和夏威夷）的zip文件形式提供数据，以及美国大陆的全范围数据。

本数据出版物是第二版，代表了美国农业部森林服务局先前发布的任何版本的社区森林火灾风险数据集的更新。有两个配套的数据出版物是WRC 2.0数据更新的组成部分：一个是描述全国范围内景观级森林火灾危害和风险（Scott等，2024年，https://doi.org/10.2737/RDS-2020-0016-2），另一个是划定森林火灾风险降低区，并提供森林火灾危害和风险栅格数据集的表格摘要（Dillon等，2024年，https://doi.org/10.2737/RDS-2024-0030）。