United States of America GIS data
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Dates of Images: May 18 Summary Surface concentrations of PM2.5 Level 4 (L4) files were generated from Tropospheric Emissions: Monitoring of Pollution (TEMPO) Satellite and Advanced Baseline Imager (ABI) aerosol retrievals. The aerosol optical depth (AOD) and PM2.5 products were created at NOAA/NESDIS. The data covers the daytime observation windows during the active fire period from May 18, 2026. Because TEMPO relies on sunlight, these observations represent approximately 10 to 12 hours of sun-lit coverage per calendar day rather than a full 24-hour cycle. For emergency managers, this highlights total cumulative exposure durations, allowing officials to efficiently target health impacts in heavily affected communities. Caveats and Limitations Since the TEMPO instrument only makes observations during daylight hours, communities likely experienced significant additional nighttime smoke exposure that is not captured in these products. Furthermore, dense cloud cover can block satellite measurements, and these values may underestimate the true duration of smoke exposure in persistently cloudy areas. TEMPO data also exhibits more noise at the edges of clouds. Suggested Use While hours when surface PM2.5 was greater than 35 µg/m³ represents the health standard referred to as "Unhealthy for Sensitive Groups," this daytime-only product is developed only for rapid disaster response and should not be used for official EPA regulatory compliance, which requires a full 24-hour average. Satellite/Sensor/Resolution The surface PM2.5 product is estimated using data from two primary instruments: the TEMPO spectrometer aboard the Intelsat-40e commercial satellite and the Advanced Baseline Imager (ABI) on the GOES-R Series satellites (GOES-East and GOES-West). The final product is derived using a geographically weighted regression (GWR) algorithm that combines satellite aerosol optical depth (AOD) and aerosol layer height (ALH) with hourly data from AIRNOW surface monitors. While the raw TEMPO data has a native resolution of 2.0 km by 4.75 km, it is re-scaled to match the ABI's fixed grid, resulting in a final product with a spatial resolution of 2 km. Credits AOD and PM2.5 were provided by NOAA/NESDIS. Data analysis and cumulative exposure maps were created by Dr. Aishwarya Raman (BAERI/NASA ARC). Point of contact for TEMPO PM2.5 data - Amy Huff (Science and Technology Corporation (STC) at NOAA) and Shobha Kondragunta (NOAA). Esri REST Endpoint: See URL to the right. Data Download For data, please contact Amy Huff (Science and Technology Corporation (STC) at NOAA) and Shobha Kondragunta (NOAA).
ACS 2012 Legal and Statistical Entities Web Map Service; January 1, 2012 vintage
Date(s) of Images: Post-Event: 5/21/2026 Summary: Satellogic’s operates a commercial constellation of satellites and sensors that offers 4 band (R,G, B and NIR) acquisitions. True Color: The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. Color Infrared: The Color Infrared composite is created using the near-infrared, red, and green channels, allowing for the ability to see areas impacted from the fires. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. Resolution: 0.5 m to 1 m depending on generation of sensor used and viewing angle. Credits: NASA Disasters Program, Satellogic. For derived products: “Includes copyrighted material of Satellogic. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program."
Unified School Districts, Secondary School Districts, Elementary School Districts
ACS 2014 Legal and Statistical Entities Web Map Service; January 1, 2014 vintage
ACS 2014 Legal and Statistical Entities Web Map Service; January 1, 2014 vintage
ACS 2014 Legal and Statistical Entities Web Map Service; January 1, 2014 vintage
ACS 2014 Legal and Statistical Entities Web Map Service; January 1, 2014 vintage
ACS 2014 Legal and Statistical Entities Web Map Service; January 1, 2014 vintage
Dates of Images: Post-Event: May 20, 2026; May 19, 2026 Pre-Event: May 7, 2026; April 20, 2026 Date of Next Image: None Summary: The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. The Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. Suggested Use: The True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: 10 meters Credits: NASA Disasters/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202605_FIRE_CA/202609_sentinel2/ImageServer/WMSServer
ACS 2014 Legal and Statistical Entities Web Map Service; January 1, 2014 vintage
Dates of Images: Post-Event: 3/12, 3/14, 3/15, 3/16, 3/17, 3/18, 3/19, 3/20, 3/21, 3/22 Pre-Event: 3/10, 3/11, Date of Next Image: Varies by region, typically 6 days since previous pass. Summary: The Alaska Satellite Facility has developed false color Red, Green, Blue (RGB) and Radiometrically Terrain-Correct (RTC) composite products of the Sentinel-1A/B Synthetic Aperture Radar (SAR) instrument which assigns the co- and cross-polarization information to a channel in the composite. When used to support a flooding event, areas in blue denotes water present at the time of the satellite overpass before or after the start of the flooding event. Sentinel-1 RGB Decomposition of RTC VV and VH imagery over United States coastlines. Blue areas have low returns in VV and VH (smooth surfaces such as calm water, but also frozen/crusted soil or dry sand), Green areas have high returns in VH (volume scatterers such as vegetation or some types of snow/ice), and Red areas have relatively high VV returns and relatively low VH returns (such as urban or sparsely vegetated areas). Suggested Use: In the RGB images, water appears in blue, vegetated areas in shades of green and urban areas in bright orange. It is recommended to use this product with ancillary information to derive flooded areas. Satellite/Sensor: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1A satellite Resolution: 20 meters REST Endpoint: See URL below to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202603_FLOOD_HI/2605_sentinel1/ImageServer/WMSServer
ACS 2014 Legal and Statistical Entities Web Map Service; January 1, 2014 vintage
ACS 2015 Legal and Statistical Entities Web Map Service; January 1, 2015 vintage
ACS 2015 Legal and Statistical Entities Web Map Service; January 1, 2015 vintage
ACS 2015 Legal and Statistical Entities Web Map Service; January 1, 2015 vintage
ACS 2015 Legal and Statistical Entities Web Map Service; January 1, 2015 vintage
Public Use Microdata Areas and ZIP Code Tabulation Areas; 2020 Census - January 1, 2020 vintage; Generalized
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
Retirement Notice: This item is in mature support as of February 2026 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. This layer shows housing units in structure by tenure (owner or renter). This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized by the count and percent of housing units that are single-family detached homes. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top left. Vintage: 2019-2023ACS Table(s): B25024, B25032 (Not all lines of ACS table B25032 are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.gov The United States Census Bureau's American Community Survey (ACS):About the Survey Geography & ACS Technical Documentation News & Updates This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases. Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey. Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate. Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution. The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate. The estimate is controlled. A statistical test for sampling variability is not appropriate. The data for this geographic area cannot be displayed because the number of sample cases is too small.
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
ACS 2016 Legal and Statistical Entities Web Map Service; January 1, 2016 vintage
ACS 2017 Legal and Statistical Entities Web Map Service; January 1, 2017 vintage
ACS 2017 Legal and Statistical Entities Web Map Service; January 1, 2017 vintage
ACS 2017 Legal and Statistical Entities Web Map Service; January 1, 2017 vintage
ACS 2018 Legal and Statistical Entities Web Map Service; January 1, 2018 vintage
ACS 2018 Legal and Statistical Entities Web Map Service; January 1, 2018 vintage
ACS 2018 Legal and Statistical Entities Web Map Service; January 1, 2018 vintage
ACS 2018 Legal and Statistical Entities Web Map Service; January 1, 2018 vintage