Global GIS data
＋ Follow new data4,064 datasets.
uav imagery by Luka Koens, acquired 2026-07-31 to 2026-07-31, 1.9 cm per pixel, published on OpenAerialMap.
Apparent Visible Wavelength (AVW) from the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Ocean Color Instrument (OCI). The AVW data product leverages OCI's continuous, hyperspectral set of remote sensing reflectance wavelengths spanning the visible spectrum (from 400-700 nanometers, nm) to calculate AVW in units of nm, a single value describing the dominant color of the water being observed (Vandermeulen et al. 2020; Vandermeulen and Cetinic 2024). AVW is provided as global, 8-day averages mapped to a standard, equal-angle, latitude-longitude grid of approximately 0.04 degrees, or 4 kilometers (km) at the equator. Pixels with no data values are masked (excluded) due to presence of land, cloud cover, or other features marked by quality control flags as described below. Data Layer Summary Name, units Apparent Visible Wavelength [nm] Apparent visible wavelength, a measure of ocean color, in units of nanometers (nm) Spatial resolution 4 km2 Level-3, mapped to standard grid, global coverage Time Resolution 8 day average Each pixel represents an average of the valid, daily values observed within that grid element during the 8-day interval (approx 1 week). Note: 8 day average data layer is calculated from daily, "refined" (archive-quality) Level 3 PACE AVW products, which are available at NASA Earthdata via this link in NetCDF format as part of the Apparent Optical Properties (AOP) suite. NASA Earthdata account required to download. Data Version Version 3.2 Data versions change as improved calibration, validation, algorithm refinements, etc are applied over time. See Version 3.2 Release Notes for details. Latency ̃1 month This imagery service provides “refined” (archive-quality) PACE data products from March 2024-present, which have an approx 1 month latency. Note: Lower latency “near real time (NRT)” Level 3 PACE AVW products are available at NASA Earthdata via this link in NetCDF format as part of the Apparent Optical Properties (AOP) suite. Latency typically account required to download. What can I do with this layer? AVW is simple and intuitive spectral classification tool that enables a more manageable handling of complex spectral information for aquatic science applications (Vandermeulen et al. 2020). Changing values in AVW are a measure of change in the ocean's dominant color: lower AVW values represent more clear water and higher values represent more turbid water. AVW is a useful as an optical water-type index, partitioning a region's ocean observations into types relevant to water quality and marine ecosystem processes. Additionally, AVW can be applied to datasets of varying multi- and hyperspectral resolutions. This provides continuity between PACE AVW and AVW from heritage satellite ocean color sensors (those launched prior to PACE), enabling examination of longer term (up to decadal) trends of AVW in a given region (Vandermeulen et al. 2020; Vandermeulen and Cetinic 2024). The time (8 day average) and space (4 km2) resolution of this data layer supports weekly to seasonal and annual insight at sub-regional to global scales. What should I know about the data? Data Status (Maturity): This product is provisional, which means that product results have been reviewed and are in family with heritage data products or other basis of expectation, but have not yet been extensively validated and so may still contain significant errors. Data layer is sufficient for qualitative determinations of product fitness-for-purpose, for testing by operational users, and may be suitable for scientific publication. Data Masking: These products are Level 3, globally-binned products from NASA’s Ocean Biology Processing Group (OBPG), which by default are masked (pixel data value is set to null, or no data) according to a standard set of quality control parameters. For a list of these parameters, see the third column of the table included here: https://oceancolor.gsfc.nasa.gov/resources/atbd/ocl2flags/. Algorithm Theoretical Basis Document (ATBD): See ATBD for algorithm details including scientific theory, calculations, etc. at DOI 10.5067/KAROCHG01RYJ. Where do I go with further questions? Visit NASA’s Earthdata Forum where users can post questions that are answered by the personnel working at NASA with the PACE mission and/or the Ocean Biology Distributed Active Archive Center (OB.DAAC) that processes and distributes PACE data. First, follow this link to view only “PACE” and “OBDAAC” tagged questions on the Earthdata Forum. Then search and read through previous posts for your question. If it has not yet been asked please post your question in the Forum and be sure "PACE" and "OBDAAC" filter tags are applied. Mission and Product Background PACE Mission Overview: Launched in February 2024, NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) observatory uniquely provides near-daily, hyperspectral coverage of Earth’s surface, plus hyperspectral and hyperangular polarimetry. PACE is a comprehensive Earth System mission, delivering all new, space-based information on the health and diversity of aquatic and terrestrial life (algae, plants), aerosol properties & modes (e.g. smoke, dust), cloud types, and more. The Ocean Color Instrument (OCI), PACE's primary sensor, is a hyperspectral (5 nm resolution) imaging spectrometer that measures properties of light from the ultraviolet (UV, 340 nm) through visible and near infrared (NIR, 895 nm) portions of the electromagnetic spectrum in 1.25 to 2.5 nm steps, plus 7 shortwave infrared (SWIR) bands (Werdell et al. 2019). Observations from OCI are moderate spatial resolution (1.2 km2), enabling a relatively frequent revisit time of 1-2 days. This combination of continuous, global coverage and spectral capabilities is unmatched by any other satellite platform, public or private. PACE benefits society by expanding our foundational knowledge of Earth and enabling novel, space-based science and applications tools across water resources (e.g. fisheries), air quality, land monitoring & management, and more. What does AVW represent and how is it calculated? AVW is a one-dimensional geophysical metric that is inherently correlated to ocean color, as defined by the remote sensing reflectance (R(λ)rs) spectral shape across the visible region of the spectrum (400-700 nm; Vandermeulen et al. 2020). R(λ)rs, the AVW algorithm input, is used to calculate the weighted harmonic mean of the wavelengths. Output is an AVW in units of nm, a quantitative descriptor of weighted mean color reflected from the water's surface. PACE AVW spans PACE's continuous hyperspectral R(λ)rs observations across the visible spectrum while AVW from heritage multi-spectral sensors is calculated from their 4-10 available R(λ)rs channels (Vandermeulen and Cetinic 2024). The entire visible spectrum is utilized in the calculation of AVW, affording the opportunity to describe and analyze spectral trends in R(λ)rs in terms of a single variable (Vandermeulen et al. 2020). This simplification allows for streamlined visualisation and monitoring of small changes in apparent color from highly complex optical data. AVW's dimensionality reduction of spectral information is a robust and user-friendly means to describe and analyze R(λ)rs in terms of spatial and temporal trends and variability. Also, AVW can be utilized across heritage and current ocean color sensors, allowing for continuity and long term monitoring of AVW in aquatic ecosystems. What other PACE data layers are available? This data layer is 1 of 11 PACE products initially selected for the Living Atlas catalog from the mission’s comprehensive aquatic, atmospheric, and terrestrial product catalog. Click here to view all 11 PACE Living Atlas imagery services. Global, hyperspectral remote sensing reflectance observations from OCI with over 250 spectral bands, and used to derive many of PACE's aquatic products, are available to download in NetCDF format from NASA Earthdata as Level 3, mapped data with 4 km2 resolution or as Level 2 granules at unprojected, native spatial resolution (no finer than 1.2km2). To learn more about obtaining PACE data from NASA, first learn about PACE data access here, next decide which product(s) you would like to use, then go to NASA Earthdata to find your product(s) of interest in NetCDF format, which can be downloaded and then imported into ArcGIS. To learn about using Earthdata Search to narrow your data product selection, watch this tutorial. An Earthdata account is needed to download data from NASA, sign up here. How can I stay up to date with the PACE mission? Join the PACE Community for mission news, events, new product release announcements, and to receive our newsletters. Would you like to see imagery services for more PACE products? Please let us know here. References: Vandermeulen, R. and Cetinic, I., authors. (2024) Algorithm theoretical basis document: Apparent Visible Wavelength, Version 1.1. NASA Goddard Space Flight Center, Ocean Ecology Lab. https://doi.org/10.5067/KAROCHG01RYJ. Vandermeulen, R. A., Mannino, A., Craig, S. E. & Werdell, P. J. (2020) 150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean. Remote Sensing of Environment, 247, 111900. https://doi.org/10.1016/j.rse.2020.111900 Werdell, P. J. et al. (2019) The Plankton, Aerosol, Cloud, Ocean Ecosystem Mission: Status, Science, Advances. Bulletin of the American Meteorological Society, 100, 1775–1794. https://doi.org/10.1175/BAMS-D-18-0056.1
The tsunami hazard map indicates the mean wave run-up height on the coast for a return period of 475 years. The map has coastal coverage with points in the countries with tsunami hazard. Run-up values below 0.1 m are considered as “Low”; run-up values between 0.1 m and 2 m (inclusive) are considered as “Moderate”; run-up values greater than 2 m are considered as “High”. Background paper: Multi-hazard Disaster Risk Model of Infrastructure and Buildings at the Global Level (2023). Cardona, O.D., Bernal, G.A., Villegas, C.P., Molina, J.F., Herrera, S.A., Marulanda, M.C., Rincón, D.F., Grajales, S., Marulanda, P.M., Gonzalez, D., Maskrey, A. (2023). https://giri.unepgrid.ch/sites/default/files/2023-11/2.4-INGENIAR-CDRI-Background-Report-Risk-model.pdf Release date: Fri Jun 30 2023 The layer was clipped to the geographic boundaries of 1) IDB Borrowing Member Countries, 2) Caribbean Development Bank (CDB) Borrowing Countries, 3) Organization of Eastern Caribbean States (OECS) Member Countries.
__Note__: _A new version of this item is available for your use. This mature version of the map remains available for use in existing applications. This item will be retired in December 2024. There is 2020 data available in the newer 9-class dataset._ Global estimates of 10-class land use/land cover (LULC) for 2020, derived from ESA Sentinel-2 imagery at 10m resolution. This dataset was generated by Impact Observatory, who used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. The global map was produced by applying this model to the relevant yearly Sentinel-2 scenes on the Planetary Computer. This dataset is also available on the ArcGIS Living Atlas of the World.
Level 1 thermal inrared data (bands 10 and 11) from Landat 8 and Landsat 9.
This Collection provides Sentinel-5P Level-2 O3 PR products, which contains ozone concentration for 33 levels in the atmosphere.
This Collection provides Sentinel-5P Level-1 RA BD1 products, which contains Earth radiance spectra for spectral band 1.
This Collection provides Sentinel-5P Level-1 RA BD1 products, which contains Earth radiance spectra for spectral band 1.
This Collection provides Sentinel-5P Level-2 CH4 products, which contains high-resolution imagery of methane concentrations.
The Copernicus Sentinel-3 SLSTR RBT products provide global brightness temperatures and radiances with a spatial resolution of 500 meters for reflectance bands and 1 kilometer for thermal infrared bands, useful for environmental monitoring and climate studies.
This Collection provides Sentinel-5P Level-2 NO2 products, which contains high-resolution imagery of nitrogen dioxide concentrations.
Current and recent floods alerts from the Global Disaster Alert and Coordination System (GDACS), a cooperation of the United Nations and the European Commission, with alert level, severity and affected population.
This Collection provides Sentinel-5P Level-2 AER LH products, which contains high-resolution imagery of the UV Aerosol Index (UVAI), also called the Absorbing Layer Height (ALH).
The Harmonized Landsat and Sentinel-2 (HLS) project takes input data from the joint NASA/USGS Landsat 8 and Landsat 9 satellites and the European Space Agency's Sentinel-2A, Sentinel-2B, and Sentinel-2C satellites to generate a harmonized, analysis-ready surface reflectance data product with observations every 1.6 days. Intended Use: The frequent revisit times of HLS allow for time series of land surface applications at the field/plot scale, which supports a wide range of applications, including agricultural health, insect infestations, and natural hazard impacts. The HLSS30 and HLSL30 products are gridded to the same resolution and tiling system and thus are “stackable” for time series analysis. Key Properties: Geographic Coverage: Global Land Temporal Coverage: March 2026 - Present Spatial Resolution: 30-meter Revisit Time: ~1 Day Update Frequency: Daily Product Level: Level-3 Source Data Coordinate System: Universal Transverse Mercator (UTM) WGS84 Service Coordinate System: Web Mercator Auxiliary Sphere (EPSG:3857) Multispectral Bands NameDescriptionUnitsData TypeFill ValueScale FactorBand 1Coastal AerosolN/Aint16-99990.0001Band 2BlueN/Aint16-99990.0001Band 3GreenN/Aint16-99990.0001Band 4RedN/Aint16-99990.0001Band 5NIRN/Aint16-99990.0001Band 6SWIR 1N/Aint16-99990.0001Band 7SWIR 2N/Aint16-99990.0001Band 9CirrusN/Aint16-99990.0001Band 10TIRS 1N/Aint16-99990.01Band 11TIRS 2N/Aint16-99990.01FmaskQuality BitsBit Fielduint8255N/ASAASun Azimuth AngleDegreeuint16400000.01SZASun Zenith AngleDegreeuint16400000.01VAAView Azimuth AngleDegreeuint16400000.01VZAView Zenith AngleDegreeuint16400000.01Processing Templates Server-side renderings available on this layer (select via the Rendering / Image Display options). The default rendering is Natural Color. Band-combination templates are for visualization; index templates (NDVI, NDWI, NBR, NDBI) return values suitable for analysis. "DRA" applies dynamic range adjustment; "Cloud Mask" variants suppress pixels flagged by the Fmask quality band. NDVI Colormap — Normalized difference vegetation index (NDVI) with colormap. Dark green represents vigorous vegetation and brown represents sparse vegetation. It is computed as (b5 - b4) / (b5 + b4) and is suitable for vegetation, land cover and plant health monitoring. (also available: Cloud Mask) NDVI Raw — Normalized difference vegetation index (NDVI) computed as (b5 - b4) / (b5 + b4) and is suitable for vegetation, land cover and plant health monitoring. (also available: Cloud Mask) NDWI Raw — The NDWI index is computed as Green(Band03)-NIR(Band05)/ Green(Band03)+NIR(Band05) and is most suitable for mapping of water bodies, droughts, boundary evaluation. Water bodies have strong absorbability and low radiation within the visible to infrared spectral ranges and this index is based on this phenomenon. (also available: Cloud Mask) Natural Color — Natural Color bands red, green, blue(4, 3, 2) displayed with fixed stretch applied. (also available: Cloud Mask, DRA, DRA and Cloud Mask) Normalized Burn Ratio — The NBR index is computed as NIR(Band05)-SWIR(Band7)/NIR(Band05)+SWIR(Band7) and appropriate for highlighting burned areas and estimating fire severity. It highlights burnt areas in fire zones greater than 500 acres. You will need to generate a differenced NBR image by subtracting a post-fire image from a pre-fire image. The resulting darker pixels represent burned areas. (also available: Cloud Mask) Normalized Difference Built-Up Index — The NDBI index is computed as SWIR(Band6)-NIR(Band05)/ SWIR(Band6)+NIR(Band05) and is suitable for watershed runoff predictions, tracking urbananisation and land-use planning. It highlights urban areas with higher reflectance in the SWIR region, compared to the NIR region. This index also contains a cloud mask. (also available: Cloud Mask) Limitations of Use: HLSL30 v2.0 data contain several known limitations related to atmospheric correction, cloud masking, geolocation, and metadata that users should carefully consider before analysis. A full description of these known issues is available here. Latency: Imagery tiles are configured to render at a 150 meter scale. Dynamic Mosaic rendering can take an extended period of time. Resource Links: Download Data User Guide General Documentation For inquiries about this service, please contact support@earthdata.nasa.gov or post/view questions on the Earthdata Forum Citation: Neigh, C., Ju, J., Roger, J.-C., Skakun, S., Vermote, E., Claverie, M., Dungan, J., Yin, Z., Freitag, B., & Justice, C. (2021). HLS Operational Land Imager Surface Reflectance and TOA Brightness Daily Global 30m v2.0 [Dataset]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/HLS/HLSL30.002
Natural Earth admin 0 boundary lines maritime indicator at 1:10 million scale: public domain cartographic vector data built to make small-scale world, regional and country maps.
The Prediction Of Worldwide Energy Resource (POWER) Project gathers NASA Earth Observation data and parameters related to the fields of surface solar irradiance and meteorology to serve the public in several free, easy-to-access, and easy-to-use methods. POWER helps communities become resilient amid observed climate variability by improving data accessibility, aiding research in renewable energy development, building energy efficiency, and agriculture sustainability. POWER is funded through the NASA Earth Action Program within the Earth Science Mission Directorate at NASA Langley Research Center (LaRC). --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- This climatology meteorology service provides climatologically-averaged global Analysis Ready Data (ARD) parameters for 2001 to 2020 for POWER’s communities. Time Interval: Climatology Time Extent: 2001/01/01 to 2020/12/31 (monthly and annual averages) Time Standard: Local Sidereal Time (LST) Grid Size: 0.5 x 0.5 Degree Projection: GCS WGS84 Extent: Global Source: NASA Prediction Of Worldwide Energy Resources (POWER) For questions or issues please email: larc-power-project@mail.nasa.gov Meteorology Data Sources: NASA's GMAO MERRA-2 archive (Jan. 1, 2001 – Dec. 31, 2020) Meteorology Data Parameters: CDD10 (Cooling Degree Days Above 10 C): The daily accumulation of degrees when the daily mean temperature is above 10 degrees Celsius. CDD18_3 (Cooling Degree Days Above 18.3 C): The daily accumulation of degrees when the daily mean temperature is above 18.3 degrees Celsius. DISPH (Zero Plane Displacement Height): The height at which the mean velocity is zero due to large obstacles such as buildings/canopy. EVLAND (Evaporation Land): The evaporation over land at the surface of the earth. EVPTRNS (Evapotranspiration Energy Flux): The evapotranspiration energy flux at the surface of the earth. FROST_DAYS (Frost Days): A frost day occurs when the 2m temperature cools to the dew point temperature and both are less than 0 C or 32 F. GWETTOP (Surface Soil Wetness): The percent of soil moisture a value of 0 indicates a completely water-free soil and a value of 1 indicates a completely saturated soil; where surface is the layer from the surface 0 cm to 5 cm below grade. HDD10 (Heating Degree Days Below 10 C): The daily accumulation of degrees when the daily mean temperature is below 10 degrees Celsius. HDD18_3 (Heating Degree Days Below 18.3 C): The daily accumulation of degrees when the daily mean temperature is below 15.3 degrees Celsius. PBLTOP (Planetary Boundary Layer Top Pressure): The pressure at the top of the planet boundary layer. PRECSNOLAND_SUM (Snow Precipitation Land Sum): The snow precipitation sum over land at the surface of the earth. PRECTOTCORR_SUM (Precipitation Corrected Sum): The bias corrected sum of total precipitation at the surface of the earth. PS (Surface Pressure): The average of surface pressure at the surface of the earth. QV10M (Specific Humidity at 10 Meters): The ratio of the mass of water vapor to the total mass of air at 10 meters (kg water/kg total air). QV2M (Specific Humidity at 2 Meters): The ratio of the mass of water vapor to the total mass of air at 2 meters (kg water/kg total air). RH2M (Relative Humidity at 2 Meters): The ratio of actual partial pressure of water vapor to the partial pressure at saturation, expressed in percent. T10M (Temperature at 10 Meters): The air (dry bulb) temperature at 10 meters above the surface of the earth. T2M (Temperature at 2 Meters): The average air (dry bulb) temperature at 2 meters above the surface of the earth. T2MDEW (Dew/Frost Point at 2 Meters): The dew/frost point temperature at 2 meters above the surface of the earth. T2MWET (Wet Bulb Temperature at 2 Meters): The adiabatic saturation temperature which can be measured by a thermometer covered in a water-soaked cloth over which air is passed at 2 meters above the surface of the earth. TO3 (Total Column Ozone The total amount of ozone in a column extending vertically from the earth's surface to the top of the atmosphere. TQV (Total Column Precipitable Water): The total atmospheric water vapor contained in a vertical column of unit cross-sectional area extending from the surface to the top of the atmosphere. TS (Earth Skin Temperature): The average temperature at the earth's surface. WD10M (Wind Direction at 10 Meters): The average of the wind direction at 10 meters above the surface of the earth. WD2M (Wind Direction at 2 Meters): The average of the wind direction at 2 meters above the surface of the earth. WD50M (Wind Direction at 50 Meters): The average of the wind direction at 50 meters above the surface of the earth. WS10M (Wind Speed at 10 Meters): The average of wind speed at 10 meters above the surface of the earth. WS2M (Wind Speed at 2 Meters): The average of wind speed at 2 meters above the surface of the earth. WS50M (Wind Speed at 50 Meters): The average of wind speed at 50 meters above the surface of the earth.
This Collection provides Sentinel-3 SRAL Level-2 Land Altimetry Hydrology products, which contains surface topography estimations of lakes and rivers.
This Entity describes the stretch of land adjacent to the sea, designed to allow consents, assets, RFS etc to be assigned to the correct Property or Functional Location where no RatingUnit exists. The coverage extends from a RatingUnit or AssetStreetCatchment out to the estimated Mean Low Water Spring tide and is further defined by features in close proximity, such as placenames, parks or localities. It was initially populated via a one off derivation but will be maintained manually as future updates are required. When deleted, the record is Archived. It is spatially abstracted to an area. Entity Type: Concept.
Landslides are a widespread and often underestimated natural hazard, causing thousands of deaths and significant economic damage each year. They routinely block roads, destroy infrastructure, and disrupt communities worldwide. While intense or prolonged rainfall is the most common landslide trigger, earthquakes and human activities can also cause them. The global Landslide Hazard Assessment for Situational Awareness (LHASA) model provides users with a comprehensive view of landslide hazard in near real-time. Using machine learning, LHASA combines rainfall data from the Global Precipitation Measurement (GPM) satellite with antecedent soil moisture from the Soil Moisture Active Passive (SMAP) satellite to identify areas currently at risk from landslides. The model shows where and when landslides are most probable, then calculates the exposed population and road length within each administrative district, helping users understand both the hazard and potential impacts on communities and infrastructure. Daily global landslide exposure assessment from the LHASA (Landslide Hazard Assessment for Situational Awareness) model. Color-coded hazard levels range from red (very high exposure) to yellow (low exposure), helping users identify areas where landslides may occur. To learn more please visit: https://landslides.nasa.gov/
The Harmonized Landsat and Sentinel-2 (HLS) project takes input data from the joint NASA/USGS Landsat 8 and Landsat 9 satellites and the European Space Agency's Sentinel-2A, Sentinel-2B, and Sentinel-2C satellites to generate a harmonized, analysis-ready surface reflectance data product with observations every 1.6 days. Intended Use: The frequent revisit times of HLS allow for time series of land surface applications at the field/plot scale, which supports a wide range of applications, including agricultural health, insect infestations, and natural hazard impacts. The HLSS30 and HLSL30 products are gridded to the same resolution and tiling system and thus are “stackable” for time series analysis. Key Properties: Geographic Coverage: Global Land Temporal Coverage: May 2026 - Present Spatial Resolution: 30-meter Revisit Time: ~1 Day Update Frequency: Daily Product Level: Level-3 Source Data Coordinate System: Universal Transverse Mercator (UTM) WGS84 Service Coordinate System: Web Mercator Auxiliary Sphere (EPSG:3857) Multispectral Bands Name Description Units Data Type Fill Value Scale Factor Band 1Coastal AerosolN/Aint16-99990.0001 Band 2BlueN/Aint16-99990.0001 Band 3GreenN/Aint16-99990.0001 Band 4RedN/Aint16-99990.0001 Band 5Red Edge 1N/Aint16-99990.0001 Band 6Red Edge 2N/Aint16-99990.0001 Band 7Red Edge 3N/Aint16-99990.0001 Band 8NIR BroadN/Aint16-99990.0001 Band 8ANIR NarrowN/Aint16-99990.0001 Band 9Water VaporN/Aint16-99990.0001 Band 10CirrusN/Aint16-99990.0001 Band 11SWIR 1N/Aint16-99990.0001 Band 12SWIR 2N/Aint16-99990.0001 FmaskQuality BitsBit Fielduint8255N/A SAASun Azimuth AngleDegreeuint16400000.01 Processing Templates Server-side renderings available on this layer (select via the Rendering / Image Display options). The default rendering is Natural Color. Band-combination templates are for visualization; index templates (NDVI, NDWI, NBR, NDBI) return values suitable for analysis. "DRA" applies dynamic range adjustment; "Cloud Mask" variants suppress pixels flagged by the Fmask quality band. NDVI Colormap — Normalized difference vegetation index (NDVI) with colormap. Dark green represents vigorous vegetation and brown represents sparse vegetation. It is computed as (b5 - b4) / (b5 + b4) and is suitable for vegetation, land cover and plant health monitoring. (also available: Cloud Mask) NDVI Raw — Normalized difference vegetation index (NDVI) computed as (b5 - b4) / (b5 + b4) and is suitable for vegetation, land cover and plant health monitoring. (also available: Cloud Mask) NDWI Raw — The NDWI index is computed as Green(Band03)-NIR(Band05)/ Green(Band03)+NIR(Band05) and is most suitable for mapping of water bodies, droughts, boundary evaluation. Water bodies have strong absorbability and low radiation within the visible to infrared spectral ranges and this index is based on this phenomenon. (also available: Cloud Mask) Natural Color — Natural Color bands red, green, blue(4, 3, 2) displayed with fixed stretch applied. (also available: Cloud Mask, DRA, DRA and Cloud Mask) Normalized Burn Ratio — The NBR index is computed as NIR(Band05)-SWIR(Band7)/NIR(Band05)+SWIR(Band7) and appropriate for highlighting burned areas and estimating fire severity. It highlights burnt areas in fire zones greater than 500 acres. You will need to generate a differenced NBR image by subtracting a post-fire image from a pre-fire image. The resulting darker pixels represent burned areas. (also available: Cloud Mask) Normalized Difference Built-Up Index — The NDBI index is computed as SWIR(Band6)-NIR(Band05)/ SWIR(Band6)+NIR(Band05) and is suitable for watershed runoff predictions, tracking urbananisation and land-use planning. It highlights urban areas with higher reflectance in the SWIR region, compared to the NIR region. This index also contains a cloud mask. (also available: Cloud Mask) Limitations of Use: HLSS30 v2.0 data contain several known limitations related to atmospheric correction, cloud masking, geolocation, and metadata that users should carefully consider before analysis. A full description of these known issues is available here. Latency: Imagery tiles are configured to render at a 150 meter scale. Dynamic Mosaic rendering can take an extended period of time. Resource Links: Download Data User Guide General Documentation For inquiries about this service, please contact support@earthdata.nasa.gov or post/view questions on the Earthdata Forum Citation: Neigh, C., Ju, J., Roger, J.-C., Skakun, S., Vermote, E., Claverie, M., Dungan, J., Yin, Z., Freitag, B., & Justice, C. (2021). HLS Sentinel-2 Multi-spectral Instrument Surface Reflectance Daily Global 30m v2.0 [Dataset]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/HLS/HLSS30.002.
Overview Chlorophyll Index Red Edge (CIRE) product from the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Ocean Color Instrument (OCI). CIRE describes the canopy content of chlorophyll in terrestrial vegetation. CIRE is calculated as (R800/R705)-1, where R800 is the surface reflectance at 800 nanometers (nm) and R705 is the reflectance at 705 nm (Gitelson et al. 2005). Data provided as global, 8-day averages mapped to a standard, equal-angle, latitude-longitude grid of 0.02 degrees, which equates to ~2 kilometers (km) at the equator. Data has been corrected for atmospheric scattering and absorption. Pixels with no data values are masked (excluded) due to presence of water, cloud cover, or other features marked by quality control flags as described below. Data Layer Summary Name, units Chlorophyll Red Edge Index (CIRE) Measure of canopy chlorophyll content using red edge (near infrared) surface reflectance measurements, describes plant health and abundance. CIRE is unitless. Spatial resolution 2 km2 Level-3, mapped to a standard grid, global coverage Time Resolution 8 day average Each pixel represents an average of the valid, daily values observed within that grid element during the 8-day interval (approx 1 week). Note: 8 day average data layer is calculated from daily, "refined" (archive-quality) Level 3 PACE CIRE products available here from NASA Earthdata in NetCDF format. Earthdata account required. Each NetCDF file includes all 10 PACE vegetation indexes, including CIRE. Data Version Version 3.1 Data versions change as improved calibration, validation, algorithm refinements, etc are applied over time. See Version 3.1 Release Notes for details. Latency ~1 month This imagery service provides “refined” (archive-quality) PACE data products from March 2024-present, which have an approx 1 month latency. Note: Daily, “near real time (NRT)” Level 3 PACE CIRE products with less than approximately 24-48 hour latency available here from NASA Earthdata in NetCDF format. Earthdata account required. Each NetCDF file includes all 10 PACE vegetation indexes, including CIRE. Intended Use: What can I do with this layer? There are three major classes of plant pigments: chlorophylls, carotenoids, and anthocyanins. The Chlorophyll Index Red Edge (CIRE) is related to vegetation chlorophyll content, a proxy of plant abundance. Chlorophyll content controls potential photosynthesis and provides an indirect estimate of plant nutrient status (Ustin et al. 2009). The time (8 day average) and space (2km2) resolution of this data layer enables weekly to seasonal and annual insight at local to global scales. Limitations of Use: What should I know about the data? Data Status (Maturity): This product is provisional, which means that product results have been reviewed and are in family with heritage data products or other basis of expectation, but have not yet been extensively validated and so may still contain significant errors. Data layer is sufficient for qualitative determinations of product fitness-for-purpose, for testing by operational users, and may be suitable for scientific publication. Data Masking: This is a Level 3, globally-binned product from NASA’s Ocean Biology Processing Group (OBPG). By default, OBPG Level 3 data values are masked (value is set to null, or no data) according to a standard set of quality control parameters. Please see Level 3 Algorithm Usage Constraints for masking parameter details. Algorithm Theoretical Basis Document (ATBD): See ATBD for algorithm details including scientific theory, calculations, etc. https://doi.org/10.5067/8L77O0Y8GHV8. Where do I go with further questions? Visit NASA’s Earthdata Forum where users can post questions that are answered by the personnel working at NASA with the PACE mission and/or the Ocean Biology Distributed Active Archive Center (OB.DAAC) that processes and distributes PACE data. First, follow this link to view only “PACE” and “OBDAAC” tagged questions on the Earthdata Forum. Then search and read through previous posts for your question. If it has not yet been asked please post your question in the Forum and be sure "PACE" and "OBDAAC" filter tags are applied. Mission and Product Background PACE Mission Overview: Launched in February 2024, NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) observatory uniquely provides near-daily, hyperspectral coverage of Earth’s surface, plus hyperspectral and hyperangular polarimetry. PACE is a comprehensive Earth System mission, delivering all new, space-based information on the health and diversity of aquatic and terrestrial life (algae, plants), aerosol properties & modes (e.g. smoke, dust), cloud types, and more. The Ocean Color Instrument (OCI), PACE's primary sensor, is a hyperspectral (5 nm resolution) imaging spectrometer that measures properties of light from the ultraviolet (UV, 340 nm) through visible and near infrared (NIR, 895 nm) portions of the electromagnetic spectrum in 1.25 to 2.5 nm steps, plus 7 shortwave infrared (SWIR) bands (Werdell et al. 2019). Observations from OCI are moderate spatial resolution (1.2 km2), enabling a relatively frequent revisit time of 1-2 days. This combination of continuous, global coverage and spectral capabilities is unmatched by any other satellite platform, public or private. PACE benefits society by expanding our foundational knowledge of Earth and enabling novel, space-based science and applications tools across water resources (e.g. fisheries), air quality, land monitoring & management, and more. Terrestrial Remote Sensing from an Ocean Color Sensor? Designed and optimized to operate across a broad dynamic range, from the dark target of the ocean to bright, highly reflective cloud tops, PACE’s OCI also collects surface reflectance data from the world's terrestrial environments across 122 bands, resolving spectral properties of the Earth more finely than previous multispectral missions could achieve. Work thus far has demonstrated viability of OCI’s land data products for terrestrial investigations (Caplan et al. 2025). OCI’s coverage and capabilities enable provision of both novel, hyperspectral-enabled land observations as well as maintenance and extension of certain historical multispectral data records. Advanced vegetation indexes (VIs) enabled by OCI’s narrow-wavelength surface reflectance measurements provide continuous, synoptic insights into foliar pigment amounts (chlorophylls, carotenoids, and anthocyanins), water content, and photosynthetic light use efficiency across the globe each day. Heritage VIs (e.g., normalized difference vegetation index, NDVI; reviewed in Huang et al. 2021) can also be calculated by aggregating (averaging) OCI’s narrow bandwidths across ranges that approximate the multi-spectral, broadband reflectances of instruments such as MODIS, see the Mathematical Theory section of the ATBD for details. See the full list of heritage and hyperspectral-enabled VIs produced by PACE here. What other PACE data layers are available? This data layer is 1 of 11 PACE products initially selected for the Living Atlas catalog from the mission’s comprehensive aquatic, atmospheric, and terrestrial product catalog. Click here to view all 11 PACE Living Atlas imagery services. The Level 3, 122-band hyperspectral surface reflectance data (SFREFL) used to derive all VIs is available from NASA Earthdata to download at 2 kilometer resolution in NetCDF format. To access PACE mission data products available from NASA, first learn about PACE data access here, next decide which PACE product(s) you would like to use, then go to NASA Earthdata to find PACE products in NetCDF format, which can be downloaded and then imported into ArcGIS. An Earthdata account is needed to download data from NASA, sign up here. To learn about using Earthdata Search to find data, watch this tutorial. How can I stay up to date with the PACE mission? Join the PACE Community for mission news, events, new product release announcements, and to receive our newsletters. Would you like to see imagery services for more PACE products? Please let us know here. References: Algorithm Theoretical Basis Document: https://doi.org/10.5067/8L77O0Y8GHV8 Caplan, S. and Huemmrich, K. F. (2025) Unveiling PACE OCI’s hyperspectral terrestrial data products. Remote Sensing Letters, 16(4), 422–433. https://doi.org/10.1080/2150704X.2025.2470905 Gitelson, A. A., Viña, A., Ciganda, V., Rundquist, D.C., and Arkebauer, T.J. (2005) Remote Estimation of Canopy Chlorophyll Content in Crops. Geophysical Research Letters, 32(8):2005GL022688. https://doi.org/10.1029/2005GL022688 Huang, S., Tang, L., Hupy, J. P., Wang, Y. and Shao, G. (2021) A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. Journal of Forestry Research, 32(1), 1-6. https://doi.org/10.1007/s11676-020-01155-1 Ustin, S.L., Gitelson, A.A., Jacquemoud, S., Schaepman, M., Asner, G.P., Gamon, J.A., and Zarco-Tejada, P. (2009) Retrieval of foliar information about plant pigment systems from high resolution spectroscopy. Remote Sensing of Environment, 113(1), S67-S77. https://doi.org/10.1016/j.rse.2008.10.019 Werdell, P. J. et al. (2019) The Plankton, Aerosol, Cloud, Ocean Ecosystem Mission: Status, Science, Advances. Bulletin of the American Meteorological Society, 100, 1775–1794. https://doi.org/10.1175/BAMS-D-18-0056.1
Chlorophyll-a (Chlor_a) data layer from the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Ocean Color Instrument (OCI). Chlor_a, a proxy of phytoplankton biomass, is calculated from a multi-spectral algorithm that blends the OC4 band ratio (O'Reilly & Werdell, 2019) and color index (CI) algorithms (Hu et al., 2019). Inputs include remote sensing reflectance (Rrs) values at Rrs(442), Rrs(490), Rrs(410), and Rrs(555) nanometers (nm) and 5 empirically-derived coefficients, see algorithm mathematical theory in section 3.2 of this document for details. Chlor_a layer provided here as global, 8-day averages of surface chlorophyll-a concentration (mg m-3) mapped to a standard, equal-angle, latitude-longitude grid of approximately 0.04 degrees, or 4 kilometers (km) at the equator. Pixels with no data values are masked (excluded) due to presence of land, cloud cover, or other features marked by quality control flags as described below. Data Layer Summary Name, units Chlorophyll-a [mg m-3] Surface chlorophyll-a concentration in milligrams per cubic meter Spatial resolution 4 km2 Level-3, mapped to standard grid, global coverage Time Resolution 8 day average Each pixel represents an average of the valid, daily values observed within that grid element during the 8-day interval (approx 1 week). Note: 8 day average data layer is calculated from daily, "refined" (archive-quality) Level 3 PACE Chlor_a products, which are available at NASA Earthdata via this link in NetCDF format as part of the Biogeochemical Properties (BGC) suite. NASA Earthdata account required to download. Data Version Version 3.2 Data versions change as improved calibration, validation, algorithm refinements, etc are applied over time. See Version 3.2 Release Notes for details. Latency ̃1 month This imagery service provides “refined” (archive-quality) PACE data products from March 2024-present, which have an approx 1 month latency. Note: Lower latency “near real time (NRT)” Level 3 PACE Chlor_a products, which are available at NASA Earthdata via this link in NetCDF format as part of the Biogeochemical Properties (BGC) NRT suite. NASA Earthdata account required to download. What can I do with this layer? As a measure of phytoplankton abundance and distribution in surface waters, Chlor_a supports analysis such as time-series, climatologies, and anomaly detection for ocean ecosystem and fisheries applications, teaching/training, and more. Chlor_a pairs well with other water quality parameters such as sea surface temperature (SST), sea surface height (SSH), and winds for environmental context. The time (8 day average) and space (4 km2) resolution of this data layer enables weekly to seasonal and annual insight at sub-regional to global scales. What should I know about the data? Data Status (Maturity): This product is provisional, which means that product results have been reviewed and are in family with heritage data products or other basis of expectation, but have not yet been extensively validated and so may still contain significant errors. Data layer is sufficient for qualitative determinations of product fitness-for-purpose, for testing by operational users, and may be suitable for scientific publication. Data Masking: These products are Level 3, globally-binned products from NASA’s Ocean Biology Processing Group (OBPG), which by default are masked (pixel data value is set to null, or no data) according to a standard set of quality control parameters. For a list of these parameters, see the third column of the table included here: https://oceancolor.gsfc.nasa.gov/resources/atbd/ocl2flags/. Application of Chlor_a in varied water types: The Chlor_a algorithm was developed in clear, open ocean waters. End users are advised to carefully consider the validity of retrievals in extreme conditions such as highly turbid, optically shallow, and inland/freshwater systems where values may carry higher uncertainty. For example, Chlor_a values may be erroneously elevated in the presence of high sediment and/or colored dissolved organic matter concentrations often found at the land-sea interface. Algorithm documentation, and references therein, provide an overview of uncertainty and error in Chlor_a observations from heritage (missions prior to PACE) satellite ocean color observations. For PACE-specific performance evaluation see PACE Chlor_a compared to ship-based chlorophyll a concentrations, results of ongoing field efforts to evaluate performance of PACE algorithms in waters across the globe. Algorithm Theoretical Basis Document (ATBD): See ATBD for algorithm details including scientific theory, calculations, etc. at DOI 10.5067/JCQB8QALDOYD. Where do I go with further questions? Visit NASA’s Earthdata Forum where users can post questions that are answered by the personnel working at NASA with the PACE mission and/or the Ocean Biology Distributed Active Archive Center (OB.DAAC) that processes and distributes PACE data. First, follow this link to view only “PACE” and “OBDAAC” tagged questions on the Earthdata Forum. Then search and read through previous posts for your question. If it has not yet been asked please post your question in the Forum and be sure "PACE" and "OBDAAC" filter tags are applied. Mission and Product Background PACE Mission Overview: Launched in February 2024, NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) observatory uniquely provides near-daily, hyperspectral coverage of Earth’s surface, plus hyperspectral and hyperangular polarimetry. PACE is a comprehensive Earth System mission, delivering all new, space-based information on the health and diversity of aquatic and terrestrial life (algae, plants), aerosol properties & modes (e.g. smoke, dust), cloud types, and more. The Ocean Color Instrument (OCI), PACE's primary sensor, is a hyperspectral (5 nm resolution) imaging spectrometer that measures properties of light from the ultraviolet (UV, 340 nm) through visible and near infrared (NIR, 895 nm) portions of the electromagnetic spectrum in 1.25 to 2.5 nm steps, plus 7 shortwave infrared (SWIR) bands (Werdell et al. 2019). Observations from OCI are moderate spatial resolution (1.2 km2), enabling a relatively frequent revisit time of 1-2 days. This combination of continuous, global coverage and spectral capabilities is unmatched by any other satellite platform, public or private. PACE benefits society by expanding our foundational knowledge of Earth and enabling novel, space-based science and applications tools across water resources (e.g. fisheries), air quality, land monitoring & management, and more. What does Chlor_a represent? Daily, global Chlor_a has been continuously collected by NASA since 1997 utilizing a heritage, multi-band algorithm designed for the open ocean. The Chlor_a algorithm calculates the concentration of a major photosynthetic pigment, chlorophyll a, found within aquatic phytoplankton residing in the sunlit layer of the water column. Phytoplankton are single-celled, photosynthetic organisms that form the bottom levels of the marine and freshwater food webs. Functioning as the “plants” of the aquatic environment, they are an energy source for most life in aquatic ecosystems and also make the ocean an important food source for humans. Nearly all phytoplankton have the photosynthetic pigment chlorophyll a, hence Chlor_a is considered a proxy of the abundance and distribution of the total phytoplankton community. The input data for Chlor_a are satellite measurements of various wavelengths of light exiting the water. Chlorophyll a absorbs blue, green, and red wavelengths differently depending on its concentration. This changes the intensity and color of light exiting the aquatic system, which gives the water its color, and allows relationships to be developed that relate the light detected by the sensor to chlorophyll a concentration. In the past decades, the identification of phytoplankton from satellite remote sensing has been mainly focused on chlorophyll a, and the products have been widely used to represent the phytoplankton biomass in primary productivity estimation and biogeochemical models. What other PACE data layers are available? This data layer is 1 of 11 PACE products initially selected for the Living Atlas catalog from the mission’s comprehensive aquatic, atmospheric, and terrestrial product catalog. Click here to view all 11 PACE Living Atlas imagery services. Global, hyperspectral remote sensing reflectance observations from OCI with over 250 spectral bands, and used to derive many of PACE's aquatic products, are available to download in NetCDF format from NASA Earthdata as Level 3, mapped data with 4 km2 resolution or as Level 2 granules at unprojected, native spatial resolution (no finer than 1.2km2). To learn more about obtaining PACE data from NASA, first learn about PACE data access here, next decide which product(s) you would like to use, then go to NASA Earthdata to find your product(s) of interest in NetCDF format, which can be downloaded and then imported into ArcGIS. To learn about using Earthdata Search to narrow your data product selection, watch this tutorial. An Earthdata account is needed to download data from NASA, sign up here. How can I stay up to date with the PACE mission? Join the PACE Community for mission news, events, new product release announcements, and to receive our newsletters. Would you like to see imagery services for more PACE products? Please let us know here. References: Algorithm Theoretical Basis Document: https://doi.org/10.5067/JCQB8QALDOYD. Hu, C., Feng, L., Lee, Z., Franz, B. A., Bailey, S. W., Werdell, P. J. & Proctor, C. W. (2019). Improving satellite global chlorophyll a data products through algorithm refinement and data recovery. Journal of Geophysical Research: Oceans, 124(3), 1524--1543. https://doi.org/10.1029/2019JC014941 O'Reilly, J. E. & Werdell, P. J. (2019). Chlorophyll algorithms for ocean color sensors - OC4, OC5 & OC6. Remote Sensing of Environment, 229, 32--47. https://doi.org/10.1016/j.rse.2019.04.021 Werdell, P. J. et al. (2019). The Plankton, Aerosol, Cloud, Ocean Ecosystem Mission: Status, Science, Advances. Bulletin of the American Meteorological Society, 100, 1775–1794. https://doi.org/10.1175/BAMS-D-18-0056.1
__Note__: _A new version of this item is available for your use. This mature version of the map remains available for use in existing applications. This item will be retired in December 2024. There is 2023 data available in the newer 9-class v2 dataset._ Time series of annual global maps of land use and land cover (LULC). It currently has data from 2017-2022. The maps are derived from ESA Sentinel-2 imagery at 10m resolution. Each map is a composite of LULC predictions for 9 classes throughout the year in order to generate a representative snapshot of each year. This dataset was generated by Impact Observatory, who used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. The global map was produced by applying this model to the Sentinel-2 annual scene collections on the Planetary Computer. Each of the maps has an assessed average accuracy of over 75%. This map uses an updated model from the 10-class model and combines Grass(formerly class 3) and Scrub (formerly class 6) into a single Rangeland class (class 11). The original Esri 2020 Land Cover collection uses 10 classes (Grass and Scrub separate) and an older version of the underlying deep learning model. The Esri 2020 Land Cover map was also produced by Impact Observatory. The map remains available for use in existing applications. New applications should use the updated version of 2020 once it is available in this collection, especially when using data from multiple years of this time series, to ensure consistent classification. All years are available under a Creative Commons BY-4.0.
OPERA Level-2 Radiometric Terrain Corrected (RTC) products in VV polarization generated from Sentinel-1 SAR imagery, processed by OPERA (JPL). Values for the VV polarization are commonly driven by surface roughness and/or soil moisture, with rougher surfaces and higher soil moisture returning higher backscatter values. Surface water appears very dark under calm conditions, as the signal bounces off the surface away from the sensor. OPERA RTC-S1 data is available over all landmasses (excluding Antarctica) for Sentinel-1 acquisitions starting April 14, 2016, but only products from October 4, 2023, onward are included in this image service. The source rasters referenced in this service are hosted by the Alaska Satellite Facility in NASA's Earthdata Cloud, and the service is updated daily to include new products. More information about the dataset is available at https://asf.alaska.edu/datasets/daac/opera/. OPERA includes partners from NASA’s Goddard Space Flight Center, the U.S. Geological Survey (USGS), the University of Maryland College Park, the University of Alaska Fairbanks, Southern Methodist University, and EarthScope. Refer to https://www.jpl.nasa.gov/go/opera for more details. This service is still under development. Please contact hjkristenson@alaska.edu if you encounter any problems.
Identifies areas of special character as set out in the policy framework of D18 Special Character Areas Overlay – Residential and Business and Schedule 14 of the Plan.
The Prediction Of Worldwide Energy Resource (POWER) Project gathers NASA Earth Observation data and parameters related to the fields of surface solar irradiance and meteorology to serve out to the public in several free, easy-to-access and easy-to-use methods. POWER helps communities become resilient amid observed climate variability by improving data accessibility, aiding research in renewable energy development, building energy efficiency, and supporting agriculture projects. POWER is funded through the NASA Applied Sciences Program within the Earth Science Mission Directorate at NASA Langley Research Center (LaRC). --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- This is the data grid for GMAO GEOS-IT that is used by the time-enabled global Analysis Ready Data (ARD) provided by the NASA Prediction Of Worldwide Energy Resource (POWER) Project's web applications and services. Grid Size: 0.5 x 0.625 Degree Projection: GCS WGS84 Extent: Global Source: NASA Prediction Of Worldwide Energy Resources (POWER) For questions or issues please email: larc-power-project@mail.nasa.gov
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 basic population and housing context. This is shown by tract, county, and state boundaries. 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 to show the predominant housing type: owner-occupied, renter-occupied, or vacant. 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): B01001, B03002, B05003, B05011, B19049, B25002, B25003, B25058, B25077Data 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.
uav imagery by Luka Koens, acquired 2026-08-01 to 2026-08-02, 1.0 cm per pixel, published on OpenAerialMap.
uav imagery by WebODM, acquired 2026-01-11 to 2026-01-12, 5.1 cm per pixel, published on OpenAerialMap.
uav imagery by WebODM, acquired 2026-01-11 to 2026-01-12, 6.0 cm per pixel, published on OpenAerialMap.
uav imagery by WebODM, acquired 2026-01-10 to 2026-01-10, 10.0 cm per pixel, published on OpenAerialMap.
uav imagery by WebODM, acquired 2026-01-03 to 2026-01-03, 5.1 cm per pixel, published on OpenAerialMap.
Natural Earth admin 0 antarctic claims at 1:10 million scale: public domain cartographic vector data built to make small-scale world, regional and country maps.
Core property information for properties within Upper Hutt City. Data is sourced from LINZ except for valuation number which is sourced from UHCC.
This dataset contains the daily count of transits on select maritime passageways during the following events of disruption: i) Suez Canal blockage, ii) Russian Invasion of Ukraine for Bosporus Strait, and iii) the Houthi attacks for Bab el-Mandeb Strait. The counts are derived from Automatic Identification System (AIS) data--high frequency ship signals during navigation--using the framework developed in the publication Analyzing anomalous events in passageways with high-frequency ship signals. Data to validate the transits and other supplementary dataof the publication are also included.
This dataset contains a list of the countries affected by the El Niño as at April 21, 2016 as reported jointly by FAO, the Global Food Security Cluster and WFP on 21 April 2016 in the 2015-2016 El Niño: WFP and FAO Overview update. According to the World Bank, El Niño is likely to have a negative impact in more isolated local food markets, and many countries are already facing increased food prices. Food Security Cluster partners have implemented preparedness activities and are responding in countries where the effects of El Niño have materialised, such as Ethiopia, Papua New Guinea, Malawi and throughout Central America. In Southern Africa, many areas have seen the driest October-December period since at least 1981, and some 14 million people in the region are already facing hunger, which adds to fears of a spike in the numbers of the food insecure later this year through 2017.