Global environment data
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Soil organic carbon density in g/dm³ at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org.
The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Datum of 1983.
This data is served directly from FEMA gis service servers. https://hazards.fema.gov/femaportal/wps/portal/NFHLWMS View the status of the NFHL map services here: https://floodmaps.fema.gov/NFHL/status.shtml
FEMA Service for current National Flood Hazard Layers For more information, visit: https://hazards.fema.gov/femaportal/wps/portal/NFHLWMS
Global glaciated areas and permanent ice sheets at 1:10 million scale from Natural Earth. Includes major glaciers, ice fields, and permanent snow cover worldwide. Use this layer for climate change monitoring, cryosphere studies, freshwater resource assessments, and cartographic base mapping at global and continental scales. No additional information provided.
This map service represents Flood Insurance Rate Map (FIRM) data important for floodplain management, mitigation, and insurance activities for the National Flood Insurance Program (NFIP). The National Flood Hazard Layer (NFHL) data present the flood risk information depicted on the FIRM in a digital format suitable for use in electronic mapping applications.
GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.
Clay content (0-2 micro meter) mass fraction in ‰ at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org.
THIS LAYER IS HOSTED BY FEMA, not NAPSG Foundation. We are simply pointing to their layer with this ArcGIS Online item. The National Flood Hazard Layer (NFHL) dataset represents the current effective flood data for the country, where maps have been modernized. It is a compilation of effective Flood Insurance Rate Map (FIRM) databases and Letters of Map Change (LOMCs). The NFHL is updated as studies go effective. For more information, visit FEMA's Map Service Center (MSC). You can view this information in a standalone viewer here: https://hazards-fema.maps.arcgis.com/apps/webappviewer/index.html?id=8b0adb51996444d4879338b5529aa9cd REST URL: https://hazards.fema.gov/gis/nfhl/rest/services/public/NFHL/MapServer Base Map Considerations The default base map is from an ESRI service and conforms to FEMA's specification for horizontal accuracy. This base map is composed of the orthoimagery used when the Flood Insurance Rate Maps (FIRMs) were initially created combined with standard imagery products managed by ESRI. This map should be considered the best online resource to use for official National Flood Insurance Program (NFIP) purposes when determining locations in relation to regulatory flood hazard information. If a different base map is used with the NFHL, the accuracy specification may not be met and the resulting map should be used for general reference only, and not official NFIP purposes. Further Information For more flood map data, tool, and viewing options, visit the FEMA NFHL page. Several fact sheets are available to help you learn more about FEMA’s NFHL utility: National Flood Hazard Layer (NFHL) GIS Services Users Guide National Flood Hazard Layer (NFHL): New Products and Services for FEMA's Flood Hazard Map Data NFHL GIS Data: Perform Spatial Analyses and Make Custom Maps and Reports
Total nitrogen in cg/kg at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org.
Upper Hutt's current District Plan Hazards. See Uppper Hutt City Council's District Plan for more information.
The National Flood Hazard Layer (NFHL) is a geospatial database that contains current effective flood hazard data. FEMA provides the flood hazard data to support the National Flood Insurance Program.
GIS Web Services for the FEMA National Flood Hazard Layer (NFHL)FEMA’s National Flood Hazard LayerFEMA provides access to the National Flood Hazard Layer (NFHL) through web mapping services. The NFHL is a computer database that contains FEMA�s flood hazard map data. The simplest way for you to access the flood hazard data, including the NFHL, is through FEMAs Map Service Center (MSC). If you want to explore the current digital effective flood hazard data in a map, the best tool to use is the NFHL Viewer. From the NFHL Viewer, you may view, download, and print flood maps for your location The data depict effective flood hazard information and supporting data used to develop the information. The primary flood hazard classification is indicated in the Flood Hazard Zones layer. The NFHL layers include: Flood hazard zones and labels River Miles Markers Cross-sections and coastal transects and their labels Letter of Map Revision (LOMR) boundaries and case numbers Flood Insurance Rate Map (FIRM) boundaries, labels and effective dates Coastal Barrier Resources System (CBRS) and Otherwise Protected Area (OPA) units Community boundaries and names Levees Hydraulic and flood control structures Profile and coastal transect baselines Limit of Moderate Wave Action(LiMWA) Not all effective Flood Insurance Rate Maps (FIRM) have geographic information system (GIS) data available. To view a list of available county and single-jurisdiction flood study data in GIS format and check the status of the NFHL GIS services please visit the NFHL Status Page. Preliminary & Pending National Flood Hazard LayersThe Preliminary and Pending NFHL dataset represents the current pre-effective flood data for the country. These layers are updated as new preliminary and pending data becomes available, and data is removed from these layers as it becomes effective. Preliminary & Pending Data Preliminary data are for review and guidance purposes only. By viewing preliminary data and maps, the user acknowledges that the information provided is preliminary and subject to change. Preliminary data are not final and are presented in this national layer as the best information available at this time. Additionally, preliminary data cannot be used to rate flood insurance policies or enforce the Federal mandatory purchase requirement. FEMA will remove preliminary data once pending data are available. The preliminary flood hazard data is available through the preliminary FEMA Map Products page. If the preliminary flood hazard data search tool is unavailable, please use the alternate site. To explore the current digital preliminary flood hazard data in a map, the best tool to use is the Flood Map Changes Viewer (FMCV). From the Flood Map Changes Viewer, you may view, download, and print flood maps for your location. Pending data are for early awareness of upcoming changes to regulatory flood map information. Until the data becomes effective, when it will appear in FEMA's National Flood Hazard Layer (NFHL), the data should not be used to rate flood insurance policies or enforce the Federal mandatory purchase requirement. FEMA will remove pending data once effective data are available. To better understand preliminary data please see the Preliminary National Flood Hazard Layer webpage. FEMA GeoPlatformFEMA's GIS flood map services are available through FEMAs GeoPlatform, an ArcGIS Online portal containing a variety of FEMA-related data. To view the NFHL on the FEMA GeoPlatform go to NFHL on FEMA GeoPlatform. Technical Information Flood hazard and supporting data are developed using specifications for horizontal control consistent with 1:12,000–scale mapping. If you plan to display maps from the NFHL with other map data for official purposes, ensure that the other information meets FEMA’s standards for map accuracy. The minimum horizontal positional accuracy for base map hydrographic and transportation features used with the NFHL is the NSSDA radial accuracy of 38 feet. United States Geological Survey (USGS) imagery and map services that meet this standard can be found by visiting the Knowledge Sharing Site (KSS) for Base Map Standards (420). Other base map standards can be found at https://riskmapportal.msc.fema.gov/kss/MapChanges/default.aspx. You will need a username and password to access this information. The NFHL data are from FEMA’s FIRM databases. New data are added continually. The NFHL also contains map changes to FIRM data made by LOMRs. The NFHL is stored in North American Datum of 1983, Geodetic Reference System 80 coordinate system, though many of the NFHL GIS web services support the Web Mercator Sphere projection commonly used in web mapping applications. Organization & DisplayThe NFHL is organized into many data layers. The layers display information at map scales appropriate for the data. A layer indicating the availability of NFHL data is displayed at map scales smaller than 1:250,000, regional overviews at map scales between 1:250,000 and 1:50,000, and detailed flood hazard maps at map scales of 1:50,000 and larger. The "Scalehint" item in the Capabilities file for the Web Map Service encodes the scale range for a layer. In addition, there are non-NFHL datasets provided in the GIS web services, such as information about the availability of flood data and maps, the national map panel scheme, and point locations for LOMA and LOMR-Fs. The LOMA are positioned less accurately than are the NFHL data. Layers in the public NFHL GIS services:Use the numbers shown below when referencing layers by number. 0. NFHL Availability1. LOMRs2. LOMAs3. FIRM Panels4. Base Index5. PLSS6. Toplogical Low Confidence Areas7. River Mile Markers8. Datum Conversion Points9. Coastal Gages10. Gages11. Nodes12. High Water Marks13. Station Start Points14. Cross-Sections15. Coastal Transects16. Base Flood Elevations17. Profile Baselines18. Transect Baselines19. Limit of Moderate Wave Action20. Water Lines21. Coastal Barrier Resources System Area22. Political Jurisdictions23. Levees24. General Structures25. Primary Frontal Dunes26. Hydrologic Reaches27. Flood Hazard Boundaries28. Flood Hazard Zones29. Submittal Information30. Alluvial Fans31. Subbasins32. Water AreasGIS Web Services InformationFor users experienced with GIS, a variety of services are offered for the public to access NFHL data. The services contain predefined symbology similar to the printed FIRM panels onto which the data is mapped. Though the services contain all NFHL spatial layers, some are only available in certain scale ranges; for instance, detailed flood maps are only available when zoomed past 1:50,000 scale. ArcGIS REST ServiceThe ArcGIS REST service provides direct access to NFHL spatial information through Environmental Systems Research Institute (ESRI) applications such as ArcGIS Desktop or ArcGIS Online. This service supports mapping, data, and query requests. To access the public NFHL service directly through a web map viewer such as ArcGIS Online, you can use the service-specific URL. Copy & Paste the following URL into your web map viewer: NFHL (effective data only): https://hazards.fema.gov/gis/nfhl/rest/services/public/NFHL/MapServer Preliminary Chances Since Last FIRM (CSLF) GIS Service:: https://hazards.fema.gov/gis/nfhl/rest/services/CSLF/Prelim_CSLF/MapServer Draft CSLF GIS Service:: https://hazards.fema.gov/gis/nfhl/rest/services/CSLF/Draft_CSLF/MapServer Preliminary National Flood Hazard Layer: https://hazards.fema.gov/gis/nfhl/rest/services/PrelimPending/Prelim_NFHL/MapServer Pending NFHL: https://hazards.fema.gov/gis/nfhl/rest/services/PrelimPending/Pending_NFHL/MapServer Draft National Flood Hazard Layer:: https://hazards.fema.gov/gis/nfhl/rest/services/AFHI/Draft_FIRM_DB/MapServer To access the service through a client like ArcGIS Desktop, you can use the service directory URL: https://hazards.fema.gov/gis/nfhl/rest/services Then navigate to the desired service. OGC Web Mapping Service (WMS)Use the following URL in your GIS Application: https://hazards.fema.gov/gis/nfhl/rest/services/public/NFHLWMS/MapServer/WMSServer The WMS Capabilities file is available here:https://hazards.fema.gov/gis/nfhl/services/public/NFHLWMS/MapServer/WMSServer?request=GetCapabilities&service=WMS The NFHL Web Mapping Service provides an OGC-compliant protocol for obtaining map images and querying feature information. This service can be consumed by a number of free and commercial GIS clients. OGC Web Feature Service (WFS)Use the following URL in your GIS Application: https://hazards.fema.gov/gis/nfhl/services/public/NFHL/MapServer/WFSServer The NFHL Web Feature Service provides an OGC-compliant protocol for direct download of GIS data from the NFHL. This service can be consumed by a number of free and commercial GIS clients. Requests are currently limits to 1000 features, so it is recommended that users focus on a very limited area of interest when requesting data through WFS. If a larger amount of data is needed, it is recommended that users download the NFHL data by state or county from the MSC. Due to limitations on the number of features that can be requested, it is recommended that users supply bounding box coordinates when constructing WFS requests. Here is an example of a WFS GetFeature request for the Flood Hazard Zone layer. For more information on constructing WFS requests, see the topic on the ESRI help site. If you have any questions or concerns please contact MIP Help (miphelp@riskmapcds.com ) or the FEMA Map Information eXchange (FMIX) at 1-877-FEMA-MAP
This dataset illustrates the tropical cyclone IRMA-17 path with low, medium and strong wind impact zones observed and predicted at 7 September 2017. The tropical cyclone path and wind speed zones were derived from Joint Research Centre data (Warning 33 issued the 07 th September 2017 at 09:00 UTC). This is a preliminary analysis and has not yet been validated in the field.
The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission measures the temperature of plants to better understand how much water plants need and how they respond to stress. ECOSTRESS is attached to the International Space Station (ISS) and collects data globally between 52° N and 52° S latitudes. The ECOSTRESS Tiled Surface Energy Balance Instantaneous L3 Global 70 m (ECO_L3T_SEB) Version 2 data product provides estimated incoming surface radiation (Rg) and net radiation (Rn) aligned with each daytime ECOSTRESS overpass. The Rg was generated using the Forest Light Environmental Simulator (FLiES) radiative transfer model implemented in an artificial neural network using Cloud Optical Thickness (COT) and Aerosol Optical Thickness (AOT) from Goddard Earth Observing System Version 5 (GEOS-5) Forward Processing (FP) along with albedo from ECOSTRESS Tiled Ancillary NDVI and Albedo Level 2 Global 70 m (ECO_L2T_STARS) Version 2 as variables. The Rg output from the FLiES model was bias corrected to Rg from GEOS-FP. The Rn is an output from the Breathing Earth System Simulator (BESS) algorithm. This data product is tiled using a modified version of the Military Grid Reference System (MGRS), which divides Universal Transverse Mercator (UTM) zones into square tiles that are 109.8 km by 109.8 km with a 70 meter (m) spatial resolution. The ECO_L3T_SEB Version 2 data product is provided in Cloud Optimized GeoTIFF (COG) format with each data layer distributed as a separate COG. This product contains four layers including Rg, Rn, cloud mask, and water mask. Known Issues * Data acquisition gap: ECOSTRESS was launched on June 29, 2018, and moved to autonomous science operations on August 20, 2018, following a successful in-orbit checkout period. On September 29, 2018, ECOSTRESS experienced an anomaly with its primary mass storage unit (MSU). ECOSTRESS has a primary and secondary MSU (A and B). On December 5, 2018, the instrument was switched to the secondary MSU and science operations resumed. On March 14, 2019, the secondary MSU experienced a similar anomaly, temporarily halting science acquisitions. On May 15, 2019, a new data acquisition approach was implemented, and science acquisitions resumed. To optimize the new acquisition approach TIR bands 2, 4, and 5 are being downloaded. The data products are as previously, except the bands not downloaded contain fill values (L1 radiance and L2 emissivity). This approach was implemented from May 15, 2019, through April 28, 2023. * Data acquisition gap: From February 8 to February 16, 2020, an ECOSTRESS instrument issue resulted in a data anomaly that created striping in band 4 (10.5 micron). These data products have been reprocessed and are available for download. No ECOSTRESS data were acquired on February 17, 2020, due to the instrument being in SAFEHOLD. Data acquired following the anomaly have not been affected. * Data acquisition: ECOSTRESS has now successfully returned to 5-band mode after being in 3-band mode since 2019. This feature was successfully enabled following a Data Processing Unit firmware update (version 4.1) to the payload on April 28, 2023. To better balance contiguous science data scene variables, 3-band collection is currently being interleaved with 5-band acquisitions over the orbital day/night periods. * Missing Cloud Layer Alert: All users of ECOSTRESS Tiled and Gridded L3 Soil Moisture and Surface Energy Balance v002 products (ECO_L3T_SM, ECO_L3G_SM, ECO_L3T_SEB and ECO_L3G_SEB) should be aware that the 'cloud mask' layer may be unavailable for a select number of granules for the year 2023. Users are encouraged to get that information from the corresponding Level 2 Standard Cloud Mask products (ECO_L2_CLOUD and ECO_L2G_CLOUD) to assess if a pixel is clear or cloudy (see section 3 of the User Guide). * Solar Array Obstruction: Some ECOSTRESS scenes may be affected by solar array obstructions from the International Space Station (ISS), potentially impacting data quality of obstructed pixels. The 'FieldOfViewObstruction' metadata field is included in all Version 2 products to indicate possible obstructions: * Before October 24, 2024 (orbits prior to 35724): The field is present but was not populated and does not reliably identify affected scenes. * On or after October 24, 2024 (starting with orbit 35724): The field is populated and generally accurate, except for late December 2024, when a temporary processing error may have caused false positives. * A list of scenes confirmed to be affected by obstructions is available and is recommended for verifying historical data (before October 24, 2024) and scenes from late December 2024. * The ISS native pointing information is coarse relative to ECOSTRESS pixels, so ECOSTRESS geolocation is improved through image matching with a basemap. Metadata in the L1B_GEO file shows the success of this geolocation improvement, using categorizations "best", "good", "suspect", and "poor". We recommend that users use only "best" and "good" scenes for evaluations where geolocation is important (e.g., comparison to field sites). For some scenes, this metadata is not reflected in the higher-level products (e.g., land surface temperature, evapotranspiration, etc.). While this metadata is always available in the geolocation product, to save users additional download, we have produced a summary text file that includes the geolocation quality flags for all scenes from launch to present. At a later date, all higher-level products will reflect the geolocation quality flag correctly (the field name is GeolocationAccuracyQA). * During the time period of May 15th, 2025, through July 1st, 2025, ECOSTRESS data was noisier than expected. Cycling the payload resolved the issue, but researchers should use all levels of ECOSTRESS data acquired during this time period with caution. * Coarse Resolution Artifacts: Users may sometimes observe coarse resolution (~500m - 1km) artifacts in the L3 and L4 gridded and tiled products. These artifacts are caused by corresponding artifacts within the ECO_L2T_STARS Version 2 data product. The ECO_L2T_STARS product is produced through a data fusion of Suomi NPP VIIRS (~500 m - 1 km resolution) and Harmonized Landsat Sentinel-2 (HLS, 30 m) products. When there is significant temporal lag between HLS acquisitions, the VIIRS data dominates, which can produce coarse resolution artifacts in the ECO_L2T_STARS product. This, typically corresponds to relatively large uncertainty values.
The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission measures the temperature of plants to better understand how much water plants need and how they respond to stress. ECOSTRESS is attached to the International Space Station (ISS) and collects data globally between 52° N and 52° S latitudes. The ECOSTRESS Tiled Evapotranspiration Auxiliary Level 3 Global 70 m (ECO_L3T_ETAUX) Version 3 data product provides downscaled meteorology, soil moisture, and surface energy balance data variables aligned with each daytime ECOSTRESS overpass and includes the following components: * The meteorology component (MET) provides instantaneous near-surface air temperature (Ta) and relative humidity (RH). These variables are downscaled to 70 m using linear regression with ECOSTRESS surface temperature (ST), Normalized Difference Vegetation Index (NDVI), and albedo as predictors and Goddard Earth Observing System Version 5 (GEOS-5) Forward Processing (FP) fields as the target, followed by bias correction. * The soil moisture component (SM) provides instantaneous soil moisture estimates that are downscaled to 70 m using the identical linear regression method with ST, NDVI, and albedo as predictors and GEOS-5 FP soil moisture as the target, followed by bias correction. * The surface energy balance component (SEB) provides incoming global radiation (Rg) and net radiation (Rn). Incoming global radiation (Rg) is generated using an artificial neural network implementation of the Forest Light Environmental Simulator (FLiES) radiative transfer model driven by GEOS-5 cloud and aerosol optical thickness along with ECOSTRESS albedo and bias-corrected to GEOS-FP. Net radiation (Rn) is computed from the Breathing Earth System Simulator (BESS) algorithm. This data product is tiled using a modified version of the Military Grid Reference System (MGRS), which divides Universal Transverse Mercator (UTM) zones into square tiles that are 109.8 km by 109.8 km with a 70 meter (m) spatial resolution. The ECO_L3T_ETAUX Version 3 data product is provided in Cloud Optimized GeoTIFF (COG) format, and each variable is distributed as a separate COG. This product contains seven variables including Near-surface air temperature (Ta), Relative Humidity (RH), Global Radiation (Rg), Net Radiation (Rn), Soil Moisture (SM), cloud mask, and water mask. Known Issues * Solar Array Obstruction: Some ECOSTRESS scenes may be affected by solar array obstructions from the ISS, potentially impacting data quality in obstructed pixels. The 'FieldOfViewObstruction' metadata field is reliably populated and accurate for all products generated on or after October 2024, following fixes to the Product Generation Executive (PGE) docker configuration and updates to the L1A_RAW_PIX software. Prior to October 2024, the field was not reliably populated; a separate list of confirmed affected scenes was maintained and is recommended for verifying historical data. * Historical acquisition gaps and anomalies (2018–2023): Irrecoverable data loss occurred due to Mass Storage Unit (MSU) failures, resulting in permanent gaps in the observational record where no ECOSTRESS data was acquired during the following periods: - September 29, 2018 – December 4, 2018 (primary MSU failure) - March 14, 2019 – May 14, 2019 (secondary MSU failure) - February 17, 2020 (instrument in SAFEHOLD mode) - Other early issues, including band 4 striping (February 8–16, 2020), 3-band mode limitations (May 15, 2019–April 28, 2023), and noisy data periods (e.g., May–July 2025), have been mitigated through reprocessing, firmware updates, and instrument recovery. Version 3 products incorporate these improvements where data exists and are unaffected by ongoing issues, but the permanent historical gaps remain, and caution is advised for time-series analyses spanning affected periods. * Geolocation considerations: While geolocation is improved in Version 3 tiled products (fixed MGRS grid), gridded products may reference legacy "GeolocationAccuracyQA" flags. Use "best" and "good" scenes for applications sensitive to precise positioning.
The Earth Surface Mineral Dust Source Investigation (EMIT) instrument measures surface mineralogy, targeting the Earth’s arid dust source regions. EMIT is installed on the International Space Station (ISS). EMIT uses imaging spectroscopy to take measurements of the sunlit regions of interest between ~52° N latitude and ~52° S latitude. An interactive map showing the locations of carbon dioxide plumes along with metadata, regions being investigated, current and forecasted data coverage, and additional data resources can be found on the VSWIR Imaging Spectroscopy Interface for Open Science (VISIONS) EMIT Open Data Portal. EMIT has demonstrated the capacity to characterize methane (CH4) and carbon dioxide (CO2) point-source emissions by measuring gas absorption features in the short-wave infrared bands. The EMIT Level 2B Greenhouse Gas (GHG) series of products can be used to identify and quantify point source emissions. The EMIT Level 2B Estimated Carbon Dioxide Plume Complexes (EMITL2BCO2PLM) Version 2 data product provides estimated carbon dioxide plume complexes in parts per million meter (ppm m) along with uncertainty data. The EMITL2BCO2PLM data product will only be generated where carbon dioxide plume complexes have been identified. To reduce the risk of false positives, any EMIT Level 2B Carbon Dioxide Enhancement Data (EMITL2BCO2ENH) granules where plume complexes have been identified undergo a manual review (or identification and confirmation) process before being confirmed as a plume complex. For more information on the manual review process, see Section 4.2.4 of the EMIT GHG Algorithm Theoretical Basis Document (ATBD). Each EMITL2BCO2PLM granule is sized to a specific plume complex but may cross multiple EMITL2BCO2ENH granules. A list of source EMITL2BCO2ENH granules is included in the Cloud Optimized GeoTIFF (COG) file metadata as well as the GeoJSON file. Each EMITL2BCO2PLM granule contains two files: one COG file at a spatial resolution of 60 meters (m) and one GeoJSON file. The EMITL2BCO2PLM COG file contains a raster image of a carbon dioxide plume complex extracted from EMITL2BCO2ENH v002 data. The EMITL2BCO2PLM GeoJSON file contains a vector outline of the plume complex, a list of source scenes, coordinates of the maximum enhancement values, emission rate estimate, and the uncertainty of the plume complex. The emission rate estimate will be entered as ‘N/A’ if the plume does not meet criteria that are described in Section 4.2.5 of the ATBD. Known Issues * Data acquisition gap: From September 13, 2022, to January 6, 2023, a power issue resulted in a shutdown of the EMIT sensor. No data were acquired during that time frame.
The CAMS Global Fire Assimilation System (GFAS) utilises satellite observations of fire radiative power (FRP) to provide near-real-time information on the location, relative intensity and estimated emissions from biomass burning and vegetation fires. Emissions are estimated by conversion of FRP observations to the dry matter (DM) consumed by the fire, and application of emission factors to DM for different biomes, based on field and laboratory studies. Provided as continuous raster GeoTIFFs.
This map represents the spatial distribution of land under irrigation which is affected by some degree of salinization. It was produced by combining FAO AQUASTAT country statistics regarding irrigated areas affected by salinization with spatial information on irrigated areas where precipitation is not sufficient to leach away salt residues that are built up in the soil due to irrigation. It was assumed that the risk of salinization of irrigated areas can occur only in areas with an Aridity Index lower than 0.65 (where the Aridity Index is defined as Yearly Precipitation divided by Yearly Reference Evapotranspiration). **Data publication:** 2010-11-08 **Contact points:** Resource Contact: [Jippe Hoogeveen](mailto:Jippe.Hoogeveen@fao.org) Metadata Contact: [AQUASTAT](mailto:aquastat@fao.org) **Data lineage:** By combining the Global Map of Irrigation Areas with the spatially distributed Aridity Index, irrigated areas could be identified as potentially at risk of salinization. The AQUASTAT country statistics on areas salinized by irrigation were distributed over the irrigated areas at risk of salinization to obtain the map with the "extent of irrigated areas affected by salinization". Source data: -Global Map of Aridity at 10 arc-min (FAO) -Global map of irrigation areas at 5 arc-min (Siebert et al., 2007) The legend indicates the share of land affected by salinization in each pixel. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY-4.0) **Online resources:** SOLAW website FAO AQUASTAT website
A measure of the acidity or alkalinity in soils, defined as the negative logarithm (base 10) of the activity of hydronium ions (H+) in a CaCl2 solution, as specified in the analytical method descriptions. WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
UNICEF Data Warehouse dataflow HAZARD_EXPOSURE: [DRAFT] Hazard exposure, by country and year.
Percentage of firms tracking their own CO2 emissions over the past three years
Measured in 1:x soil:water solution (mainly determines P in dissolved forms) (mg/kg). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.