Global environment data
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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 KCl 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.
A measure of the acidity or alkalinity in soils, defined as the negative logarithm (base 10) of the activity of hydronium ions (H+) in water. 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.
A measure of annual emissions of carbon dioxide (CO2), one of the six Kyoto greenhouse gases (GHG), from the transportation sector (subsector of the energy sector) including IPCC 2006 codes 1.A.3.a Civil Aviation, 1.A.3.b_noRES Road Transportation no resuspension, 1.A.3.c Railways, 1.A.3.d Water-borne Navigation, 1.A.3.e Other Transportation. The measure is standardized to carbon dioxide equivalent values using the Global Warming Potential (GWP) factors of IPCC's 5th Assessment Report (AR5).
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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each 1000 m cell.
Important Note: This item is in mature support as of November 2018 and will be retired in December 2020. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Note: This data was acquired in 2013. The FEMA Mapping Products web page may have more recent data for your area of interest. Flood Hazard Mapping is an important part of the U.S. National Flood Insurance Program. The Federal Emergency Management Agency publishes Flood Insurance Rate Maps that show areas where the annual likelihood of a flood is 1% or greater (Special Flood Hazard Areas). Because standard homeowners insurance does not cover flood damage the congress created the National Flood Insurance Program in 1968. In participating communities homeowners and renters are able to by federally-backed flood insurance. Dataset Summary This layer's data represents Federal Emergency Management Agency's (FEMA) Flood Insurance Rate Map (FIRM) data. This data is based upon the original vector data from FIRM. These data are 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. The NFHL database is a subset of the information created for the Flood Insurance Studies (FIS) and serves as a means to archive a portion of the information collected during the FIS. The NFHL data incorporates Digital Flood Insurance Rate Map (DFIRM) databases published by Federal Emergency Management Agency (FEMA). This layer initially shows the flood zones by FEMA Flood Zone Designations with this symbology: The layer covers the continental U.S. What can you do with this layer? The vector features for this layer can be used for visualization and analysis in ArcGIS. The features in this layer are only visible at scales larger than 1:1,155,582.
Measured according to the Bray-I method, a combination of HCl and NH4 F to remove easily acid soluble P forms, largely Al- and Fe-phosphates (for acid soils) (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.
Change of emissions (as %) of current year with respect to emissions in baseline year 1990 emissions of nitrous oxide (N2O), one of the six Kyoto greenhouse gases (GHG), from the agriculture, energy, waste, and industrial sectors, excluding LULUCF.. The measure is standardized to carbon dioxide equivalent values using the Global Warming Potential (GWP) factors of IPCC's 5th Assessment Report (AR5). Negative values indicate that the emission level for that year is lower than the emissions level in 1990.
This map layer 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. The NFHL database is a subset of the information created for the Flood Insurance Studies (FIS) and serves as a means to archive a portion of the information collected during the FIS. The NFHL data incorporates Digital Flood Insurance Rate Map (DFIRM) databases published by Federal Emergency Management Agency (FEMA). The 100-year flood is referred to as the 1% annual exceedance probability flood, since it is a flood that has a 1% chance of being equaled or exceeded in any single year. 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 1% annual chance (base flood) is the flood that has a 1% chance of being equaled or exceeded in any year. The Special Flood Hazard Area (SFHA) is the area subject to flooding by the 1% annual chance flood. Areas of Special Flood Hazard include Zones A, AE, AH, AO, AR, A99, D, V, VE, and X. The NFHL data are derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data where available. The NFHL data is available at State level. The data is updated on a monthly basis and FEMA is in the process of mapping all the flood zones and so some counties do not have complete data. 100-Year Flood Zones(*Note: the data can only be viewed when zoomed in at the Counties or larger scale)Data Currency: 2011 For more information: FEMA Flood Map Service CenterTo learn more about flood zones: Flood ZonesFor feedback please contact: ArcGIScomNationalMaps@esri.comThumbnail image courtesy of U.S. Geological Survey FEMA content on ArcGIS Online: FEMA's Homepage Other Federal User Community federally focused content that may interest you Department of Homeland Security Federal Emergency Management Agency Open Data: USDHS Open Data: FEMA
This harmonized dataset of derived soil properties for the world (WISE30sec) is comprised of a soil-geographical and a soil attribute component. The GIS dataset was created using the soil map unit delineations of the broad scale Harmonised World Soil Database, version 1.21, with minor corrections, overlaid by a climate zones map (Köppen-Geiger) as co-variate, and soil property estimates derived from analyses of the ISRIC-WISE soil profile database for the respective mapped ‘soil/climate’ combinations. The dataset considers 20 soil properties that are commonly required for global agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil gaseous emissions, and analyses of global environmental change. It presents ‘best’ estimates for: organic carbon content, total nitrogen, C/N ratio, pH(H2O), CECsoil, CECclay, effective CEC, total exchangeable bases (TEB), base saturation, aluminium saturation, calcium carbonate content, gypsum content, exchangeable sodium percentage (ESP), electrical conductivity, particle size distribution (content of sand, silt and clay), proportion of coarse fragments (less than 2 mm), bulk density, and available water capacity (-33 to -1500 kPa); also the dominant soil drainage class. Soil property estimates are presented for fixed depth intervals of 20 cm up to a depth of 100 cm, respectively of 50 cm between 100 cm to 200 cm (or less when appropriate) for so-called ‘synthetic’ profiles’ (as defined by their ‘soil/climate’ class). The respective soil property estimates were derived from statistical analyses of data for some 21,000 soil profiles managed in a working copy of the ISRIC-WISE database; this was done using an elaborate scheme of taxonomy-based transfer rules complemented with expert-rules that consider the ‘in-pedon’ consistency of the predictions. The type of rules used was flagged to provide an indication of the possible confidence (i.e. lineage) in the derived data. Best estimates for each attribute are given as means and standard deviations (STD), as calculated for the sample populations that remained upon application of a robust data outlier detection scheme. Results of the analyses can be linked to the spatial data through the unique map unit (grid cell) identifier, which is a combination of the soil unit and climate class code. Most map units are comprised of up to ten different components; each of these with their own range of derived soil properties and associated statistical uncertainties. Estimates of global soil organic carbon (SOC) stocks to 200 cm are presented in the technical documentation as an example of possible application. For citation use: Batjes NH 2016. Harmonised soil property values for broad-scale modelling (WISE30sec) with estimates of global soil carbon stocks. Geoderma 2016(269), 61-68 ( http://dx.doi.org/10.1016/j.geoderma.2016.01.034 ) Note: The chemical and physical soil property estimates generated for WISE30sec have been used to populate version 2.0 of the Harmonised World Soil Database (see https://data.isric.org/geonetwork/srv/eng/catalog.search#/metadata/54aebf11-ec73-4ff8-bf6c-ecff4b0725ea).
These three data sets, produced by WWF and RESOLVE, show the location of current tiger habitat and priority areas for habitat conservation. *Tiger Conservation Landscapes: * Tiger Conservation Landscapes (TCLs) are large blocks of contiguous or connected area of suitable tiger habitat that that can support at least five adult tigers and where tiger presence has been confirmed in the past 10 years. The data set was created by mapping tiger distribution, determined by land cover type, forest extent, and prey base, against a human influence index. Areas of high human influence that overlapped with suitable habitat were not considered tiger habitat. *Tx2 Tiger Conservation Landscapes: * This data set displays 29 Tx2 Tiger Conservation Landscapes (Tx2 TCLs), defined areas that could double the wild tiger population through proper conservation and management by 2020. *Terai Arc Landscape corridors: * This data set displays 9 forest corridors on the Nepalese side of the Terai Arc Landscape (TAL). Corridors are defined as existing forests connecting current Royal Bengal tiger meta-populations in Nepal and India. These three layers show the location of current tiger habitats, areas of habitat expansion, and critical tiger corridors.
UNICEF Data Warehouse dataflow HAZARD_POPULATION: [DRAFT] Hazard Population, by country and year.
A measure of annual emissions of carbon dioxide (CO2), one of the six Kyoto greenhouse gases (GHG), from industrial processes including IPCC 2006 codes 2.A.1 Cement production, 2.A.2 Lime production, 2.A.3 Glass Production, 2.A.4 Other Process Uses of Carbonates, 2.B Chemical Industry, 2.C Metal Industry, 2.D Non-Energy Products from Fuels and Solvent Use, 2.E Electronics Industry, 2.F Product Uses as Substitutes for Ozone Depleting Substances, 2.G Other Product Manufacture and Use and 5.A Indirect N2O emissions from the atmospheric deposition of nitrogen in NOx and NH3. The measure is standardized to carbon dioxide equivalent values using the Global Warming Potential (GWP) factors of IPCC's 5th Assessment Report (AR5).
Flood Hazard Mapping is an important part of the U.S. National Flood Insurance Program. The Federal Emergency Management Agency publishes Flood Insurance Rate Maps that show areas where the annual likelihood of a flood is 1% or greater (Special Flood Hazard Areas). Because standard homeowners insurance does not cover flood damage the congress created the National Flood Insurance Program in 1968. In participating communities homeowners and renters are able to by federally-backed flood insurance. Dataset Summary This layer's data represents Federal Emergency Management Agency's (FEMA) Flood Insurance Rate Map (FIRM) data. This data is based upon the original vector data from FIRM. These data are 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. The NFHL database is a subset of the information created for the Flood Insurance Studies (FIS) and serves as a means to archive a portion of the information collected during the FIS. The NFHL data incorporates Digital Flood Insurance Rate Map (DFIRM) databases published by Federal Emergency Management Agency (FEMA). This layer initially shows the flood zones by FEMA Flood Zone Designations with this symbology: The layer covers the continental U.S. Link to source metadata What can you do with this layer? The vector features for this layer can be used for visualization and analysis in ArcGIS. The features in this layer are only visible at scales larger than 1:1,155,582. The features can also be downloaded for use with ArcGIS desktop by with the Extract Landscape Source Data tool. This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks. This collection includes a raster layer that was derived from these data.
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
Net flux of carbon dioxide (CO2) in the category "Organic soil".
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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each 1000 m cell.
This map was prepared based on the Harmonised World Soil Database (HSWD), v1.2 and using the World Reference Base for Soil Resources (WRB) 2014, update 2015. The map units were derived from aggregation of the HWSD units using the ‘soil associations’ as defined in the short key of the WRB2014 document. The aggregated World Soil Map map was prepared at ISRIC on request of the Heinrich-Boell-Stiftung.
Volumetric Water Content at 10 kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) 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. This map is the result of resampling the mean SoilGrids 250 m predictions (Turek et al. 2021) for each 1000 m cell.
Cation exchange capacity (buffered at pH 7) of fine earth fraction in mmol(c)/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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each 1000 m cell.
Derived saturated water content (volumetric fraction) teta-S at 7 standard depths predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: v%.
Date of Image(s): January 11, 2025 Summary: This product shows the char/ash fraction of each pixel based on airborne imaging spectroscopy measurements from NASA JPL AVIRIS-3. The surface reflectance was first estimated using ISOFIT, after which a Spectral Unmixing algorithm was used to determine the amount of char and ash within each pixel, based on the MESMA approach. See credits for citations and more information on ISOFIT, Spectral Unmixing, and the MESMA approach. The char/ash fractional cover value is displayed as a single band pseudocolor grayscale, with thresholds at minimum detectable bounds of 50% and 80% char/ash fractional cover for Palisades and Eaton Fires, respectively. Suggested Use: The product describes the relative amount of char and ash (0-1) within each pixel. In order to deliver a product with low latency, the endmember library used was constrained to that common to a Southern California urban environment, and manual masking was also used. Locations that are heavily shaded may have errant solutions. The product also only indicates the char/ash fraction of the exposed surface - not what lies underneath. Areas covered by ash, for example, may express as having a fraction despite having only a thin coating of ash on top. This is a research grade product with known false positives and false negatives. Improvements to product accuracy are ongoing and linear spectral mixture model was used to approximate char/ash fractional cover; however, due to multiple scattering effects of complex surfaces, actual the relationship between observed char/ash reflectance and actual char/ash abundance may be non-linear. Resolution: The product ground spatial resolution is approximately 2.8 m, and flights occurred between 19:40 and 21:00 UTC on Jan 11th 2025. Raw data are available for download here: https://popo.jpl.nasa.gov/pub/LA_Fires/working/eaton_1.tif Point of Contact: Philip G. Brodrick (JPL) and David R. Thompson (JPL) Credits: AVIRIS-3 Radiance Data: Eckert, R., D.R. Thompson, A.M. Chlus, J.W. Chapman, M. Eastwood, M. Bernas, S. Geier, M. Helmlinger, D. Keymeulen, E. Liggett, S. Nadgauda, L.M. Rios, L.A. Shaw, W. Olson-Duvall, P.G. Brodrick, and R.O. Green. 2024. AVIRIS-3 L1B Calibrated Radiance, Facility Instrument Collection. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2356 AVIRIS-3 Reflectance Data: Brodrick, P.G., A.M. Chlus, U.N. Bohn, E. Greenberg, J. Montgomery, J.W. Chapman, M. Eastwood, S.R. Lundeen, R. Eckert, W. Olson-Duvall, D.R. Thompson, and R.O. Green. 2025. AVIRIS-3 L2A Orthocorrected Surface Reflectance, Facility Instrument Collection. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2357 ISOFIT: Thompson, D.R., Natraj, V., Green, R.O., Helmlinger, M.C., Gao, B.C. and Eastwood, M.L., 2018. Optimal estimation for imaging spectrometer atmospheric correction. Remote sensing of environment, 216, pp.355-373. Philip G Brodrick, David R Thompson, Niklas Bohn, Nimrod Carmon, Regina Eckert, James Montgomery, Kevin Wurster, & Nicholas Vaughn. (2024). isofit (v3.2.2). Zenodo. https://doi.org/10.5281/zenodo.14135462 Spectral Unmixing: https://github.com/emit-sds/SpectralUnmixing MESMA Approach: Quintano, C., Fernández-Manso, A. and Roberts, D.A., 2013. Multiple Endmember Spectral Mixture Analysis (MESMA) to map burn severity levels from Landsat images in Mediterranean countries. Remote Sensing of Environment, 136, pp.76-88.
The sum of total Kjeldahl nitrogen (ammonia, organic and reduced nitrogen) and nitrate-nitrite (g/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.
Absolute depth to bedrock (in cm) predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: cm.
Bulk density of the fine earth fraction*, equilibrated at 33 kPa (kg/dm³). 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.
Volumetric Water Content at 1500kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) 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. This map is the result of resampling the mean SoilGrids 250 m predictions (Turek et al. 2021) for each 5000 m cell.
This harmonized, gridded global data set of soil parameter estimates includes files listing: (1) soil parameter estimates for the component soil units of each terrestrial grid cell, in un-binned format, and (2) soil parameter estimates aggregated or binned into a number of predefined classes. The spatial data, with a resolution of ½ by ½ degree, was derived from the ISRIC-WISE soil database. The land surface between longitudes -180o W and +180o E and latitudes +90o N and -90o S has been characterized using 45948 unique map units; each of these can comprise from one to ten soil units, characterized according to the original legend of the 1:5 million scale Soil Map of the World (FAO-Unesco 1974). Soil parameter estimates for each of these units were derived from analyses of some 9600 profiles held in a working copy of WISE (ver. 2.0). Twenty-two soil variables, identified as being useful for agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil gaseous emissions and analyses of global environmental change, were considered. Parameter estimates for the topsoil (0-30 cm) and the subsoil (30-100 cm) are presented for the following variables: content of organic carbon, total nitrogen, the C/N ratio, pH(H2O), CECsoil, CECclay, base saturation, total exchangeable bases, aluminum saturation, exchangeable sodium percentage (ESP), electrical conductivity of saturated paste (ECe), calcium carbonate content, gypsum content, content of sand, silt and clay, content of fragments less than 2 mm, bulk density, total porosity. For soil drainage class, effective soil depth, and available water capacity (-10 to -1500 kPa), however, parameter estimates are presented on a profile basis. The parameter estimates - median values - presented here should be seen as best estimates; possible types and sources of uncertainty are discussed in the report. The data are considered appropriate for exploratory studies at global scale (greater than 1:5 000 000). Note: A more recent assessment, at a resolution of 30arcsec (WISE30sec), is available at: http://data.isric.org/geonetwork/srv/eng/catalog.search#/metadata/dc7b283a-8f19-45e1-aaed-e9bd515119bc
Soil moisture content by weight, at tension 200 kPa (pF 3.3) (g/100g). 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.
Grade of a sub-soil being acid e.g. having a pH greater than 5 and low BS predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: grade.