Soil Data Viewer is a tool built as an extension to ArcMap that allows a user to create soil-based thematic maps. The application can also be run independently of ArcMap, but output is then limited to a tabular report. The soil survey attribute database associated with the spatial soil map is a complicated database with more than 50 tables. Soil Data Viewer provides users access to soil interpretations and soil properties while shielding them from the complexity of the soil database. Each soil map unit, typically a set of polygons, may contain multiple soil components that have different use and management. Soil Data Viewer makes it easy to compute a single value for a map unit and display results, relieving the user from the burden of querying the database, processing the data and linking to the spatial map. Soil Data Viewer contains processing rules to enforce appropriate use of the data. This provides the user with a tool for quick geospatial analysis of soil data for use in resource assessment and management. Resources in this dataset:Resource Title: Soil Data Viewer. File Name: Web Page, url: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/home/?cid=nrcs142p2_053620 Soil Data Viewer is a tool built as an extension to ArcMap that allows a user to create soil-based thematic maps. The application can also be run independent of ArcMap, but output is then limited to a tabular report. Soil Data Viewer contains processing rules to enforce appropriate use of the data. This provides the user with a tool for quick geospatial analysis of soil data for use in resource assessment and management. Links to download and install Download Soil Data Viewer 6.2 for use with ArcGIS 10.x and Windows XP, Windows 7, Windows 8.x, or Windows 10. Earlier versions are also available.

These data depict the western United States Map Unit areas as defined by the USDA NRCS. Each Map Unit area contains information on a variety of soil properties and interpretations. The raster is to be joined to the .csv file by the field "mukey." We keep the raster and csv separate to preserve the full attribute names in the csv that would be truncated if attached to the raster. Once joined, the raster can be classified or analyzed by the columns which depict the properties and interpretations. It is important to note that each property has a corresponding component percent column to indicate how much of the map unit has the dominant property provided. For example, if the property "AASHTO Group Classification (Surface) 0 to 1cm" is recorded as "A-1" for a map unit, a user should also refer to the component percent field for this property (in this case 75). This means that an estimated 75% of the map unit has a "A-1" AASHTO group classification and that "A-1" is the dominant group. The property in the column is the dominant component, and so the other 25% of this map unit is comprised of other AASHTO Group Classifications. This raster attribute table was generated from the "Map Soil Properties and Interpretations" tool within the gSSURGO Mapping Toolset in the Soil Data Management Toolbox for ArcGIS™ User Guide Version 4.0 (https://www.nrcs.usda.gov/wps/PA_NRCSConsumption/download?cid=nrcseprd362255&ext=pdf) from GSSURGO that used their Map Unit Raster as the input feature (https://gdg.sc.egov.usda.gov/). The FY2018 Gridded SSURGO Map Unit Raster was created for use in national, regional, and state-wide resource planning and analysis of soils data. These data were created with guidance from the USDA NRCS. The fields named "*COMPPCT_R" can exceed 100% for some map units. The NRCS personnel are aware of and working on fixing this issue. Take caution when interpreting these areas, as they are the result of some data duplication in the master gSSURGO database. The data are considered valuable and required for timely science needs, and thus are released with this known error. The USDA NRCS are developing a data release which will replace this item when it is available. For the most up to date ssurgo releases that do not include the custom fields as this release does, see https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/home/?cid=nrcs142p2_053628#tools For additional definitions, see https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053627.

Gridded Soil Survey Geographic (gSSURGO)gSSURGO User Guide Version 2.4User guide for soil data management toolbox for ArcGISGuide for creating soil maps using the soil data development toolbox for ArcGIS

The Soil and Terrain database for the Upper Tana River Catchment (version 1.1) (SOTER_UT_v1.1) at scale 1:250,000 was compiled to support the Green Water Credits (GWC) programme by creating a primary SOTER dataset for a hydrology assessment of the basin. The Kenya Soil Survey of the Kenya Agriculture Research Institute(KARI-KSS) and ISRIC-World Soil Information compiled the SOTER_UT dataset ... according to the standard SOTER methodology. The dataset includes both data of the original KENSOTER database (1:1M) for the Upper Tana Catchment and, new SOTER units and soil profile data taken from other, existing soil surveys mainly at scale 100,000 and from more detailed studies.

The SOTER database was used for the hydrology assessment of Upper Tana basin using the model Soil and Water Assessment Tool (SWAT)to quantify the impact of land management practices change in the basin's waterbalance.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale but large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.Individual Metadata [XML]

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

The Soil Data Management Toolbox consists of five toolsets organized within a single toolbox. Each toolset contains several ArcTools that can be used to acquire, assemble and manage individual SSURGO datasets and to create gSSURGO databases. It is recommended that the tools be run in foreground mode (not background) because a lot of useful status information is printed to the geoprocessing window. SSURGO datasets for an entire state or region can require a large amount of storage space and computer resources to process. These tools are designed to make the process of acquiring, managing and using SSURGO datasets for large land areas much easier and faster. Each tool contains detailed built-in help which can be displayed on the right side of the tool dialog box. Much of this information in the help is not available in this document, so it would be a good idea to read the help for each parameter before using the tool. If the Help window is not visible, click on the ‘Show Help>>’ button. Other Documents to Reference:gSSURGO FactsheetgSSURGO User Guide ArcMap version 2.4Soil Data Development Toolbox User Guide v5 for ArcMapgSSURGO Mapping Detailed GuidegSSURGO Valu1 table column descriptions

Version 3.1 of the ISRIC-WISE database (WISE3) was compiled from a wide range of soil profile data collected by many soil professionals worldwide. All profiles have been harmonized with respect to the original Legend (1974) and Revised Legend (1988) of FAO-Unesco. Thereby, the primary soil data ─ and any secondary data derived from them ─ can be linked using GIS to the spatial units of the digitized Soil Map of the World as well as more recent digital Soil and Terrain (SOTER) databases through the soil legend code. WISE3 holds selected attribute data for some 10,250 soil profiles, with some 47,800 horizons, from 149 countries. Individual profiles have been sampled, described, and analyzed according to methods and standards in use in the originating countries. There is no uniform set of properties for which all profiles have analytical data, generally because only selected measurements were planned during the original surveys. Methods used for laboratory determinations of specific soil properties vary between laboratories and over time; sometimes, results for the same property cannot be compared directly. WISE3 will inevitably include gaps, being a compilation of legacy soil data derived from traditional soil survey, which can be of a taxonomic, geographic, and soil analytical nature. As a result, the amount of data available for modelling is sometimes much less than expected. Adroit use of the data, however, will permit a wide range of agricultural and environmental applications at a global and continental scale (1:500 000 and broader). Preferred citation: Batjes NH 2009. Harmonized soil profile data for applications at global and continental scales: updates to the WISE database. Soil Use and Management 5:124–127, http://dx.doi.org/10.1111/j.1475-2743.2009.00202.x

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

The Free Brazilian Repository for Open Soil Data – febr, www.ufsm.br/febr – is a centralized repository targeted at storing open soil data and serving it in a standardized and harmonized format. The repository infrastructure was built using open source and/or free (of cost) software, and was primarily designed for the individual management of datasets. A dataset-driven structure helps datasets authors to be properly acknowledged. Moreover, it gives the flexibility to accommodate many types of data of any soil variable. This is accomplished by storing each dataset using a collection of spreadsheets accessible through an online application. Spreadsheets are familiar to any soil scientist, the reason why it is easier to enter, manipulate and visualize soil data in febr. They also facilitate the participation of soil survey experts in the recovery and quality assessment of legacy data. Soil scientists can help in the definition of standards and data management choices through a public discussion forum, febr-forum@googlegroups.com. A comprehensive documentation is available to guide febr maintainers and data contributors. A detailed catalog gives access to the 14 477 soil observations – 42% of them from south and southeastern Brazil – from 232 datasets contained in febr. Global and dataset-specific visualization and search tools and multiple download facilities are available. The latter includes standard file formats and connections with R and QGIS through the febr package. Various products can be derived from data in febr: specialized databases, pedotransfer functions, fertilizer recommendation guides, classification systems, and detailed soil maps. By sharing data through a centralized soil data storing and sharing facility, soil scientists from different fields have the opportunity to increase collaboration and the much needed soil knowledge.

This data set includes soil moisture data for the following 10 Iowa counties: Boone, Dallas, Franklin, Hamilton, Hardin, Jasper, Marshall, Polk, Story, and Wright. These data were created by appending existing county digital soils data provided by the Iowa Cooperative Soil Survey (ICCS) and clipping them by the SMEX02 project area boundary.

The SSURGO database contains information about soil as collected by the National Cooperative Soil Survey over the course of a century. The information can be displayed in tables or as maps and is available for most areas in the United States and the Territories, Commonwealths, and Island Nations served by the USDA-NRCS (Natural Resources Conservation Service). The information was gathered by walking over the land and observing the soil. Many soil samples were analyzed in laboratories. The maps outline areas called map units. The map units describe soils and other components that have unique properties, interpretations, and productivity. The information was collected at scales ranging from 1:12,000 to 1:63,360. More details were gathered at a scale of 1:12,000 than at a scale of 1:63,360. The mapping is intended for natural resource planning and management by landowners, townships, and counties. Some knowledge of soils data and map scale is necessary to avoid misunderstandings. The maps are linked in the database to information about the component soils and their properties for each map unit. Each map unit may contain one to three major components and some minor components. The map units are typically named for the major components. Examples of information available from the database include available water capacity, soil reaction, electrical conductivity, and frequency of flooding; yields for cropland, woodland, rangeland, and pastureland; and limitations affecting recreational development, building site development, and other engineering uses. SSURGO datasets consist of map data, tabular data, and information about how the maps and tables were created. The extent of a SSURGO dataset is a soil survey area, which may consist of a single county, multiple counties, or parts of multiple counties. SSURGO map data can be viewed in the Web Soil Survey or downloaded in ESRI® Shapefile format. The coordinate systems are Geographic. Attribute data can be downloaded in text format that can be imported into a Microsoft® Access® database. A complete SSURGO dataset consists of:

GIS data (as ESRI® Shapefiles) attribute data (dbf files - a multitude of separate tables) database template (MS Access format - this helps with understanding the structure and linkages of the various tables) metadata

Resources in this dataset:Resource Title: SSURGO Metadata - Tables and Columns Report. File Name: SSURGO_Metadata_-_Tables_and_Columns.pdfResource Description: This report contains a complete listing of all columns in each database table. Please see SSURGO Metadata - Table Column Descriptions Report for more detailed descriptions of each column.

Find the Soil Survey Geographic (SSURGO) web site at https://www.nrcs.usda.gov/wps/portal/nrcs/detail/vt/soils/?cid=nrcs142p2_010596#Datamart Title: SSURGO Metadata - Table Column Descriptions Report. File Name: SSURGO_Metadata_-_Table_Column_Descriptions.pdfResource Description: This report contains the descriptions of all columns in each database table. Please see SSURGO Metadata - Tables and Columns Report for a complete listing of all columns in each database table.

Find the Soil Survey Geographic (SSURGO) web site at https://www.nrcs.usda.gov/wps/portal/nrcs/detail/vt/soils/?cid=nrcs142p2_010596#Datamart Title: SSURGO Data Dictionary. File Name: SSURGO 2.3.2 Data Dictionary.csvResource Description: CSV version of the data dictionary

The use of soils data within the Earth sciences often requires the researcher to harmonize and reconcile data from multiple sources. This process can take up to 80% of a researcher’s time (OGC, 2016). Multiple groups are discussing standards for data collection, archival, and metadata to increase the ease-of-use and portability of data. These groups include (1) the International Union of Soil Sciences Working Group on Soil Information Standards, which has conducted an Open Geospatial Consortium (OGC) Soil Data Interoperability Experiment (OGC, 2016); (2) the UN Food and Agriculture Organization (FAO) Global Soil Partnership, which has developed the “Five Pillars of Action” -- three of which relate directly to the research data lifecycle (UNFAO, 2018); (3) the USDA National Institute of Food and Agriculture (NIFA), which has co-convened a Data Science in Agriculture Summit (NIFA, 2017); and (4) the USDA Natural Resources Conservation Service (NRCS), which recently released a technical note on common protocols to improve data quality and facilitate data sharing (NRCS, 2018).In this session, we will hear from speakers in the Earth sciences community who are utilizing soils data in their research. We will focus on integration challenges they've had using these data through the research data lifecycle, from data creation to archival in a repository for re-use. The session will also provide perspectives on how these problems were (or may be) addressed and the effect these problems -- and solutions -- have on data analysis and the re-use of data. We will have presentations from researchers conducting both primary and secondary research, with the goal of highlighting solutions and next steps for the use and curation of soils data in the Earth sciences. By the end of the session, we aim to have identified the major challenges in using and re-using soils data, particularly as they relate to the use of soils standards.Speakers1) Ben Bond-Lamberty, “The global soil respiration database: goals, impacts, lessons.”2) David Klinges, “A network for coastal carbon research: soil data archival as a community resource and to reduce uncertainties in modeling and mapping.”3) Greg Wilson, “Agricultural Collaborative Research Outcomes System (AgCROS)”This session and these presentations took place at the Earth Science Information Partners (ESIP) Winter Meeting in January 2019.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

Soil information, from the global to the local scale, has often been the one missing biophysical information layer, the absence of which has added to the uncertainties of predicting potentials and constraints for food and fiber production. The lack of reliable and harmonized soil data has considerably hampered land degradation assessments, environmental impact studies and adapted sustainable land management interventions.

Recognizing the urgent need for improved soil information worldwide, particularly in the context of the Climate Change Convention and the Kyoto Protocol for soil carbon measurements and the immediate requirement for the FAO/IIASA Global Agro-ecological Assessment study (GAEZ v3.0), the Food and Agriculture Organization of the United Nations (FAO) and the International Institute for Applied Systems Analysis (IIASA) took the initiativeof combining the recently collected vast volumes of regional and national updates of soil information with the information already contained within the 1:5,000,000 scale FAOUNESCO Digital Soil Map of the World, into a new comprehensive Harmonized World Soil Database (HWSD).

This database was achieved in partnership with: • ISRIC-World Soil Information together with FAO, which were responsible for the development of regional soil and terrain databases and the WISE soil profile database; • the European Soil Bureau Network, which had recently completed a major update of soil information for Europe and northern Eurasia, and • the Institute of Soil Science, Chinese Academy of Sciences which provided the recent 1:1,000,000 scale Soil Map of China.

Soil Landscapes of the United States (SOLUS)metadataDescriptionSoil Landscapes of the United States, or SOLUS, is a national map product developed by the National Cooperative Soil Survey that is focused on providing a consistent set of spatially continuous soil property maps to support large scope soil investigations and land use decisions. SOLUS maps use a digital soil mapping framework that combines multiple sources of soil survey data with environmental covariate data and machine learning. Digital soil mapping is the production of georeferenced soil databases based on the quantitative relationships between soil measurements made in the field or laboratory and environmental data. Numerical models use the quantitative relationships to predict the spatial distribution of either discrete soil classes, such as map units, or continuous soil properties, such as clay content. SOLUS maps use continuous property mapping, which predicts soil physical or chemical properties in horizontal and vertical dimensions. The soil properties are represented across a continuous range of values. Raster datasets of select soil properties can be predicted at specified depths or depth intervals. Continuous soil property maps such as SOLUS provide critical natural resource information to support environmental researchers and modelers, conservationists, and others making land management decisions. SOLUS will be updated annually with improved data and methodology. SOLUS100The first version of SOLUS, called SOLUS100, is 100 m spatial resolution. Each 100 m raster cell represents a 100 m by 100 m square on the ground with soil property values estimated at seven depths: 0, 5, 15, 30, 60, 100, and 150 cm. The next version will be 30 m spatial resolution and called SOLUS30. SOLUS100 predicts 20 soil properties (listed below with units) at seven depths for the continental United States for a total of 512 maps.Very fine sand (%)Fine sand (%)Medium sand (%)Coarse sand (%)Very coarse sand (%)Total sand (%)Silt (%)Clay (%)pHSoil organic carbon (%)Calcium carbonate equivalent (%)Gypsum content (% by weight)Electrical conductivity (mmhos/cm)Sodium adsorption ratioCation exchange capacity (meq/100g)Effective cation exchange capacity (meq/100g)Oven dry bulk density (g/cm3)Depth to bedrock (cm)Depth to restriction (cm)Rock fragment volume (%)Property Prediction and Uncertainty LayersEach property-depth prediction is accompanied by estimates of uncertainty expressed as prediction interval low and high and relative prediction interval (RPI). Prediction interval low and high define the range within which future predictions may occur. The relative prediction interval ranges from 0 to 1 and is a relative measure of uncertainty with high values being more uncertain. It is computed as the ratio of the 95% prediction interval width to the training set 95% quantile width (97.5% quantile value – 2.5% quantile value). Values closer to 0 indicate lower uncertainty and values closer to 1 indicate higher uncertainty. Values greater than 1 indicate that the prediction at that location is outside the range of the training data used for that property at that depth. The Soil and Plant Science Division delivers each property-depth combination through Google Cloud Platform as four raster data layers: the property prediction, the prediction interval low and high, and the RPI. Property prediction and uncertainty layers follow the naming convention: propertyname_depth_cm_p (predicted property values)propertyname_depth_cm_rpi (relative prediction interval)propertyname_depth_cm_l (prediction interval low)propertyname_depth_cm_h (prediction interval high)SOLUS100 map of clay content predicted at the 0 cm depth for the continental U.S.AccessSOLUS100 maps are available for download or use within scripting or GIS software environments: SOLUS100 Cloud Storage BucketDetails on background, methodology, accuracy, uncertainty, and other results and discussion of SOLUS100 maps are available at SOLUS100 Ag Data Commons Repository and in the following publication:Nauman, T. W., Kienast-Brown, S., Roecker, S. M., Brungard, C., White, D., Philippe, J., & Thompson, J. A. (2024). Soil landscapes of the United States (SOLUS): developing predictive soil property maps of the conterminous United States using hybrid training sets. Soil Science Society of America Journal, 1–20. https://acsess.onlinelibrary.wiley.com/doi/10.1002/saj2.20769Data CitationsSoil Survey Staff. Soil Landscapes of the United States. United States Department of Agriculture, Natural Resources Conservation Service. Available online at storage.googleapis.com/solus100pub/index.html. Month, day, year accessed (year of official release).Citation ExampleThe following example is for the 2024 SOLUS maps. Such citations should appear in the reference section of your document.Soil Survey Staff. Soil Landscapes of the United States. United States Department of Agriculture, Natural Resources Conservation Service. Available online at storage.googleapis.com/solus100pub/index.html. May 22, 2024 (2024 official release).

This data set provides soil maps for the United States (US) (including Alaska), Canada, Mexico, and a part of Guatemala. The map information content includes maximum soil depth and eight soil attributes including sand, silt, and clay content, gravel content, organic carbon content, pH, cation exchange capacity, and bulk density for the topsoil layer (0-30 cm) and the subsoil layer (30-100 cm). The spatial resolution is 0.25 degree. The Unified North American Soil Map (UNASM) combined information from the state-of-the-art US General Soil Map (STATSGO2) and Soil Landscape of Canada (SLCs) databases. The area not covered by these data sets was filled by using the Harmonized World Soil Database version 1.21 (HWSD1.21). The Northern Circumpolar Soil Carbon (NCSCD) database was used to provide more accurate and up-to-date soil organic carbon information for the high-latitude permafrost region and was combined with soil organic carbon content derived from the UNASM (Liu et al., 2013). The UNASM data were utilized in the North American Carbon Program (NACP) Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) as model input driver data (Huntzinger et al., 2013). The driver data were used by 22 terrestrial biosphere models to run baseline and sensitivity simulations. The compilation of these data was facilitated by the NACP Modeling and Synthesis Thematic Data Center (MAST-DC). MAST-DC was a component of the NACP (www.nacarbon.org) designed to support NACP by providing data products and data management services needed for modeling and synthesis activities.

This map runs on this app: http://nmcdc.maps.arcgis.com/home/item.html?id=2088cfcae5e84568bee211db7e226c28Map depicts NRCS soil types in several layers of increasing detail as the zoom level is increased. Generated through ESRI ArcGIS Online services. It was assembled from ESRI and NRCS sources by Johnsonson Engineering.This map shows the Soil Survey Geographic (SSURGO) by the United States Department of Agriculture's Natural Resources Conservation Service. It also shows data that was developed by the National Cooperative Soil Survey and supersedes the State Soil Geographic (STATSGO) dataset published in 1994. SSURGO digitizing duplicates the original soil survey maps. This level of mapping is designed for use by landowners, townships, and county natural resource planning and management. The user should be knowledgeable of soils data and their characteristics. The smallest scale map shows the Global Soil Regions map by the United States Department of Agriculture’s Natural Resources Conservation Service.