The PLANTS Database provides standardized information about the vascular plants, mosses, liverworts, hornworts, and lichens of the U.S. and its territories. It includes names, plant symbols, checklists, distributional data, species abstracts, characteristics, images, crop information, automated tools, onward Web links, and references. This information primarily promotes land conservation in the United States and its territories, but academic, educational, and general use is encouraged. PLANTS reduces government spending by minimizing duplication and making information exchange possible across agencies and disciplines.

PLANTS is a collaborative effort of the USDA NRCS National Plant Data Center (NPDC), the USDA NRCS Information Technology Center (ITC), The USDA National Information Technology Center (NITC), and many other partners. Much of the PLANTS data and design is developed at NPDC, and the Web application is programmed at ITC and NITC and served through the USDA Web Farm. Here’s more information about who does what on the PLANTS Team, our Partners, and our Data Contributors.

This dataset was created to monitor the status, condition and trend of national BLM resources in accordance with BLM policies. It focuses on the BLM terrestrial core indicators, which include measures of vegetation and soil condition such as plant species cover and composition, plant height, and soil stability. The BLM terrestrial core indicators and methods were identified through a multi-disciplinary process and are described in BLM Technical Note 440 (https://www.blm.gov/nstc/library/pdf/TN440.pdf). The Landscape Monitoring Framework (LMF) dataset was collect using the Natural Resource Conservation Services (NRCS) National Resource Inventory (NRI) methodology which mirrors the data collected by the BLM using the Monitoring Manual for Grassland, Shrubland, and Savannah Ecosystems (2nd edition; https://www.landscapetoolbox.org/manuals/monitoring-manual/). Specific instructions for data collectors each year the data were collected can be found at https://www.nrisurvey.org/nrcs/Grazingland/. Also see Interpreting Indicators of Rangeland Health (version 5; https://www.landscapetoolbox.org/manuals/iirhv5/). The monitoring locations were selected using spatially balanced, random sampling approaches and thus provide an unbiased representation of land conditions. However, these data should not be used for statistical or spatial inferences without knowledge of how the sample design was drawn or without calculating spatial weights for the points based on the sample design. General Definitions Noxious: Noxious status and growth form (forb, shrub, etc.) are designated for each BLM Administrative State using the state noxious list and local botany expertise often after consulting the USDA plants database. Each state’s noxious list can be found in tblStateSpecies Table, where the Noxious field is ‘YES’ and the StateSpecies field has the two letter state code for the desired state (e.g. ‘NM’). Non-Noxious: Non-Noxious status and growth form (forb, shrub, etc.) are designated for each BLM Administrative State using the state noxious list and local botany expertise often after consulting the USDA plants database. Non-Noxious status can be found in tblStateSpecies Table, where the Noxious field is ‘NO’ and the StateSpecies field has the two letter state code for the desired state (e.g. ‘NM’). Sagebrush: Sagebrush species are designated for each BLM Administrative State using local botany expertise. This list can be found for each state in in the tblStateSpecies Table, where SG_Group field is ‘Sagebrush’ and the StateSpecies field has the two letter state code for the desired state (e.g. ‘NM’). Non-Sagebrush Shrub: Non Sagebrush Shrub species are designated for each BLM Administrative State as the plants determined to be shrubs that are not also Sagebrush. This list can be found for each state in in the tblStateSpecies Table, where SG_Group field is ‘NonSagebrushShrub’ and the StateSpecies field has the two letter state code for the desired state (e.g. ‘NM’). Tall Stature Perennial Grass: Tall Stature Perennial Grasses status was determined by Sage Grouse biologist and modified slightly in each state and this list can be found in tblStateSpecies in the SG_Group field where SG_Group field is ‘TallStaturePerennialGrass’ and the StateSpecies field has the two letter state code for the desired state (e.g. ‘NM’). Short Stature Perennial Grass: Short Stature Perennial Grasses status was determined by Sage Grouse biologist and modified slightly in each state and this list can be found in tblStateSpecies in the SG_Group field where SG_Group field is ‘ShortStaturePerennialGrass’ and the StateSpecies field has the two letter state code for the desired state (e.g. ‘NM’). Preferred Forb: Preferred forb for Sage Grouse status was determined for each state by Sage Grouse biologist and other local experts and this list can be found in tblStateSpecies in the SG_Group field where SG_Group field is ‘PreferredForb’ and the StateSpecies field has the two letter state code for the desired state (e.g. ‘NM’). Live: The NRI Methods measure Live vs Dead plant cover – i.e. if a pin drop hits a plant part and that plant part is dead (even if it’s on a living plant) that hit is considered a dead hit. Any occurrence of Live Sagebrush calculations indicates that the measurement is only hits that were live plant parts. If a pin hits both a live and a dead plant part in the same pin drop – that hit is considered live. Growth Habit: The form of a plant, in this dataset the options are Forb, Graminoid, Sedge, Succulent, Shrub, SubShrub, Tree, NonVascular. The most common growth habit for each state was determined by local botany expertise often after consulting the USDA plants database. The growth habit for each species is a state can be found in tblStateSpecies in the GrowthHabitSub field. The values are used to place each plant in a Growth Habit/Duration bin such as Perennial Grass, or Annual Forb, etc. Duration: The life length of a plant. In this dataset we consider plants to be either Perennial or Annual – Biennial plants are classified as Annuals. The most common duration for each state was determined by local botany expertise often after consulting the USDA plants database. The duration for each species is a state can be found in tblStateSpecies in the Duration field. The values are used to place each plant in a Growth Habit/Duration bin such as Perennial Grass, or Annual Forb, etc. tblStateSpecies: This table in the database contains the Species Lists for each state. In the instance where a species code does not have a Growth Habit, Growth Habit Sub, or Duration – any occurrence of that code will not be included in calculations that require that information – for example a code that has NonWoody Forb but no information about annual or perennial will not be included in any of the calculations that are perennial or annual forb calculations. Most codes with no information will have the following in the notes – indicating that the only calculation it will be included in is Total Foliar which doesn’t require any growth habit and duration information – “Not used for calculations except Total Foliar.”

The gridded National Soil Survey Geographic Database (gNATSGO) is a USDA-NRCS (Natural Resources Conservation Service) Soil & Plant Science Division (SPSD) composite ESRI file geodatabase that provides complete coverage of the best available soils information for all areas of the United States and Island Territories. It was created by combining data from the Soil Survey Geographic Database (SSURGO), State Soil Geographic Database (STATSGO2), and Raster Soil Survey Databases (RSS) into a single seamless ESRI file geodatabase. The gNATSGO database contains a 10-meter raster of the soil map units and 70 related tables of soil properties and interpretations. It is designed to work with the SPSD gSSURGO ArcTools. Users can create full coverage thematic maps and grids of soil properties and interpretations for large geographic areas, such as the extent of a State or the conterminous United States. SSURGO is the SPSD flagship soils database that has over 100 years of field-validated detailed soil mapping data. SSURGO contains soils information for more than 90 percent of the United States and island territories, but unmapped land remains. The current completion status of SSURGO mapping is displayed (PDF). STATSGO2 is a general soil map that has soils data for all of the United States and island territories, but the data is not as detailed as the SSURGO data. The Raster Soil Surveys (RSSs) are the next generation soil survey databases developed using advanced digital soil mapping methods. The first version of gNATSGO was created in 2019. It is composed primarily of SSURGO data, but STATSGO2 data was used to fill in the gaps. Three RSSs have been published as of 2019. These were merged into the gNATSGO after combining the SSURGO and STATSGO2 data. The extent of RSS is expected to increase in the coming years. Resources in this dataset:Resource Title: Website Pointer for Gridded National Soil Survey Geographic Database (gNATSGO). File Name: Web Page, url: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcseprd1464625 The gNATSGO website provides an Overview slide presentation, Download links for gNATSGO databases (CONUS or States), ArcTools, Metadata, Technical Information, and Recommended Data Citations.

Soil map units are the basic geographic unit of the Soil Survey Geographic Database (SSURGO). The SSURGO dataset is a compilation of soils information collected over the last century by the Natural Resources Conservation Service (NRCS). Map units delineate the extent of different soils. Data for each map unit contains descriptions of the soil’s components, productivity, unique properties, and suitability interpretations.Each soil type has a unique combination of physical, chemical, nutrient and moisture properties. Soil type has ramifications for engineering and construction activities, natural hazards such as landslides, agricultural productivity, the distribution of native plant and animal life and hydrologic and other physical processes. Soil types in the context of climate and terrain can be used as a general indicator of engineering constraints, agriculture suitability, biological productivity and the natural distribution of plants and animals.Dataset SummaryPhenomenon Mapped: Soils of the United States and associated territoriesCoordinate System: Web Mercator Auxiliary SphereExtent: The 50 United States, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaVisible Scale: 1:144,000 to 1:1,000Resolution/Tolerance: 1 meter/2 metersNumber of Features: 36,543,233Feature Request Limit: 10,000Source: USDA Natural Resources Conservation ServicePublication Date: October 1, 2019ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/rest/servicesData from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).AttributesKey fields from nine commonly used SSURGO tables were compiled to create the 173 attribute fields in this layer. Some fields were joined directly to the SSURGO Map Unit polygon feature class while others required summarization and other processing to create a 1:1 relationship between the attributes and polygons prior to joining the tables. Attributes of this layer are listed below in their order of occurrence in the attribute table and are organized by the SSURGO table they originated from and the processing methods used on them.Map Unit Polygon Feature Class Attribute TableThe fields in this table are from the attribute table of the Map Unit polygon feature class which provides the geographic extent of the map units.Area SymbolSpatial VersionMap Unit SymbolMap Unit TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the table using the Map Unit Key field.Map Unit NameMap Unit KindFarmland ClassInterpretive FocusIntensity of MappingIowa Corn Suitability RatingLegend TableThis table has 1:1 relationship with the Map Unit table and was joined using the Legend Key field.Project ScaleSurvey Area Catalog TableThe fields in this table have a 1:1 relationship with the polygons and were joined to the Map Unit table using the Survey Area Catalog Key and Legend Key fields.Survey Area VersionTabular VersionMap Unit Aggregated Attribute TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the Map Unit attribute table using the Map Unit Key field.Slope Gradient - Dominant ComponentSlope Gradient - Weighted AverageBedrock Depth - MinimumWater Table Depth - Annual MinimumWater Table Depth - April to June MinimumFlooding Frequency - Dominant ConditionFlooding Frequency - MaximumPonding Frequency - PresenceAvailable Water Storage 0-25 cm - Weighted AverageAvailable Water Storage 0-50 cm - Weighted AverageAvailable Water Storage 0-100 cm - Weighted AverageAvailable Water Storage 0-150 cm - Weighted AverageDrainage Class - Dominant ConditionDrainage Class - WettestHydrologic Group - Dominant ConditionIrrigated Capability Class - Dominant ConditionIrrigated Capability Class - Proportion of Mapunit with Dominant ConditionNon-Irrigated Capability Class - Dominant ConditionNon-Irrigated Capability Class - Proportion of Mapunit with Dominant ConditionRating for Buildings without Basements - Dominant ConditionRating for Buildings with Basements - Dominant ConditionRating for Buildings with Basements - Least LimitingRating for Buildings with Basements - Most LimitingRating for Septic Tank Absorption Fields - Dominant ConditionRating for Septic Tank Absorption Fields - Least LimitingRating for Septic Tank Absorption Fields - Most LimitingRating for Sewage Lagoons - Dominant ConditionRating for Sewage Lagoons - Dominant ComponentRating for Roads and Streets - Dominant ConditionRating for Sand Source - Dominant ConditionRating for Sand Source - Most ProbableRating for Paths and Trails - Dominant ConditionRating for Paths and Trails - Weighted AverageErosion Hazard of Forest Roads and Trails - Dominant ComponentHydric Classification - PresenceRating for Manure and Food Processing Waste - Weighted AverageComponent Table – Dominant ComponentMap units have one or more components. To create a 1:1 join component data must be summarized by map unit. For these fields a custom script was used to select the component with the highest value for the Component Percentage Representative Value field (comppct_r). Ties were broken with the Slope Representative Value field (slope_r). Components with lower average slope were selected as dominant. If both soil order and slope were tied, the first value in the table was selected.Component Percentage - Low ValueComponent Percentage - Representative ValueComponent Percentage - High ValueComponent NameComponent KindOther Criteria Used to Identify ComponentsCriteria Used to Identify Components at the Local LevelRunoff ClassSoil loss tolerance factorWind Erodibility IndexWind Erodibility GroupErosion ClassEarth Cover 1Earth Cover 2Hydric ConditionHydric RatingAspect Range - Counter Clockwise LimitAspect - Representative ValueAspect Range - Clockwise LimitGeomorphic DescriptionNon-Irrigated Capability SubclassNon-Irrigated Unit Capability ClassIrrigated Capability SubclassIrrigated Unit Capability ClassConservation Tree Shrub GroupGrain Wildlife HabitatGrass Wildlife HabitatHerbaceous Wildlife HabitatShrub Wildlife HabitatConifer Wildlife HabitatHardwood Wildlife HabitatWetland Wildlife HabitatShallow Water Wildlife HabitatRangeland Wildlife HabitatOpenland Wildlife HabitatWoodland Wildlife HabitatWetland Wildlife HabitatSoil Slip PotentialSusceptibility to Frost HeavingConcrete CorrosionSteel CorrosionTaxonomic ClassTaxonomic OrderTaxonomic SuborderGreat GroupSubgroupParticle SizeParticle Size ModCation Exchange Activity ClassCarbonate ReactionTemperature ClassMoist SubclassSoil Temperature RegimeEdition of Keys to Soil Taxonomy Used to Classify SoilCalifornia Storie IndexComponent KeyComponent Table – Weighted AverageMap units may have one or more soil components. To create a 1:1 join, data from the Component table must be summarized by map unit. For these fields a custom script was used to calculate an average value for each map unit weighted by the Component Percentage Representative Value field (comppct_r).Slope Gradient - Low ValueSlope Gradient - Representative ValueSlope Gradient - High ValueSlope Length USLE - Low ValueSlope Length USLE - Representative ValueSlope Length USLE - High ValueElevation - Low ValueElevation - Representative ValueElevation - High ValueAlbedo - Low ValueAlbedo - Representative ValueAlbedo - High ValueMean Annual Air Temperature - Low ValueMean Annual Air Temperature - Representative ValueMean Annual Air Temperature - High ValueMean Annual Precipitation - Low ValueMean Annual Precipitation - Representative ValueMean Annual Precipitation - High ValueRelative Effective Annual Precipitation - Low ValueRelative Effective Annual Precipitation - Representative ValueRelative Effective Annual Precipitation - High ValueDays between Last and First Frost - Low ValueDays between Last and First Frost - Representative ValueDays between Last and First Frost - High ValueRange Forage Annual Potential Production - Low ValueRange Forage Annual Potential Production - Representative ValueRange Forage Annual Potential Production - High ValueInitial Subsidence - Low ValueInitial Subsidence - Representative ValueInitial Subsidence - High ValueTotal Subsidence - Low ValueTotal Subsidence - Representative ValueTotal Subsidence - High ValueCrop Productivity IndexEsri SymbologyThis field was created to provide symbology based on the Taxonomic Order field (taxorder). Because some mapunits have a null value for soil order, a custom script was used to populate this field using the Component Name (compname) and Mapunit Name (muname) fields. This field was created using the dominant soil order of each mapunit.Esri SymbologyHorizon TableEach map unit polygon has one or more components and each component has one or more layers known as horizons. To incorporate this field from the Horizon table into the attributes for this layer, a custom script was used to first calculate the mean value weighted by thickness of the horizon for each component and then a mean value of components weighted by the Component Percentage Representative Value field for each map unit. K-Factor Rock FreeEsri Soil OrderThese fields were calculated from the Component table using a model that included the Pivot Table Tool, the Summarize Tool and a custom script. The first 11 fields provide the sum of Component Percentage Representative Value for each soil order for each map unit. The Soil Order Dominant Condition field was calculated by selecting the highest value in the preceding 11 soil order fields. In the case of tied values the component with the lowest average slope value (slope_r) was selected. If both soil order and slope

This feature service displays all disclosable soil descriptions (pedons) mined directly from the USDA-NRCS National Soil Information System (NASIS) Database. It is intended for NRCS-Soil and Plant Science Division (SPSD) employees, NRCS soil scientists, and National Cooperative Soil Survey Cooperators.The service can be opened in an ArcMap or ArcGIS Pro session by clicking on the upper right option ‘Open in ArcGIS Desktop’ and choose ArcMap or ArcGIS Pro. To add the service to an existing ArcGIS Pro session following the instructions here. To download all NASIS Pedon related tables use the NCSS-Pedons ArcGIS Toolbox. The feature service can also be accessed through other popular platforms such as QGIS and R by authenticating with your NRCS ArcGIS Online username and password.FYI for SPSD users: Pedons are rendered into a point layer using the Std Latitude and Std Longitude coordinates from the Site table with attributes from the pedon table as sourced from the NASIS Pedon Object. If a pedon does not have coordinates populated in the Site table, then a Longitude (X) and Latitude (Y) of 0.0 E and 90.0 N are used to represent the pedon. Pedons with an “Undisclosed Location” attribute in the Subcategory field from the Site Text table will not be published in this feature service.A pedon is a three-dimensional body of soil that has sufficient area (roughly 1 to 10 m2) and depth (up to 200 cm) to be used in describing the internal arrangement of horizons and in collecting representative samples for laboratory analysis.Currently, the NASIS Pedons feature layer contains 795,481 pedons and was last updated November 09 2023 at 10:21 PM CST.

From gridded National Soil Survey Geographic Database (gNATSGO). Used Soil Data Development Toolbox > gSSURGO Mapping Toolset > Create Soil Map Tool, Exported Data Layer to TIFF, and Used Spatial Analyst > Reclass > Lookup Tool to create this data layer and display the HYDROLGRP_. Follow instructions in "How to Create an On-Demand Soil Property or Interpretation Grid from gNATSGO". Shows sSSURGO data for California. A - sand, loamy sand, sandy loam B - loam, silt, loam or silt C - sandy clay loam D - clay loam, silty clay loam, sandy clay, silty clay, or clay The gridded National Soil Survey Geographic Database (gNATSGO) is a USDA-NRCS Soil & Plant Science Division (SPSD) composite database that provides complete coverage of the best available soils information for all areas of the United States and Island Territories. It was created by combining data from the Soil Survey Geographic Database (SSURGO), State Soil Geographic Database (STATSGO2), and Raster Soil Survey Databases (RSS) into a single seamless ESRI file geodatabase. The state-wide gNATSGO databases contain a 10-meter raster of the soil map units and 70 related tables of soil properties and interpretations. It is designed to work with the SPSD gSSURGO ArcTools. Users can create full coverage thematic maps and grids of soil properties and interpretations for large geographic areas, such as the extent of a State or the conterminous United States. Please note that for the CONUS database, only a 30 meter raster is included. SSURGO is the SPSD flagship soils database that has over 100 years of field-validated detailed soil mapping data. SSURGO contains soils information for more than 90 percent of the United States and island territories, but unmapped land remains. Click here for the current completion status of SSURGO mapping. STATSGO2 is a general soil map that has soils data for all of the United States and island territories, but the data is not as detailed as the SSURGO data. The Raster Soil Surveys (RSSs) are the next generation soil survey databases developed using advanced digital soil mapping methods. https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcseprd1464625) Use the Create A Soil Map ArcTool from the gSSURGO Mapping Toolset in the Soil Data Development Toolbox to make a TIFF data layer (Instructions: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcseprd1464625#grid). Make a Hydrological Soils Group Map, and display it using the Hydrolgrp_ attribute. NotesThe SPSD refreshes all published soil databases annually. gNATSGO will be included in the refresh cycle, which will provide a new up-to-date version of the database each year. gNATSGO is an ESRI file geodatabase. The soil map units are delivered only as a 10-meter raster version and are uniquely identified by the mukey, which is included in the attribute table. No vectorized version of the soil map units is included in gNATSGO. The database has 70 tables that contain soil attributes, and relationship classes are built into the database to define relationships among tables. The raster can be joined to the Mapunit and Muaggatt tables in the MUKEY field. The database contains a feature class called SAPOLYGON. The “source” field in this feature class indicates whether the data was derived from SSURGO, STATSGO2, or an RSS. A gNATSGO database was created for the conterminous United States and for each state or island territory that does not have complete coverage in SSURGO or has a published RSS. If you encounter an ArcMap error when working with a gNATSGO dataset that reads “The number of unique values exceeds the limit” try increasing the maximum number of unique values to render in your Raster ArcMap Options. Specific instructions can be obtained here: https://support.esri.com/en/technical-article/000010117