Tag Archives: SSURGO
New Map Packages for the SSURGO Downloader
by Rich Nauman, Product Engineer, Esri. Do you need to use soil data in your analysis? Simply open the SSURGO Downloader Application, navigate to your project area, click the map to open a pop-up and then click the download link … Continue reading
Agricultural capability of soils web maps now on ArcGIS Online
by Michael Dangermond, Senior Digital Cartographer, Esri
Two new web map applications showing agricultural capability for the soils of the United States are now on ArcGIS Online: Agricultural Capability of Soils and Agricultural Capability of Soils with Prime Farmland. Find out where the best agricultural lands are, and if there are any soil limitations. Find out where to find Prime Farmland, which takes into consideration soil quality, growing season, and moisture supply needed for the agricultural productivity to sustainably produce high yields of crops.
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Soil hydrology web map with hydrologic group and hydric classification
by Michael Dangermond, Senior Digital Cartographer, Esri
The Soil Hydrology of the United States Web Map Application brings some of the most important hydrologic soil properties together in one map. Find hydrologic group codes for hydrologic and hydraulic models. Find hydric soil information to determine wetland land classification. Find depth to the water table for groundwater analysis and well drilling operations.
SSURGO Soils Tools: Part 2
We added a new tool for summarizing classified data to our SSURGO toolbox. The SSURGO Component Classified tool takes a categorical field in the SSURGO component table and produces an output table summarizing the proportion of each category in the field for each map unit.
The SSURGO Tools version 2.0 toolbox is available in the Esri Hydro Resource Center and the Soils Atlas Group on ArcGIS.com.
In SSURGO Soils Tools Part 1, we discussed how values contained in the SSURGO component table could be mapped by flattening the many-to-one relationship between records in the component table and the map unit polygons using a weighted average approach. However, many useful fields in the component table contain categorical data. For example, the component table field hydricrating has values of yes, no, unranked, and not prime. Since each map unit polygon has one or more records in the component table, the components must be aggregated to produce a map. The Component Classified Tool aggregates the data by summing the proportion of each class for all the components in each map unit. To produce a map, the output table from this tool is joined to the map unit polygons using the mukey field and symbolized.
Like the weighted average tool, the SSURGO component classified tool takes three inputs:
- A list of component table fields to process separated by semicolons
- A path to a geodatabase containing two tables – “component” and “mapunit”
- A path to an output folder or geodatabase
For each field in the input field list, the script creates an output table using the field’s name as the output table name and adds a field to the table to store the mukey which is later used to join to the map unit polygons and a no data field to store the proportion of the map unit with no data in the selected field. The script reads through the field and creates a list of unique values and adds a field in the output table for each unique value.
Note that if more than 20 unique values are detected the script will abort the current field and begin processing the next field in the list. This value can be changed by modifying the maxLen value in line 127 of the script.
Once the output table has been set up, the script cycles through each record in the map unit table, selects all the component table records associated with that map unit, and sums the proportion of each value in the component table field for the map unit. The summed proportion of each value is then written to the appropriate field in the output table.
Figure 1: Example of output table.
The output from this tool can be mapped in a number of ways. In this example we can join the output table to the map unit polygons and symbolize areas by the proportion of prime farmland with hydric soils (hydricrating = “yes”).
Figure 2: Hydric soils in the Sacramento, California area.
The Classifed and weighted average tools can be downloaded from the Hydro Resource Center Script Gallery or the ArcGIS.com Soil Atlas Group.
For more information, comments, and to share ideas contact Richard Nauman (RNauman@esri.com) or Michael Dangermond (MDangermond@esri.com).
SSURGO Soils Tools: Part 1
The ArcGIS.com Soil Atlas Group provides access to soil data, services, and applications. In addition to other resources, the group currently contains 17 dynamic services derived from the National Resource Conservation Service’s Soil Survey Geographic Database (SSURGO).
SSURGO provides a vast array of information about soils in the United States. These data are stored in over 60 tables that provide information at three basic levels – map units, soil components, and soil horizons. Map unit polygons are the geographic unit associated with the SSURGO tables. Each map unit polygon has an “MUKEY” that connects it to a record in the map unit table.
Map unit polygons provide the basic geographic unit of the SSURGO dataset.
Records in the map unit table are associated with one or more records in the component table. Each component is associated with one or more records in the horizon table and each record in the horizon table represents one soil horizon for its associated component.
The map unit is the basic geographic element of the SSURGO database. Each map unit is associated with one or more components and each component is associated with one or more horizons.
With a few exceptions, the other tables in the SSURGO dataset are linked to the map unit, component, or horizon tables through the key fields MUKEY, COKEY or CHKEY.
Mapping some SSURGO fields is relatively straight forward. For example, the map unit table contains fields that can be mapped by joining the map unit polygons and the map unit table. Similarly, the map unit aggregated attribute table (MUAGGATT) provides nearly 40 fields that can be directly joined to the map unit polygons using the MUKEY field.
Our first efforts to provide direct access to the more challenging tables in SSURGO dataset have involved the component table. In order to map data from the component table, the 1-to-many relationship with the map unit polygons must be flattened to 1-to-1. For numeric fields (e.g. slope_r, elev_r), the most straightforward way to aggregate components for each map unit is to calculate the weighted average of each component. Each component has a field (comppct_r) that contains its relative proportion in the associated map unit allowing the calculation of a weighted average for each map unit.
We recently added the SSURGO Component Weighted Average tool to the Hydro Resource Center that calculates weighted average for numeric fields in the SSURGO Component Table. The script tool, build using Python and ArcGIS 10.0 takes three inputs:
- A list of component table fields to process separated by semicolons
- A path to a geodatabase containing two tables – “component” and “mapunit”
- A path to an output folder or geodatabase
For each component field in the input list of fields, the script tool makes an output table using the name of the field. The script then iterates through the records in the Map Unit table selecting the components associated with each one. The script multiplies the value of each component by the proportion of that component in the map unit and then sums the product for each map unit. Because the components of some map units do not sum to 100%, the script divides the sum of values by the sum of the proportion field. The final weighted average value and MUKEY for the map unit are then written to the output table.
An example of an output table created using the SSURGO Weighted Average script tool. The script uses the component field as the output table name (e.g. map_r.dbf ) and adds fields and values for MUKEY and the weighted average of the selected field for all components in each map unit.
Note that input fields must be a numeric type (float, double, short integer, long integer) and that the two data tables (map unit and component) must both be in the same geodatabase.
To find the tool, please check out the Hydro Resource Center Script Gallery.
For more information, comments, and to share ideas contact Richard Nauman (RNauman@esri.com) or Michael Dangermond (MDangermond@esri.com).
Citation
Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. Soil Survey Geographic (SSURGO) Database for [Survey Area, State]. Available online at http://soildatamart.nrcs.usda.gov.
Special thanks to NRCS for providing SSURGO data.
Is This Land Any Good? Land Capability Maps on arcgis.com
Let’s say you’re a farmer or farm real estate broker, and you are evaluating whether or not to buy a piece of land. Your business and your livelihood depends completely on the land and its capability to produce income.
How do you tell the difference between a bad piece of land and a piece of land that has good potential but hasn’t been managed well or has otherwise been neglected? What can the piece of land do, and what is it really worth?
In a time of great uncertainty and volatility in financial markets and real estate valuation, the inherent capability of a piece of land’s soil asset has just become a lot easier to estimate. Image credit: USDA
To help answer these questions, esri has produced two new maps and map layers on arcgis.com. Both are planning-level maps of the economic capability of the United States’ soils. One map shows the economic capability when the soil is irrigated and the other when the soil is not irrigated. These maps are entitled Irrigated Land Capability Class and Non-Irrigated Land Capability Class, respectively.
Both maps are made directly from the SSURGO planning level soil dataset from NRCS. For the more technical among us, we used the MUAGGATT table fields ICCDCD and NICCDCD from SSURGO. Both maps cover the entire USA including Hawaii, Alaska, and Puerto Rico.
At 1:24,000 scale, each part of the United States falls into one of eight broad land capability classes.
The first four classes (1-4) are useful for growing crops, where each class from one to four needs more management or treatment, and has more limitations than the previous class. For example, classes 3 and 4 require more management or treatment than classes 1 and 2.
The last four land capability classes (5-8) are not useful for crops. NRCS recommends these lands be used for things other than crops, like rangeland, forestland, or wildlife habitat. Class eight isn’t even good for forestry, pasture or rangeland, and so instead NRCS recommends those lands be used for recreation, wildlife habitat, watershed, or aesthetic purposes.
These maps feature a color scheme (shown here in 50% transparency) that matches an image of a sample landscape that you see when you click on each soil map unit. This graphic may then be used like a second legend, displaying the eight classes for you on a replica landscape.
Land Capability Class is one of the most important concepts in the US soil dataset SSURGO. Land Capability Class is even used in some states for property tax assessment. In the State of Ohio, for example, the tax code prescribes specifically how to use this map to determine property tax.
Esri plans to release more land capability maps, specifically Land Capability Subclass. We will let you know as soon as these maps are complete and online, and rest assured that the subclasses will be in a format that is easily mashed up with either the Irrigated or Non-Irrigated Capability Class maps.
Special thanks to Michael Dangermond for providing this post. Questions for Michael: mdangermond@esri.com
Now on ArcGIS.com: More Hydro-Related Webmaps
Of interest to its hydro customers, Esri has web-enabled four more hydro-related soil maps of the United States from the NRCS SSURGO dataset. The source of the data for these maps is the Map Unit Aggregate Attribute table or MUAGGATT.
The new maps released are as follows:
Ponding Frequency – Presence*
The percentage of the map unit that is subject to water being ponded on the soil surface, expressed as one of four classes; 0-14%, 15-49%, 50-74% or 75-100%.
Water Table Depth – Annual Minimum*
The shallowest depth to a wet soil layer (water table) at any time during the year expressed as centimeters from the soil surface, for components whose composition in the map unit is equal to or exceeds 15%.
Water Table Depth – April-June Minimum*
The shallowest depth to a wet soil layer (water table) during the months of April through June expressed in centimeters from the soil surface for components whose composition in the map unit is equal to or exceeds 15%.
The distance from the soil surface to the top of a bedrock layer, expressed as a shallowest depth of components whose composition in the map unit is equal to or exceeds 15%.
In addition to the new maps, some changes were made to the cartography
on the previously released maps entitled Drainage Class-Dominant
Condition and Drainage Class-Wettest. In these webmaps, the new color
scheme has been improved to allow for an easier comparison of soil
drainage characteristics. With the new scheme it is now much easier to
read whether soil drains too much or too little (according to NRCS’
existing classification scheme), and how much or how little in
comparison to neighboring soils.
*These maps are ready to use, but are still beta products at the moment. They will undergo further review, so keep in mind that map colors and the contents page are subject to change. The data is in the same state it was since being provided by the NRCS. So, the data itself is not subject to change, only the cartography and the web medium.
Special thanks to Michael Dangermond for providing the post. Questions for Michael: MDangermond@esri.com.
New Hydro-Related Web Maps on Arcgis.com
Esri has web-enabled four soil maps of the United States based upon the NRCS SSURGO dataset. They will be served directly to the ArcGIS system, and their content nodes may be retrieved from arcgis.com or within arcmap itself in version 10. The first maps to be enabled will be from the MUAGGATT attribute table provided in the NRCS SSURGO dataset encapsulating their recommended map unit aggregations. All SSURGO based web maps are enormous in size, they cover the entire United States at once at the planning scale of 1:24:000. At the moment they are being served by the amazon cloud where they may be used in your maps and applications immediately.
The four soil maps are:
HYDROLOGIC GROUP – DOMINANT CONDITIONS
In this web map, infiltration rates are grouped into some very broad class estimates. You may use dominant hydrologic group as a basic input to estimate runoff potential in a watershed. A full explanation of the hydrologic group codes may be found on its arcgis.com service page.
HYDRIC CLASSIFICATION – PRESENCE
This web map indicates some very basic facts about the presence of hydric soils in a soil map unit, whether the soil map unit is made up of all hydric or part hydric soils, or if the map unit is not made of hydric soils at all.
DRAINAGE CLASS – DOMINANT CONDITION
These web maps show drainage class for each soil map unit. There are two drainage class maps based upon two methods of computing the class. The first method shows drainage class by the wettest soil component in the soil map unit, and the second shows drainage class by the most dominant component in each map unit. You may want to use one or the other in modeling depending on what you are trying to simulate in your model.
These soil maps are only the beginning for Esri. Stay tuned to the mapping center and the hydro blog for more hydro related soil maps which will probe deeper into the SSURGO datasets with increasing sophistication.
Special thanks to Michael Dangermond for providing the post. Questions for Michael: MDangermond@esri.com
ArcGIS Online Soils Survey Map now available
A national map of the Department of Agriculture’s SSURGO data is
available on ArcGIS Online.
Two blogs have already been written
about the topic:
Here are some images from the online map service…
