Soil Maps & GIS Using SSURGO Data in ArcView

Transcription

1 Soil Maps & GIS Using SSURGO Data in ArcView A guide to obtaining, preparing, and using SSURGO soil data in ArcView projects. Dan Harms Jo Daviess Carroll AVC Elizabeth, IL 1

2 Table of Contents Introduction 1 Part I: Obtaining SSURGO Data 3 Downloading SSURGO Data 3 Using Soil Data Mart 3 Downloading Data not on Soil Data Mart 6 Part II: Preparing SSURGO Data for Use 8 Soil Data Mart Data 9 Using the Access Template 10 SSURGO Website Data (ftp) 11 Part III: Using SSURGO Data in GIS with ArcView 3.x 13 Understanding SSURGO Spatial Data 14 Understanding SSURGO Tabular Data 15 Building ArcView Projects SSURGO in ArcView 16 Selecting the Appropriate Fields with the Database Access Extension 35 Converting Tables to ArcView.dbf tables 39 Using co.. tables Creating Component Look-up Tables 41 Summary 43 Acknowledgements Appendix 2

3 Introduction Using SSURGO Data in ArcView Projects There are few interactions between mankind and planet earth more intimate and common than man s contact and dependence upon soil. Soil sustains and supports the plants which feed, clothe and shelter man, soil purifies the water man uses, provides banks and levees which divide dry land from water and swamps, formed into bricks, spread on walls, and pushed between logs, soil is an integral part of man s shelter from the elements. Soil supports our houses and roads and cushions our activities from the harsh realities of bedrock. Along with all of the benefits man derives from soils, man s mismanagement of soil can make it one of mankind s biggest problems. Eroded soils clog navigation of rivers and streams. Landslides destroy houses and lives. Wind borne soil particles destroy machines, make breathing difficult, and mar the beauty of man s structures. Soil scientists or pedologists have studied and documented the chemical and physical properties of soils and the impact of these properties on man s activities for years. Farmers and ranchers, land use managers and planners, engineers and environmentalists have used soil maps for decades. Soils, their properties and their locations have influenced many decisions. When dealing with something which has many properties and many locations GIS is moving to the forefront as the tool of choice. Recognizing the role of GIS in applying the 3

4 data and mapping of soils in modern agriculture, environmental management, and engineering, the United States Department of Agriculture (USDA) through its Natural Resources Conservation Service (NRCS) has made soil maps of much of the United States available to the public. These maps and data, known as SSURGO (Soil Survey Geographic Data) are available in digital formats either by ordering CDs or by download. The formats available are compatible with the most popular GIS desktops and can be quite easily used in ESRI ArcView 3.x and ArcGIS. The tabular data is designed to work with one of the most popular Relational Database Managers, Micro Soft Access. This project is designed to help a GIS user, student, instructor, or professional obtain, sort through and use the SSURGO data. The project is not about the soils, soil maps, or how they are created, rather it is about obtaining the data and beginning to understand how to mine the wealth of information in the data. It is hoped that this work will help the teacher develop more meaningful and applied local GIS problems for the classroom. The guidelines here should help instructors develop the data and present it in ways that the students can use to apply GIS to problems in Vocational Agriculture, Soils Studies and Community Planning, Biology and Environmental Studies and Civil Engineering. The information may also give advanced GIS students experience in working with very extensive data sets and incorporating RDBMs like Access in their experiences. 4

5 There are extensive metadata files available exploring all of the intricacies of SSURGO data available from the NRCS, this project is by no means to be considered a replacement of this information. Rather, this is to be a guide to help the user new to SSURGO data find the information needed for their specific set of problems. Although the activities included in this project are not very advanced it will be helpful if the user is comfortable with ArcView. The Database Access Extension is used, and the user should be able to load and activate this extension. The user should be familiar with creating folders, naming files, locating data, and many other common Windows skills. The user wishing to access SSURGO data and prepare it for use in the classroom should be somewhat familiar with databases and especially Micro Soft Access. The user also needs to be able to work with compressed files and WinZip. SSURGO data is extensive, involving many tables and many many records in the tables. The size of the dataset can tax even the largest computers. Instructors building lessons with the data may want to pay particular attention to the instructions on how to create customized tables for the data they want their students to analyze. Part of this project is an archive containing examples of SSURGO data, and datasets which will allow a user to work with the examples provided here. Several sample lessons using various data are also provided. 5

6 SSURGO data can be a very valuable tool in helping teachers find applicable, freely available GIS data which can provide real-world experiences for students. Using SSURGO data, local problems can be approached using data used by professionals in the field. Students in rural areas particularly can benefit from the data, but Urban students can also use the data. Soil mapping data is most applicable to lands undisturbed by development, a type of land often rare in Urban environments. However, the availability of the data from recognized national areas, like the Dinosaur National Monument data used in one of the lessons, plus the fact that more and more areas are being set aside as natural areas by the Federal, State, and Local governments should allow imaginative applications of the data. Finally, a word of caution, SSURGO data is extensive and detailed. From it one can do all kinds of GIS enhanced analysis. It should be kept in mind however that the data is at best accurate at the Macro level, and the USDA does not recommend its application to areas of less than five acres. SSURGO data can be applied to determine general trends and attributes for an area, but in no case does it replace or supersede on-site investigation, testing, or observation by trained professionals. Part I Obtaining SSURGO Data: SSURGO data can be obtained from a number of sources. Many local NRCS offices have local soil data available on CD that can be had for a nominal charge. The data may also 6

7 be ordered from the NRCS on CDs. More information about ordering hard copies of the data is available at: The data can also be obtained by downloading from the NRCS Soil Data Mart at: Many state GeoSpatial data websites are also making SSURGO data available, or are providing links to the national sites. Downloading SSURGO Data: To use SSURGO data obtained from the NRCS site in ArcView 3.x (or ArcGIS), several tools must be used. Prior to downloading the data, the user should make sure that the tools are available to handle the data. SSURGO attribute data is delivered as compressed.txt files that can be imported into Micro Soft Access using tools provided by the NRCS, the data is compressed using WinZip. Therefore, the user should have Wizip and Access available prior to accessing the data. The data sets are large (even compressed they may be nearly 50MB), so adequate data storage should be available. Due to the size of the datasets a high speed internet connection is strongly recommended. 7

8 Presently, the NRCS Soil Data Mart is under development so there are two different routes that may appear depending upon the status of the site. Using the Soil Data Mart Access the Soil Data Mart at: The first page of this site will link you to a page allowing the selection of a state Clicking this button will load a table allowing you to select the state of interest. Notice that the column on the right indicates the number of datasets available from the Soil Data Mart for the state. 8

9 Highlight the state desired, and click the Select County or Select Survey Area button. The Select Survey Area button will result in a table of the available surveys listed by identifier number, and will also list the county name or area covered by the survey. The Select County button will give you a list of the counties in the state that have surveys available. After selecting the soil survey (either from the county or the soil survey area), the download page will open. Across the top of this page the user is allowed to select the amount of data desired. For our purposes, both tabular (attribute) and spatial data will be downloaded. The spatial data format is selectable, the data is available as ESRI shapefiles, ArcInfo coverage, or ArcInfo exchange (.e00) formats. Shapefiles will be used in this demonstration. 9

10 The user is also allowed to specify the coordinate system for the data. The data maybe obtained as GCS (Geographic Coordinate System) in NAD 83, or in UTM (Universal Transfer Mecator) zone data, NAD 83. Once the format and the coordinate system are selected, the user has several database template choices available. Tabular data is transferred to Micro Soft Access via a database template. National NRCS templates are available for Access 2000, 2002 and Access 97. Some states have also developed templates for local use. The available templates can be determined by using the scroll button to the right of the table. The template choice will depend upon the version of Access available to the user. For the purposes here, the soildb_us_2000 template will be used. All of the templates operate similarly. After the appropriate dataset is selected, the user is asked to provide an address. Clicking the Submit Request button will send the request to the NRCS server. An acknowledgement will flash on the screen informing that the request has been received and notification will be sent when the data is ready. 10

11 Depending upon how busy the servers are, the notification that the data is ready will be sent relatively rapidly (frequently within a few minutes). The notification will review the parameters sent in the request. The data will be available on the NRCS ftp server for 5 days. A link to the server is contained in the header of the , and clicking on the link will take the user to the server. (if the hotlink does not work, cut and paste the link into a browser). Clicking on the link will open the Save As dialog box in Windows, allowing selection of the storage site. Note: Due to the size of the files it is advisable to create the appropriate folders for the data prior to beginning downloads. The downloaded zip archive will contain the spatial data, as shapefiles, the tabular data for the soil survey area, and a copy of the Access template necessary to view and work with the tabular data. Downloading data not on the Soil Data Mart 11

12 Although more and more data is being made available through the Soil Data Mart, not all of the available data may be transferred to this site. The data may be available through the older SSURGO interface. If the area in question is not found through the Soil Data Mart, check the National SSURGO website: (This link appears at the top of the SSURGO web page as: check the National SSURGO Website. ) Clicking this link will open the Soil Survey Geographic (SSURGO) Database. Scrolling to the bottom of the page will give access to a link: Download SSURGO Data Clicking Download SSURGO Data will open a page allowing the selection of the state the desired information is in. Selecting the desired state will result in a table listing the available soil surveys by county (in some cases larger areas covering several counties may be available). 12

13 The counties or areas highlighted as a hotlink in the table indicate the available soil surveys. The counties with asterisks and not highlighted To the right of the county name is a metadata file. Clicking on the file will open it in the browser. The metadata should be saved to the soils folder as it gives valuable information. Clicking on the desired county will open the ftp site for that data. There are a number of files available for download from the site. For the purposes of this project, the data will be downloaded as shapefiles. Not all data is available as shapefiles. The data may be available as ArcInfo exchange files (.e00) in these cases..e00 data is in the out.zip archive. 13

14 Clicking on the desired file will open the Save As dialog box allowing the download to be directed to the appropriate folder. (in some cases, clicking on the file will attempt to open it, if this happens, right click and select Copy to Folder ) In most cases, the compressed shapefile archive will also contain a compressed set of the tabular data. The tabular data is also available in the tab.zip file. If the data is downloaded from the ftp site (not the Soil Data Mart), the appropriate Access Template must also be downloaded. The template is available for download at: This page may be accessed via hotlink from the Soil Survey Geographic Database page.. Access Link A selection of templates will be available. The selection used depends upon the version of Access available to the user. Whenever possible, the most recent version of the template should be used. 14

15 Save the selected template to an appropriate folder. (Generally save the template in the same folder as the data.) Part II Preparing SSURGO Data for Use. The materials contained in the downloaded zip archives will vary depending upon the source. The newer Soil Data Mart downloads are more inclusive and somewhat easier to use, although the data from the earlier SSURGO Website can also be adopted fairly simply. The data from the different sources will each be discussed in this project. Soil Data Mart Data 15

16 Data downloaded from the Soil Data Mart will contain both the spatial and tabular data along with the template specified in the request. Opening the archive with WinZip (or similar utility) will show the shapefiles in their component forms, the ASCII text files of tabular data, a zip archive containing the Access template and a Readme.txt file. Metadata files in both.txt and.xml formats will also be available. Extracting the archive with WinZip will result in a directory structure containing the data. (the specific structure and more information is outlined in the Readme.txt file contained in the achieve) In the example to the right, data for North Carolina (Anson County) was downloaded to a North Carolina folder. A subfolder data was created and the downloaded archive extracted The soil_nc007 folder also contains the metadata, a copy of the Readme file, and an archive containing the Access template. 16

17 After extracting the original archive, use Windows Explorer to browse to the folder containing the extracted files. Double click on the soildb_us_2000.zip (or appropriate template) file to open it in WinZip. Extract the template to the tabular folder. Note: It is not absolutely necessary to place the template in the same folder as the data, however if several sets of data will be used, a separate copy of the template must be used for each dataset. Downloading a new template with each dataset and using it exclusively for the data it is downloaded with may simplify data management later. Using the Access Template In order to load the soil tabular data into Access using the template, the path to the folder containing the tabular data will need to be entered. This process can be simplified by using cut & paste techniques. To use this technique, the full path to a folder must be shown in the address bar of windows explorer if the full path does not appear adjust using the Folder Options selection under the Tools pull-down in Windows Explorer. 17

18 Use Windows Explorer to browse to and open tabular folder. The contents (right) pane of Explorer should display the ASCII text files of tabular data and the soildb_us_2000.mdb files. In the address bar, highlight the path to this folder. Right click and select Copy. Open the Access template. This may be accomplished by: 1. Start Access; In the dialog box that opens select Open an existing file. 2. Click More Files. 3.Browse to folder containing the template. 4. Open the template or 1. Browse to the folder containing the template. 2. Double click the soildb_us_2000.mdb to open it in Access. Access will open and the following dialog box will appear. 18

19 Click in the white box. Right click and select Paste to enter the path to your tabular data. Make sure the path includes the drive letter. Click OK. Access will work for a while, importing the ASCII files to Access tables. When the import is finished, close the report generator that opens. This report generator is a valuable tool for creating printed reports of the data in the database, but will not generally be used in this project. Exit Access. A database that contains the tabular data associated with the downloaded soil survey has now been created. Since the template was accessed from the Tabular folder, the database was saved back to and can be opened from that folder. This data is ready to be imported into ArcView. SSURGO Website Data (ftp) Development of the data downloaded via the ftp site is similar to the previous data. Since the data does not benefit from the organization provided by the Soil Data Mart, the user must do some of the organization. 19

20 The shp.zip file downloaded contains the spatial data (shapefiles) and a zipped file containing the tabular data. Archive containing tabular One method of working with the data duplicates the system used by the Soil Data Mart. Under the folder containing the downloaded data create an identified soils folder. In this example, the folder was named with the soil survey identifying number shown above. In this folder create two subfolders named Spatial and Tabular. Open the shp.zip archive in WinZip. Select the shapefile components using the Shift key in windows. When the shape files are selected, click Extract. In the resulting dialog box browse to the spatial folder created under the soil identifier folder. (in 20 this case soil_il037)

21 Click Extract Next, extract the tabular data. Double Click the.gz archive from within WinZip. When asked if you wish to open the file in a temporary location respond OK. WinZip will open displaying the ASCII text files containing the tabular data. Click Extract. Browse to the tabular folder created under the soils folder. Make sure All files is selected. Click Extract. The tabular data files will be extracted to the tabular folder. To keep all of the data together, extract the readme file to the root soils folder. Return to the download site and extract the Access template to the tabular data folder. 21

22 Convert the tabular data to an Access database using the steps outline previously in the section: Using the Access Template. When the data has been downloaded and extracted into the appropriate folders and the tabular data moved to an Access database, the soils data is ready to be used in ArcView or ArcGIS. The next sections will discuss how to develop projects based upon the data and how to load the data into ArcView. The tabular data may be used in ArcView directly from the Access database, or may be moved into ArcView and converted to dbf files. Converting the files to.dbf maybe necessary if the data and projects are to be used on workstations not equipped with Micro Soft Access or will be used with ArcExplorer. Part III Using SSURGO Data in GIS with ArcView 3.x SSURGO data is highly complex and contains literally thousands of polygons and attributes which can be associated with the polygons. Although the data is generally organized on a countywide basis many applications will use smaller subsets clipped from 22

23 the county. To make the data usable, it is necessary to understand how it is organized and how it can be sorted so that only the data necessary to solve the current problems is actually loaded into the desktop GIS. As seen in the download section, SSURGO data has two components, the spatial data and the tabular data. Understanding SSURGO Spatial Data SSURGO data is primarily developed in UTM, NAD83 projections. Data obtained from the Soil Data Mart may be requested in different projections including Geographic Coordinate System (decimal degrees), NAD83. Data from the ftp site will be in the UTM projections. Careful notes and reference to the appropriate metadata are necessary to properly use the data. Due to the nature of the soil maps and soil mapping units it is almost always necessary to use ground features to assist in locating the area the data applies to. Ground identifying features may be obtained from other GIS data including US Census Tiger files or aerial photos. Local GIS cadastral data is also an important source of location features. Some of the SSURGO data contains polygons which represent the USGS quadrangles covered by the soil mapping units. These are quite valuable tools to assist in determining the area covered by the soil maps. 23

24 Spatial data downloaded as part of SSURGO Soil Data Mart will always contain the following files. Soilsa_a: Soil Survey Area Boundary Polygons. These polygons identify the individual soil series or soil complexes mapped. Soilmu_a: Map unit boundary polygons. This polygon represents the entire area mapped by this data. It frequently is the county boundary. The spatial data may also include the following shapefiles, although all of them are considered optional: Soilmu_l: line map units Soilmu_p: point map units Soilsf_l: line spot features Soilsf_p: point spot features Soilsf_t: spot feature descriptions The actual name that appears in the extracted data will be as follows: Soilmu_a_NCOO7.shp The NC007 refers to the NRCS soil survey symbol. 24

25 Data downloaded from the older ftp site will be named differently. In this case, the files will be identified by the NRCS soil survey symbol followed by a letter. For instance, Dekalb County Illinois soils survey symbol is il037. The following shapefiles appear: Il037_a: Soil Survey Area Boundary Polygons. These polygons identify the individual soils series or soil complexes mapped. Il037_b: Soil Survey Map unit boundary Polygon. This polygon identifies the entire area mapped, frequently it is the county polygon. Il037_p: Point map units Il037_l: Line map units Il037_q: USGS 7.5 minute quadrangle polygons. The soil survey area boundary polygons, indicated by a are the files most used for site analysis with SSURGO data. Investigation of some of the other shapefiles is worthwhile, and more detailed maps can be created using the points and lines. The points frequently locate features such as rock outcrops, depressions, springs, or other naturally occurring phenomena. The lines may indicate ridges or other geographic or geological linear features. Understanding SSURGO Tabular data The tabular data associated with SSURGO data is extensive, 50 to 60 different tables of attribute data is not uncommon. To use SSURGO data, especially in a classroom, it is important to be able to identify and sort the information. 25

26 A brief introduction to soil mapping. Soils are a dynamic part of our world. Scientests working with soils, called pedologists, and especially those mapping soils attempt to differentiate soils from place to place. The differences in soils impact how crops will grow, waste will be purified, buildings and roads will be supported, and generally how man and earth will interact. Soils are the product of many different influences. The parent material or the materials soils are developed from impacts the final soil. The plants that grow on the soil effect what the soil becomes, the amount of precipitation and temperature change affects the soil, as well as the soil s aspect or slope and slope direction. Soils that are at the bottom of a slope will be different from those at the top due to run-off, erosion, and sedimentation. All of these developmental factors influence what a soil becomes as it matures. The soil development process creates differing layers of soil called horizons. A vertical slice through the horizons of a soil is called a soil profile. Pedologists test and observe the differences in the soil as one goes deeper. The differences found identify the horizons. The description of a soil through its layers is called a soil pedon. Many factors change as the soil gets deeper. Pedologists determine the amount of mineral matter, and percentage of sand, silt, and clay. They look at the amount of organic matter that has been added to the soil by plants and animals. Rainfall has a major impact on the soil development as water drains through the soil; it moves materials and changes the chemistry of the materials. The downward movement of materials by water is called leaching. Temperature extremes affect the soil, hot desert-like conditions dry the soil and prevent downward water movement, freezing and thawing moves particles and impacts the life of microbes and other plants and animals in the soil. These factors and more create changes in the horizons, and thus create unique pedons. The unique pedons are given names that are called Soil Series. Many soil mapping projects create areas identified by each soil series, where the mapping is more difficult or more complex groups of similar soil series are often grouped together as Soil Complexes. Mapping of Soil Series and Soil Complexes are both found in SSURGO data. The following illustration shows some of the SSURGO tables typically created when an Access template is used to import the SSURGO tabular data. 26

27 For the purposes of this project, we will be using a limited number of tables. The tables will be: Mapunit: This table lists the Soil Series or Complex names and commonly used map symbols. It contains the fields (generally mapunit key) which will provide the link between the spatial data and the tabular data. Muaggatt: This table summarizes many of the soil use limitations and allows the ranking of soils uses as Limited, slightly limited, or not limited. Component: This table lists many agriculture related and some engineering properties of the soil map units and is also valuable for developing site suitability, yield potential, and general use categories for the soil map units. The NRCS has provided more complete descriptions of the tables and their relationships. The documentation may be downloaded as.pdf files at: Building ArcView Projects SSURGO in ArcView To understand how the SSURGO data is in incorporated into ArcView, an ArcView project will be built using the data. 27

28 To start this project, SSURGO data must have been downloaded, unzipped, and the tabular data converted to an Access database using the applicable template. The data used in the following demonstration is from Anson County, North Carolina and is in the archive (soil_nc007.zip) in the SSURGO folder. [to work with the data, extract it to a write able storage device like the hard drive] ArcView 3.x is used with the Database Access extension active. 1. Start ArcView 2. When asked if you want to start with a new view click OK 3. When asked if you want to add data to the view click NO 4. Click the File pull-down and click Extensions 28

29 5. In the Extension window which opens, place a checkmark next to Database Access Click OK 29

30 6.Click the add data button. In the add theme dialog box, browse to the location of the North Carolina SSURGO spatial data. - Select the soilmu_a_nc007.shp shapefile. 7. The soilmu_a_nc007 features will load in the view. This is a very complex feature set so the load may take awhile. a. Check the mark next to the theme to make it visible if it is not. b. Make sure you expand ArcView to fill the screen and enlarge your view so you can see the individual polygons. Your view should be similar to the one below. 30

31 Make sure the theme is active with the highlighted box around as shown above. We will look at the attributes of this theme to determine the fields available. Identifying the field names is essential to joining the SSURGO tabular data. 8. Open the theme table using the Open Theme Table button. The double arrow is used to stretch the table so all of the fields are visible. 31

32 The table has eight fields. Shape field tells us that this is a polygon theme. Areasymbol identifies the soil mapping area and relates to the number on the downloads. Spatialver is an internal (NRCS) indicator of the original version of the data. Musym refers to the map symbols used to indicate soil series or mapping units on printed maps used with farmers and landowners. The mapping symbols used on soil maps vary from state to state. Mukey is a numerical key which will be used to join the tabular data and the spatial data. A unique key is used for each soil series or complex mapped. Shape_area is the area of each polygon. Since the North Carolina data was downloaded in GCS and the view properties for map units were not set in this example, the values here are meaningless for most uses. Shape_length is the length of the polygon perimeter. As above, the values in this example are meaningless. Objectid is a unique identifier for each polygon. 9. Adding SSURGO tabular data to the project. Close the attributes table. Click on Tables in the Project Window. 32

33 Click on the Project pull-down menu 33

34 Click Add Database Table The Database Access extension dialog box will open This dialog box controls what tables and the fields in those tables you will import into the ArcView project. There are several steps which must be completed in order to set-up the link between the database and ArcView. The Database Access extension provides a driver which translates the database tables (in this case Access The first table we will load is muaggatt First, create a unique name for the table, since we are using North Carolina data, and the table will be the map unit aggregate table an appropriate name might be NC-maggrat Highlight Table1 next to Table Name: and enter NC-maggrat 34

35 Next, the driver between the database and ArcView must be set. Click the button next to Create a new connection. At the top right of the dialog box there is a Database Access window, click the cascade arrow and select OBDC. SDE refers to ESRI s Spatial Database Engine which allows one to connect to ESRI SDE server. ODBC refers to Open Database Connectivity which provides drivers to a number of RDBM (Relational Database Managers) such as Access Click the Connect Button to the right of Create a new connection Connection button The Select Data Source dialog box will open. 35

36 Click the Machine Data Source tab. Using the scroll bar on the right, scroll down until you can select MS Access Database Click MS Access Database to select. Click OK. 36

37 The Select Database dialog box will open. Browse to the location of your North Carolina tabular data. (in the section on preparing SSURGO it was suggested that the Access database be placed in the same folder as the unzipped tabular data) Select the soildb_us_2000.mdb file and click OK. The database table list will load into the Database Access extension dialog box. 37

38 List of Tables in the Database. Use the scroll bar to the right of the Tables box to scroll down so that you can select muaggatt. When you locate muaggatt double click on it. Double clicking will cause the table name to appear in the Unique Column Table and the From boxes on the dialog box. 38

39 We want to bring all of the columns of this table into ArcView. Move to the Columns box and double click <All Columns> If you have set the query correctly, the Query button at the bottom right of the dialog box will be active. Click it. The NC-maggrat table will appear in your ArcView Project. Close the Database Access dialog box. Expand the NC-muagratt table you have just brought into ArcView. (Drag to the side to fill the screen) 39

40 Notice the field names. Understanding these field names is very important to using the data is analysis. Complete field name descriptions are available in the SSURGO Metadata. This may be downloaded from: The data is also available in the archive. The document is SSURGO table columns.pdf. Note: The entire set of metadata for the SSURGO data downloaded is available in report form in the Access database created with the NRCS Access template. Click on the Reports tab in the database contents in Access: It may be easier to print specific parts of the metadata from Access. The metadata is organized as follows: 40

41 Domains: This is the largest of the documents. This document gives descriptions of the classes that are listed as attributes in the fields or columns. For instance, definitions are given as to what Frequent, Very Frequent, and Rare refer to. If the field is filled with a value, the value is explained. Indexes: Defines the table s index field. Relationships: Identifies the type of database relationships, ie: One to One, One to Many Table Column Descriptions: This document gives a technical description of each field or column in each table. Table Columns: Gives technical data about each table. Lists number of columns. Tables: Description of the type of data found in each table. In order to understand the muagratt tables it is helpful to open the table in Access. Access will show the field or column names in Plain English, ArcView because of 16bit limitations condenses the field names. The following chart shows the field name comparisons. Access Name Mapunit Symbol ArcView Name musym 41

42 Mapunit Name Status Slope Gradient-Dominate Condition Slope Gradient-Weighted Average Bedrock Depth-Minimum Water Table Depth-Annual-Minimum Water Table Depth-April-June Flooding Frequency-Dominate Condition Flooding Frequency-Maximum Ponding Frequency-Presence Available Water Storage 0-25cm Weighted Average Available Water Storage 0-50 cm Weighted Average Available Water Storage cm Weighted Average Available Water Storage cm Weighted Average Drainage Class-Dominate Condition Drainage Class Wettest Hydrologic Group- Dominate Condition Irrigation Capability Class-Dominate Condition Irrigation Capability Class-Dominate Condition Aggregate Percent Non-irrigated Capability Class-Dominate Condition Non-Irrigated Capability Class-Dominate Condition Aggregate Percent Eng-Dwellings w/o Basements-Dominate Condition Eng-Dwellings with Basement-Dominate Condition Eng-Dwellings with Basements-Least Limiting Eng-Dwellings with Basements-Most Limiting Eng-Septic Tank Absorption Fields- Dominate Condition Eng-Septic Tank Absorption Fields-Least Limiting Eng-Septic Tank Absorption Fields-Most Limiting Sewage Lagoons-Dominate condition Sewage Lagoons-Dominate condition Muname Mustatur slopegraddcp slopegradwta brockdepmin wtdepannmin wtdepaprjunmin flodfreqdcd flodfreqmax ponfreqprs aws025wta aws050wta aws0100wta aws0150wta drclassdcd drclasswettest hydgrpdcd iccdcd iccdcdpct niccdcd niccdcdpc engdwobdcd engdwbdcd engdwbll engdwbml engstafdc engstafll engstafml engsldcd engsldcp 42

43 percentage Local Roads and Streets-Dominate Condition Construction Materials; Sand Source- Dominate Condition Construction Materials; Sand Source-Most Probable URB/REC-Paths and Trails-Dominate Condition URB/REC-Paths and Trails-Weighted Average FOR-Potential Erosion Hazard(Road/Trail)-Dominate Condition Hydric Classification-Presence AWM-manure and Food Processing Waste-Weighted Average Mapunit Key englsrdcd engcmssdcd engcmssmp urbrecptdcd urbrecptwta forpehrtdcd hydclps awmmfpwwta mukey Observation should show that the ArcView fieldnames result from abbreviations of the full name shown in Access. Note: In some cases importing the Access tables into ArcView results in duplicate field names. Duplicate field names will cause abnormal results in queries. After importing tables, check for duplicate field names. If they exist create an alias in the Table Properities. Some of the terminology repeats, understanding how the attributes are applied will help in the understanding; Dominate Condition: The soil polygons or mapunits are necessarily groups of similar soil conditions. The dominate condition is the most prevalent condition in the area but not necessarily the only condition. 43

44 Weighted Average: This value is the average of all of the conditions represented in the mapunit. Most Limiting & Least Limiting: These values represent the extremes of the conditions found in the mapunit. 10. Joining SSURGO tables in ArcView to do Site Analysis. As an example, the suitability of land for Septic Tank Absorption Fields will be analyzed. Make sure the NC-mauaggrat table is loaded in the ArcView project. Activate View 1, make sure the Soilmu_a_nc007 theme is active. Click the Open Theme Table button. Arrange the tables so that both can be seen.. 44

45 The common field in the two tables is Mukey. Use the slider bar at the bottom of the tables so that Mukey field is visible in both tables. Click the mukey field in the NC-muaggratt table. Click the Mukey field in the attributes of soilmu_a_nc007 table. Access the Table pull down and click join. 45

46 Activate View 1 by clicking on it. Double click the soilmu_a_nc007 theme in the table of contents to open the legend editor. In the legend type, click the cascade arrow to the right. 46

47 Select Unique Value. Click the cascade arrow next to Values Field: Scroll down until the Engstafdcd can be selected. Click on it. The result should be similar to that shown below. 47

48 Notice that 625 mapunits are not rated. This indicates that no data is available for these. In the final site analysis map these are generally shown as null value or white. Click on the symbol box next to Not Rated. Change the color to white or hollow. 48

49 Change the color of Not limited to Green. Change the color of Somewhat Limited to Yellow. Change the color of Very Limited to Red. Click Apply. The resulting map shows that very few places in Anson County North Carolina are suitable for a conventional septic system. Any developer or builder in this area needs to be aware that additional engineering and costs are likely to be incurred building in this area. 49

50 Selecting the appropriate fields with the Database Access Extension. There is a wealth of information available in the SSURGO data. One of the problems that arise is that the tables are so large they can cause a computer system to operate very slowly or crash. Some of the potential problems can be overcome by carefully selecting the tables and fields brought into ArcView. The database access extension has the ability to select the data from the Access database so that custom tables can be used in ArcView. In the following example, the soils of Anson Co. North Carolina will be used to develop a coniferous tree planting suitability map. 50

51 A study of the metadata will show that the attributes necessary for determining the suitability of the soils for coniferous trees are found in the component table. The component table is extremely large, and loading the entire table will tax the capacity of the computer system we are working on. To solve the problem we will create a table in ArcView that will only contain the fields necessary to do the analysis. 1. Open ArcView and add the soilmu_a_nc007 theme to a View (this may be already open from the previous work, in that case simply create a second view and add the theme) 2. Select Tables in the ArcView Project dialog box. 3. From the Project pull-down menu select Add Database Table 4. The Add Database Table dialog box will open. 51

52 If the connection to the North Carolina SSURGO tabular data has already been set for this project the connection will remain and the tables should appear in the Tables window. If the connection has not been made, see the previous instructions to create the connection. 5. Name this table NC-Comp CS Note: Each organization working with GIS should develop standardized ways of naming tables, views, and themes. These naming conventions are very important in organizing and using GIS data efficiently. NC-Comp CS can be interpreted as: North Carolina, Component Table, Coniferous Suitability. 6. Select the Component table in the Tables selection area: Make sure you double click the component table so that it loads 52

53 7. In the Columns selection box select the desired fields from the table Scroll to select the mukey field and the wlconiferous field. Double click on each to load them.. Click Query to build the table in ArcView. The resulting table will have two fields 53

54 8. Join the NC-Comp CS table to the attributes of soilmu_a_nc007 table using the common mukey field. 9. Use the Legend Editor-Unique Value tools to develop a view showing the suitability of soils in Anson County for growing coniferous trees. (Leave this project open to go on to the next area) Converting Access Tables to ArcView dbf tables 54

55 Linking ArcView to a RDBM using the Database Access extension provides flexible access to a very large pool of attribute data. As seen, the ability to pick and choose the tables and fields imported can be very valuable and give flexibility. There are cases however, where it may be advantageous to convert the tables loaded from Access to a.dbf form so that they may be used as traditional ArcView tables. The ability to export the Access (or other RDBM) tables to a dbf file is especially important when developing projects where limited computing power is used, where the RDBM software is unavailable, or where limitations in user skills makes using the database manager such as Access unadvisable. Converting the tables to dbf format is especially recommended for instructors developing tutorials or lessons. To convert a table developed via query with the Database Access extension. 1. Make the NC-Comp CS table active by clicking on the title bar From the File pull-down menu, select Export 55

56 The Export Table dialog box will open. 2.Select and click dbase 56

57 (ArcView will also import the tables saved as INFO and can work with Delimited Text, however when working with ArcView the dbase or dbf file format is much more familiar to most users.) 2. A second Export Table dialog box will open. The user may now name the table and select a site for storing the new.dbf table. 3. Close ArcView. Using Co tables to create maps. Creating Component Look-up Tables. SSURGO tabular data can be divided into categories based upon the table names. Table names (in Access) beginning with ch contain attributes of individual horizons. These attributes are important for advanced soil analysis and have limited application to most initial land use and site suitability analysis. Tables names beginning with co contain attributes of the soil components (subunits of the mapping units) and have application in forestry, wildlife and conservation management, agriculture and engineering. 57

58 Tables beginning with mu have direct linkage to the mukey in the mapunits shapefile. These tables, particularly the muaggatt have extensive applications in land use and suitability studies. The key to using the co tables to develop maps is to create a link between the soil component keys (cokey) and the mapping units (mukey). This is accomplished by creating a lookup table which lists the Mapunit Key and the corresponding Component Key. The component table contains the fields necessary to create joins to the other co.. tables. Access fields The Database Access dialog box can be used to query these fields from the component table into ArcView. 58

59 The resulting table must be saved in ArcView with a descriptive name like CompKey. This table can be used in joining the attributes of the co tables to the shapefile attributes allowing the display of the attributes as a map. 59

60 To link attributes in the various co.. tables (cocropyld, coforprod, coeplants, etc.) with the attributes of the mapunit shapefile the applicable fields are queried from the selected table. The queried table is joined to the lookup table using the Component Key (cokey) field. The resulting table with the join must be exported and then added to ArcView as a unique table. This table can them be joined to the mapunit shapefile attributes using the Mapunit Key (mukey) field. Summary: SSURGO data can be almost overwhelming in its scope and detail. This project attempts to provide some guidance in working with the data. Soils and their characteristics should be important components of any land management plan. Soil maps can create graphic links between students and their environment. GIS allows the students or instructors to make unique maps which can be taken to the field to observe first-hand how the soil properties affect how we live on the land. Some possible activities where students may see the impact of soil differences are listed below: - Observe a road-cut or construction excavation to see the horizons in the soil 60

61 - Obtain a soil probe (NRCS offices and engineering firms generally have these tools or sources for the tools) and create a soil profile. Describe the pedon. - In farming communities, many modern harvestors are equipped with real-time yield measurements and GPS locations. Use GIS to map the yield differences and observe the effect of the soils. - Observe from a distance set-aside, prairie, or grass-lands. Many seasons of the year vegetative differences from area to area can be observed as differences in color, texture, and size. Have the students sketch maps showing the observed differences (color, texture, size). Compare these to the soil maps. Is there a correlation? - Watch a tilled field dry in the spring after a rain. Color differences will occur as the soils dry at a different rate. Is there a correlation between the soil maps and the colors? - Identify plant communities in old growth forests or naturalized areas. Naturalized plants tend to grow in groups, is there a correlation between the soils and the plants? The NRCS provides a number of teacher links to more information about soils at: The following appendixes show schematics of some soil attributes that might be of interest in building lessons for students. 61

62 Acknowledgements The data contained in this project was obtained from the United States Department of Agriculture, Natural Resources Conservation Service. The techniques and analysis included in this report are not in anyway associated with or endorsed by the USDA. Any work or analysis done with SSURGO data is subject to the following USDA disclaimer: Example Disclaimers for Soil Survey Geographic Data (SSURGO) (Exhibit 648-2) The Soil Survey Geographic (SSURGO) database was produced by the U.S. Department of Agriculture, Natural Resources Conservation Service for the Soil Survey of County,. The soils were mapped at a scale of with a minimum size delineation. Delineations depict the dominant soil(s) making up the landscape. Other dissimilar soils, too small to be delineated, are present within a delineation. Enlargements of these maps to a scale that is more than that at which they were originally mapped can cause misinterpretation of the data. If enlarged, maps do not show the small areas of contrasting soil that could have been shown at a larger scale. The depicted soil boundaries and interpretations derived from them do not eliminate the need for onsite sampling, testing, and detailed study of specific sites for intensive uses. Thus, this map and its interpretations are intended for planning purposes only. Source: 62

63 Appendix a. Query for Potential Crop Yields b. Query for rangeland or forestland plants c. Query for recommended trees for planting or management d. traditional soil maps with symbols. e. Query to mauaggatt table 63

64 Query Area: Potential Crop Yields SSURGO Table: cocropyld Domain: crop_yield_units : Tons (Tons/Acre), Bushels (Bushels/Acre), Boxes (Boxes/Acre), Crates (Crates/Acre), Sacks (Sacks/Acre), Thousands (thousands/acre), Pounds (pounds/acre), CWT (100lbs/acre) AUM (animal units monthly), Comments: Representative values are common. Many datasets indicate nonirrigated (nirr) and irrigated (irr) land. The values may not be representative of current production levels but can be used to compare one mapping unit with another. Mukey Cokey lookup table 1. Query cocropyld for Crop Name (cropname), Units (yieldunits), Yield- Representative Value ( yield_r) and Component Key (cokey) 3. Join 4. Export the table as a dbf table. Add the saved table to the project 2. Export the table as a dbf table. Add the saved table to the project Shapefile attributes 5. Join 64

65 Query Area: Typical rangeland or forestland plants for an area. SSURGO Table: coeplants Domain: Non-cultivated plants typically found (native or naturalized) on soil component 6. Query for Comments: These attributes can give a good indication of what the native plant community yield levels. was like. Also can provide valuable guideline for habitat or natural area restoration. Mukey Cokey lookup table 1. Query table: coeplants for plantsciname, plantcomname, and cokey 4. Export table as.dbf table and add to project 3. Join Shapefile attributes 5. Join 2. Export table as.dbf table and add to project 65

66 Query Area: Determine tree species recommended for planting or management on areas. 6. Plants, by common SSURGO Table: cotreetomng and scientific names Domain: Trees by common and scientific name that are recommended for the soil component. are associated with Comments: Data can be used to recommend trees to plant for forestry, or trees to encourage mapping through units. forest management practices. 1. Query cotreetomng table for: Scientific Name (plantsciname), Common Name (plantcomname), and Component Key (cokey) Mukey Cokey lookup table 4. Export table as.dbf file and add to project 3. Join 5. Join Shapefile attributes 2. Export table as.dbf file and add to project Use Legend Editor, Unique value to determine tree species to manage or plant on soils.