The following tutorial will describe the features of the NASIS Legend Builder form in the Pedon_PC database.
Open Pedon_PC and navigate to Setup then Relink Tables.
Make sure you are linked to the correct pedon.mdb file and workspace_legend.mdb.
If you have not built a “workspace” legend yet, then make a copy of the “mt618_workspace_legend.mdb” file included in the Pedon_PC .zip file.
Notice the database window minimized in the lower left of the screen. Maximize it.
Looking at the tables, notice all of the linked tables with a "workspace_" prefix.
These are the tables from the workspace_legend.mdb.
Open each of the tables and investigate what is inside them.
Workspace_chorizon_pedon is an enhanced replica of the SSURGO chorizon table.
This is where all component horizon layers derived from aggregated pedons are stored.
Workspace_component_horizon_default_layers holds the default segnum assignments for horizons in a pedon dataset.
Workspace_component_legend and Workspace_mapunit_legend store the set of mapunits and components that are referenced in a pedon dataset.
Workspace_mapunit_polygon_comp_type stores any polygon note. If the polygon note belongs to a transect, make sure to reference the corresponding User Transect ID.
Workspace_mapunit_polygon_composition stores the composition estimates for a given polygon note.
The tables with the "workspace_ssurgo" tables are where SSURGO data resides.
If you are using the sample MT618 dataset and would like to use it for your own workspace legend, then delete the records in all of the tables EXCEPT the "horizon_default_layers" table. You will need this to do horizon aggregation.
To take advantage of all of the features of this legend building tool, some minimum data requirements are assumed.
You have pedon data in an EDITABLE pedon.mdb file and the components and mapunits you wish to analyze have a representative sample of complete pedon descriptions.
Mapunits are assigned to pedons in some fashion, either by Mapunit Overlaps within the Pedon framework or via spatial overlap with a soil polygon layer.
The “Soil Name as Sampled” field in the pedon table is populated.
That “sampled” name is a UNIQUE component concept and includes the full phase name if present.
The “Soil Name as Correlated” field is COMPLETELY BYPASSED. Component correlations are instead handled within the “workspace” framework. If you have already used the “Soil Name as Correlated” field to handle correlation decisions, back up your dataset and update your “sampled” soil name with your “correlated” soil name using a basic update query like:
UPDATE pedon SET soinmassamp = [soinmascorr] WHERE soinmascorr Is Not Null And soinmascorr <> [soinmassamp]
The “Horizon Designation” field in the phorizon table is populated. (Not just master horizons)
The “Sequence Number” field within the phorizon table is OVERWRITTEN when aggregating pedon horizons into component horizon layers.
To take advantage of the advanced spatial features of this legend building tool, some additional data requirements are assumed.
You have a spatial polygon layer with an OBJECTID, MUSYM, and Shape_Acres field.
If you are missing either the MUSYM or Shape_Acres field, calculate them in ArcMap.
You are working with ONE soil polygon layer.
To begin working with a “workspace” legend, you will open Pedon_PC and go to Forms then NASIS Legend Builder.
NASIS Legend Builder - Workspace Mapunits
Manage/View “Workspace” Mapunit and Component Legends.
Manage/View supporting polygon and pedon documentation.
Soil Survey Area
Click the drop-down arrow to see the number of mapunits and components in each area.
If you do not see your survey area in the drop-down list, close the form and go to Setup then Customize Choice Lists then Edit Choice Lists and on the Area tab, place a checkmark next to your area of interest.
Selection – control what mapunits and/or components to use for spatial display, aggregation, and calculations
Mapunits – enter polygon composition, make mapunit correlations, view acreages
Components – view pedon documentation, make component correlations, aggregate pedon horizons into component layers
Options – set default layer groups, build legends from SSURGO, spatial, or pedon sources
All – shows the current dataset on the Analysis Form.
This may be the “full” dataset or it may be filtered by any other interpretive group. Example: Select sites with a particular parent material or diagnostic horizon on the Analysis Form. Then open the Workspace Legend and the mapunit and component lists will include only those mapunits and components meeting your criteria.
Selected – allows selections of mapunits or components from the lists below
Reports can be built and linked to.
Calculations can be built to aggregate point data into NASIS data mapunit and component horizon data.
Mapunit Selector Box
Select one or more mapunits from this list.
Click the “Selected” option above.
Mapunits and components will filter to only those selections.
Component Selector Box
Select one or more components from this list.
Click the “Selected” option above.
Mapunits and components will filter to only those selections.
NASIS Legend Builder – Mapunits Tab
Aggregated Mapunit Composition
Composition Type Examples:
Line-intercept or Point-intercept Transect
DEM Elevation, Slope Class, or Curvature Intersect
Polygon - Composition Type
Alaska relies on line-intercept transects.
Polygon - Percent Composition
Estimated or Calculated composition of a given polygon
Polygon-Point Intersect - Acre Documentation
Mapunit Component Pedon Count
Shows supporting pedon documentation by descending count
Viewing/Checking Data - Aggregated Composition Data
(NOT EDITABLE: calculated from actual composition estimates (estimated or derived)
7 line-intercept transects were taken for this mapunit.
All 7 had composition estimates.
4 of the 7 had at least 2 pedons per transect.
Note: In Alaska, each mapunit should have a minimum of 3 complete line-intercept transects, all of which contain composition estimates and 2+ pedons per transect.
Referenced in 5 of 7 line-intercept transect composition notes (RV = 30% of MU)
Normalized Percent = (5 / 7) X 30% = 21%
Listed below are all 7 line-intercept transects for this mapunit.
Transect 00MC114: STTU component was estimated at 40% of polygon.
Viewing/Checking Data – Polygon-Point Intersect
(NOT EDITABLE: calculated an actual soil polygon – documentation point intersect)
Total Acres - total mapunit acres
#Polygons - total number of mapunit polygons
%Acres - % of mapunit acres with existing point documentation
%Poly - % of mapunit polygons with existing point documentation
Acres Avg - average delineation size
List of Points that intersected these mapunit polygons.
4 pedons sampled as STTU (or correlated to STTU) fell within these 49 Mapunit 1FW1 polygons.
Mapunit Legend Management - Common Tasks
How do I add a new mapunit to my legend?
Scroll to the bottom of the mapunit list at the left of the form.
Type in a new mapunit name.
The “as sampled” and “as correlated” mapunit name will be defaulted as the same. When the “as sampled” name is the same as the “as correlated” name, it is considered a “correlated” mapunit.
How do I correlate one mapunit to another mapunit?
Change the “as correlated” name to the “correlated” mapunit you wish to correlate to.
How do I add a line-intercept transect or polygon note to my mapunit documentation?
Choose the mapunit from the mapunit list at the left of the form.
In the Polygon section of the form, select the transect from the drop-down list in the Transect Column.
(It only contains transects that are not yet linked to a mapunit.)
After the record has been created, click the + sign at the left of the record.
Enter the estimated % for all components.
How do I change the mapunit of a transect?
In the Polygon section of the form, find the transect of interest and select a new mapunit in the MUSYM column.
NASIS Legend Builderï¿½Workspace Components
Manage/View “Workspace” Mapunit and Component Legends.
Manage/View supporting polygon and pedon documentation.
Aggregated Component Horizon Layers
# - Number of Horizons being aggregated
Layer Group – groups horizons within a profile
Example: Cg1 and Cg2 horizons can be assigned to the same Cg layer group.
Correlated Components List (with pedon count) (NOT EDITABLE)
Lists all components that have been correlated to the current component.
Note: In Alaska, each component should have a minimum of 3 “full” pedon descriptions. Only full pedon descriptions are used to aggregate horizon layers.
Layer Horizon List (EDITABLE DATASET)
Shows the Pedon Horizons that were aggregated into the Component Horizon Layers
The Layer Group or Horizon Designation can be manually reassigned for a given horizon.
Component Pedons (EDITABLE DATASET)
List of Pedons – only those pedons with a Pedon Purpose of “full pedon description” will be used to aggregate into component horizon layers.
Pedon Horizons (EDITABLE DATASET)
Viewing/Checking Data – Basic Controls
If you have an internet connection, double clicking the component name in any of these locations will open a new window showing the OSD. Place your cursor in any of these fields and press the ctrl key to view the series extent.
Changing the Component in the Correlated Component List refreshes the list of Pedons.
Changing the Pedon refreshes the list of Horizons.
Changing the Component Horizon Layer refreshes the list of Pedon Horizon Layers.
Changing the Pedon Horizon Layer changes the current Pedon.
Changing the Layer Group for the current Horizon and then double clicking in either of these locations refreshes the Component Horizon Layers above.
Depress the “View Childs” toggle button to view or edit the “first” texture and/or fragment records.
NOTE: This slows down the form by “pulling” up the first child records in the phtexture and phfrags tables. Like on the site data entry forms, it allows population of “child” table fields as if they were part of the phorizon table.
NASIS Legend Builder – Component Tab Enhancements
By removing the checkmark, you can remove the component from aggregation.
Correlated Component List was moved up to the top row.
Texture Count was added.
View Childs was moved to the left of the pedon horizons. This must be depressed to view/edit horizon child records like texture and fragments.
The current component name, component layer, and texture class control the horizon list.
NASIS Legend Builder – Options Tab
Edit Horizon Default Layer Groupings.
Update Layer Groups (of actual horizons).
Build mapunit and/or component legend from multiple sources.
Intersect Points and Polygons – After intersecting points and polygons in ArcMap, use this option to import the intersection into the Pedon_PC database. This lets you take advantage of the advanced spatial features of the form (acreage reporting, polygon selection, etc.).
Press the Intersect Points and Polygons button to close down the NASIS Legend Builder and bring in the tables from the intersection.
Intersect Points and Polygons
Before using this feature, make sure you have followed the following steps:
Within ArcMap, load your soils polygon layer and retitle it "soil_a." If you are looking at more than one soil survey area, merge them into one file, renaming it "soil_a."
Ensure that this "soil_a" file has a "MUSYM" column and a "Shape_Acres" column. If it does not, calculate these fields.
Within ArcMap, load your Pedon_PC data points by adding the tTempAnalyzeSpatial table from the spatial_link_mdb in use.
Display the tTempAnalyzeSpatial table as XY coordinates, using latlongs or UTMs. If the area that you will be looking at covers more than one UTM zone, the points should be displayed as latlongs.
Within ArcMap, run the "Polygon-Point Interest" tool within the "Digital Soil Survey - Pedon PC Analysis" Toolbox. This intersects a soils polygon layer with overlapping Pedon_PC points.
After following the instructions on the form (see the “Setup for Pedon PC Spatial Linkage.ppt”), press the OK button and the following acreage summary will appear. Check the acreage estimates. Then close the form and open Forms then NASIS Legend Builder.
The following exercise will investigate the documentation for the McMannamy component within the MT618 dataset.
We will use the Analysis Form and NASIS Legend Builder in conjunction with ArcMap to view the extent of McMannamy within the MT618 survey area.
To do a similar exercise with your own set of data, make sure you have already watched the “Pedon_PC_AnalysisForm.ppt” and the “ArcMap_Setup_for_Spatial_Linkage.ppt."
We will build a NASIS McMannamy component by aggregating our McMannamy pedon horizons into component horizon layers.
First, some background on the McMannamy series concept.
I will open the Analysis Form by going to Forms then Analyze Point Data.
After pressing the “Remove Filter” button, I start with a fresh query and see that I have 73 sites sampled as “McMannamy.”
To select only these McMannamy sites, I will select “McMannamy” from the PickList then press the Filter button.
But first I will depress the “Continuous Spatial Refresh” button so that this selection can be viewed in ArcMap.
I am now filtered only to “McMannamy” so I go over to ArcMap and refresh my screen.
Notice that these sites only occur in the eastern half of the survey area.
Most of this survey area was glaciated, but only in the eastern half did the glaciers leave behind the calcareous till that this soil is derived from.
Back on the Analysis Form, I select the Subgroup field. You can see that the dominant taxonomic subgroup was the “inceptic haplustalfs.”
Let us look at some photos of this soil so you can see just how weak or “inceptic” the argillic horizons in these soils really are.
I click the photo button, which opens the Photo Link Manager form.
After selecting the “Selected Sites – Analysis Form” option and choosing to view only the Profile photos, I find this beautiful profile of one of the weakest argillics you will ever see.
Are you starting to get a feel for the McMannamy series?
Then let us go to the NASIS Legend Builder at Forms then NASIS Legend Builder.
Notice that upon opening, it is already filtered to McMannamy. This is because the NASIS Legend Builder is tethered to the Analysis Form. This powerful feature allows you take advantage of the full querying capabilities of the Analysis Form when viewing and aggregating data.
Go back to ArcMap and refresh the view. The soil polygons with McMannamy documentation are now selected.
Suppose McMannamy is, in fact, a component in all of the mapunits you saw selected.
Selecting all of the mapunits in the list will show the theoretical extent of the McMannamy series across the full extent of mapunit polygons, not just the polygons where McMannamy documentation actually occurred.
But remember, the form is limited by the records on the Analysis Form. So, before making the selection, either close the Analysis Form or click the Remove Filter button on the Analysis Form to start a fresh set.
After refreshing the ArcMap view, you notice that the extent of mapunits with McMannamy is much larger than the extent of polygons with McMannamy documentation.
So far we have seen:
the mapunits with McMannamy pedon documentation
the extent of McMannamy points and polygons
the extent of the mapunits that they occurred in
a typical profile of McMannamy
Now let us turn all of that into the beauty that is NASIS: A data mapunit component.
Let us go back to the NASIS Legend Builder at Forms then NASIS Legend Builder.
Select McMannamy from the Component List and hit Select.
Then go to the Components Tab and see that of the 73 McMannamy pedons, 19 were complete enough for me to call “full pedon descriptions,” while the rest we will just call “field notes.”
A “layer” may consist of one or more “horizons” within the same pedon. These pedon layers are then aggregated into a “component horizon layer.”
Of the 19 “full” pedons, I see that only 3 had Bw horizons. Since these were not called Bts in the field, I want to correlate these Bw horizons to my E layers.
Since the current “component horizon layer” is Bw, the 3 Bw pedon horizons that make it up are displayed below.
Change the “Layer Group” of the 3 Bw horizons from Bw layers to E layers. Then double click the little gray form selector.
Notice that we now have a McMannamy component with 4 “clean” horizon layers.
There are a total of 19 pedon “layers” making up each of the 4 component “horizon layers.”
The depths of each horizon layer match the corresponding horizon layer depths above and below.
A clear increase in clay accompanies the Bt horizon.
But also notice that the current O horizon layer has 1 silt loam texture in it. Clean this editing error by depressing the View Childs button. Then remove the silt texture from the Oi horizon.
Go back to the Selection Tab.
We are ready to create a McMannamy component to help populate the component horizon table in NASIS.
Click the Calculation drop-down arrow and select the highlighted calculation.
Enter “McMannamy” into the parameter box and a query called “q_workspace_chorizon_pedon” opens. This query references the “workspace_chorizon_pedon” table. In the absence of quality lab data, the calculation we just ran estimates many of the required NASIS component horizon data elements from pedon data.
Check the existing data fields and enter the missing Low and High data fields.
Close the query, return to the NASIS Legend Builder, and run the “Component Horizon (sieves)” calculation.
Notice in the bottom row that the sieves have been calculated.
So how does it work you wonder? Let us take a look.
Some of these calculations are straightforward, others are not.
L, RV, and H Depths and RV Fragment Percents are calculated directly from pedons.
Fine-earth estimates for sand, silt, and clay are based on a texture-driven guide-sheet model.
CEC, Bulk Density, and Ksat are also based on a texture-driven guide-sheet model.
Sieves are based on a simple calculator used in Alaska that draws on the coarse fragment (by volume) ranges and sand, silt, and clay ranges.
The guide-sheet models are customizable and are stored in the t_component_guide_calculations table.
Open this table and take a look at the “Sand Fractions Ratios - AK Defaults (texture)” calculation.
Notice that it sets a default sand and clay percentage for each texture.
Example: Silt Loam (sil) has a default clay% = 5% and a default sand% = 30%.
It also sets the sand-fraction ratios (these are a fraction of the total sand percentage).
Example: Silt Loam (sil) has 30% total sandï¿½67% of that total is very fine sand, 17% is fine sand, and 17% is medium sand.
Unlike the NASIS sand-fraction calculation, you can adjust these numbers to reflect the soils in your own area. The values that you see were compiled from Alaska’s lab data.
NOTE: If sand and/or clay was estimated for a pedon horizon, that value overrides the default estimates for a texture.
EXAMPLE: If a pedon horizon with a silt loam texture had a field estimated clay% = 10%, that 10% field estimated value will override the 5% default value.
Open the t_component_guide_calculations table and look at “Db and Ksat – NSSH Exhibit 618-9 Approximation.” These values were estimated from the NSSH Exhibit 618-9. Some values were then adjusted slightly to reflect conditions in Alaska.
This NSSH exhibit plots Db and Ksat on a texture triangle for low, medium, and high texture densities. Alaska is testing the use of the moist consistence field as the density “separator.” A “very friable” sil is “low” density while a “friable” sil is “medium density.”
Compare the Db and Ksat of low (l) density silt loam with that of medium (m) density silt loam.
The pedon horizon “density” for Db and Ksat is actually determined in the “workspace_component_phorizon_texture_density_from_rupresblkmst” query.
Open that query in design view and look at the density expression.
This a simple rule that can be as complex as you would like:
Default sets of textures into different density groups
Apply a correction based on some other factor, etc.
In this same query, you will notice an “ash_correction.”
This reduces the bulk density by 0.2 for any horizon with “low” density and a subgroup like “*and*.”
Take a look at the “CEC (AK) estimates from texture, pm, horizon des.” calculation.
This is the most complex of the pre-built calculations because the horizon CEC values in this model are dependent on Horizon Designation, density, texture, and presence of ash.
Notice that a horizon like “B*” with low density silt loam is defaulted to a CEC_r of 20.
The CEC_r_aa field is an “ash adjustment. Any horizon from a subgroup like “*and*” will have a CEC equal to the CEC_r and the CEC_r_aa columns.
Example: CEC_r(20) + CEC_r_aa(15) = 35
These defaults were compiled from Alaska’s lab data.
Like the Db and Ksat calculation, horizon density is determined in a query. You will find the density expression in the “workspace_layer_CEC_AK_phorizon_density.”
The sieve calculation is different from the others in that it is handled by an update query in Access. This is like the traditional NASIS calculations that simply look at values in the table to update and sets a different field equal to the value determined by the calculation.
Make sure to fill in the following fields before running the “wp_chorizon_sieves” update.
NOTE: place a checkmark in the “Allow Updates” field for the horizons you want to update. Remove the checkmark if you do not want to update the horizon sieves.
By following the model of the sieve calculation, one could build more “update” calculations based on fields already populated in the “workspace_chorizon_pedon” table.
EXAMPLE: Build a calculation for LL and PI.
Calculations that can be linked to the NASIS Legend Builder are stored in the “t_analyze_calculations” table.
If you build your own query that calculates one or more fields in the workspace_chorizon_pedon table, open the “t_analyze_calculations” table:
Enter the Access query object name in the SQL Query Column.
Name the calculation in the Calculation Name.
Open the NASIS Legend Builder, filter the data to the set of choice, then run the calculation.
Complete Exercise - Summary
After learning our way around the NASIS Legend Builder,
We used some powerful visual tools to become familiar with the McMannamy series concept.
We aggregated horizons into component horizon layers.
We calculated many of the required NASIS component horizon data elements from our pedon documentation.
Until NASIS incorporates these powerful analysis and aggregation tools, the data mapunit component horizon you see below will have to be hand entered into NASIS.