FR5130 - Paul Bolstadpaulbolstad.org/5thedition/Instructions/L6 Digital Data... · Web view2016. 3. 11. · Field Calculator. in the dropdown menu. Note the Field Calculator also

GIS Fundamentals: Digital Data, Basic Tables Lesson 6

Lesson 6: DEMs, National Wetlands Inventory and Basic Table Manipulations in ArcMap

What You’ll Learn: This lab introduces some commonly available digital data types, and introduces a number of rudimentary table operations.

You should read Chapter 7 and Chapter 8 through in the GIS Fundamentals textbook before doing this lesson.

Data: Unless noted, data are in UTM Zone 15, NAD83, meters, coordinates, and the data files are found in the \L6 subdirectory, including:

US_cities, a point layers of cities and towns, in NAD83 geographic coordinates,cen_Stx_U83, a subset of U.S. census bureau block group data, for a small area

spanning the Minnesota/Wisconsin border,nlcd_border, a National Landcover data set, in an Alber’s conic projection,USGS_sheds, watershed boundaries at the hydrologic unit code level 8 (HUC-8),NED_lstx30, a National Elevation Dataset for the lower St. Croix HUC-8 watershedNHD_LStx_high.mdb, a National Hydrologic Dataset geodatabase for the lower St.

Croix HUC-8 watershedStil_wetU83, wetlands data for the Stillwater, Minnesota USGS 7.5 minute quadrangle

What You’ll Produce: four maps: 1) a census data set, with subset cities from a US data set 2) shaded relief/hydrography map, 3) summary of wetlands by size, and 4) summary of wetlands by type.

Background: This exercise introduces table queries. Most GIS store attribute data in tables. Each feature in a data layers is associated with a row in a table. A table query is a selection of rows (also called table records) based on a set of criteria. For example, you might select all polygons that are more than 100 hectares in size. We typically then further process the selected set, for example, assign values for a specific item, or export the records.

You’ll be doing this sort of table manipulation in most of the remaining labs, so we’ll keep these first selections and subsequent operations rather simple. First, we’ll compose two maps including some of the wide range of data that are available for download from web sources.

Next, we will introduce table operations using National Wetlands Inventory (NWI) data. We will select subsets of these data based on the size of the wetland polygons, and on wetland type (is it an upland or wetland, is it in Wisconsin or Minnesota), and produce corresponding maps.

1


Digital DataA wide range of data is available for download from the worldwide web, as described in Chapter 7 and appendix B of the GIS Fundamentals textbook. We will examine a few of these data types, and compose maps using downloaded data.

Start ArcMap and add the raster data set named nlcd_border.(Video: Layers)Notice the table of contents lists a set of numbers for the NLCD dataset. Each code corresponds to a defined landcover type, e.g., 11 = open water, 43 = mixed forest. These data are available for the entire U.S. for approximately 1990, and 2000, although the numbering system changes slightly between dates.

It is inefficient to re-enter a pleasing color scheme every time we load the data (i.e., blue water, green trees), and even more burdensome to retype the labels. Try the following:

Open the symbology tab for the NLCD data set (remember, right click on the name in the TOC, Properties > Symbology).

Make sure you have selected Unique values in the “Show” window to the left, and then, left click on the Import button in the Layer Properties window and the Import Symbology window that opens.

Browse to the \L6 folder and left click on the nlcd.lyr file in the Browse window

Then click Add to close the Browse

OK to close the Import Symbology

And Apply-OK in Layer Properties.

2


Notice that this now applies a “standard” color scheme and lists the names for the NLCD data set?

.Any time you have the “standard” data set to display, you can apply a saved layer file.

How do you create this layer file?

By first producing in manually, that is, assigning the colors one at a time, and left clicking on each label and typing in your text.

After you’ve applied a Symbology, you may save it by:

Right clicking on a file name in the table of contents,

and then left-clicking on Save As Layer File….

Next time you display a data set with the same categories, you can import this layer file via Symbology > Import, as described above.

Census DataAdd a new data frame, and delete the nlcd_boarder data frame. Add the census data, cen_StX_U83.shp to your new empty data frame. This is a subset of the census attributes for a portion of the Minnesota/Wisconsin border. Each polygon is a block group, a unit of aggregation in collecting population census data.

Open the attribute table (right click on cen_StX_U83 in TOC, then click Open Attribute Table), and inspect the values for the column labeled pden_psqkm.

This is the population density for the census block groups in this area.

Next, right click on the column name, and select Statistics (see right). This should display a column summary, and a histogram (see below).

3


Note that the data has quite a few small values, and a few very large values. This “long-tailed” distribution is common in some types of data, and often displays better with a non-uniform set of symbol ranges. We’ll demonstrate here by example.

Close the table, and open the Symbology Properties menu.

Symbolize this as Quantities-Graduated Colors, and display the population density data (pden_psqkm) in the Value field, with no normalization.

Keep the default number of classes, and select a gradient color ramp (in the example to the right, I selected the orange-purple-blue color ramp).

Notice the rather useless symbology, in that the lines obscure the colors for the small polygons, and there is little range. (Video: MoreSymbols)

We can get a more useful symbology by opening the Layer Properties menu (you done this before, but as a reminder, right click the file name in TOC, then left click on Properties, then the Symbology tab).

Specify a Quantities symbol scheme in the list of the leftmost panel

Left click on the Classify button on the right, near the top, opening the classification window (shown at right)

Set the Classification Method to Geometric Interval

Classes to 20

Then OK – Apply – OK

Notice this improves the colors somewhat, but the lines still obscure the small polygons.

4


To remove the lines, open the Layer Properties menu one more time.

Now select all the symbols and remove the outline.

To do that first, left click in the first color patch and right click. Select Properties of All Symbols.

This should open the Symbol Selector menu.

Set the Outline Color to “No Color”.

Then left click on OK – Apply – OK

This should display the layer in a manner similar to that shown at right.

This symbology provides a clearer view of the variation in the data, due both to removal of the border lines, and placing a geometric spacing of symbol ranges.

Note that there are many other options that appear in the menu that contains the Properties for All Symbols.

You may group, flip, ramp, or otherwise change a set of selected symbols, or all symbols.

Experiment with these to see their effects.

5


Cities Add the US_cities.shp point layer to the data frame.

These are data on cities for the entire U.S. and territories. Use the Zoom to Full

Extent button to view the entire dataset, and then Zoom to Previous Extent button to return to the area of the cen_StX_U83.shp area.

It is burdensome to work with a large data set when we only wish a small portion or subset. Now we will select just the cities data that corresponding with our census data set. (Video: Subset)

Do this by:

Selection > Select by Location in the main menu

And specifying in the dropdown,

Select features from:Target Layer, US_cities (check the box in front of US_cities)

Use cen_Stx_U83 as the Source Layer and select the Spatial Selection Method of Target layer(s) features intersect the source layer feature.

Then Apply – OK. This should display a view similar to the right. The selected cities show up in the current selection color, in this case, cyan.

Saving a Selected Set to a New File

To save this selected set into a new file: Right click on the US_cities file name in the Table of Contents, Left click on Data > Export.

Make sure you specify “Export: Selected features” and change the filename and directory as appropriate.

You can add the subset layer to the view, and remove the original US_cities layer.

6


Map 1Create a layout view, include both the selected population density and cities data layers, a suitable legend, North arrow, scale bar, and description.

Digital Elevation and NHD DataWe’ll now explore digital elevation and related hydrologic data a bit. We’ll hold off an in-depth treatment of DEMs until Chapter 11 in the GIS Fundamentals textbook, and a later lesson. We’ll just introduce the data, and you show how to make an interesting shaded-relief map, suitable for backgrounds and many illustrations.

Create a new ArcMap project, and set the data frame coordinate system to the UTM Zone 15N, NAD83 projection.

Add the USGS_sheds.shp dataset to the data frame. These are watershed boundaries derived from elevation data, and downloaded from the US Geological Survey.

Label these features: Right click on USGS_sheds in the TOC > Properties > Labels

Then left click on the checkbox “label features in this layer”,

Choose SUBBASIN as the Label Field, and then Apply - OK

This should paint the name of the each sub-basin with a polygon, something like the figure to the right.

7


Try to copy/create a data set that consists of the outline of only the Lower St. Croix watershed, near the center of the data set.

We won’t give you exact instructions, we’ve covered it before, but here is a hint. Use a selection tool (there are several selection methods/tools that will work), then Data > Export to save your data to a new file shapefile.

Now, remove all the data from your data frame.

Create a Shaded-relief Elevation Map (Video: Shaded Relief)Add the ned_lstx30 DEM to your data frame.

Use Properties > Symbology to display the Layer Properties menu and set a stretched color ramp.

Use a Stretch Type of Standard Deviations, set n: 2, and use the elevation color ramp:

Select Apply, Okay.

Now, calculate a hillshade surface:

Select ArcToolbox Spatial Analysis Surface Hillshade.

8


This should open a Hillshade menu.

Set the Input raster to ned_lstx30 (the DEM).

Select a location for the output and a name, Hillshade1 for example.

Keep the Azimuth at 315 (direction to the Sun).

Set the Altitude to 25 (Sun’s elevation).

Check the box to Model shadows.

Set the Z factor to 4 (4x vertical exaggeration), then OK.

This should create a hillshade surface, and if it isn’t done automatically, place it on top of your DEM.

Now make the hillshade semi-transparent:Right click on the hillshade in the TOC, then Properties > Display.

Set the Transparency to something near 50%, then Apply – OK.

You should now see the DEM, with the hillshading “painted” on top (see the figure, below, shown with additional data added). This is a commonly-used affect in producing maps.

Finally, let’s add some hydrologic data from the National Hydrologic Dataset (NHD). These are lakes, streams, and other water features, derived from DEMS and other sources, and integrated into a consistent hydrologic network:

Open the geodatabase for the NHD by clicking on the Add Data icon, then double clicking on the NHD_LStX_high.mdb.

Note the large number of data sets and files.

Double left click on the Hydrography file, then

double left click on the NHDWaterbody file.

This should display a set of polygons, including types labeled Estuary, Ice Mass, LakePond, Playa, Reservoir, and Swampmarsh.

Remove the labels for all but the LakePond and Reservoir (Properties > Symbology,

9


right click on a symbol, then Remove Value(s).

Symbolize these two water types blue, with no border.

Finally, add the data layer NHDFlowline from the GeoDatabase.

Symbolize the StreamRiver and Artificial Paths in blue, and CanalDitch in red.

Remove the other line types from the legend. Your data view should appear approximately as the figure here.

Map 2: Create a layout with the usual map elements, and save your project.

10


NWI Data and Table ManipulationsOpen a new ArcMap project, and Add the data layer Stil_wetU83.shp to a new, empty project.

Right click on the Stil_wetU83 layer in the table of contents. Video: Select & Assign.

Left click on Open Attribute Table in the dropdown menu.

You will see the attributes of the wetlands layer. The Field called “Area” displays the area of the polygon in square meters (m2). The “Wet_type” field displays the type of wetland. Detail codes are listed at the end of this document.

Right click over the heading of the “Area” column and select Sort Descending (as shown right).

This brings the largest polygons to the top of the table. Notice that the largest areas are coded “U”, for uplands, and “Out”, area outside the mapping jurisdiction for these data, in this case, in Wisconsin.

We will be classifying the polygons by their size, which is contained in the “Area” attribute.

Left click on the dropdown in the upper left corner, below the word Table. You may need to expand the window to the right to view the button.

Then left click on Select By Attributes in the dropdown menu

11

1

2

4

3


This opens a query builder. You select a Method at the top (for this Lab use “Create a new selection”).

You use the items listed in the second pane with the operation buttons listed below it to build an expression in the bottom pane.

This expression is applied to the data table to select features.

In the Select by Attributes box, 1) double click on the “Wet_type” field, 2) single click on the = button, 3) double click on the “Get unique Values” button, 4) scroll to and double click on the “Out” value. Your selection expression should appear as shown to the right.

Remember to use the buttons on the menu to compose the selection expression, e.g., the “Wet_type” = Out”. Typing in a selection via the keyboard is possible, but it is easy to make mistakes which cause syntax errors.

Click Apply. This selects all the records in the file that have the “Out” code.

Next click on the Table Options and select “Add Field”. This will add a new empty field (column) to you file.

Name the field “Size”, select the Type as “Text” and change the Length to 10 (as shown at right).

Left click on Okay.

12


Now right click on the column heading of the “Size” field and Select Field Calculator. This will allow you to change the selected values in the “Size” field (column).

In the Field Calculator, there is an entry window for expressions in the bottom half, which should have Size= above the entry area. Type “Wisconsin”, with quotes into the window, left click on OK.

13


Your file should appear as below:

Now sort the file by the Area field:

Right click on the “Area” column heading in the wetlands attribute table, and left click on Sort Ascending.

Left click on the Options button at the upper left of the table, then Select by Attributes.

Build the query to select the areas between 222.61195 and 2993.85555, inclusive, as shown in the bottom panel, at right.

Left click on Apply, Close

Again, open the Field Calculator by right clicking on the “Size” column, and change the “Size” values for the selected records to “Small”.

Do the same steps as above for the "AREA" >= 3001.8695 AND "AREA" <= 9969.29615, use the Field Calculator to assign a value of “Medium” to for the Size field.

Repeat the process for "AREA" >= 10076.1794 AND "AREA" <= 5103526.79121 OR “AREA” = 95146516.60342. Assign a value of “Large” to the Size field for the selected records.

Finally, with the data table still open, select OptionsSelect by Attributes, select the Wet_type = “U” and use the Field Calculator to change that record’s value in the Size field to “Uplands”.

14


Clear Selected Features (on the main ArcMap menu, under Selection). Close the Table.

Open the Properties - Symbology of the stil_wetU83 layer and left click in the Show box to display: Categories Unique values. Change the Value Field to Size. Click on the Add All Values button and the then Apply, OK.

15


Map 3Create a map to display the modified wetlands data layer, similar to that found below, add appropriate title, legend, scale bar and north arrow.

Wetlands Tables We’ll now assign a new column to identify general wetland types, based on recurrent selections.

Create an ArcMap project, and add the shapefile Stil_wetU83.

Right click on Stil_wetU83 in the TOC, and left click on Open Attribute Table.

The field, or item, named “Wet_type” contains the wetland classification used by the US Fish and Wildlife Service. A complete list is found at the end of this lab exercise.

Close the table.

Open the Properties > Symbology tab for the wetlands data.

Select Categories – Unique values for the symbology type in the box on the left labeled “Show”.

16

Select wet_type in the “Value field” box.

Uncheck <all other values>.

Click on Add all Values.


And left click on Apply and OK.

Your display should appear something like that below:

17

Add Field


This figure displays far too many categories. From the zoom tool bar, left click on the

identify cursor

A left click on a polygon will display a popup list of polygon attributes. Examine a few polygons. The item Wet_type specifies the wetland class, as shown by the code table at the end of the exercise.

For simplicity, we will aggregate wetland classes to a few main categories. Readers can only distinguish a limited number of colors or shades on a map. We will reclassify the detailed classes into five groups, aggregating the detailed wetland types into their “parent” categories.

Note that there are several numbers and letters together in a string in the wetland type column, e.g., L1UBHh. These give the wetland System-Subsystem-Class-Subclass and any modifiers, as described in the key at the back of this lab.

The first letter is for the system (L=Lacustrine, P=Palustrine, etc.), the second is for the subsystem (defined for each system) the third is for Class, etc. Your job is to add a system/subsystem column, with appropriate designators for each record. There are many ways to do this; we’ll do this by modifying the tables.

The basic steps are 1) add a new field (also called a new item or column), 2) select the appropriate records, and 3) assign appropriate values to the new field for these selected records, 4) repeat steps 2 and 3 until all records are processed.

First, we’ll add an field. Open the attribute table and select the Table Options in the upper left of the

window, then left click on Add Field.

18

To display the actual values with in a field (such as ‘attribute’), left click to highlight the item, then left click on the Get Unique Values button. This will allow you to pick your selection values from a complete list of data values.


Add a field with a name you can remember, something like “reclassed”.

Make sure your new field has a “Text” type, length 10. Other wise you will be restricted to only using numbers in your new field.

Narrow the columns or expand the window to the right and look at your new field. You have created an additional column at the end of the table that looks like this:

Select Table Options in the upper left of the table window

Left click on Select by Attribute

19


Now we need to select the records to reclassify. You build a series of expression from the variables and operators shown in the “Select by Attributes window” shown above. Note that you’ll always want to double click on the Fields and Values (e.g. reclassed and L1UBHhx) you enter in a formula, but only single click on the operators (<, =, etc.). Double-left click the field named Wet_type on the left, then single-left click the <= operator in the middle, and then double-click the “L1UBHhx” value on the right.

In this way you build the expression to select all string values an attribute which meet your criteria. The < , <= or >= operators work in that the string values are ranked in alphabetical order, as an ordinal ranking, with uppercase listed before lower case. The expression in the example below selects all the polygons in the system/subsystem L1.

If you don’t have a correct expression, a syntax error window may pop up. If so, clear the expression and try again.

To convince yourself that this operation selected the records you want, click on the Selected records icon, found near the bottom-center of the Table window, and shown below.

Clicking on the selected button displays only the selected records. Verify your selection only contains records beginning with L1.

Then, revert back to Show All records.

Right click on the “Reclassed” column, and left click on the Field Calculator in the dropdown menu.

Once you have the proper expression left click Apply.

20


21

Note the Field Calculator also has fields and functions, similar to the Select by Attributes window. But note that the target is defined as the currently active field, in this case the field named Reclassed.

Enter the code you want to assign to the selected variable and records. Here we will use the 1st two positions of the detailed classification, “L1”

We must enclose the value in quotes because this is a text field.


Click OK. If records are selected, the assignment only occurs for these selected records. Verify that “L1” appears for only the selected records.

Now repeat the process for the next group of items (those with “Wet_type” fields starting with “L2”). This is a bit trickier because it is a compound selection, so we’ll have to use the AND operation in building our formula.

The example for “L2” is shown in the figure to the right:

Assign the value “L2” to the Reclassed field, using Field Calculator as described above.

Repeat this selection/assignment until Reclassed values have been assigned for each record (five categories, L1, L2, P, U, and OUT).

22


Next change your legend display item (TOC, PropertiesSymbology) to your new Reclassed field.

Finally, change the legend symbols used for the Reclassed field to colors and patterns that will display nicely. PropertiesSymbology can also be used to add more descriptive legend labels.

Map 4Produce a map of the wetland data. Use your system/subsystem categories for the legend. Color the upland (U) and OUT polygons white and the others as appropriate to distinguish among them. Remember to include a scale bar (coverage units are meters), North arrow, name, title, description, legend, and a descriptive name to the legend heading.

23


WETLANDS AND DEEPWATER HABITATS CLASSIFICATION

Wetlands codes are typically a string of characters, each corresponding to an attribute in a hierarchy. For example, a wetland might be labeled L1UBG, indicating it is a Lacustrine (System, see below), Limnetic (Subsystem), Unconsolidated Bottom(Class), which is intermittently exposed (modifier G in L1UBG, see modifiers at end of this list). There are at least two shortened designators which may appear on wetlands maps, U = Uplands, and

OUT = out of the mapped area

Below is the hierarchy.

SYSTEM SUBSYSTEM CLASS SUBCLASS

|- RB=Rock Bottom 1=Bedrock | 2=Rubble | |- UB=Unconsolidated Bottom 1=Cobble-Gravel | 2=Sand | 3=Mud | 4=Organic | |-- 1=LIMNETIC----|- AB=Aquatic Bed 1=Algal | | 2=Aquatic Moss | | 3=Rooted Vascular | | 4=Floating | | Vascular | | 5=Unknown | | Submergent | | 6=Unknown Surface | | | |- OW=Open Water/Unknown Bottom (used on older | maps)L=LACUSTRINE----| | | | |- RB=Rock Bottom 1=Bedrock | | 2=Rubble | | | |- UB=Unconsolidated Bottom 1=Cobble-Gravel | | 2=Sand | | 3=Mud | | 4=Organic | | | |- AB=Aquatic Bed 1=Algal | | 2=Aquatic Moss | | 3=Rooted Vascular | | 4=Floating |-- 2=LITTORAL----| Vascular | 5=Unknown | Submergent | 6=Unknown Surface | |- RS=Rocky Shore 1=Bedrock | 2=Rubble | |- US=Unconsolidated Shore 1=Cobble-Gravel | 2=Sand | 3=Mud | 4=Organic | 5=Vegetated | |- EM=Emergent 2=Nonpersistent | |- OW=Open Water/Unknown Bottom (used on older maps)

24



|- RB=Rock Bottom 1=Bedrock | 2=Rubble | |- UB=Unconsolidated Bottom 1=Cobble-Gravel | 2=Sand | 3=Mud | 4=Organic | |- AB=Aquatic Bed 1=Algal | 2=Aquatic Moss | 3=Rooted Vascular | 4=Floating | Vascular | 5=Unknown | Submergent | 6=Unknown Surface | |- US=Unconsolidated Shore 1=Cobble-Gravel | 2=Sand | 3=Mud | 4=Organic | 5=Vegetated | |- ML=Moss-Lichen 1=Moss | 2=Lichen |P=PALUSTRINE----------------------|- EM=Emergent 1=Persistent | 2=Nonpersistent | |- SS=Scrub-Shrub 1=Broad-Leaved | Deciduous | 2=Needle-Leaved | Deciduous | 3=Broad-Leaved | Evergreen | 4=Needle-Leaved | Evergreen | 5=Dead | 6=Indeterminate | Deciduous | 7=Indeterminate | Evergreen | |- FO=Forested 1=Broad-Leaved | Deciduous | 2=Needle-Leaved | Deciduous | 3=Broad-Leaved | Evergreen | 4=Needle-Leaved | Evergreen | 5=Dead | 6=Indeterminate | Deciduous | 7=Indeterminate | Evergreen | |- OW=Open Water/Unknown Bottom (used on older maps)

25



|- RB=Rock Bottom 1=Bedrock | 2=Rubble | |- UB=Unconsolidated Bottom 1=Cobble-Gravel | 2=Sand |--1=TIDAL--------| 3=Mud | | 4=Organic | | | |-*SB=Streambed 1=Bedrock | | 2=Rubble | | 3=Cobble-Gravel |--2=LOWER | 4=Sand | PERENNIAL----| 5=Mud | | 6=Organic | | 7=Vegetated | | | |- AB=Aquatic Bed 1=AlgalR=RIVERINE------|--3=UPPER | 2=Aquatic Moss | PERENNIAL----| 3=Rooted Vascular | | 4=Floating | | Vascular | | 5=Unknown | | Submergent |--4=INTERMITTENT-| 6=Unknown Surface | | | |- RS=Rocky Shore 1=Bedrock | | 2=Rubble | | | |- US=Unconsolidated Shore 1=Cobble-Gravel |--5=UNKNOWN | 2=Sand | PERENNIAL----| 3=Mud (used on older | 4=Organic maps) | 5=Vegetated | |-**EM=Emergent 2=Nonpersistent | |- OW=Open Water/Unknown Bottom (used on older | maps) |-*STREAMBED is limited to TIDAL and | INTERMITTENT SUBSYSTEMS, and comprises | the only CLASS in the INTERMITTENT SUBSYSTEM. | |-**EMERGENT is limited to TIDAL and LOWER | PERENNIAL SUBSYSTEMS.

26


MODIFIERS

|- A=Temporarily Flooded |- B=Saturated |- C=Seasonally Flooded |- D=Seasonally Flooded/Well Drained |- E=Seasonally Flooded/Saturated |- F=Semipermanently Flooded |--Non-Tidal------|- G=Intermittently Exposed | |- H=Permanently Flooded | |- J=Intermittently Flooded | |- K=Artificially Flooded | |- W=Intermittently Flooded/Temporary (used on | | older maps) | |- Y=Saturated/Semipermanent/Seasonal (used on | | older maps) | |- Z=Intermittently Exposed/Permanent (used on | | older maps)WATER REGIME----| |- U=Unknown | | | | |- K=Artificially Flooded | |- L=Subtidal | |- M=Irregularly Exposed | |- N=Regularly Flooded |--Tidal----------|- P=Irregularly Flooded |-*S=Temporary-Tidal |-*R=Seasonal-Tidal |-*T=Semipermanent-Tidal |-*V=Permanent-Tidal |- U=Unknown | |-*These water regimes are only used in | tidally influenced, freshwater systems.

|- 1=Hyperhaline |- 2=Euhaline |--Coastal |- 3=Mixohaline (Brackish) | Halinity-------|- 4-Polyhaline | |- 5=Mesohaline | |- 6=Oligohaline | |- 0=Fresh | |WATER CHEMISTRY-| | |- 7=Hypersaline |--Inland |- 8=Eusaline | Salinity-------|- 9=Mixosaline | |- 0=Fresh | | | |--pH Modifiers |- a=Acid for all |- t=Circumneutral Fresh Water----|- i=Alkaline

SOIL------------------------------|- g=Organic |- n=Mineral

|- b=Beaver |- d=Partially Drained/DitchedSPECIAL MODIFIERS-----------------|- f=Farmed |- h=Diked/Impounded |- r=Artificial Substrate

27

Documents

FR5130 - Paul Bolstadpaulbolstad.org/5thedition/Instructions/L6 Digital Data... · Web view2016. 3. 11. · Field Calculator. in the dropdown menu. Note the Field Calculator also