geog 487 lesson 4 - pennsylvania state university

GEOG 487 Lesson 4: Step-by-Step Activity; Author: Rachel Kornak, GISP. Updated 12/13/2017. of 15 © 1999-2017 The Pennsylvania State University.

GEOG 487 Lesson 4: Step-by-Step Activity

Part I: Visually Explore Trends

In Part I, we will explore several tools and technique to make it easier to visually interpret patterns in

your data using ArcGIS. These can be especially helpful when you have multiple datasets to compare.

1. Organize Your Map and Data

a. Create a new map and save it in your L4 folder.

b. Set your Current Workspace and Scratch Workspace to your L4 folder (Geoprocessing >

Environments…>Workspace).

c. Add the study area boundary (Study_Site), Ottawa National Wildlife Refuge boundary

(OttawaNWR), polygons of vegetation groups (60s_VegGrp, 70s_VegGrp, 00s_VegGrp), and

polygons of invasive species classes (60s_Invasive, 70s_Invasive, and 00s_Invasive) from

your L4 folder.

d. Change the study site and refuge boundaries to hollow outlines. You don’t need to alter the

symbology of the remaining layers since we will be doing this in Step 3.

e. Check the projection of the data frame by right clicking on “Layers” in the Table of Contents

> Layers > Properties > Coordinate System. It should say “NAD_1983_UTM_Zone_17N.”

f. Add the Open Street Map layer.

g. Save your map.

2. Review Contextual Information

a. One of our main research questions is how vegetation within our study area changes over

time in response to fluctuating water levels. We need to know what the water elevation

was for our study area for each of our study years. Since the wetlands in our study area are

hydraulically connected to Lake Erie, we know they will both have the same water elevation.

b. The water levels in the table below are from the Lake Erie Hydrograph (graph of water level

over time). Compare the water levels for each year and rank them as high, medium, or low.

Year Water Level (m) High, Med, Low

1962 173.9

1973 174.9

2005 174.2

https://www.glerl.noaa.gov/data/dashboard/GLD_HTML5.html


Based on the Lake Erie Hydrograph, how do the water levels for 1962, 1973, and 2005 compare to the long term averages for Lake Erie? Which years had the highest and lowest water levels between 1920 and the present?

3. Set Layer Symbology

a. One of the first steps to understand trends in your data is to simply look at the spatial

patterns. To compare time-series datasets, you want to make sure all of your layers have

the same symbology settings. If not, it won’t make sense to visually compare them because

changes in patterns may be related to different symbology settings instead of changes in

your actual data.

b. Layer files (.lyr) are a way to save symbology settings in ArcGIS. I’ve already created layer

files for you for two purposes, first to save you time and second to demonstrate some of the

tools available in ArcGIS to make your life easier.

c. Right click on the “00s_VegGrp” > Properties > Symbology > Import. Choose “Import

symbology definition from another layer in the map or from a layer file.” Browse to the

“00s_VegGrp.lyr” file in your L4 folder. Make sure the Value Field matches as shown below.

Click OK to apply the Symbology and then OK to close the Properties Dialog Box.

d. For the 60s and 70s time periods, we will import the symbology a slightly different way.

Right click on the “70s_VegGrp” > Properties > Symbology > Import. Choose “Import

symbology definition from another layer in the map or from a layer file.” Select the

“00s_VegGrp” file from the drop down menu. Click OK, OK, and OK again. Repeat for the

“60s_Veg_Grp” file. This option is particularly helpful if you don’t have a layer file to start

with. Using this method, you can choose your symbology settings once and then import the

settings to all remaining datasets.


e. Use the “00s_Invasive.lyr” layer in your L4 folder to set the symbology for the time series

invasive shapefiles. Save your map.

f. Turn the different layers on and off to explore the changes over time.

One of the challenges of looking at time series data of the same location is that

all of the datasets overlap each other. It is very difficult to see all of the datasets

at the same time if you have them all in the same data frame, especially if they

are polygon files.

4. Create Time Series Animation

a. Turning layers on and off manually is not really the best technique to visualize changes over

time, especially if you have a lot of datasets or if you want to repeat the task many times.

ArcMap has a tool that allows you to easily set up animations of datasets that are in the

same Group Layer within the Table of Contents.

b. To use this tool, we need to organize our data into different group layers within the Table of

Contents. Hold down the Ctrl key and select the “60s_VegGrp,” “70s_VegGrp,” and

“00s_VegGrp.” Right click > Group.

c. Name the group “Vegetation Groups.” Repeat for the invasive species shapefiles. Name the

group “Invasive.”

d. The order in which the layers appear in the animation we are going to create is based on the

order the layers are arranged in the Table of Contents. Arrange the layers within each group

so they increase in time from top to bottom like the example below.


In this lesson, we arranged the layers within each group chronologically. You could also arrange them in a different order, such as by their water level (low, medium, high) to visualize how the vegetation changes correlate with water level changes.

e. We’ll start by creating an animation of the vegetation groups over time. Turn the “Invasive

Group Layer” off in the Table of Contents.

f. Add the Animation Toolbar to your map (Customize > Toolbars > Animation).

g. Click on the “Animation” drop down list on the Animation Toolbar > Create Group

Animation.

h. Use the settings shown below and click OK to create the animation.


i. Click on the “Open Animation Controls” icon on the Animation Toolbar. On the menu that

appears, click the play button to preview your animation. Note: Make sure you can see the

entire study area when you view your animation.

Make sure you have the correct answer before moving on to the next step.

When you preview your animation, you should see one layer turned on at a time

beginning with the VegGrp_60s and ending with the VegGrp_00s.

Another way to check your animation is to look at the “Time View” settings by

going to Animation Toolbar > Animation Manager > Time View. You may need to

adjust the size of the popup window to see all 3 of the files.

If your data does not match the example below, go back and redo the previous

step. You’ll need to clear the animation first by going to Animation Toolbar >

Clear Animation.


j. If you are happy with the results, save the animation in your L4 folder (Animation Toolbar >

Animation Drop Down List > Save Animation File.)

k. Now we’ll create an animation of the invasive species data over time using the Invasive

Group Layer. Make sure you uncheck the “Vegetation Group Layer” and check the

“Invasive Group Layer” in the Table of Contents.

l. Repeat steps g and h. Use the Base Name and Group Layer settings shown below:

m. Preview your animation. Once you are satisfied with it, save it in your L4 folder. Go to the

Animation Toolbar, Animation drop down menu > Save Animation File.

If you want to be able to view your animation outside of ArcGIS, you can export your animation to a video file using the tool on the Animation Toolbar. You can also make your animations more sophisticated by exploring the available animation tools and options within ArcMap. For example, you can add looping, string multiple animations together, add time series labels, and add graphs that update over time along with your animation. You can find more information, such as help articles, sample animations, and tips in the Esri help topics stored with your software under “Help > ArcGIS Desktop Help > Desktop > Mapping > Animation.”


5. Create a Map Layout with Multiple Data Frames

Animations are great for emailing to a client or adding to a presentation. However, if you want

to print your maps, you need to create a map layout. We are going to create a map layout with

multiple data frames to make it easier to compare our data over time. When working with

multiple data frames that show similar information, it is easier to set the symbology, extent, and

scale in one data frame, then make copies of the data frame, instead of setting up each data

frame separately.

The final map layout should include all of the following elements:

• 7 data frames

o The six main data frames should show the study area boundary, the Ottawa

National Wildlife Boundary, and the Open Street Map layer.

▪ 3 of these data frames should show the vegetation group data, one for

each time period (60s, 70s, 00s), each with its own title.

▪ 3 of these data frames should show the invasive species data, one for

each time period (60s, 70s, 00s), each with its own title.

o 1 data frames should contain a locator map (see instructions below). This

should be at a scale to show the study area in relation to the state of Ohio. It

should include the Open Street Map layer and the location of the study area.

• Legend (do not use default layer names with “_” or abbreviations)

• Water level during each time period (m)

• Scale (with units of km or miles)

• North Arrow

• Source Information

a. Switch to the layout view. Switch off the Open Street Map Basemap for now, as it will

increase the loading time while you are setting up your layout.

b. Set up page layout. File > Page and Print Setup. Uncheck the box under the “Map Page

Size” that says “Use Printer Paper Settings.” Choose a page size of “Tabloid” (or other 11x

17 inch equivalent) and Portrait Orientation. Click OK.

c. Resize the data frame to be approximately 5 inches wide by 4 inches tall. You may want to

right click on Layers in the Table of Contents > Properties > Size and Position and adjust the

size there.

d. To adjust your scale and extent, right click on “Study_Site” in the Table of Contents > Zoom

to Layer.

e. Select the data frame in your layout, Right Click > Copy, Right Click > Paste. Repeat so you

have 7 data frames in your layout.

f. Resize one of the data frames to be 3 inches by 2 inches. This will become the locator map.

g. Next we’ll organize the data frames. We’ll start by setting up snapping to make it easier to

format your layout.

h. Right click in the white space outside of your data frame > Grids to display the grid on your

layout. Click on the “Snap to Grid” while in this dialog box.


i. Drag the data frames so they look like the example on the following page. The locator map

should fit in the area that says “Insert legend and other map elements here” in the graphic

below.


j. Notice one of your data frames has a dashed line border. This means it is the active data

frame. The title of the active data frame will also appear bold in the Table of Contents. You

can change which data frame is active by either selecting it in the layout or right clicking on

its name in the Table of Contents > Activate.

Notice that all of the data frames are named “Layers.” Next we’ll rename each data frame

so we can tell which data frame belongs to which table of contents entry. It may help to

click the minus sign next to the titles in the Table of Contents to hide the contents.

k. In the map layout, right click on the data frame in the top left > Properties > General. Type

“1962 Veg Groups” in the “Name” and Click OK. Notice the data frame name also updates in

the Table of Contents. Rename the remaining data frames as shown in the graphic from

step g above. Name the smallest data frame “Locator Map.”

l. Remove the datasets that do not belong in each of the data frames. For example, in the

“1962 Veg Group” remove the 70s and 00s VegGrp and all the invasive shapefiles.

m. Add a legend, scale bar, north arrow (you only need one of each since all of the data frames

have the same symbology and scale), titles for each data frame, and source information.

n. ArcGIS only allows you to add layers from the active data frame in a particular legend. You

will need to create two different legends and arrange them side by side (one with the

vegetation groups and one with the invasive species types). Do not include an entry for the

base map in either legend.

o. Include the water levels for each year, from the table earlier in this document, on your map

layout to aid in showing relationships between the water levels and the map layers.

p. Turn back on the base maps in all of the data frames and save your map.

Adding neatlines to your map layouts helps to visually group elements together. This is helpful when your map has a lot of information. To add a neatline around multiple data frames, hold down the Ctrl key and select the data frames in your layout you want to group together. For example, you could group the data frames by topic (Vegetation Groups) or by time period. Go to Insert > Neatline. You can select the symbology settings of the neatline in this menu.


6. Visually Interpret Trends Using Maps

a. Use the map layout you created in Step 5 to try to answer the following questions. We will

repeat this exercise in Part II using statistical techniques instead of visual techniques.

• How has the amount and location of emergent vegetation changed over time? For

example, has it increased or decreased?

• How has the amount and location of invasive species changed over time?

• How has the quality of habitat changed over time?

• How has the amount of emergent vegetation changed in response to water level

fluctuations?

Part II: Statistically Explore Trends

Visually exploring your data is a good way to start interpreting your results. However, it is difficult to

determine the magnitude of change just by looking at a map. Calculating statistics allows you to have

actual numbers to work with, allowing you to say that “variable x increased by 12%” instead of “variable

x increased.”

It is very easy to make mistakes while calculating statistics, such as typos, choosing

incorrect input layers, or using incorrect order of operations. To avoid possible errors,

you should first visually explore your data so you have an idea of the trends that exist

in the data. After calculating statistics, you can compare your results to your visual

interpretation to make sure your statistical results seem reasonable.

1. Calculate Area Statistics

a. Use the attribute tables of the vegetation groups and invasive species data to fill in the table

below. You will use this table to answer some of the Lesson 4 Quiz questions.

Study Year

Water Level (High,

Med, Low)

Area Open Water (sq m)

Area Emergent Vegetation

(sq m)

Area Invasive Species (sq m)

Area Controlled

Invasive Species (sq m)

1962 1973

2005


Which year has the most emergent vegetation? Which year has the most open water? Did you find it difficult to compare such complex numbers (lots of digits and decimal places)?

b. Another technique to compare multiple datasets is to use percent total area values instead

of actual areas. It is important that all of the datasets you want to compare have the same

area to use this technique, which is why we had to union and clip our starting data with the

Study Area Boundary in Lesson 3.

c. Add a new short integer field with a precision of 0 to the 60s_VegGrp named “pct_tot.” In

this case, we are using an integer data type since we are not concerned with decimal places.

d. Calculate the percent total of each vegetation group using the field calculator. (Percent

Total Area = Area of Each VegGroup/Area of All VegGroups * 100). Hint: You can use the

Statistics Tool to easily find the combined area of all VegGroups. The graphics below shows

the area value from the 60s_Veg_Group file. There may be slight difference in the total area

values between the different layers.


e. Repeat for all of the remaining vegetation and invasive shapefiles.

f. Fill in the table below based on your results. You will use this table to answer some of the

Lesson 4 Quiz questions.

Study Year

Water Level (High, Med,

Low)

% Tot. Area Open Water

% Tot. Area Emergent

Vegetation

% Tot. Area Invasive

% Tot. Area Controlled

Invasive

1962

1973 2005

Which year has the most invasive species? Which year has the least open water? How does this correlate with water levels? Which files have the most missing data? After comparing several datasets using calculated areas and percent total areas, which technique do you find is easier to detect trends between multiple datasets?

2. Create Graphs from Attribute Tables

a. You can combine statistical techniques with visual techniques by creating graphs from your

attribute tables. There are many different types of graphs to choose from. In this lesson,

we will look at two options: pie charts and vertical bar charts.

b. First, we’ll use the vertical bar type. Open the attribute table of “60s_VegGrp” > Click on the

drop down menu in the upper left corner > Create Graph. A wizard will open that guides

you through the graph creation process. Use the settings below:

i. Graph Type: Vertical Bar

ii. Layer/Table: 60s_Veg_Grp

iii. Value field: SUM_sqm

iv. X field (optional): VegGrp

v. X label field: VegGrp

vi. Uncheck the box “Add to legend”

vii. Color: Match with Layer

c. Click Next, give the graph a meaningful title in the “General graph properties” section and

meaningful axes labels in the “Axis properties” section. Note: Do not use the default

names, which have “_” and abbreviations that may be confusing to your target audience.

d. Accept the defaults for the remaining options and click Finish. You may need to resize it to

view all of the labels.


e. Look at the output graph. Is it easy to tell how the amount of vegetation within each group

compares to other groups? Notice how the y axis defaults to the highest value in your

dataset. If you wanted to compare graphs from multiple datasets, you would need to make

sure that all of the graphs have the same minimum and maximum values on the y axis.

f. Right click on the graph and explore the available options. The menu to manually adjust the

axes is on the Advanced Properties > Chart > Axis > Scales.

g. Notice that you can add the graph directly to your layout. We are not going to do this in this

lesson, but you could see how this may be valuable for other projects, especially if you

combined it with the available animation tools.

SAMPLE GRAPH


h. Now let’s use the pie chart type. Open the attribute table of “60s_VegGrp”again > Drop

Down Menu > Create Graph. A wizard will open that guides you through the graph creation

process. Use the settings below:

i. Graph Type: Pie

ii. Layer/Table: 60s_Veg_Grp

iii. Value field: SUM_sqm

iv. Sort field: VegGrp

v. Label field: VegGrp

vi. Uncheck the box “Add to legend”

vii. Color: Match with Layer

i. Click Next, give the graph a meaningful title, accept the defaults for the remaining options

and click Finish.

j. Look at the output graph. With a pie chart, you don’t have to worry about the minimum

and maximum values on the y-axis to compare multiple datasets. However, you need to

make sure all of the datasets have the same total area.

Which graph type do you think best demonstrates the trends in our data, vertical bars or pie charts? Why?

3. Interpret Trends Using Statistics and Graphs

a. Use the statistics and graphs you calculated to answer the following questions again.

Compare them to your answers from step 6 of Part I.

• How has the amount and location of emergent vegetation changed over time?

• How has the amount and location of invasive species changed over time?

• How has the quality of habitat changed over time?

• How has the amount of emergent vegetation changed in response to water level

fluctuations?

After experimenting with both visual and statistical techniques to determine trends in your data, can you think of any scenarios in which one is preferable over the over?

That’s it for the required portion of the Lesson 4 Step-by-Step Activity. Please consult the Lesson

Checklist for instructions on what to do next.


Try one or more of the optional activities listed below.

• In Lesson 1, we briefly explored Operations Dashboard, an app from Esri that you can use to you create dashboards with interactive maps, charts and statistics and share them in ArcGIS Online. Review the documentation at doc.arcgis.com/en/operations-dashboard/ (you may need to type this manually in your browser) and consider how you could use this tool to replace the static map layout we created in this lesson.

• In Lesson 4, we created graphs using the “vertical bar” and “pie chart” graph types. Experiment with the other available graph types. Is there a particular type that makes the data trends jump out at you more than others?

• Use the xx_Species shapefiles from your L4 folder to answer the question, “Has the dominant invasive species changed over time?” Hint: Look at the Veg_Type and Invasive fields.

Note: Try This Activities are voluntary and are not graded, though I encourage you to complete

the activity and share comments about your experience in Canvas Lesson 4 Discussion.

doc.arcgis.com/en/operations-dashboard

geog 487 lesson 4 - pennsylvania state university

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