ArcGIS Pro Lesson 1: Getting Started by Mapping Census Data

by Bailey Clark and Joshua MacFadyen, University of Prince Edward Island

October 7, 2020

This lesson will introduce you to a geographic information system (GIS), namely ArcGIS Pro. By following along with this lesson, you will learn how to add spatial data (maps) and attribute data to the program, and how to assign the latter to geographic locations on the former. This process of linking attribute data with actual geographic locations on Earth is one of the unique features of GIS. Once you learn this, the GIS will help you answer descriptive historical questions, and it will also inspire you to explore analytical historical questions.

Table of Contents

Before We Begin: Downloading the Lesson Files

This tutorial uses examples from the Canadian Census of Agriculture and the province of Prince Edward Island (PEI). Before we begin, we need to download the files necessary to complete the tutorial. These files are contained in a zipped folder. Once downloaded, the zipped folder will also provide the folder structure for our project.

  • Click here to access the zipped folder, and download  it to your computer’s Downloads folder.
  • Navigate to your computer’s Downloads folder, right-click the zipped folder and click Extract all….
  • Click Browse.
  • Navigate to C:\Users\<username>\ArcGIS, and click Select Folder. 
  • Under “Files will be extracted to this folder,” it should now say C:\Users\<username>\ArcGIS.
  • Click Extract.
  • After you extract the zipped folder, the file path should be C:\Users\<username>\ArcGIS\ArcGIS_Lesson1.

Step 1: Saving a New Project File in ArcGIS Pro

  • Open ArcGIS Pro (at the time of writing we were using ArcGIS Pro 2.5)
  • Under the New heading, click Map
  • Name your project PEI 1971 and save it in the following location: ArcGIS_Lesson1\ProjectFiles
    • Note: ensure “Create a new folder for this project” is checked.

Note: GIS programs will often malfunction if you change the names or locations of files or their folders after saving them. Thus, it is best to set up a file structure and not change it; for this tutorial, you will use the file structure contained in the provided zipped folder. Here is an explanation: when you “save” your ArcGIS project in ArcGIS Pro, it does not save the data. The data is stored elsewhere on your computer. When you click “save,” ArcGIS Pro remembers the location of your data and how you instructed it to display the data. Thus, you must keep a clear file path structure in place or ArcGIS Pro will not know where to access the data. 

Note: save your work in ArcGIS Pro early and often to avoid data loss if the program unexpectedly crashes.

Step 2: Finding and Adding Spatial Data

Key Concept: the map data we will add in this step is vector data in the form of polygons. Vector data can also come in the form of lines and points. Vector data, in whatever shape, can be added to ArcGIS as a shapefile layer or a file geodatabase feature class layer. The key characteristic of GIS is that it assigns geographic coordinates to pieces of vector data. By contrast, a graphics software program can also create points, lines, and polygons, but it will not assign them a geographic location.

Finding Spatial Data

We need spatial data to explore PEI’s 1971 Census of Agriculture data visually. Because no spatial boundary file data exists for Canada in 1971, and because the geographic boundaries within PEI did not change substantially between 1971 and 1951, we will use 1951 spatial data to explore PEI’s 1971 census of agriculture data visually.

Spatial data can be obtained from multiple sources, one of which is the Scholars GeoPortal. We will download our spatial data for Canada in 1951 from this site. To do so,

  • Go to Scholars GeoPortal 
  • Type 1951 into the search bar
  • Find Boundary Files, 1951 Census of Canada (CCRI) in the results list
  • Click Add
  • Under Census Subdivisions / Tiled map service – Vector, click Add again
  • Select the Download tab
  • Choose the Download entire datasets option
  • Click Download (a separate button below)
  • A zipped folder called will download. Let it download to your Downloads folder, and Extract it in this folder. Open the extracted folder and Extract its subfolder (which is also zipped) called to the following location: C:\Users\<username>\ArcGIS\ArcGIS_Lesson1\SpatialData

Adding Spatial Data to ArcGIS Pro

We will now add to ArcGIS Pro the spatial data we just downloaded.

  • In ArcGIS Pro, click Add Data
  • In the unzipped CCRI_CANADA_CENSUS_SUB_DIVISIONS_1951 folder, go to Shapefile, then CCRI_Shapefiles_CSD_1951, then double-click CANADA_CSD_1951_MW.shp to add this shapefile (.shp) to the project.

Note: When you click Add Data and navigate to the location of the file you wish to add to ArcGIS, sometimes the file will not appear. This problem can happen when you are trying to add any type of data, and it can happen even if you can see the file in that particular location in your computer’s built-in file explorer. Nonetheless, resolving this issue is almost always a simple matter of clicking Refresh in ArcGIS Pro.

Step 3: Adding Attribute Data

Key Concept: While spatial data provides a visual representation of a geographic place through points, lines, and polygons, attribute data provides textual or numerical descriptions about a geographic place. An example of attribute data is agricultural census data.

We will now add an attribute table containing PEI’s data from the 1971 Canadian Census of Agriculture, which is included in the zipped folder provided at the beginning of this lesson.

  • Click Add Data
  • In C:\Users\<username>\ArcGIS\ArcGIS_Lesson1\AttributeData, go to CSD_PE_1971.xlsx, and then double-click PEI Data 1971$ to add it to the project.

We have just added an attribute table to our project. The data in this table has not yet been assigned a geographic place, so it does not yet appear on our map.

To view the data in the attribute table,

  • Right-click PEI Data 1971$ in the Table of Contents
  • Click Open

The first two columns contain the geographic places (in this case, PEI’s census subdivisions), while the remaining columns contain attributes of these places. The attribute headings are given as codes here, but there is a legend included in the Excel file. You can open this spreadsheet separately in Excel to view this legend.

The attributes in this dataset provide numerical information about such things as the acres of woodland and cropland, as well as the acres dedicated to growing various crops (including potatoes). The geographic places in this data set are all of the 67 townships that existed in PEI in 1971, plus Charlottetown Royalty.

We will use the attribute data in this table to learn about the agricultural characteristics of Prince Edward Island in 1971.

Step 4: Joining Spatial Data and Attribute Data


We have added to our project spatial and attribute data that describe the same place (i.e., PEI) at—for all intents and purposes—the same time point (i.e., 1971). We know that the spatial and attribute data are related, but ArcGIS Pro does not—as of yet. In this step, we will link the two sets of data in ArcGIS Pro in a process called joining. 

Key Concept: the ability of a GIS to join spatial and attribute data is what sets it apart from graphics and database software. While a graphics program can produce digital maps, and while a database program can manipulate attribute data, only a GIS can assign attribute data to a geographic location on a digital map. GIS is thus a tool that allows researchers to see the spatial aspects of attribute data.

The spatial data we added earlier contains an attribute table. You can view it by right-clicking the 1951 map of Canada layer (i.e., CANADA_CSD_1951_MW) in the Table of Contents and then clicking Attribute Table.

This table is pretty barren compared to the plethora of information contained in the 1971 Census of Agriculture table (i.e., PEI Data 1971$). However, each table contains columns of attribute data that correspond to rows of PEI census subdivisions (CSDs).

There is a column of attribute data—UID_CSD_51—that is identical in both tables. The values in this column are unique IDs for each CSD in PEI. For example, Township 40 has the same unique ID—PE011003—in both tables. These unique IDs will allow ArcGIS to append—or join—the data for each CSD in the 1971 Census of Agriculture table to the corresponding row in the attribute table of the 1951 map of Canada layer. The joining process thus allows us to assign geographic coordinates to the attribute data in the 1971 Census of Agriculture table.

Note: when joining two tables, it does not matter if the column heading containing the unique IDs is different between the two tables being joined. However, the unique IDs themselves must be identical in both value and type—i.e., they must each be numbers or they must each be letters. 

Caution: ensure that you have no cells, rows, or columns selected in your agricultural attribute data table or your spatial data’s attribute table. If you do have anything selected, click Clear before continuing. (You can find Clear under the Map tab and in the Selection group.)

Join Process

To join the 1951 map of Canada with the 1971 Census of Agriculture table,

  • In the Table of Contents, right-click CANADA_CSD_1951_MW
  • Click Joins and Relates > Add Join 
  • In the Add Join pane to the right, input the following:
    • Layer Name or Table View: CANADA_CSD_1951_MW
    • Input Join Field: UID_CSD_51
    • Join Table: PEI Data 1971$
    • Output Join Field: UID_CSD_51
    • Uncheck the box called Keep All Target Features.
  • Click OK (note: if you create a join using the geoprocessing tool, as we did the button will say Run, instead).

While the PEI Data 1971$ table remains unchanged, we have just joined its data to the 1951 map of Canada’s attribute table; we have given its data a geographic coordinate. The 1951 map of Canada has changed, however. By unchecking the box called “Keep All Target Features,” we have removed all of the jurisdictions for which there was no match in the 1971 attribute data. In other words, we have removed all jurisdictions outside of Prince Edward Island.

Now, when you open the 1951 map of Canada’s attribute table, you will see PEI’s data from the 1971 Census of Agriculture appended to it.

However, this join process is only temporary.

Making the Join Permanent

To save the joined table permanently,

  • Right-click CANADA_CSD_1951_MW in the Table of Contents
  • Click Data > Export Features
  • In the Feature Class to Feature Class window to the right, input the following:
    • Input Features: CANADA_CSD_1951_MW
    • Output Location: PEI 1971.gdb
    • Output Feature Class field: CANADA_CSD_1971_JOIN_CENSUS 
  • You can ignore the rest of the settings in this Feature Class to Feature Class pane.
  • Click Run.

In the Table of Contents, the permanently joined table will then appear. While there, you can also right-click both CANADA_CSD_1951_MW and and PEI Data 1971$ and Remove them from our project, as we just replaced them with CANADA_CSD_1971_JOIN_CENSUS.

Step 5: Symbolizing Attribute Data

Because we just added historical attributes to the map layer, we have created a Historical Geospatial Information System (HGIS). An HGIS allows us to explore historical questions through a process known as data exploration.

Key Concept: data exploration involves mapping the attribute data, changing a parameter, and then mapping the attribute data again. Repeating this process can reveal spatial patterns.

A historical question that we may explore as an example is: 

Which townships in PEI had a lot of land dedicated to potato production in 1971?

Let’s create a choropleth map to find out.

  • Right-click the CANADA_CSD_1971_JOIN_CENSUS in the Table of Contents
  • Click Symbology
  • In the pane to the right of the screen, under “Primary symbology,” select Graduated Colors 
  • For Field, select POTATS, which stands for Potatoes, acres. 
  • Choose the Color Scheme called Blues (Continuous)

The Method field is where you can choose how you would like to create class breaks to represent your data. Class breaks are the points at which your data is divided. Establishing class breaks creates classes, which are ranges of data that are each assigned their own colour in our choropleth map.There are multiple options for creating class breaks. Essentially, you can divide your data into ranges manually, or you can have ArcGIS Pro divide your data according to a particular method. Visit the ArcGIS Pro website to learn more about the various methods.

  • We will use Natural Breaks (Jenks). Select this option in the Method field dropdown menu.
  • Set the number of classes to 7.

The greater the acreage of potato-producing land in a township, the darker blue ArcGIS Pro will shade the township on the map. 

Throughout the process of data exploration, you can adjust the number of classes and the numbers at which you break each class. You can also change the colour scheme and the variable that ArcGIS maps. Exploring your data in this way allows you to discover spatial patterns that can be useful to your research.


We just symbolized the acreage of potato-producing land in each township; however, we did not account for the total amount of cropland that farmers had to work with when they chose to plant a certain acreage of potatoes. We can thus ask the question:

Which PEI townships dedicated the most cropland to potato production?

To account for the amount of cropland, we will use a process called normalization.

Key Concept: normalization in GIS differs from its uses in statistics. In GIS, normalization is the process whereby we make one value proportional to another. Normalizing your data can be a more accurate and honest way of presenting it. 

In our case, we will normalize the acres dedicated to potato production in each township against the total amount of cropland there.

  • Set the Normalization field to CRPLND, which stands for Cropland, acres.

ArcGIS now colours in the darkest blue the townships that had the most acres dedicated to potato production out of all of the acres used for cropland. How has the normalization process changed the look of our map?

Step 6: Overlay Analysis

Descriptive Questions, Analytical Questions, and Overlay Analysis

Key Concepts: We have just created a couple of thematic maps—those that chart the spatial distribution of a single attribute—to answer descriptive questions about where potato-producing acres were in PEI. The descriptive answers thematic maps provide often inspire analytical questions as to why things happened where they did in the past. Thematic maps alone are often insufficient to answer such analytical questions; we need to employ traditional research methods and/or use Overlay Analysis.

In our case, we can now ask the following analytical question, for example:

Why did some townships on PEI dedicate more land to potato production than others?

Asking this analytical question can lead us to investigate the environmental conditions in each township, among other things:

Did some townships have soil that was better suited to growing potatoes? What factors caused the soil to be better suited?

We would likely need to do some traditional research to fully explore these two questions, especially the second one. But we can also use Overlay Analysis to help provide answers to the first question. 

Key Concept: Overlay Analysis allows us to see two different types of spatial data at the same time to explore any potential relationships between them. 

In our case, we can create an overlay layer using data from the Government of Canada. This data will show us the soil types present on PEI in 1996. Because soil types take centuries to change, this data from 1996 will be accurate for our 1971 data.

Finding and Adding Overlay Data

  • Go to the Government of Canada’s Soil Landscape of Canada site
  • Under Availability, download the SLC V2.2 zip folder. Extract it to the ArcGIS_Lesson1\SpatialData folder.
  • In ArcGIS Pro, click Add Data and add the slc_v2r2_canada.shp file to your project.
    • This file charts the soil landscapes of Canada.
  • Click Add Data and add the table called slc_v2r2_canada_cmp.dbf to your project.
    • This file—a Component Table—is attribute data that provides the code for the type of soil contained in each soil landscape. Although this file is attribute data, it has downloaded alongside slc_v2r2_canada.shp to the SpatialData folder.
  • Go to Soil Name Table and Soil Layer Table from the Government of Canada
  • Download the soil name file for Prince Edward Island, which is called soil_name_pe_v2r20130705.dbf, to ArcGIS_Lesson1\AttributeData, and then add it to ArcGIS Pro using Add Data.

Joining the Spatial and Attribute Overlay Data

The join that we completed earlier in step 4 was a one-to-one join. The join we will complete now is a multiple-to-one join.

Joining the Component Table to the Map Layer

  • In the Table of Contents, right-click the map layer, slc_v2r2_canada
  • Click Joins and Relates > Add Join 
  • In the window to the right, input the following:
    • Layer Name or Table View: slc_v2r2_canada
    • Input Join Field: SL
    • Join Table: slc_v2r2_canada_cmp
    • Output Join Field: SL
    • Uncheck the box called Keep All Target Features.
  • Click Run.

Joining the Soil Name Table to the Map Layer

In the previous step, by joining the Component Table to the map layer, we added its field called “SOIL_CODE” to the map layer. In this step, we will use this “SOIL_CODE” variable to join the soil name table to the map layer.

  • In the Table of Contents, right-click slc_v2r2_canada
  • Click Joins and Relates > Add Join 
  • In the window to the right, input the following:
    • Layer Name or Table View: slc_v2r2_canada
    • Input Join Field: slc_v2r2_canada_cmp.SOIL_CODE
    • Join Table: soil_name_pe_v2r20130705
    • Output Join Field: SOIL_CODE
    • Uncheck the box called Keep All Target Features.
  • Click Run.

Make the Join Permanent

To save the joined table permanently, 

  • Right-click slc_v2r2_canada in the Table of Contents
  • Click Data > Export Features
  • In the window to the right, input the following:
    • Input Features: slc_v2r2_canada
    • Output Location: PEI 1971.gdb
    • Output Feature Class field: slc_v2r2_canada_join_soilname 
  • Click Run.

You can now right-click and Remove the original spatial layer called slc_v2r2_canada and the tables called slc_v2r2_canada_cmp and soil_name_pe_v2r20130705

We can now click on a soil landscape and, in the popup window, we can see the SOILNAME variable for that landscape. In other words, we can see what type of soil is present in that part of Prince Edward Island.

Using Overlay Analysis to Answer Analytical Questions

To use overlay analysis to answer analytical questions, we first need to make the different soil types easier to see, and then we need to make the overlay and potato-production maps visible at the same time. 

To make the different soil types easier to see,

  • Right-click slc_v2r2_canada_join_soilname
  • Click Symbology
  • Change the Primary symbology to Unique values
  • For Field 1, select SOILNAME.
  • Set the Color Scheme to Pastels

Each soil type is now given a unique pastel colour. However, we cannot currently see the choropleth map of PEI’s potato-producing townships and the soil landscapes map at the same time. To do this,

  • Ensure slc_v2r2_canada_join_soilname is at the top of the Table of Contents. If it is not, drag it there.
  • With slc_v2r2_canada_join_soilname selected in the Table of Contents, input 60.0 % in the Layer Transparency field in the Effects group of the Appearance tab.

We can now view both PEI’s potato-producing townships and the soil landscapes map. We can now click on a soil landscape and, in the popup window, we can see the SOILNAME variable for that landscape. In other words, we can see what type of soil is present in that part of Prince Edward Island.

Using this information provided by the overlay map, we can see the soil types in the regions of PEI that dedicated the most land to potato production (i.e., the areas coloured in the darkest blue). Did the regions that dedicated the most land to growing potatoes have the same type of soil? If so, perhaps this type soil was better suited to growing potatoes. We can thus begin to answer the analytical question posed above, namely: Did some townships have soil that was better suited to growing potatoes?

Step 7: Creating an Exportable Map

Once you have represented your data in ArcGIS Pro (in a choropleth map or otherwise), you may wish to export an image of your final product for inclusion in a presentation, article, or book. To create a version of your map that will appear well in any of these formats, you can create a layout

Key Concept: in ArcGIS Pro, there are two ways you can view your data. There is the way we have been using thus far, Map View, which appears in the first tab. There is also Layout View, which we will use to create an exportable map. Layout View opens in a new tab.

Layouts in ArcGIS Pro are an extremely useful tool for creating static images of your map. Each Layout you create forms a separate view or tab that allows you to add elements like legends and citation information on the map and then export the map as a static image. The Layout will maintain the same map frame (including the scale and extent you selected) for each image, even as you change the layers and other contents in the original project (i.e., the Map View).

To enter layout view,

  • Under the Insert tab, click the New Layout dropdown.
  • Under “ANSI – Landscape,” click Letter.

We now see the Layout View tab.

The layout will initially appear as a blank white page, to which we will add our choropleth map and some metadata. First, however, we will add some guidelines. These guidelines do not appear when you export the image, but they help us to add our map and metadata precisely.

Adding Guidelines

To add guidelines around the border of the page,

  • Right-click the ruler
  • Click Add Guides
  • Under Orientation, select Both.
  • Choose Offset from edge in the Placement field.
  • Set the Margin to 0.25 inches
  • Click OK.

We will now create a set of guidelines that will break our layout into sections. (Into these sections we will soon add our map and metadata.) To create these guidelines,

  • Right-click the ruler and click Add Guides again. 
  • Change 
    • Orientation to Horizontal
    • Placement to Offset from edge
    • and the Margin to 1 inch
  • Right-click the top ruler and click Add Guide. (Note the difference between Add Guides and Add Guide.)
    • This step will add a single vertical guideline to the spot you clicked. 
    • Select this vertical line on the top ruler. (A blue triangle indicates you have clicked the guideline). Drag this guideline to the 8.00-inch mark.
  • Right-click the top ruler and click Add Guide again. A second vertical line appears; drag this line to the 8.25-inch mark.

Note: to delete an existing guideline, right-click it and then click Remove Guide.

Your guidelines should now look like those in this screenshot:

Inserting a Map Frame

We can use the guidelines we just created to add our map and metadata to our layout precisely. To add our map, 

  • Under the Insert tab, click the drop-down arrow underneath Map Frame
  • Click the one with the 1971 map of Prince Edward Island in the thumbnail image. 
  • With your cursor as a crosshairs, click and hold at the top left corner of the largest guideline section we created. Next, while holding your click, drag your cursor to the bottom right corner of this section and release. 

Our map is now on our layout page, but it may not be showing the precise geographic area that we want. To remedy this, 

  • Click the image of the map to select it
  • Under the Layout tab, click Activate

With the map frame activated, you can click on your map and drag and zoom using the mouse wheel to reposition the geographic area shown. 

Note: if we had not activated the map frame first, clicking and dragging would have repositioned the entire map frame within the layout page. 

Try to reposition the map of PEI to the centre of the frame, like in this screenshot:

  • Under Activated Map Frame, click Close Activation 

Inserting Metadata

With our map added to our layout, we can now add some metadata to help viewers understand our map. 

A legend would be useful to explain the meaning of the different shades of our choropleth map. To add one,

  • Under the Insert tab, click Legend 
  • Click and drag it into place like you did with the map frame. Add the legend to the guideline-created column on the right, however.

We will update our legend’s headings to make them easier for a viewer to understand. Because they are dynamically linked to ArcGIS Pro’s Table of Contents, we can make our changes there and see them reflected in the legend. In the Table of Contents,

  • Rename slc_v2r2_canada_join_soilname to Soil Landscapes of Canada.
  • Rename SOILNAME to Soil Type.
  • Rename CANADA_CSD_1971_JOIN_CENSUS to Prince Edward Island, 1971.
  • Rename POTATS/CRPLAND to % Cropland Used for Potatoes.

We will also make the percentage figures easier to understand. In the Table of Contents,

  • Right-click Prince Edward Island, 1971 and click Symbology.
  • Click Advanced symbol options
  • Expand the list called Format labels
  • Change the category from Numeric to Percentage.
  • Under the Percentage heading, click Number represents a fraction. Adjust it to show as a percentage.
  • Change the number of Decimal places to 0.

To provide the geographic context of our map, we will add a north arrow and a scale bar. 

  • Under the Insert tab, click North Arrow and pick one you fancy
  • Click and drag to position the arrow below the map frame. 
  • Under the Insert tab, click a desirable Scale Bar
  • Click and drag it into position to the right of the North Arrow

To add a title to our layout, 

  • Under the Insert tab and in the Text group, click Rectangle
  • Click and drag the rectangle into the guideline space above the map frame
  • Type in Prince Edward Island Soil Landscapes and Areas of Potato Production in 1971
  • Use the options under the Format tab to format the text as Tahoma, bold, and size 22 pt.

We will now insert a smaller inset map into our layout to show the geographic context of Prince Edward Island. To add this inset map, 

  • Under the Insert tab and the Map Frames group, change the shape from Rectangle to Circle
  • Click the Map Frame dropdown, click Default Extent, and click and drag it into place above PEI in the Gulf of St. Lawrence. 
  • Activate the inset map, and then drag and zoom (with your mouse wheel) until the area around Atlantic Canada and New England is shown. Make sure to click Close Activation before proceeding.
  • Under the Insert tab, click Extent Indicator and click Map Frame. 
    • In the inset map, a rectangle will appear around Prince Edward Island.
  • Once you have added the Extent Indicator rectangle, click Format and change its Line colour to Poinsettia Red and the Line width to 2 pt.

We will also edit our layout so that the credits for the base maps used in the main map frame and the inset map frame are not shown twice. 

  • Ensure no elements of the layout are selected.
  • Under the Insert tab and in the Text group, click the Dynamic Text dropdown menu.
  • Under Layout, click Service Layer Credits
  • Draw a small text box for the Service Layer Credits in the top-right of the main map frame, between the Magdalen Islands and Cape Breton. 
  • Highlight the text of the Service Layer Credits and, under the Format tab, type in a text size of 6 pt.

Your layout should now look something like the one in this screenshot:

Exporting the Layout

When you have completed adding your map frame and metadata to your layout, you can print the layout or export it as a digital image file. 

To print your layout, 

  • Under the Share tab and in the Print group, click Layout.

To export your layout as a digital image file, 

  • Under the Share tab and in the Export group, click Layout
  • In the Export pane to the right, 
    • change the File Type to PNG
    • Change the Name to C:\Users\<username>\ArcGIS\ArcGIS_Lesson1\OutputMaps\PEI_1971_Layout.png
    • Click Export

Take note of the fact that the guidelines are not included in the exported PNG image file.

For more information about creating layouts, visit this article on the ArcGIS Pro website, upon which this section of this guide was based.

Step 8: Exploring Historical Change between 1971 and 1911

Key Concept: a key element of Historical GIS is showing change over time, but this is not something we can accomplish with one thematic map. To show changes in time, we can create a sequence of thematic maps that show the same attributes mapped at different dates. To be accurate, the sequence of maps must all have the same scale, legend (e.g., class breaks for choropleth maps), and colour scheme.

We have access to the 1911 Canadian Census of Agriculture data for PEI. Although some differences exist between the attributes contained in the 1911 census versus the 1971 census, we can pick an attribute that is contained in both and map it for each year. Let’s create another choropleth map; this time we will chart the amount of land dedicated to potato production in 1911 so that we can see how it was different from 1971.

Mapping PEI’s 1911 Agricultural Census Data

To create this choropleth map using PEI’s 1911 Census of Agriculture data, we will begin by repeating elements of steps 1 through 4:

  • In our PEI 1971 project file, click Project and then  Save As. Name this new file as PEI 1971 and 1911 and save it in the ArcGIS_Lesson1\ProjectFiles\PEI 1971 folder.
    • This new copy of our project will reference data in all of the same locations as our original project file, so we need to save it in the PEI 1971 folder.
  • To find the 1911 spatial data for this new copy of the project, repeat the process from step 2. This time, however, download the file called Boundary Files, 1911 Census of Canada (produced by Canadian Century Research Infrastructure) from Scholars GeoPortal. Make sure to download the Census Subdivisions layer, and then add it to ArcGIS Pro.
  • Add to our new project the attribute data from the 1911 Census of Agriculture, which comes in the zipped folder downloaded at the beginning of this lesson. The attribute data is located in the ArcGIS_Lesson1\AttributeData folder. Go to CSD_PE_1911.xlsx and then double-click PEI Data 1911$ to add it to the project.
  • Join the 1911 attribute data to the 1911 spatial data using the unique ID field called UID_CSD_11. Because the attribute data only pertains to PEI, be sure to uncheck “Keep All Target Features” when completing the join process. 
  • When making the join permanent, set the Output Location to PEI 1971.gdb and, in the Output Feature Class field, type CANADA_CSD_1911_JOIN_CENSUS. After making the join permanent, feel free to Remove the original CANADA_CSD_1911_MW and PEI Data 1911$ layers.

Symbolizing the 1911 Map Data

For step 5 (i.e., “Symbolizing Attribute Data”), we will import the symbology class breaks from the 1971 map to the 1911 map.

  • Select CANADA_CSD_1911_JOIN_CENSUS in the Table of Contents
  • Under the Appearance tab, and in the Drawing group, click Import
  • In the Apply Symbology From Layer pane to the right, input the following:
    • Input layer: CANADA_CSD_1911_JOIN_CENSUS
    • Symbology layer: Prince Edward Island, 1971
    • Under Symbology Fields, enter:
      • Type: Value field
      • Source field: POTATS
      • Target field: POT_XH_A
    • Click the “+” (Add New) button to add another Symbology Field. In the second Symbology Field, input the following:
      • Type: Normalization field
      • Source field: CRPLND
      • Target field: CRP_XX_A
    • Under Update Symbology Ranges by Data, choose Maintain ranges.
  • Click Run.
Importing symbology settings from the 1971 map to the 1911 map.

Once the Apply Symbology From Layer process is complete, 

  • Drag the CANADA_CSD_1911_JOIN_CENSUS layer beneath the Soil Landscapes of Canada layer and above the Prince Edward Island, 1971 layer in the Table of Contents.

Comparing 1911 to 1971 to Answer Descriptive and Analytical Questions

Now, the class breaks are identical between the maps containing 1971 and 1911 attribute data, allowing for accurate comparison of the 1971 and 1911 maps. As a descriptive question, we could ask: What differences existed between the amount of land dedicated to potato production in 1911 versus 1971? 

  • Toggle on the Soil Landscapes of Canada layer. 

Because soil types take centuries to change, the Soil Landscapes of Canada data will be accurate for both our 1971 and 1911 data. With the Soil Landscapes of Canada layer turned on, consider the following: Did the areas that dedicated a lot of cropland to potato production in 1911 remain the same ones that did so in 1971? If so, perhaps we have further indication that their soil type is the best suited to growing potatoes on Prince Edward Island. We thus have more evidence with which to address the analytical questions posed in step 6 above, namely: Did some townships have soil that was better suited to growing potatoes?

Step 9: Further Exploring PEI’s 1971 and 1911 Agricultural Data

Now that you know how to symbolize attribute data to answer historical questions and how to export the maps you create, it is time for you to explore other aspects of PEI’s agricultural data from 1971 and 1911.

Create a Copy of Your Project

Before you start the exploration process, however, it may be a good idea to create another copy of your project so that you do not overwrite the steps you have taken so far. 

  • Click Project and then Save As
  • Name your file and save it in the ArcGIS_Lesson1\ProjectFiles\PEI 1971 folder.
    • Each time you are ready to explore a new question, start by creating a copy of your project in this folder.

Further Explore

Because we have already added and joined PEI’s spatial and attribute data for 1971 and 1911, you can skip steps 1 through 4. Repeat the processes described in steps 5 and 6 to explore your own historical questions using not only PEI’s Census of Agriculture data from 1911 and 1971, but also the soil landscape data. There are many different attributes contained in the 1971 and 1911 datasets. Try to map different elements, and see if you can find the symbolization settings that present your mapped data most accurately. Make sure to use step 8 to import the symbology setting from the 1971 layer to the 1911 layer, or vice versa. Once you have completed the symbolization process, try exporting your map as a layout, as described in step 7.

Step 10: Exploring Other Data from the 1911 Canadian Census

The map we added in step 8 charts all of Canada as it existed in 1911. In that step, we used PEI-specific attribute data from the 1911 Census of Agriculture. Attribute data pertaining to the whole country from the regular, non-agricultural 1911 Canadian census is available at the Canadian Century Research Infrastructure (CCRI) website. The CCRI site offers Excel files containing census data on the number of Canadians in 1911, as well as their conjugal condition, religions, origins, and literacy rates.

Creating a New Project; Adding and Analyzing Data

To explore this Canada-wide attribute data from 1911, 

  • Start a new project file in the ArcGIS_Lesson1\ProjectFiles folder. Name your project Canada 1911. (See step 1.)
  • Add the 1911 Canadian spatial data, which is still in your ArcGIS_Lesson1\SpatialData folder. (See step 2.)
  • Download an Excel file from the CCRI site and save it to ArcGIS_Lesson1\AttributeData.
    • On the linked CCRI site, the type of attribute data contained in each Excel is shown beside the word “Title.”
    • There are two files that you can download for each type of attribute data. The download link to the Excel is listed first, and listed second is a link to a PDF that explains the variables used in the Excel.
  • Add the Excel file you just downloaded to your project. (See step 3.)
  • Join the spatial data and attribute data. (See step 4.)
    • The Input Join Field will be UID_CSD_11. Depending on which Excel you download from CCRI, the Output Join Field will be some variant of “V1T1_1911.The numbers after the V and the T may change, but the “_1911” part will remain the same.
    • This time, because we have attribute data for the entire country of Canada, we want to check the box called “Keep All Target Features.”
  • Make the join permanent. (See step 4.)

You are now ready to explore historical questions by symbolizing the attribute data (see step 5). You can also export your results as a layout (see step 7).

Arc 5: Map Design with ArcGIS


This exercise has three goals:  1) to review and reinforce GIS skill learned so far; 2) to put some of the design and symbolization principles from Monmonier’s Mapping it Out into practice; and 3) to learn how to create a map layout for print or export.

The example included here address how much and where land was plowed for crops in the 1930s.  It brings together maps based on two distinct spatial primary sources:  the 1935 Agricultural Census and a set of digitized aerial photos taken in Weld County, Colorado in 1938.


  1. Add data

All data are in the Workshop 5 folder.  For this exercise we’ll use two of the same datasets as in the previous Overlay Excercise.

  1. From the Design1.gdb geodatabase add the following polygon layers:
  • Weld_1930s (land use polygons digitized from a sample of 1938 air photos—8 cells of 9 square miles each)
  • AgCensus_1935 (land use attributes from the 1935 agricultural census for all Great Plains counties)
  1. Save your project by clicking the Save button, navigating to your Workshop 5 folder, and assigning an appropriate name. This will create a single file with the extension .mxd. Most of the finished maps you create for final output in ArcMap will be saved with an .mxd extension.  Each time you want to change a map design, you should immediately save it as an .mxd file with a new name, using the Save or Save As commands.  Today, you should click Save about every 10 minutes or so as you go along.
  1. Explore data
  1. Locate the small air photo polygons in relation to the much larger county map. Look at the attribute tables for the 2 polygon layers in order to understand the information they contain. For the AgCensus_1935 layer you can refer to 04254-0009-Codebook.pdf for variable descriptions.  Keep in mind the two very different scales represented by these two datasets.

III. Sybmolize data

  1. Make a map showing the amount of cropland in each county of the Great Plains. The best attribute for this map is CRP_XK_A. For the county-level AgCensus_1935 layer, choose an appropriate symbolization scheme.   (You may need to refer to Workshop I:  Mapping Great Plains Agriculture section V. Sybolize attribute data to refresh your memory.)  To start, right click on the AgCensus_1935 layer name in the Table of Contents and go to Properties and then the Sybmology tab.  For this map, the Quantities, Graduated colors options are most appropriate.  You’ll need to set the Value field to CRP_XK_A, select a color ramp you like, and choose a number of classes (then click Classify to determine the range of each class).  The result should be a map of counties in which those with the most cropland are darkest in color, and those with little cropland are lightest in color.
  1. Now zoom in to the Weld_1930s aerial photo layer, and sybmolize this map to show the locations of cropland in each cell. Again, you’ll right click on the Weld_1930s layer name in the Table of Contents, then select Properties and the Symbology tab. This time you’ll select Categories, Unique values.  Set the Value Field to Land_cover and click the Add All Values button below.  From this window you can set the color for each type of land cover identified from the air photos.  In this case we want to highlight the Cropland polygons only (perhaps using the same color as in your county map?), and set all other polygons to show a black outline with no fill.
  1. Separate layers into two data frames

Once you have both maps designed to your satisfaction, you’ll have to confront the fact that it will be very difficult to present these two maps at the same scale, since one covers only a small part of a single county and the other covers more than 1000 counties.  If you zoom the map so that one is visible, the other becomes hopelessly obsured.

One solution is to present the maps at two different scales on your layout.  In cartography, this approach is called an “inset map” or a “locator map.”

  1. So far in this class we’ve only employed one data frame, which in the Table of Contents is called Layers. Now it is time to branch out. Go to Insert and select New Data Frame.  Notice that in the Table of Contents the label New Data Frame has appeared in bold, and your maps have disappeared from the map window.  Right click on Layers and select Activate:  it becomes bold, New Data Frame is no longer bold, and your maps have reappeared.  In Data View, you can only see and work with one data frame at a time.

You can create as many data frames as you want, and when you Add Data to insert layers, the new maps, tables, or images will appear only in the currently active data frame (although it is easy to then drag them to other data frames if you want the same map in more than one).

  1. Rename the two data frames. Right click on Layers, select Properties, and then the General tab. Change the Name to read “Weld County Cropland.”  Now do the same to change the name of New Data Frame to read “Great Plains Cropland.”
  1. Click on the AgCensus_1935 layer and drag it down to the Great Plains Cropland data frame. A duplicate map layer appears with all of your symbolization intact. We don’t need the original any more, so right click on the original AgCensus_1935 layer and select Remove to delete it from the Weld County Cropland data frame.
  1. Zoom to the full extent of both maps. Activate Weld County Cropland then click the Zoom to Full Extent button. Activate the other data frame and do the same.

You’ve now put your two maps in separate data frames, and selected a scale that is appropiate to each.  Great—but now you can no longer view the two maps at the same time.  Because we are working in Data View, we can only deal with one data frame and scale at a time.

  1. Create a layout
  1. Now it is time to discover a section of ArcMap we haven’t dealt with yet: the Layout View. So far, all of our exercizes have taken place in Data View, which is the nuts-and-bolts mechanical part of ArcMap, where the interesting GIS analysis and basic symbolization takes place.  But once the hard core analysis is done and the map is symbolized to your satisfaction, we need more artistic options, and that’s where Layout View comes in.


Look in the map window section of the ArcMap interface, and go down to the bottom left corner.  Two tiny icons to the left of the scroll bar allow you to toggle between Data View and Layout View.  First, hold your mouse over each to confirm that you’ve found the right buttons—they’re not easy to spot.  Then click on Layout View.


Now you see a mocked-up page with your two maps both visible, though probably not where you want them to appear.  Layout View mimicks graphics programs like Adobe Illustrator (although with many fewer functions), so you might find commands that are familiar from that environment.  Here you can do the final design for an output map.


Key concept:  Complete all analysis and map symbolization in Data View before you start working in Layout View.  Going back later to change color choices, data categories, or the scale will often create havoc in Layout View, requiring re-working your final map design.  After years of heartache, take this advice from a grizzled veteran!


Note:  the program defaults to a Portrait layout, but you can change to Landscape if you like.  It also defaults to an 8.5 x 11 inch page size, but this can be re-set.  Make both changes by going to File and selecting Page and Print Setup.


  1. Click on each map to highlight its window, which can be dragged to a new location or resized by clicking on an anchor around the outside. Arrange the 2 maps as you like on the page. If you think that the Weld_1930s maps are still too hard to see, you could consider going back into Data View and zooming in on only one of the cells.  Then you would come back to Layout View to complete the map.


  1. From the Insert menu, insert each of the following map elements. In each case, use your own design sensibilities to choose from among the many options offered.


  • Title (create one)
  • Scale bar (one for each map, since they are at different scales)
  • Text box (in which you should identify the map author and date)
  • North arrow
  • Legend (one for each map, unless you used the same colors for both)


You can drag these elements into correct position, resize them, and format text (double click on the element, click the Text tab, and click Change Symbol) as you like.  If you don’t like the outcome, just select the element, hit delete, and start again.


Warning:  While it is very helpful to zoom in and out on the page and pan around as you do the design work, be careful to use only the zoom and pan buttons for the Page View (and not the very similar buttons connected to Data View).



  1. Generate a final map


  1. Once you are satisfied with your map layout, you can create two kinds of output. First, print a hard copy, by going to File and selecting Print. In order to get full color, send it to HP Color LaserJet CP4005 PCL6, which is the color laser printer in Kirk 213.


  1. Then export a .jpg file of your map, which could be used to post to a web site or to insert into a word document. Go to File and select Export Map. From the dialog box, set Save as Type to JPEG.  Here you can also adjust the resolution if you like (many publishers specifiy 300 dpi for print graphics, while web designers like 150 dpi or even lower for online purposes).  You can save the file to your Workshop 5 folder, then copy and paste it into a Word document.

Using Google Earth as an entry into basic GIS

By Daniel Macfarlane and Jim Clifford
From the Otter.
In the first installation of this series, we discussed how to use basic Google Maps to create a custom map. You might be surprised to know that, in doing so, you are actually doing GIS mapping (Global Information System – basically, GIS involves merging of cartography, statistical analysis and database technology). I’ll admit I didn’t know that. I asked how I could turn my custom map into a GIS map; Jim told me I already had. So if you have used the custom maps function provided by Google, you are already using a basic form of GIS mapping!

In this installation, we will discuss Google Earth, another free and easy option for creating a basic GIS database. Using Google Earth we created a multi-dimensional form of Dan’s original St. Lawrence Seaway and Power Project map.

Converting a custom Google Map to Google Earth is very easy: on the top of a custom map, just click on “View in Google Earth.” A prompt will ask whether you want to open or download the file. Unlike a custom map, which remains stored and saved online, a Google Earth map can be downloaded to your desktop (You can download Dan’s map. You’ll need a copy of Google Earth first, which is free).

Within a few seconds, you will be looking at your initial map in a three-dimensional space in Google Earth. All the same landmarks and such you already created will still be there. You now have a variety of options. For example, you can now tilt so that you are looking at the earth from an angle, rather than from straight above (like Google Maps, one has the option of “Street View” which simulates the map’s appearance form the perspective of someone standing in front of a landmark). This is a particularly effective way of following the seaway route – start at one end, and go along from about a 45 degree angle.

Google Earth is a good place to start, as it is effectively GIS-lite software. It provides the option to create custom lines, polygons and points (see the buttons along the top of the map). In GIS these shapes are collectively know as “vectors” and they are one of the main ways we represent geographic features in historical GIS. We trace the roads or railways of old maps using lines, the outlines of building or agricultural fields using polygons and identify particular places or things using points. Google Earth also allows you to attach descriptions to these lines, polygons and points. In the map below, (download sample here) we’ve added descriptions to a few geographic features of Toronto. This is another key functionality of GIS, the ability to link spatial data with other forms of data. Google Earth limits you to names and basic descriptions and does not allow you to link statistical data or dates, but it still provides a lot of opportunity to build a historical GIS database of the landscape you study.

Toronto Waterfront GIS

There is a Historical Imagery” option which will be especially appealing for environmental historians and geographers; however, it is limited to what Google has inn its database (which in the case of the St. Lawrence Valley, only goes back to 1997). In the region Jim studies, the Lower Lea Valley in East London, Google Earth has a 1945 aerial map.


Another options is “layers”: a huge collection of GIS data included with Google Earth. You’ll find these layers located along the sidebar, you have the choice of adding thousands of provided options. Take if from us, you don’t want to turn these all on at the same time, or you will be faced with an overwhelming and jumbled map. These include normal features such as labels, places, roads, pictures, etc., but also allow NASA, National Geographic, etc. These are effectively GIS layers provided by Google and partner organizations and the process of creating maps by adding and removing various layer options will prepare you for how more complex GIS software functions.

The most useful for historical research and teaching is the David Rumsey Historical Maps collection (found under the gallery tab) that includes dozens of historical maps “pined” onto their location on the digital globe. However, the user is limited to what is already provided and creating more layers, historical imagery, and such that are specific to one’s project requires the use of more specific GIS software, which will be the subject of the next series of post. There are a lot of options for the United States, but the options for Canada are a bit sparse.


In the meantime, if you are a student, staff or faculty member at a university you should ask your map librarian for a trial copy of ArcGIS and/or download and install Quantum GIS (a less powerful, but free, open source GIS package).

Learning GIS: A Google Seaway Map

By Dan Macfarlane and Jim Clifford
From the Otter.

This is the first of series exploring my metamorphosis, under the tutelage of Jim Clifford, from a digital mapping neophyte to a master mapper … or, to appropriate a title from quintessential Cold War film, this could be called “Dr. Macfarlane or: How I Learned to Stop Worrying and Love GIS Maps.”

I did my dissertation on the history of the St. Lawrence Seaway and Power Project and, as one might expect, encountered a great deal of maps and engineering studies along the way. I wished I could somehow usefully bring together or juxtapose all this spatial and geographical information, not only for my own benefit but for others who might be interested. I had used Google Maps many times, albeit for run-of-the-mill purposes, and had even made a few custom maps (e.g. to give directions to guests at our wedding) but the type of a multi-layered and interactive mapping I envisioned for my St. Lawrence research seemed well beyond my capabilities. Throw in the demands of a new baby and a dissertation to finish, and the idea was effectively shelved.

But as I saw others in NiCHE producing excellent GIS mapping projects, I kept wondering if I could do it. With some down time after my defence I randomly opened Google Maps one afternoon and started exploring the custom maps feature. Pretty soon I had marked off the main seaway channel, and quickly found that I could use anchors and signs to designate key points of interests and different features.

Over the following few days, I came back to this custom map when I had a few moments, and began to add text, maps, and pictures to the various points of interest. Then I started tracking the lines of older canals which the seaway had replaced. In just a few combined hours, I had essentially produced the map you see in this posting. I conversed with Jim and Sean Kheraj about the map, and they gave me encouragement and advice (such as viewing this map in Google Earth, which will be the subject of the next posting in this series).

The whole process was quick and user-friendly, and done from my couch with various football and hockey games going on in the background. I am most certainly no computer expert – when someone refers to java script I’m hoping they are going to serve me a cappuccino. I had taken a first-year computer science course over a decade ago but if I remember correctly, the major assignment was creating a website for a virtual golf course. And I forgot everything I had learned in that class anyway – I just remember typing a bunch of 0s and 1s. Bottom line: if you are computer literate enough to be reading this post, you can probably create a custom Google map.

In the next post we will show you how to make a map like Dan’s Seaway Map and explore how to view this map in Google Earth.

GIS and Time

By Jim Clifford

From the Otter.

One of the major weaknesses in using GIS for historical research are the limitations in showing change over time. GIS was designed with geography in mind and until recently historians needed to adapt the technology to meet our needs.

Generally this meant creating a series of maps to show change overtime or as Dan MacFarlane did last week, include labels identifying how different layers represent different time periods (see MacFarlane Map2). More recently, ArcGIS and Quantum GIS introduced features to recognize a time field in data and make it possible to include a time-line slider bar or animate the time series data in a video.

UK Tallow Imports, 1865-1904 from Jim Clifford on Vimeo.

I am currently studying the sources of raw material imported into Britain during the nineteenth century as a way to connect the environmental consequences of manufacturing in London with the ecological transformations taking place in other parts of the world. One of the first industries I’m studying is soap making. These factories relied on an increasingly global supply of fat (tallow, palm oil, coconut oil, and cottonseed oil), potash, essential (i.e. fragrant) oils, and pine resin. As a part of this research I’ve started a small database tracing the source of some of these products. Tallow is particularly interesting, as the Russians dominated the trade through to the 1860s, when large herds of cattle and sheep raised on American and Australasia grasslands drove down the price of tallow and led to the collapse of Russian exports to the UK. The most obvious way to visualize this data is to make a graph using the features included in Excel.


I also experimented, using a slightly different dataset, with the Source Map platform, to create a series of maps showing change over time. These maps visualize the changing geography of Britain’s tallow supply, but it would be impractical to create or present fifty maps, so they only work to show the general trend using averaged data from three years in the middle of the decades:

British Tallow Imports 1864-1866(Total imports: £2,737,000)

British Tallow Imports 1874-1876 (Total imports: £2,407,000)

I wanted to see how I could best represent this data in GIS and I also wanted to learn the new time functions in ArcGIS. The result is the video (above), showing the changing source of tallow, based on quantity, from 1865 through to 1904. The advantage of this time series video is that it shows the volatility of Britain’s tallow supply, with significant booms and busts from each of the regions. Whether this particular animated map provides any insight not available from the Excel graph is up for debate, but the method might become essential as we create significantly larger text mined datasets in the Trading Consequence project.

For readers familiar with ArcGIS and who have a copy of version 10, I’ve include the Data File. QGIS has an experimental add-on called Time Manager, but it might not function properly for the nineteenth century yet. We will try and develop a lesson for this feature in the future, but for now I’ll provide instructions for people with copies of ArcGIS. The hardest part of the process was rearranging my data into a format that would work with the ArcGIS time function. First of all, the dates need to be listed in a column, not across the top row. It is possible to cut and past using Excel and switch your rows with your columns, by right clicking and using the “Special Paste” options. Don’t use “Date” as the field name as this might confuse the database. I’ve used “t” instead and included a simple list of years from 1865-1904 (the dates repeat for each location). The other fields I include are the quantity of tallow, a code for the geographic location and the latitude and longitude of where I want the quantities represented on the map.

Screenshot from 2012-12-17 11:45:49

You can use a spreadsheet program, like Excel, to manipulate this data, but I generally find it is best to save it as a CSV file before importing it into ArcGIS. Once you have a CSV file (or once you’ve downloaded my tallow_xy.csv file below), you can launch ArcGIS. It would be possible, and perhaps preferable, to create a database table for each location and avoid repeating the dates over and over again for each location, but that would make it more complicated.

Once you launch ArcGIS 10 you can import the CSV using the import XY data option. It should automatically identify the fields called x and y as the spatial data. It will then instruct you to export the data so the program will add a unique identifier number (making it a part of your database). Right click on the layer and chose Export Data. It will then give you the option to add this new layer to the map. If you are using my sample data, I would suggest choosing a simple world map as the base layer. The next step is to tell ArcGIS which field includes the time data. Double click on the layer and find the Time tab in the preferences menu. Choose “t” as the time field and if you click “calculate” it should give you the time range of 1865 to 1904. Do not click the “Display data cumulatively” check box. Next you will need to change the symbology of the layer to display the points as circles that represent the quantity of tallow from each place. I used proportional symbols, but you could also choose graduated symbols. Finally, you need to find the time slider menu button (it has a little clock face). Enable the time slider and it should allow you to slide through the years or click play to see an animation similar to the video above (play with the setting to slow down the animation).

Data File

The Geospatial Historian: Part 1, Niagara Falls

By Dan Macfarlane

From the Otter.

The modules are designed similar to Programming Historian lessons, and will potentially be offered there as well. After getting the necessary software that allowed me to run ArcGIS 10 on my Mac, taking online training modules made available for free through the Carleton University library, and collaborating with Jim and Josh, I have been available to develop these skills beyond what appeared in my original posts. What follows is the first of a series of examples of what will appear in our hands-on learning modules on using historical GIS.

The two maps contained in this post are both of Niagara Falls, and are part of my ongoing research about the engineering of the Niagara Falls hydro-electric landscape – basically, showing how Niagara Falls borders on the artificial – to the point that one would be tempted to say that the waterfall is little more than an elaborate faucet – because it has been so manipulated by Canada and the U.S. to produce hydro power and the effect on the actual cataract.

I’m writing a book on this subject, but for those who are curious and don’t want to wait several years for the book to be done, I have a chapter on Niagara in the upcoming environmental histories of southern Ontario collection that will coincide with ASEH Toronto (in fact, I’m co-leading a tour to Niagara as part of the conference) and I have an article on the topic forthcoming in the journal Environmental History. And for those who don’t want to wait several more months, see a blog post I did earlier this year on

Back to the mapping. For the first map (Hydro-electric Landscape of Niagara Falls) the initial step was finding the right base maps and layers (a base map is akin to a background image on which you do your digital mapping – in this case the base map is a Google Earth picture). I wasn’t entirely sure what I was looking for, but I knew that I wanted to create a map of the hydro-electric landscape of Niagara Falls. I scoured the internet for appropriate base maps of Niagara Falls, both present and historic. I also searched for aerial photos, which are sometimes used as base maps. In an Otter post earlier this year Josh gave useful tips on places to look for map data.

I used a .jpg of map from Canadian Geographic as a raster image, which are common to use as base maps (there are two main types of data/image: vectors, which are essentially made up of points, lines and polygons, and raster images, which like any digital image are made up of pixels on a grid), and then matched it up with an aerial photo using georeferencing (which I’ll explain a bit further down). At first I attempted a straight-above aerial view without any raster image – so that the different features you see in the final map were all on a white background. So after some quasi-successful starts, and going back for help to the various ArcGIS education resources I had at my disposal, I had made some headway.

The simplicity and non-cluttered effect of the blank background had some advantages, but I wanted a different angle as well as a representation of the surrounding communities geographic features, such as the water. I downloaded a map from Google Earth at an oblique angle to use as a base map, which is what you see in this post, and set out to georeference and digitize the Canadian Geographic map.

Georeferencing involves creating control points so that the software will match up the maps, as maps of the same area don’t necessary line up perfectly (some maps of the same features will be to such different dimensions and proportions that it won’t be possible to match them up without extreme distortion). So I put control points at Horseshoe Falls, Goat Island, Lake Ontario, Grand Island, various older hydro stations – and kept adding control points until the maps lined up.

Then I started digitizing features. Digitizing features really just means any type of drawing, tracing, or creating of something on a new layer as a digital vector (i.e. a point, line, or polygon). So the hydro station, the tunnels, the outline of the reservoirs are all digitized information that I created via the drawing feature on ArcGIS 10. An easy aid for doing this is to adjust the transparency on one of the two stacked maps so that you can see them both at the same time for tracing purposes.

All this of talk of layers might have you wondering what a layer is. Think of layers as transparencies on the overhead projectors your teacher might have used in elementary or high school. Each feature – be it road or a type of building or a type of tree – that you create is done on a new layer; thus, the information is independent of the other types of information, and you can add or remove it as you wish

To digitize vectors as a point line or polygon, one has to decide which best represents the real world feature. For representing cities on a world wide map, a point would be a good idea; but to represent the limits of that city in a zoomed-in view, a polygon would be useful. If we were looking at a map of North America, the Niagara River would be best represented with a line; but if we are looking at a close-up of the river, such as in the post, a polygon of the river’s shape would more effectively show its shape.

In the map you see here, the canals, conduits, and tunnels are line features, while the power stations and reservoirs are polygons (transparent on the inside to show the features in the base map, below). I didn’t actually use a polygon for the actual river and waterfalls, as I found that the the base map better illustrates those.

Adding labels was fairly straightforward, and it was relatively easy to shape text labels around certain features (e.g. running parallel to tunnels). For other features, there is an indicator line from the label text to the feature – this is a “call-out” line.

The second map (Modifications of Horseshoe Falls) shows the fill and excavations that were done in the 1950s, while the former crestlines indicate the amount of recession that has taken place. Because it used mostly the same approach and skills, as well as similar types of data (photographs and blueprints), I had used in creating Map 1, I completed this map much quicker.

Horseshoe Falls

There you have it. Nothing too complex compared to the kind of stuff GIS can do – in fact, what I was doing was mostly cartographic map-making rather than using the full abilities of the software to compute numbers and create new information (for example, the information in Map 2 could be used to measure the amount of feet the crestline has receded, or the amount of square feet that were reclaimed from the waterfall at the flanks). But I also found what I created quite useful for representing spatially what I was writing about in my research, and thus this is the type of end product that is within the reach of historians with a general competence around computers. Each map would benefit from further work, such as having a table of contents to better explain features, but I haven’t had time for that yet … after all, who knows what inane trend I’ve been missing while writing this post.