Tasks

Reading

Read the first chapter (4 pages) in Mark Monmonier’s book, How to Lie with Maps.

Find four locations

Maps are unique among visual media formats in that they attempt to show the location of things on the planet in relationship to each other. Because maps can be so useful, we often accept them as truthful representations. But, we’ll discover that all maps lie in some way, and they have to, otherwise maps become unusable.

One of the ways that maps lie is by omission. Whether by author or algorithm, a map shows a only small, curated selection of what actually exists. This selection begs the questions, “Why show me this but not that? What is the intention of this map?”

Deliverables

To complete this task, use your favorite map(s) and explore Lexington and the UK campus. Do not go outside of New Circle Road (look on a map 😊 if you’re not familiar with Lexington).

Please follow these requirements for this task:

1. Find four places that should be on your map, but are not – or not labeled or identified the way you think they should be. These are places that you find important, e.g., your favorite places to enjoy a quiet walk, play pinball, do parkour, etc. You may or may not want to use these locations in the following lab component of the module.
2. Provide brief responses to the following prompts:
   • Provide a name for each location. Why is this place important to you?
   • What map(s) did you use?
   • Why do you think these locations are not on the map(s) you chose to use?

This task is worth 2 pts (4 locations @ 0.5 pts each).

Submitting the task

Provide a text submission to the Module 1 Task on Canvas by the published due date.

Lab

In this lab we will explore how to take observations of places we find important and encode them into a data format that can be stored, shared, and mapped. We will discover that we can locate any place on the planet with two numbers – an elegant and powerful concept. We will then visualize this data and explore our primary mapping application, QGIS.

Table of Contents

• Introduction
• Owning your data
  • Creating your local workspace
• Downloading remote files
• Viewing and editing spatial data
  • Creating new features
• Visualizing the data
• Assignment
  • Video tutorial (12 min)
  • Deliverables
  • Submitting the assignment
• Addendum: Making a quick visualization in QGIS
  • Adding a CSV layer in QGIS
  • Addendum video tutorial (8 min)

Introduction

Without data, we wouldn’t have much to show on a map. Let’s first loosely define data as observations encoded into a format that can be stored and shared. An observation might be made from a satellite above Earth taking photographs or a surveyor on the ground measuring the location of a property boundary. The format might be a photograph or a database and the it might be shared in a report or in a map.

Let’s think about the observations of our surroundings that reside in our memory. We can make a map of these memories and perhaps you have scribbled an impromtu map for a lost tourist. Geographers call it a mental map and it can show our perceptions of place. Here are two hand-drawn examples from UKy students.

Jessica’s Recreational Space

The Arboretum in Lexington, Kentucky

Both images show the hallmarks of a classic map; a depiction of where things (the observations) are related to one another, a title that describes the theme, a legend that explains the symbols, and a scale that shows the relationship between the map and the real world.

However, we see notable differences in how the mapmakers see their world. Jessica shows a dangerous area to northwest and the scale is applied only to driving distances, her primary mode of transportation. The Arboretum map uses a grid to more precisely locate and measure things – indeed, a goal of many maps – and the color shading attempts to show relative elevations.

Let’s examine Angelique’s ‘map’ of campus. First, can we accept this as a map without a scale or legend?

Angelique’s Daily Route

Because there is only one place on the planet where these observations could be made, we can accept this is a map. More importantly, this image exposes the DNA of all maps – the are they mapmaker’s story of place. Angelique sees her world as a loop through eat, study, class, and sleep. You might appreciate this view of the world.

These examples are creative works in that they are drawings of the author’s imagination (made from multiple, disconnected observations). Hand drawn maps today are prized historical artifacts with a rich aesthetic tradition. Modern mapmakers have the benefit of computers and software to create their maps, but they are still products of an imagination that select which observations to include and which to leave out. This decision is guided by the story that wants to be told.

OK, imagination is cool, but we don’t have access to the underlying data. The original observations are embedded in the memory of the mapmaker. And, would we want to solely rely on memory to create our maps?

Let’s now explore how we can create, manage, and share exact copies of our observations. This is the basis of modern digital mapmaking.

Owning your data

The prime benefit of creating data is that you own it. You decide how and to whom you share your data. You can even sell it.

Question: Have you ever downloaded something from the internet and then couldn’t find it? “Where did it go?” It’s so frustrating! Another dimension of owning your data is being able to access the data on your device or computer. Part of this lab is cultivating good data hygiene where we proactively organize data and projects on our computers.

OK, let’s fire up our personal desktop computers (PC), either in the lab or on your personal computer, and get started.

Creating your local workspace

A local workspace is simply a directory on your computer that is dedicated to mapping. Everything you make in this course should live inside this workspace. The lab computers use the Windows operating system (OS), but you can use your personal computer if you prefer a different OS, e.g., macOS.

There are a few ways to do this, but try Right-clicking an empty space in the window and select New > Folder.

Create a workspace directory in your home directory on Windows

Create a workspace directory in your home directory on macOS

(Note: You should do these steps on any computer you intend to use for class.)

Right now, the folder is empty. Let’s add some spatial data.

Downloading remote files

The local computer is the one in front of you with a new, dedicated workspace for this lab. To get data, we often download it from a remote computer, one that we do not have physical access to and lives in the cloud (a.k.a. on someone else’s computer).

A remote file path is the location of a file on a remote computer. When we browse online, we’re using remote file paths to access files on remote computers. Often, we call these path URLs (uniform resource locator). Let’s consider this URL:

https://uky-gis.github.io/geo109/data/01/hello-world.csv

This path is unique among the billions of URLs online. Let’s break this URL down. The https:// tells the browser to use the secure hypertext transfer protocol when accessing this file, which verifies and encrypts our communications with the remote computer. The uky-gis.github.io is the remote computer’s domain name. The /geo109/data/01/ is the directory path to hello-world.csv, a comma-separated values (CSV) file that contains spatial data.

In order to download this file, we need to use a web browser.

You can use Windows File Explorer or macOS Finder to move the file.

Move data to your lab-01 folder on Windows

Move data to your lab-01 folder on macOS

Viewing and editing spatial data

Now, let’s open the file in a text editor. A text editor is an application that allows us to view and edit text files, including certain spatial data types. There are many text editors available, but we’ll use Visual Studio Code, a free and open source text editor from Microsoft. Download and install Visual Studio Code on your computer – it is also installed on the lab computers.

You should see something like this:

Viewing a CSV file

CSV files are one of the most common data formats to store spatial data. They are simple text files that can be read by almost any application. The file is a table with rows and columns. The first row is called the header and contains the names of the columns. The remaining rows are the records and contain the data. In this case, we have three columns and one record. When records represent geographical points, we often refer to them as features. This is a simple example of a tabular data type.

Let’s now examine the CSV format in some detail. Commas are special characters that separate columns, though other characters could be used instead, e.g., the tab or pipe | characters. The CSV can encode two types of values, numbers (quantities) and strings (sequences of characters).

How you type them in the CSV, defines their values. Numbers are not wrapped in quotes: 123.456. Strings are always wrapped in double quotes: "This is literally just a string of characters with a beginning and an end."

The first two columns are numbers representing the latitude and longitude of the point. Latitude measures the distance from the equator (0 degrees) and ranges from -90 to 90 degrees. Longitude measures the distance from the prime meridian in London, England (0 degrees) and ranges from -180 to 180 degrees. The third column is a string representing the name of the point.

So, where is this location? We see that the latitude is positive (northern hemisphere) and the longitude is negative (western hemisphere) – might we be in North America? Let’s use Google Maps to find out.

You should see something like this:

Viewing the locations in Google Maps

As we can see, the location is Whitehall Classroom Building.

Creating new features

Let’s create a new feature by adding a new record with a different location and name. Use Google Maps to explore campus and discover the latitude and longitude for a location.

What if we wanted to play video games, where would we go on campus? How about The Cornerstone:

Finding lat, lon in Google Maps

When we find a location on the map, click on the map to drop a marker. Then, right-click on the marker to display the latitude and longitude of the location. Click on the coordinates to copy them to the clipboard. Next past the latitude and longitude values into the CSV file and add a message for the location:

lat,lon,message
38.038093,-84.503872,"Geography, Y'all!"
38.041704,-84.504288, "One pinball machine @ The Cornerstone"

Note: The number of decimal places in the latitude and longitude values is important. The more decimal places, the more precise the location. The number of decimal places is called the precision of the value. For most data we use, 6 decimal places is adequate.

Ok, let’s add a few more video gaming parlors that are off campus:

lat,lon,message
38.038093,-84.503872,"Geography, Y'all!"
38.041704,-84.504288,"One pinball machine @ The Cornerstone"
38.053765,-84.486388,"Arcadium has Galaga!"
38.057173,-84.518648,"The Burl Arcade has multiple pinballs. Let's tilt 🤪"

We now have a file that we can share our favorite gaming locations with friends as simply as texting the content of the file. However, you might be saying, “I can just tell my friends to Google these locations.” That’s true, but what if we had locations that were not indexed by a search engine? For example, what if we wanted to share a favorite picnic spot or the best place to watch a sunset? Latitude and longitude is the most concise way to share a location anywhere on the planet. 🤯

Let’s now make a quick visualization of these locations in QGIS to verify that we have selected accurate locations.

After making some edits to the CSV file, save the file in Visual Studio Code, e.g., in the application menu, find File > Save.

Visualizing the data

GeoJSON.io is a simple web application that allows us to visualize our spatial data – and make changes in our CSV if needed. Let’s use this website to verify that our locations are correct.

Drag and drop the CSV file into the GeoJSON.io window

Do the points fall on your locations?

If the points are correctly located and attributed, you are ready to submit the assignment. Make sure to follow the lab deliverables below. If not, then make the necessary changes in VS Code (or another text editor) and re-check the CSV file to GeoJSON.io.

Assignment

A local organization called LexRex wants to create a map of the coolest places to visit and recreate in downtown Lexington. They are particularly interested in little-known, eclectic hidden gems. They don’t have any data and have asked you to help them locate four places.

In this assignment, you will create a CSV file containing the latitude, longitude, and a message describing the feature for the required four locations. Make sure you have worked through the lab documentation above before you start the assignment.

Video tutorial (12 min)

Deliverables

Please follow these requirements for the assignment:

1. Create a CSV file containing the latitude, longitude, and a message describing the feature for the required four locations. The locations and message you want to show are completely up to you – but try to have fun. No location should exist outside of New Circle Road. (4 points @ 1 point each)
2. Make sure the CSV is properly formatted. The field order and field names must be: lat,lon,message. For the feature’s message field value, make sure there is only one pair of double quotes around the message. For example, "This is a message". If you have extra double quotes, the CSV file will not load correctly. That means, you’ll need to figure out how to make a message for the feature that does not contain double quotes. (4 points @ 2 points each)
3. Name the file using lexrex and your linkblue name in the following format: lexrex-{linkblue}.csv and replace {linkblue} with your linkblue name. For example, if Taylor Swift made a submission, it might be: lexrex-TaySwi01.csv. (1 point)
4. You can use the hello-world.csv file as a template. But, make sure to delete the example data and replace it with your own data. (1 point)

Submitting the assignment

Upload your CSV file to the Module 1 assignment on Canvas by the published due date. After the submission deadline, we will have a friendly competition in lecture to see who and what is the center of cool in Lexington.

Good luck!

Addendum: Making a quick visualization in QGIS

Mapmaking is a rather complex endeavor and requires specialized software. We’ll use free and open source software (FOSS) applications to create our maps, which means that we can share our data with others and they can use the same software to view and edit it.

In this addendum to the lab, we’ll tiptoe into the world of QGIS, our main, open source mapping application. You’ll likely want to try this part in the lab, but you can also try it at home. QGIS is available for Windows, macOS, and Linux.

Find QGIS in the Start Menu on Windows or in the Applications folder on macOS. (Note: On macOS, the first time you launch QGIS, you need to right-click open.)

You should see something like this:

First view of QGIS

QGIS is a powerful application with many features, but we’ll only use a few of them in this lab. For now, let’s just get a feel for the application.

So, how do we do this? In the menu bar, select Project > New or click on the New Empty Project section in the start screen shown above. Let’s now add a basemap to our map. Basemaps are the background images that we see in maps. QGIS has a built-in basemap called OpenStreetMap, but we can add many others. In the Browser panel, right-click the XYZ Tiles name and select New Connection….

Add new XYZ tile connection

In the New XYZ Connection dialog, call the layer “Carto Voyager” and enter the following information for the URL:

http://basemaps.cartocdn.com/rastertiles/voyager/{z}/{x}/{y}{r}.png

Add Carto Voyager tiles

After you verify that you have entered the URL correctly, click OK. You should now see the new layer in the Browser > XYZ Tiles panel. Double-click the layer to add it to the map. You should now see something like this:

Adding new layer to the map

As we can see in this screen capture, we can add many base maps. We’ll find other sources to add over the semester.

Now, we need to add our CSV layer.

Adding a CSV layer in QGIS

When we add a text file that contains locations, we need to tell QGIS how to interpret the file. In our case, we need to tell QGIS that the file contains latitude and longitude values.

In the menu bar, select Layer > Add Layer > Add Delimited Text Layer…. In the Data Source Manager dialog, click the Browse button and navigate to the CSV file that we created earlier. You should see something like this:

Adding a CSV point layer

Aside from the file path for the CSV, make sure your settings match the screen capture above. Click Add (and then Close) and you should see the points appear on the map:

Viewing CSV point layer on the map

You now should have enough experience to move on the the assignment.

Addendum video tutorial (8 min)

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