Tag: Urban

Mapping Child Friendly City Initiatives in Canada and in the World using ArcGIS StoryMaps

Anastasiia Smirnova
SA8905 Geovis project, Fall 2022

Introduction

Through this project I wanted to gain and advance my skills in both storytelling and visualizing spatial data. Here you can learn more about my attempt of using ArcGIS StoryMaps to highlight the importance of including children in the urban planning agenda and to show the World- and Canada-wide spatial patterns of urban areas’ commitment to creating inclusive urban environments with children in mind.

I did it by mapping municipalities that are participating in UNICEF’s Child Friendly Cities Initiatives (CFCI), which aim to promote cities where the “ voices, needs, priorities and rights of children are an integral part of public policies, programs and decisions.”

Technology

I used ESRI’s ArcGIS Pro, Online Map Viewer and StoryMaps for my project. First, I used the desktop app (ArcGIS Pro) to import my data and create my initial maps. After that I uploaded the layers that I wanted to use as web layers to my ArcGIS account, and then I finalized them using ArcGIS online applications. I used the online map viewer to adjust symbology as necessary as was trying to figure out what worked better for each part of my story. It was easy to go back and forth between the Map Viewer and StoryMaps – to make the necessary changes, then to see how the updated maps work with the story, and then repeat these steps as needed. The Map viewer generally had the functionality I needed to change my map symbology and I did not have to go back to ArcGIS Pro too often to make modifications after I uploaded my layers online.

I liked the functionality of StoryMaps. I used the sidecar option to introduce my story, and for showing most of my maps. I find that this block type provides some of the most immersive experience while scrolling, so I used it for the parts of the story that I wanted to keep the reader’s attention on.

I found that the swipe option worked well for showing comparisons. In a regular map, it is often difficult to show all information you want without cluttering the map with too many layers and making the map unreadable. The swipe option can help solve this problem. As such, I used this function to show how many children did (not) live within the municipalities that were part of CFCI and therefore could (not) benefit from the initiative.

the map shows distribution of children and youth residences (on the left, yellow and red) and municipalities involved in CFCI (on the right, blue)

For inserting your maps to any blocks of StoryMaps, you can choose to either use your maps uploaded as images or insert the actual interactive online maps. While the image option has some benefits, such as more flexibility in styling the map and faster loading, the main benefit of inserting the actual online maps is interactivity. You can zoom in and out, search for a specific location, show/hide legend, learn more about each unit on the map and so on (as the creator of the story, you can edit and set restrictions of what readers can and cannot do with your online maps).

Since I wanted to keep my maps as simple visually as possible, I went with the second option. This way, if the reader wanted to learn more about my maps and the information they displayed, they could do so by using the interactive map functions.

Interesting findings

In addition to the main message of the project (the need to promote child friendly cities), the maps showed how the choice of data, scale and mapping methodology can influence the results and representation. On the CFCI website, the main map was showing all countries that were involved in the CFCI. The map did not consider how many municipalities in each country were actually involved in the initiatives.

The main map from the UNICEF CFCI website – CFCI countries

This way of displaying data may be misleading, since the level involvement of each country varied greatly. In some countries, most of the territory was part of CFCI, but some other countries only had a couple municipalities each with UNICEF’s child friendly initiatives.

For this story, in addition to the world CFCI country map similar to the one from the website, a proportional symbol map was created to show how many municipalities from each country were actually involved in the CFCI and I put these two maps in one sidecar block so that the reader could swipe back and forth to see how the distribution of CFCI changed with the change of the variable, and what the actual level of involvement if each country was.

A map from my StoryMap – Municipalities involved in CFCI

When zoomed in, even more information about the unevenness and clustering in the spatial distribution of the CFCI municipalities can be discovered.

The sidecar block (I used the float side by side option for my maps), and the smooth transitions it provided, worked well for showing the differences between the maps, as well as for zooming in into a smaller scale map.

Challenges

Some of the main challenges for me were associated with updating the maps if I wanted to change something. It took some time for me to figure out what could be done at which step of the process (with different apps) and how far back I had to go to modify something. As such I had trouble updating and modifying the legends for the maps.

Unfortunately, the options for adjusting the legends using the ArcStory editor or the online map viewer were limited. For instance, it was impossible to hide or edit the name of the column which contained data used in the map while using the online apps. Since I was creating my original layers in ArcGIS Pro, then uploading them as web layers, and then adjusting my maps further in the online map viewer, it was difficult to go back to change the original data in the end, just to modify one little line on the map legend. Only some parts of the legend could be modified using the online apps. So, one of the lessons I took from this experience is that you need to make sure all the column names are appropriate before making all the edits online if you are using a similar process as I did. It is also helpful to think about the legends right from the start.

Conclusion and results

In general, I am satisfied with the ArcGIS StoryMap platform. It was easy to use, and it did a good job of assisting me in creating a map-based story that looks clean and flows smoothly. I am planning on further exploring the StoryMap functionality in the future.

If you are interested in learning more about child friendly cities and seeing my StoryMap result, you can follow this link:

Canadian cities and towns for happy children (arcgis.com): Mapping Child Friendly City Initiatives in Canada and in the World using ArcGIS StoryMaps

A Glimpse of Short Term Rentals in Calgary Using Tableau

by Bryan Willis
Geovis Project Assignment @RyersonGeo, SA8905, Fall 2020

Project link – https://thebryanwillis.github.io/CalgaryShortTermRentals.html

Background

Over the years, many homeowners have decided to turn their place of residence into short term rentals, allowing their place of residence to be rented out for short periods of time. Short term rentals have also seen an increase in popularity due to their better pricing when compared with hotels and the unique neighbourhood characteristics it provides. Although Calgary has not seen the increase of short term rentals as dramatics as that of Toronto and Vancouver, Calgary has continued to see growth in the short term rental supply. The City of Calgary defines a short term rental as a place of residence that provides temporary accommodation and lodging for up to 30 days and all short term rentals in Calgary must legally obtain a business license to run.

This interactive dashboard will aim to highlight some key components related to short term rentals in Calgary such as the locations, the license status, the composition of the housing type and licenses per month

Data

The data used in this dashboard is based off of the Short Term Rentals data set which was acquired through the City of Calgary’s Open Data Portal.

Methods

  1. Data Cleaning – After downloading the data from the open data portal, the data needed to be cleaned for it to properly display the attributes we want. All rows containing NULL values were removed from the data set via MS Excel.
  2. Map Production – After importing the cleaned data into Tableau, we should quickly be able to create our map that shows where the locations of the short term rentals are. To do this, drag both the auto generated into the middle of the sheet which should automatically generate a map with the location points. To differentiate LICENSED and CANCELLED points, drag the License Status column into the ‘Color’ box.
  1. Monthly Line Graph – To produce the line graph that shows the number of licenses produced by month, drag into the COLUMN section at the top and right click on it and select MONTH. For the ROWS section, again use but right click on it after dragging and select MEASURE and COUNT. Lastly, drag License Status into the ‘Color’ box.
Finalized monthly line graph
  1. City Quadrant Table – To create this table, we first need to create a new column value for the city quadrant. Right click the white space under ‘Tables’ and click on ‘Create Calculated Field’ which will bring up a new window. In the new window input RIGHT([Address],2) into the blank space. This code will create a new field with the last two letters in the Address field which is the quadrant. Once this field is created, drag it into the ROW section and drag it again into the ROW but this time right clicking it and clicking on Measure and then Count. Finish off by dragging License Status to the ‘Color’ box.
Finalized City Quadrant Table
  1. Dwelling Type Pie Chart – For the pie chart, first right click on the ROW section and click ‘New Calculation’. In the box, type in avg(0) to create a new ‘Mark’. There should now be an AGG(avg(0)) section under “Marks’, make sure the dropdown is selected at ‘Pie’. Then drag the Type of Residence column into the ‘Angle’ and ‘Color’ boxes. To further compute the percentage for each dwelling type, right click on the angle tab with the Type of Residence column in it then go the ‘Quick Table calculation’ and finally ‘Percent of Total’ .
Finalized pie chart
  1. Dashboard Creation – Once the above steps are complete, a dashboard can be made with the pieces by combining all 4 sheets in the Dashboard tab.
Finalized dashboard with the 4 created components

Limitations

The main limitations in this project comes from the data. Older licensing data is removed from the data set when the data set is updated daily by city staff. This presents the problem of not being able to compare full year to date data. As seen in the data set used in the dashboard, majority of the January data has already been removed from the data set with the except of January 26, 2020. Additionally, there were also quite a few entries in the data set that had null addresses which made it impossible to pinpoint where those addresses were. Lastly, as this data set is for 2020, the COVID-19 pandemic might have disrupted the amount of short term rentals being licensed due to both the city shifting priorities as well as more people staying home resulting in less vacant homes available for short term rentals.