Module 2 Formstorming

Weekly Activity Template

Nicole de Guzman

Project 2

Module 2

My explorations with bivariate mapping. Activity 1 was spent familiarizing myself with Mapbox on Cartogram and colour selection that would be best understood by users. Activity 2 allowed me to explore with the backend features of Mapbox and how to create different layers with more detail and decision.

Week 6

image of burning embers in a bonfire the first iteration of the colour palette chosen from the image of burning embers, in order of left to right, top to bottom: land, road, greenspace, land, water In this first map iteration, I selected the colours for a map of Nevada. The colours in the photo reminded me of Red Rock Canyon and I selected the colours in the photo based on the colours I saw most at the park. the first iteration of the colour palette chosen from the image of burning embers, in order of left to right, top to bottom: land, road, greenspace, land, water In my second iteration of the map I selected colours that I felt still expressed the coloration of Red Rock Canyon, but had enough contrast to display the map and its components well. Reds were chosen for land and greenspace, and lighter/muted hues were chosen for the label and road. photo of the view of the sea at Stanley Park the first iteration of the colour palette chosen from the photo of the view of the sea at Stanley Park, in order of left to right, top to bottom: land, road, greenspace, land, water I chose to display a map of North Vancouver with colours chosen from a photo I took when I went on a walk at Stanley Park. The colour palette was cool toned but there was enough contrast that I felt could allow for someone viewing to differentiate between the different places on the map. The land, greenspace, and water colour selections were from each respective section of the photo. the first iteration of the colour palette chosen from the photo of the view of the sea at Stanley Park, in order of left to right, top to bottom: land, road, greenspace, land, water In my second iteration of the map I switched colours out for better visibility (mainly the label). I also chose to make the colours for the land and greenspace lighter rather than dark—Stanley Park is vibrant with life and while the photo does not have green in it, I wanted to have a lighter display. photo of people playing soccer on a field at night the first iteration of the colour palette chosen from the photo of people playing soccer on a field at night, in order of left to right, top to bottom: land, road, greenspace, land, water In this first map iteration of the neighbourhood park where I took this photo, I chose the opposite colours for land, label, and water to see how it would display on the map. I chose blue for land, green for the label, and a concrete grey for the water, If I were to look at the map with no labels I would expect blue sections were water, so this taught me that colour selection is important when it comes to viewer expectations. the first iteration of the colour palette chosen from the photo of people playing soccer on a field at night, in order of left to right, top to bottom: land, road, greenspace, land, water In my second iteration of the map I decided to select colours that would be expected when a person thinks water, land, and greenspace. From a user perspective, these colour choices would be the most intuitive and a colour legend would be additional in explaining what each colour would mean on a map. This is something I feel is important when making future design decisions. photo of the American Badlands the first iteration of the colour palette chosen from the photo of the American Badlands, in order of left to right, top to bottom: land, road, greenspace, land, water This map is from a neighbouring city to the American Badlands. Because the colours in the map are all from land, I tried to keep in mind that certain colours are associated with different elements displayed on a map. Blue was chosen for water, a lighter grey/brown was chosen for land, and to keep the fact that the colours are from the badlands, I used the warm orange tone as the accent for the roads. the first iteration of the colour palette chosen from the photo of the American Badlands, in order of left to right, top to bottom: land, road, greenspace, land, water In my second iteration of the map I tweaked colours that would enhance visibility and contrast to make the different elements distinguishable from a zoomed out view. I used a darker red for the greenspace, used a deeper teal for the water, and used a lighter hue for the label. photo of Chukchi sea in Alaska the first iteration of the colour palette chosen from the photo of Chukchi sea in Alaska, in order of left to right, top to bottom: land, road, greenspace, land, water In my previous map of the neighbourhood with the field, I switched the colours for land and water but it was more experimental with no intention. In this map, my colour choices for land and water being opposite (although in the image the warmer colours are the water and the cooler colours are the ice) were influenced by global warming. As the map is of Alaska, I wanted to choose cooler tones for the land, and the warmer colour was used for the water to denote the impact of global warming on rising water levels. the first iteration of the colour palette chosen from the photo of Chukchi sea in Alaska, in order of left to right, top to bottom: land, road, greenspace, land, water In this second map iteration, I flipped the colours back around to what would be expected of a map, warm, brown tones for land and blue for water. This map, I feel, does make the most sense when someone viewing is to think of what is land and water, but the previous map feels more impactful and carries more meaning in the colour choices.

Week 7

Display of two variables in the same dataset—proposed and existing bike routes Two variables displayed as two separate layers in Mapbox Display of the map with setting adjustments in colour for a more harmonious palette Selection of information to display the proposed bike lanes Selection of source as Cycling Routes to display the information in the dataset

Project 2

Final Project 2 Design

This final bivariate map displays the correlation between affordable rental housing (completed, and incomplete projects) and EarlyON Child and Family Centres in the Toronto area. The yellow background denotes the City of Toronto bounds, the orange circles display each EarlyON location, and the blue and grey heatmaps display the density of affordable rental housing throughout the city—blue denoting completed and under-construction projects and grey denoting projects yet to be started.
Link to Mapbox

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