By Boris Gusev, Geovis Course Assignment, SA8905, Fall 2015 (Rinner)
The way in which we settle the land around us can paint a rich picture of how our cities have developed over years. By the turn of the 19th century, urban planners generally agreed that grid-like patterns were the optimal solution and held the most promise for the future of transit. Physical planning led to the development of automotive cities like Los Angeles, Chicago and Detroit. Toronto’s history of growth can also be traced through its sprawling grid of roads.
In this visualization, a MapZen extract of OpenStreetMap road network was used to represent the compass-heading-based orientation of Toronto roads. Streets that are orthogonal, meaning that they intersect at a right angle, are assigned the same colours. At a 90 degree angle, the streets are coloured with the darkest shades of orange or blue, decreasing in intensity as the intersection angle becomes more obtuse.
By Andrew Thompson – Geovis course project, SA8905 (Dr. Rinner)
The power of data visualization is becoming increasingly more robust and intricate in nature. The demand to deliver a variety of complex information has lead to the development of highly responsive visual platforms. Libraries such as d3 are providing increased flexibility to work along multiple web technology stacks (HTML, CSS, SVG) allowing for nearly unlimited customization and capacity to handle large datatypes.
In this development, a combination of d3 and Leaflet is used to provide a data-driven visualization within an easy to use mapping engine framework; made possible through the developments of Asymmetrik. This collection of plugins, has allowed the creation of dynamic hexbin-based heatmaps and dynamically update/visualize transitions.
Geovis Course Assignment, SA8905, Fall 2015 (Rinner)
This is a time series map showing interpolated temperature change. Mount Pinatubo is located in the island of Luzon, Philippines. It erupted in 1991, which marked the second largest volcanic eruption in the 20th century. This caused a cooling effect as it released significant amounts of volcanic gases, aerosols and ash that increases albedo. This means that there is an increase in solar radiation being reflected, which decreases the amount of solar radiation reaching the troposphere and the surface. Since there is less solar radiation at the troposphere and the surface, it causes a temperature decrease. This is exactly what took place when Mount Pinatubo erupted in 1991. After the eruption, there was an observed surface cooling that took place in the Northern Hemisphere of around 0.5 to 0.6 degrees Celsius (Self et al. 1999).
In this time series map, interpolated temperatures in the Philippines from 1988 to 1995 is presented. What you should be able to see is that as time passes after the eruption (1991), there is a significant increase in blue areas which indicate lower temperatures. Originally, the years included would have been from 1985 to 1995. However, there are unusually low temperatures in 1987. In fact, the lowest ever recorded temperature in Manila was on February 4, 1987, with a temperature of 15.1 degrees Celsius. As you can see in the picture below, 1987 has large blue areas, indicating low temperatures. This may cause confusion when viewing the final time series visualization, so it was omitted from the final geovisualization project.
The purpose of including temperatures before the eruption in 1991 is so that the viewer is able to see temperature trends before the cooling occurred. This allows viewers to compare temperature trends before the eruption to temperature trends after the eruption. The years included went up to 1995 because this was the last average temperature where it shows decreasing temperatures from 1991 in most of the cities.
The temperature data in this time series geovisualization were taken from a website called Weather Spark. The data taken from this source was yearly temperature averages from 1988 to 1995 in the Philippine cities of Aparri, Batangas, Bohol, Catarman, Coron, Manila, Davao, Lapu Lapu, Pasig, El Nido, Legazpi, and Pagudpud. Temperature data for the city of Boracay was not available so the province of Malay was used in place of it. Another province used was Bulacan. These areas are very spread apart in the Philippines. Therefore this gives a more accurate representation of temperature patterns during interpolation since the data points are spread apart and covers each part of the country. Lastly, the Philippine boundary shapefile was taken from a website called PhilGIS.
The technology used for this time series visualization was Time Slider, which is available in ArcMap (in versions ArcGIS 10.0 and up). For each year, the data taken from Weather Spark for each city or province was interpolated using the Inverse Distance Weighted method. Therefore, a raster was created for every year. Since there are eight years that are being included in this visualization, eight rasters were created. After creating an interpolation raster for each year, a raster catalog was created, and each of these rasters were added onto the raster catalog. After the rasters were added, time was enabled on the raster catalog layer.
When time is enabled on a layer, ArcMap allows you to use the Time Slider tool to create the time series visualization. This time slider tool allows you to preview what the time series visualization will look like. You can then export the time series visualization to an .avi file by clicking on the icon circled in red in the picture below.
Country Boundary. (2013). In PhilGIS. Retrieved from http://philgis.org/freegisdata.htm
Historical Weather. In WeatherSpark Beta. Retrieved from https://weatherspark.com/
Self, S., Zhao, J., Holasek, R., Torres, R., & King, A. (1999). The Atmospheric Impact of the 1991 Mount Pinatubo Eruption. U.S. Geological Survey.
An animated look at TTC’s subways and LRT expansion by when they first opened. Includes 2017’s Finch West subway expansion and 2021’s Eglinton LRT expansion.
By Khakan Zulfiquar – Geovis Course Assignment, SA8905, Fall 2015 (Rinner)
As a course assignment, we were required to develop a professional-quality geographic visualization product that uses novel mapping technology to present a topic of our interest. I chose to create an animated-interactive map using CartoDB to visualize the construction of Toronto Transit Commission (TTC) stations from years 1954 to 2021. The interactive map can be found at https://zzzkhakan.cartodb.com/.
This idea was inspired by Simon Rogers who animated the London’s Rail System. It was interesting to see an animated map slowly draw together a footprint of an entire infrastructure system. A number of (non-interactive) animations of Toronto’s subway system development were collected by Spacing magazine in 2007 and can be viewed at http://spacing.ca/toronto/2007/09/21/ttc-subway-growth-animation-contest/.
A feature within CartoDB called “torque” was used to create the envisioned map. Torque is ideal for mapping large number of points over time. Torque has been famously used in media for mapping tweets as pings.
As a beginner to CartoDB, I had to go through tutorials and online courses to get familiar with the interface. As I became comfortable with CartoDB and its features, I recalled an example I had seen in the CartoDB gallery. It was Simon Roger’s London Rail System map. I knew exactly the kind of data I would need to make a similar map for TTC stations. There was an instant halt as the data was not readily available. Using Wikipedia, ttc.ca, and OpenStreetMap I was able to compile the data I required. The data was uploaded into CartoDB and the following map was created.
Tutorial / How-to-Use
For the heading numbers above, please find the associated instructions below.
Title and Subtitle – Speaks for itself.
Toronto Subway/ LRT Map [full resolution]- A Map of Toronto’s Subway and future LRT produced by the TTC. This map is the most common visual representation of TTC’s subways and LRT. The map’s color scheme was mimicked to help viewers, especially those familiar with TTC, make the transition to the animated map smoothly.
Timeline – The timeline is in a continuous-loop. You can press pause to stop the animation and resume to start the animation again. You can also control the speed of the animation by sliding the play-bar back-and-forth.
Hover Window – As you hover over the stations, a window will pop up automatically with the name of the station. No clicks required. The names will only appear if the “ttc_station” layer is switched on (more on this in step 7).
Info Window – If you would like further information on a certain station, simply click on the station and you will be presented with the station’s name, line #, grade (above, at, or underground), platform type, and etc. The info window will only appear if the “ttc_station” layer is switched on (more on this in step 7).
Legend – as the name implies…
Layer Switch – a tool to turn on or off the layers being used in this map. The map was created with the intent to be both animated and interactive. The animated bit is the stations being plotted and the interactive part was for the user to find further information about the station. However, the animated bit is both intrusive and resource-heavy. Because of this, an option is being included to turn layers on-or-off as required. Be sure to try out the combinations.
MAIN SHOW – the main map area has a beautiful CartoDB Dark Matter basemap with all of the TTC stations plotted. Feel free to zoom in and out.
Geovis Course Assignment, SA8905, Fall 2015 (Rinner)
Author: Austin Pagotto Link to Web app: http://arcg.is/1Yf8Yqn (Note: project may have trouble loading using Chrome – try Internet Explorer)
The idea of my project was to comprehensively map the past two Canadian federal election results. When looking for visualization methods to compare this data I came across the Swipe feature on the ArcGIS Online story maps. Along with all the interaction features of any ArcGIS online web map, this feature lets the user swipe left and right to reveal either different layers or in my case different maps. As you can see in the screenshot below the right side of the map is showing the provincial winners of the 2015 election while the left side of the map is showing the provincial winners of the 2011 election. The middle line in the middle can be swiped back and forth to show how the provincial winners differed in each election.
The biggest problem in executing my project was that the default ArcGIS online projection is web Mercator, which greatly distorts Canada. I was able to find documentation from Natural Resources Canada explaining how Lambert Conformal Conic basemaps can be uploaded to an ArcGIS online map and replace the default basemaps.
Another problem with my visualization of the project was that when zoomed to a national scale level, a lot of the individual polling divisions became impossible to see. This creates an issue because each polling division is designed to have a somewhat equal population count in them. So the small ones aren’t less important or less meaningful than the big ones. To solve this, when zoomed out, I changed the symbology to show the party that had won the most seats in each province, so it would show the provincial winner as seen in the previous screenshot. When zoomed in however the individual polling divisions become visible, showing the official name at increased zoom levels. The years of each election were added to the labels to help remind the user what map was on what side.
The methodology I used to create this project was to create two different online maps, one for each election year. Then I created the swipe web app which would allow both of these maps to be loaded and swipeable between the two. It was important here to make sure that all the settings for each map were the exact same (colors, transparency and attribute names).
The data that is shown on my maps were all downloaded from ArcGIS online to Arcmap Desktop and then zipped and reuploaded back to my project. It was important to change my data’s projection to Lambert Conformal Conic before uploading it so that it wouldn’t have to be reprojected again using ArcGIS online.
This project demonstrated how web mapping applications can make visualizing and comparing data much easier than creating two standalone maps.
Data Sources: Projection/Basemap information from Natural Resources Canada
Election Data from ESRI Canada (downloaded from ArcGIS Online)
The process starting from the research to the creation of the 3D Paper model included the following steps:
Collect satellite photographic data depicting the shrinkage of the summer polar ice cap over a selected period of time (1999, 2001, 2002, 2003, 2005, 2008, 2009, 2011 and 2012)
Print the photos for each of the years on letter size paper
Cut out the area of the ice cap (shown in the photos below)
Cut both of the model boards into 4 sections of 10” x 8” to create the inserts for the cube
Trace the cut out of the each stage of the ice cap and the designated area for the year onto the model board
Remove the traced areas with an exacto knife
Cut out letters spelling “Polar Ice Cap” and a snowflake design from the sides of the cube
Paint each model board in a different shade of blue
Write year on corresponding model board with permanent marker
Create the cube and then glue all inserts in chronological order
Data was collected for the years of 1999, 2001, 2002, 2003, 2005, 2008, 2009, 2011 and 2012 from the Earth Observatory website. The data collected was in the form of photographs, and depicts the permanent ice coverage for the corresponding year. Although there is not a drastic difference between each level, it is clear that the permanent ice coverage contracts. The satellite images show that the area of permanent ice coverage in the Arctic during the summer is contracting at a rate of 9% per decade.
The model materials – model paper, exacto knife, glue and paint – were retrieved from Michael’s arts and crafts store.Some of the materials used are shown in the following photograph. Other materials used were a black and white printer, a ruler and scissors.
Each cut out of the ice cap to the corresponding year was prepared by saving the images, printing the images and cutting out the area of permanent ice coverage (as shown in the photograph above – one can see the example shown by the 2008 permanent ice coverage cut out which was currently sitting on top of all the other cut outs in the right hand corner). The model boards were prepared by dividing two 16 by 20 inch sheets into eight cut outs. A larger sheet was then cut into three pieces to prepare the outside part of the cube (these three pieces were connected; slits were cut in the folds of the paper in order to allow the board to bend nicely). The 3D cube template, shown in the photo below, was the technique that was used to create the model.
Once the preparation steps were complete, the model was then ready to make. The next step taken to create the model was tracing each year’s cut out (of the permanent ice coverage) onto the individual model boards (as shown by the second photo). A rectangular section was also cut out for the years to be displayed at each level. This rectangular section became smaller for each layer added (in a descending order), in order to allow the date to be seen at the various levels.
Decorating the sides of the cube was the next step in the process. In order to write “Polar Ice Cap” on the front side of the cube, the letter were first hand drawn onto the paper, than carefully cut out using an exacto knife. On the backside of the cube, a snowflake was hand drawn and once again cut out using an exacto knife. The front and back sides of the cube are shown in the photos to the left and below.
After each layer and the sides of the box were cut out, the boards were then ordered in chronological order. The boards were then painted in various shades of blue, as shown in the photo to the left. The corresponding year was then written onto the model board with either silver or black permanent marker (whichever color was more visible on the painted board).
The final step of the process was gluing all the pieces together. The key to this step was ensuring that each of the layers was put in chronological order, and that each layer was the same distance apart. Ensuring that each layer was the same distance apart (1.25 inches to be exact) allowed the model to accurately depict the shrinking of the ice cap.
The piece that was cut out from the top layer was then glue to the top, to give the box an “opening” look. This piece allowed the model to appear as if an individual opened the top layer to look at the depiction of the shrinking polar ice cap through the 3D model, as shown in the photo below. The final dimensions of the 3D Paper model cube project are 8” x 10” x 10”.