Tag: Animated map

The Cooling Effect of the 1991 Eruption of Mount Pinatubo, Philippines

By Clarisse Reyna

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.

PrintScreen_TimeSlider3

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.
PrintScreen_TimeSlider

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.

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References

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.

TTC Subway Stations and LRT Expansion Animated 1954-2021

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/.

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Project Idea

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.

Execution

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.

khakan_1

Tutorial / How-to-Use

For the heading numbers above, please find the associated instructions below.

  1. Title and Subtitle – Speaks for itself.
  2. 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.
  3. 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.
  4. 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).
  5. 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).
  6. Legend – as the name implies…
  7. 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.
  8. 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.

Enjoy viewing and exploring.