GIS Maps

Final Project – Gentrification Risk Analysis in the City of Vancouver (Updated)

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Over the last two weeks of my GEOB 270 Introduction to Geographic Information Sciences, I worked on a final project with my three classmates Ahmed, Christina, and Jacqueline to do an analysis of gentrification risk in the City of Vancouver.

Gentrification is a process of urban regeneration involving demographic and economic changes that upgrade low-income neighbourhoods for uses that yield higher capital investment. This process displaces many of the original residents and occurs inequitably across contours of class and race difference. As such, our study will be useful to bring attention to neighborhoods and residents that face these risks.

Project Methods

To measure neighbourhoods that are at risk of gentrification, we examined previous literature on factors that lead to gentrification in Vancouver. These factors include transit and transit development areas, immigrant populations, and populations that spend greater than 30% of their total income on shelter costs to measure susceptibility. Our study uses data from the Metro Vancouver and City of Vancouver Open Databases and the 2011 National Household Survey and uses Multi-Criteria Evaluation (as seen in the above map) to weigh factors and their influence to gentrification. Through the Multi-Criteria Evaluation, one can see where all three factors overlapped in certain census tract divisions to rate the risk of gentrification on a scale of 1 (lowest) to 5 (highest).

Project Management

All four of us participated in the research, project proposal, data acquisition, map making, and analysis of our areas. To ensure organization, we kept a group calendar to decide on due dates for each stage of the project and regularly updated a spreadsheet of the data we downloaded and edited. This was a valuable experience compared to the individual GIS assignments we worked on throughout the term and after coming across issues of saving layers into different computer drives, geodatabases, and USBs, I think we have all learned a bit more about the importance of organization. Thank you to Microsoft OneDrive and the almighty Cloud (technology is great)! And most of all, thank you, team! 🙂

Project Results

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Housing Unaffordability

As many studies cited low-income housing areas as high-risk, we weighed housing unaffordability as our highest risk factor for gentrification. Adam Smith, a scholar on gentrification, argues that the idea of a “rent gap”, where a difference between the costs of monthly rent and the land’s market value exists, encourages landowners to sell these mostly aging rental units for redevelopment that will result in a higher return of capital. Unaffordability here is defined through the Canada Mortgage and Housing Corporation’s criteria of households that spend over 30% of their income on shelter.

In the above map, we see that areas such as the Southwest Marine Corridor fall quite low on the unaffordability scale. These areas, though dotted with expensive, new stock housing, are populated with some of the wealthier residents of Vancouver who are owners rather than renters. When using census data, it is important to normalize and present your information as ratios rather than just numbers of unaffordabilty in households. As such, the above map shows the number of houses spending over 30% of income on shelter over the total number of households.

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Rapid Transit Development

Developments that are within walking distance to a train station (measured by 5- and 10- minute walk buffers), are highly marketable and increase surrounding land demand and value. Transit-oriented developments (TODs) are also mapped above as these are special areas that have been zoned to promote density and access to public transit. The location of TODs are often chosen to be in areas with aging buildings and low-income residents to face minimal resistance against demolition. Rapid Transit Development has such been explored in an article on gentrification in Burnaby by Craig Jones and David Ley who state, “there are no incentives to preserve or repair aging affordable units, especially when a TOD-inspired neighbourhood plan offers more dwelling units, profit to the developer, a density bonus for the City’s coffers, public amenity enhancement, and all of the environmental gains that have made TOD such an irresistible tool”.

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Immigrant Population

Here is the map I created! Where there is high housing unaffordability and high immigrant population this may be indicative that immigrants of limited resources are living in aging rental housing that is susceptible to redevelopment. In the example of Marpole, which includes “over 4,000 units of relatively affordable market rental housing” but 85% was built prior to 1975, it is likely that, in a housing climate of increasing demand, landowners are more likely to wait to outprice the renters and sell the property to developers for a higher yield than invest in maintenance of current affordable housing.

A lot of my research and projects have been focused on gentrification in Chinatown this term, which led me to find that diversity of immigrant neighbourhoods has also been identified as attractive to gentrification. This has been seen in Chinatown which is of 60%-68% immigrant population, high on the gentrification risk scale, and already has condo developments, a renewed nightlife scene, and neighbourhood changes commonly identified in gentrification trends. Cultural diversity has a tourist value and attracts young professionals of the creative and service sector to invest in the neighbourhood.

Error and Uncertainty

Here are some of the uncertainties we came across during our project:

1. Census data is outdated (from 2011) and there have been major housing and demographic changes since.

2. Difficulty in confirming aggregate trends due to lack of statistical evidence on the City of Vancouver in particular.

3. Additional barriers due to immigrant identity as visible minority or refugee status.

4. The walk radius is speculative: People will not necessarily opt to drive over taking and buffer shape as circular does not match real walking patterns.

Conclusion

This project has been an important learning experience for me as I have combined tools of past assignments to:

  • Acquired governmental shapefile and database file (dbf) data from the Metro Vancouver and the Canadian Census 2011 to map city developments and demographics by census tract in the City of Vancouver.
  • Performed a Multi-Criteria Evaluation with ArcGIS using housing affordability, rapid transit development and immigration population to map factors of gentrification risk.
  • Researched and wrote analysis of gentrification risk GIS project with three group members to highlight findings, uncertainties, and future suggestions for research.

Update- March 13, 2017

Since finishing the course, I have found how valuable these projects were to encourage me to think about career interests and make connections to other courses I am taking. As such, I have created a simple infographic that summarizes this project. The graphic was intended for a visual portfolio I submitted to apply for the UBC Bachelors of Environmental Design Program in February.

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Learning GIS: Environmental Assessment of Garibaldi Project

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In this week’s GIS assignment I have been tasked with performing an environmental impact assessment of the proposed Garibaldi resort in Squamish.

The Garibaldi at Squamish Project

The Garibaldi at Squamish project is a proposed all-year mountain resort on Brohm Ridge, which will include 124 ski trails, 21 lifts, along with commercial developments to attract tourism. While the project has been in discussion since 1997 and boasts an increase of over 3000 jobs over years it will be built, there have been barriers in approval of the project. Namely, the BC Environmental Assessment Office and Resort Municipality of Whistler have criticized the project’s potential effects on vegetation, wildlife, economic viability, and climate
change. As a natural resource planner speaking on behalf of Northland Properties and Aquilini Investment Group of Vancouver, I have evaluated the above criticisms and made recommendations of priorities that will need to be addressed as the Garibaldi project moves forward. I have also produced a map of possible environmental concerns in project attached to this document (See above image).

Hillshade Map of Garibaldi Project

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Findings of Areas of Environmental Concern
To perform this assessment I have compiled data of the biodiversity that may be affected within the project area; this data is sourced from DataBC. These areas include ungulate winter habitat ranges, old growth forests, red-listed terrestrial ecosystems, and riparian zones which surround the rivers. I have also identified areas below the elevation of 600m which may potentially not have enough snow for ski trails. This amounts to about 31.7% of the project area (4298 acres) which is unfit for skiing. By layering these different spatial factors I was able to identify and visualize the area that is of environmental concern for the resort development.
In general, I have found that about 53.6% of the Garibaldi project includes areas of environmental concern and protection above. This amounts to about 7300 acres of the 14000 acre project. I have summarized my findings in the table below:

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Recommendations Moving Forward
The percentage of areas of environmental concern are top priorities in the development of the ski ranges and I recommend Northland Properties and Aquilini Investment Group of Vancouver to be cautious of where they locate the ski-resort’s trails and facilities so that they are the least disruptive to these sensitive biodiversity zones.
I suggest that the two greatest environmental concerns to project development include riparian zones and fish habitats, and ungulate habitat, which cover a significant amount of areas of over 600m elevation where skiing facilities would be developed. To mitigate effects on these already sensitive environments, I recommend the developers to consider methods of construction and operation that create the least amount of disruption and pollution (runoff, noise pollution, greenhouse gas emissions) in the short-run, and regular monitoring of rivers and ungulate habitats so that further damage is not done.

Conclusion of Environmental Assessment
This environmental assessment has found that over half of the Garibaldi project contains areas of environmental risk, old growth forest, threated ungulate habitat, red-listed ecosystems, and riparian zones, all of which must be a high priority in the development of the project as it moves forward. Since the resulting area that is safe for development only amounts to about 46% and there are significant environmental regulation barriers to the project, I recommend both proponents to review the extent and range of property development on the resort in consideration of whether these limits will still attract the investment originally intended. Other priorities I recommend would be further research in the viability of a resort where seasonality and climate change risk its profitability and continued consultation with the Squamish Nation so that the Garibaldi project is also socially sustainable.

Reflection on Week 4 –Environmental Assessment of Garibaldi Project

This was the most interesting and most challenging of the 4 weeks of GIS assignments because it engaged with a contentious development with many ethical implications. Personally, I do not believe the project should continue for the reasons of threatened environments listed above, however, early in this year, the project had been received environmental approval. My hope is that Northland Properties, Aquilini Investment Group of Vancouver, and other proponents have made appropriate changes to protect the ecology at risk while ensuring the social sustainability of the project as well.

Here are some skills I picked up in summary:

  • Acquired BC Government TRIM data using the online DataBC database to perform an environmental impact assessment of a ski range
  • Reclassified a DEM based on elevation to identify appropriate land for a ski range
  • Built a multi-field query using the Select by Attribute tool to identify red listed ecosystems, ungulate winter ranges, and old growth forest
  • Produced an environmental assessment map of the Garibaldi at Squamish project to highlight ecologically sensitive factors to development
  • Produced 3D hillshade map of environmental assessment to highlight topography  and slope of project area
  • Wrote a memo directed to project proponents outlining the project objectives, findings, and recommendations

Learning GIS: Housing Affordability in Vancouver and Ottawa

In this week’s GIS class I have created a map of housing affordability in Vancouver and Ottawa using Census 2011 data.

Affordability Classifications

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Here, I have presented an affordability map in 4 different classification methods. While the data is the same in all maps, affordability can be represented in different ways according to how prices are grouped or classed together.

For example, if I wanted to emphasize housing unaffordability as a journalist reporting to locals, I would use the Manual Break classification. However, if I was a real estate agent looking to attract a UBC student to rent nearby,  I would use the Equal Interval classification as it symbolizes UBC in dark yellow while other classifications symbolize it in orange or red.

Both decisions carry ethical implications as they manipulate tracts to look more or less affordable according to the classification method. As well, because the difference in intervals of housing prices may not be obvious to viewers without
closely examining a legend, it is easy to present either map as a truthful representation of affordable housing rather than a representation that depends on the chosen intervals.

Affordability in Vancouver and Ottawa

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In the above map, I have compared the housing affordability of Vancouver and Ottawa using the Demographia International Housing Affordability Survey’s categories. Affordability is measured through the ratio of median house price to median income. This ratio produces a better indication of affordability versus just the housing price as it compares how much one spends on housing in comparison to how much they make.
These housing affordability rating categories use the “median multiple” – median house price divided by gross annual median household income, according to the Demographia International Housing Affordability Survey, an international report on metropolitan housing affordability conducted in 2016. The median multiple categorizes affordability with multiples of 3.0 and under as affordable, 3.1-4.0 as affordable, 4.1-5.0 as moderately unaffordable, 5.1 and over as severely unaffordable.

Affordability as ‘livability’?

While there are many indices used to measure “livability” and Vancouver is consistently ranked as one of the most livable cities in the world, it is clear through the Demographia International Housing Affordability Survey’s classifications, that even in international standards, Vancouver is one of the least unaffordable. Livability and the quality of life depends on many factors beyond material living conditions which may be harder to measure such as happiness, leisure and social life, education, health, safety, human rights, and environment, all of which are experienced subjectively for each person.

Here are some skills I picked up in summary:

  • Created a comparative map of housing affordability of Vancouver and Ottawa using Canadian Census data and the Annual Demographia International Housing Affordability Survey’s standards
  • Acquired and spatially joined tabular data of Canadian Census 2011 income and housing cost to spatial data of census tracts to visualize census information
  • Presented affordability using 4 methods of classification: natural breaks, equal interval, standard deviation, and manual breaks to illustrate the ability of maps to manipulate meaning

Learning GIS: Identifying Vancouver’s Tsunami Risk Areas

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Hello All!

In this week, I have been tasked to prepare a map of the City of Vancouver’s tsunami risk areas on the premise that sea level change and extreme weather due to climate change may affect our coastal city. As the most immediate danger zone of a 15-metre wave will affect land at the elevation of or under 15 metres that is 1 kilometre from the shoreline, I have highlighted the neighbourhoods and land use types that will be affected.

Through my analysis, I have found that 15.5% of the City of Vancouver’s area is in in danger in a tsunami.
I came to this conclusion through:

  1. Reclassifying the areas below 15 metre elevation
  2. Performing buffer analysis of areas 1 kilometre from the shore
  3. Using the intersect tool to combine the two factors into one polygon to summarize the total area at tsunami risk.

I have also identified some of the health and educational facilities within this tsunami risk zone using the previous polygon of tsunami risk and the clip tool to isolate healthcare and education points.

Healthcare: False Creek Residence, Broadway Pentecostal Lodge, Coast West Community Home, Yaletown House Society, Villa Cathay Care Home.

Education facilities in danger zones include: St. Anthony of Padua, Ecole Rose des Vents, Heritage 3R’s School, Vancouver Montessori School, False Creek Elementary, Emily Carr Institute of Art & Design (ECIAD), Henry Hudson Elementary, St. Francis Xavier, Institute of Indigenous Government (IIG).

My resulting map summarizes the land use types and area that is at tsunami risk and identifies proper signage to the neighbourhoods affected.

Here are the skills I picked up in summary:

  • Combined spatial and tabular datasets to create a map of areas of tsunami risk in the City of Vancouver.
  •  Calculated area of risk through summary tables to identify land use types possibly affected by a tsunami.
  • Reclassified DEM of the City of Vancouver to perform buffer proximity analysis and identify low-elevation areas at tsunami risk.

Learning GIS: Coordinate Systems and Spatial Data Models

Hello and welcome to my first blog post!

In my first week of learning GIS in my Introduction to GIS course at UBC, I have started to learn how ArcGIS works and also come across a few major concepts: Coordinate systems and Landsat data.

Coordinate systems

Coordinate systems are fundamental to GIS mapping as they determine how longitude and latitude coordinates of places on Earth are displayed in mapping. They are basically the way for your place coordinates to be communicated in digital analysis. That said, in my first GIS assignment, I had to fix misaligned data layers that were improperly referenced – meaning, my data did not all have a common coordinate system, and misrepresented where my coordinates were in relation to eachother.
To fix improperly referenced data in ArcGIS you can:

  • Use the ArcToolbox Project command.
    This should let you change the coordinate systems of your data layers so they are displayed in a common coordinate system.
  • Tip: ArcGIS has a built-in function called Projecting-on-the-fly and this actually makes your layers look like they’re aligned for the ease of viewing, even if your layers are actually misaligned and not in the same coordinate system. Therefore, you should always check the coordinate systems of your layers first (by clicking on the “Properties” of the drop-down menu of the layer) to make sure your data is in the right coordinate system.

Why do coordinate systems matter?

Projecting the uneven world into a digital sphere is always a challenge in GIS, therefore, with each different coordinate system chosen, properties of distance, area, shape, and direction of places is distorted.

Landsat Data

Landsat is a remote sensing program that uses a satellite to scan and capture images of the surface of the Earth. In this assignment, we have used Landsat images of Mount St. Helen from before and after it’s eruption to observe vegetation and water body changes.

Disadvantages:

Landsat data is very useful to document large scale topographical changes, however, there are problems of representation at such a large scale, as each pixel represents several meters of surface in real life. For example, looking at a road or a river from Landsat images, you may not be able to see the actual curves and angles of it. Instead, you may be looking at a computed average mixture of gravel, grass, and asphalt that cannot be discerned in its full detail at such a scale.