Mapping recent development trends in Victoria

While it is true that the team here at LGeo is not tremendously fond of the word "insight", we do very much like conducting geospatial analysis and identifying potentially interesting data that creates conversations and confounds strongly held beliefs.   To this end, we have been working with a development company in Victoria called Aryze Developments.  Not your typical developer, Aryze is attempting to build housing in Victoria for the so-called "missing middle".  That is to say, neither high-rise developments nor single family homes, but primarily townhouses and small apartment buildings.  To further that aim, they seek to re-frame the conversation around low-rise development on their highly engaging Talk To Aryze website.  As part of their efforts, they are trying add more information to the land use and development conversation in Victoria, BC, A LOT more.  Happily we are here to help. 


As with all things land use and development-related, we knew that there were data floating around that could help us answer a few key questions about what has been going on in the City recently:

  1. What are current development trends in the City by dwelling type
  2. What are the permitted zoning patterns in the City, how much of the City of is zoned for multi-family dwellings?
  3. What are the land use patterns in the City, which developments are occurring on what designations? and
  4. Which neighbourhoods are seeing the greatest levels of development by dwelling type?

All of these questions are structured to help us understand land utilization and development, critical topics in today's rather heated housing market.

What we did

For the base layers, we have divided the city into Residential Zoning Bylaw Classifications , Official Community Plan Urban Designations (OCPs) and Neighbourhoods. The zoning bylaw classifications were created by individually reading through each by law (!!!) and assessing whether or not the zone allowed for multi-family dwellings. While the OCP classifications were created by grouping them into similar thematic groups. Happily, the Neighbourhoods were simply pulled from the city of Victoria’s open data portal.

Obtaining a complete dataset of every residential development in Victoria proved to be a lengthy task. Initially, the data was compiled by carefully combing through Building Permits issued by the city of Victoria. However, this data source was discovered to be missing quite a few key developments throughout the city. Additional sources were required, for which we turned to the Citified and BC Assessment. Even with these additional sources, there is no guarantee that this data has captured every development, but it is certainly complete enough to reveal interesting trends in how Victoria is developing as a city.67

 The data was then categorized into housing types, namely suites (i.e. Basements or garden suites), single family homes, 2,3, 4 plexes (i.e. duplex, triplex or fourplex), townhouses and apartments (including condos).  We then aggregated the data so the total number of new residential units in each zoning type, OCP and neighbourhood was summed up. We then used these totals and the area of each designation in order to determine the density of new units added to each zone, in units per hectare.

Finally, with a bit of Mapbox and D3.js magic, all the data was visualized on this interactive map.

What we found

  • 67% of zoned land that allows for housing is zoned exclusively for single detached dwellings and suites (738 ha).
  • On these single detached lands only 380 net new units (new construction after demolition) were constructed (or suited as the case may be), which amounts to 6.8% of all new housing between 2011-2018.  In terms of density, this equates to an astonishing increase of 0.05 units per hectare per year.  
  • Conversely on multi-family lands there were 5,251 net new units constructed (93.2%). In terms of density this equates to an overall increase of 1.35 units per hectare per year or 28 times the density increase in single detached areas.
  •  63.4% of designated land that allows for housing is designated as "traditional residential" (677 ha), on these lands we saw 7.4% of new dwellings constructed. Conversely the "urban core designation which only accounts for 12.2% of land designated for housing accounted for 70.3% of all growth!
  • In 8 years we located 180 demolitions of single detached homes... this is about 0.3% of the single detached housing stock per year.
  • of the 5,700 constructed units that we mapped, only 2.3% (141) of them were townhouses or "plex style" developments.
  • The vast majority of constructed units in the City were apartments at 88.3% (5,0126) 
  • Five neighbourhoods (Downtown, Harris Green, Vic West, James Bay and North Park) accounted for 73.7% of all net new units constructed.
  • Conversely, the five neighbourhoods (South Jubilee, North Jubilee, Gonzales, Oaklands and Rocklands) account for only 4.7% of growth (263 net new units)
  • Analyzing OCP designations has yielded some interesting findings: 
    • We noticed that 70% of unit growth occurred in the Urban core, compared to 17% proximal to Town Centres and Urban Villages and the remaining 13% in the remainder of the City.
    • This can be directly compared to aspirational targets in the OCP which have the Urban Core at 50%, Town Centres/Urban Villages at 40% and the remainder of the City at 10%. 
    • The real question is: will these trends continue or will development follow policy??

Want to learn more check out the map here

How to use the map

Use the buttons on the right-hand side to change the base layer and filter the housing types. The pie chart will give you a summary of the new housing data based on the housing type filter and base layer buttons you have pressed. Mouseover each slice of the pie chart for more detailed statistics and an explanation of what they represent. You can also mouseover the squares in the legend to highlight the respective portion of the base layer on the map. For more information and data sources, click the “i” button in the top left-hand corner. In addition, when the neighbourhood layer is selected, you can click on a legend square or pie chart slice to zoom to that neighbourhood. 

Translink Service Costs: An Interactive Webmap

It's totally fabulous to be both a data nerd and fan of public organizations that publish annual reviews.  Now, your normal human would probably want to curl up and die rather than review reams of data from public agencies, but if you dig deep and ask right questions, we can find real information hidden in annual reviews! This weeks blog post target is Translink, who helpfully post their annual system performance review for all to enjoy.... as long as you enjoy reading through pages of pdfs!.. Personally, when I see data like this, my mind immediately goes to mapping.  I want to see where the system is doing well and see what routes are well utilized.  Visualizing data like this can help all of us see how we can influence and understand our vital public transportation services  So.... Now on to why you are here:

Data from the app: Screenshots of various attributes


Like any other agencies, transit authorities are not incredibly different in their search for improvement through detailed system reviews. As someone who is curious about transit use and how cities run, I couldn't help myself but create an interactive map of TransLink's (the transit authority in Metro Vancouver) various public reports spurred from their 2016 Transit Service Performance Review (note: when new data is available it will be added to the map and we will do some skookum analysis on it, I promise). The intent of the map is to show the geographic variation of various service metrics and to stimulate discussions with regards to transit planning.  It's also a nice medium for simply taking a look at how all of the pieces of our transit system fit together.

Regarding their findings, TransLink highlights that "from 2015 to 2016 ridership across the system continued to grow" and:

  • Total journeys across the system increased 4.5% to 233 million.
  • System-wide boardings increased 4.5% to a record 384.8 million.
  • Bus boardings increased by 4.6%.
  • Canada Line boardings grew by 5.5%.
  • Expo and Millennium lines grew by 4.1%.
  • West Coast Express boardings decreased by 3.0%.
  • Boardings on the SeaBus declined by 2.8%.

TransLink sourced the data for the the Service Review from a number of sources including:

  • automatic passenger counter (APC) units on buses;
  • turnstiles at SeaBus terminals;
  • fare gates at SkyTrain stations; and
  • Compass Card validators and selective manual counts at West Coast Express stations.


The data in the Service Report was weighted by boardings/revenue hour and then loaded into our online mapping system as Average Cost per Boarded Passenger (given the total cost to run the bus and number of passengers how much does it cost to translink to run this bus per passenger), Annual Service Cost (the total cost of running this bus), Peak Load Factor (how full this bus is during rush hour), Average Boardings Per Revenue Hour, and Avverage Bus Speed layers. The bus routes were colour coded to show blue as the least, green the middle, and yellow the most (cost, or fullness, or speed etc depending on the map).  Where two or more bus routes overlap, we've taken an average of the above variables using average boardings per revenue hour as a weighting factor.


When viewing the interactive map, use the layers button to switch between different service metrics. A list of routes can be shown using the route buttons, and each route can be clicked on to obtain detailed information in the route summary box. Alternatively, a route segment can be clicked on and an individual route can be selected from the popup. The works great on desktop computers, but we are having a bit of issue on touch with mobile.. Bear with us!!

understanding the map

Ride Cost: Blue are cheaper lines to run per passenger and yellow are the most expensive.. It's cool to note where there are geographies of great high costs per passenger and where there are lower costs. It's neat to see what is going on in Surrey, for instance.

Service Cost: This is annual total cost, so it is unsurprising that areas with the most transit service show up as the highest values... it costs a lot of money to run frequent transit as the layer clearly portrays

Peak Load Factor: Expressed as percentages,  these data show routes that are well or poorly utilized during rush hour.  Take a look at the commuter busses, they may have lower service hours but they are dialed for occupancy

Boarding Per Hour: This layer shows average boardings per revenue hour.  It is a good measure of transit use. Check out the bright yellow routes of the number 20 and the 99/9/14/16 corridor.

Bus Speed: My favorite layer! If you spend a lot of time on the bus and wonder if it is going slow, well now you know.  It's not all Vancouver for slowness, check out the North Vancouver slow down as well. good times!

We love feedback

If you like this (or hate it), let us know. We are happy to make changes such that you can see and understand the data a little bit better such that you can transform these data into information. 

    Hop Circuit 2018: How to Drink Efficiently as Possible

    A favourite pastime of ours at LGeo is supporting local businesses, and in particular local breweries. From the casual vibe to the friendly smiles, from the passion behind great beer to the knowledge supporting the process, there is no shortage of breweries to visit in East Vancouver’s brewing district, affectionately termed Yeast Van by many. This year Hop Circuit is hosting its 3rd annual open-door self-guided brewery tour on Sunday, April 22 from 1-5pm. During this time you can choose the breweries & distilleries (out of 17 total participants) that you want to visit and join in the various festivities as desired, or not and just fill yourself up with beer. Activities include behind-the-scene-tours, food trucks to keep you fed in between stops, and even a scavenger hunt to further increase your knowledge and enjoyment.

    The challenge

    With 17 breweries and an nearly infinite number of combinations of breweries & distilleries to visit in 5 hours, how does a participant at Hop Circuit tour and drink as efficiently as possible??? Well if there ever was a functional use for geospatial analysis, this surely is it.  Read below for what we did or jump right to the app if you can't stand to read an explanation. 


    To support your participation, we have tackled the traveling salesman problem (errr. traveling beer crawler problem), in other words finding the shortest possible route between all location combinations to optimize travel time.  Our results are presented in this app here to assist you in a) attending the event, b) hitting up as many breweries as possible in the most efficient manner, and c) to reduce the stress of planning where you are going, as well as travel during the event.

    How you get to Hop Circuit is up to you but leave the planning to us and we will make sure you get the most brewery out of your Yeast Van adventure! Follow these simple steps to make it your best Hop Circuit:

    1)      Choose a starting brewery on the right side of the map;

    2)      Decide how many additional breweries you want to visit during the time that you have and select that number to the right of the brewery numbers;

    3)      Watch the map pick the most efficient route to hit breweries near to your starting point;

    4)      Enjoy the day!


    Solving the traveling beer crawler problem is actually quite tricky and there are even whole journals devoted to route optimization.  With 17 stops and literally millions of combinations, we had to find some solution that saved us on processing power and reduced the number of optimization solutions.  While we here at LGeo has aspirations of genius even this one had us stumped.  Thankfully, there was easy way out, which is to simply brute force our through the calculations with a little help from some python combination libraries and some educated reasoning in route choices.  The results are functional and it only took us about two days in total to run the calculations. Check the figure below for all of the combinations with the optimized routes shown on top!


    For fun we used our GIS wizardry and calculated the optimal location for a pretzel cart, dependent on projected highest volume of foot traffic based on all breweries experiencing equal patronage throughout the day. To do this we took our optimal routes data created in the work above and used the a density tool to find the routes that are most commonly suggested by our web app. Tada – time to perfect your pretzel making abilities and make use of our analysis for pretzel volume sale optimization (you have two days!).

    Optimal location for a pretzel stand April 22nd, 2018: Franklin and Commercial. Grab the mustard!

    As always, comments, criticisms and kudos preferred though not in that order!

    Happy beer touring and travel safely!


    Assessing the Impact of a New Site for Vancouver's Daytox/Detox Centre

    While bopping around in the twittersphere the other day, something I tend to do after my toddler is put to bed and a calm descends on our home, I came across a group concerned about the proposed site for the relocation of Vancouver's Daytox/Detox programme. My brain started mulling over the issues that they had raised and I couldn't shake the feeling that this required a closer look - which of course includes my good old friends: Spatial Analysis and Maps, which is why we are here. So here we go... 



    The current location is at 333 E 2nd Ave and is a Vancouver Coastal Health facility that offers outpatient withdrawal services for those aged 19 and older. Withdrawal programmes offered here last 6-weeks, are medically monitored and include a variety of resources such as counselling, acupuncture, and other services. 


    The proposed site at 1636 Clark Drive will provide a new, updated home for these services and will offer inpatient withdrawal support, which the current site does not, as well as housing through a mixed use development that is 5 stories high and provides 60-100 units for long term stays, and 20 short term beds for those who have completed the treatment. Additionally, BC Housing has proposed to offer social enterprise programmes, culturally appropriate services relevant to the neighbourhood, as well as be a teaching and knowledge sharing facility for staff and health providers. All in all, this proposal is an important improvement for those seeking support in their addiction and beyond.


    That said, there are concerns from a residents' group have regarding the new location and the impact on the neighbourhood that are both legitimate and persuasive, and include: 

    • Another BC Housing development less than 100m away from the proposed site and within 2 blocks there are almost 200 existing BC Housing units;
    • Safety for seniors, children and property due to the proximity of those being offered addiction related services; and
    • The building height shadow and potential to dwarf adjacent buildings.

    In an effort to add clarity to what is sure to be an emotional issue, and to understand the potential effect of the site compared to the perceived impact, let's take a closer look at these concerns through an analytical lens mentioned in my opening paragraph...


    According to listings on BC Housing's website, there are 374 buildings in the City of Vancouver that they oversee. These range in type of housing from low income family housing to seniors supportive housing, and everything in between (or at least pretty darned close). Buildings range in size from 3 units - a housing cooperative - to over 450 units - a subsidized housing option for seniors and those with disabilities.

    To satisfy my curiosity raised regarding the potential site, I needed to calculate the density of units and crime per hectare as can be seen in two maps below. To accomplish this I calculated the density of  both BC Housing units for the below illustration and crime points as reported by the City of Vancouver (2017) further below.


    Image 1: BC Housing Density of Units/ha - comparing current levels (brown) to proposed levels (blue).


    Reviewing the maps above, as well as the data that is produced alongside these visualizations, it is notable that there are numerous pockets of BC Housing density (the map coloured yellow to brown) scattered throughout the City as well as in Grandview Woodlands somewhat proximal to the proposed site. That being said, it is hard to argue that this area represents the highest concentration of BC Housing units in the City! The densities of BC Housing units in the Downtown Core, Strathcona, and Downtown South and the West End are nearly double that of the light brown blob Southeast of 1st Ave. When we take a look at the effect of the new development (blue blobs), we can note that there is a small change in the overall density of BC Housing units in the area, but again not a tremendous effect when compared to the rest of the City.

    Another way to look at this data is to take a look at the relationship between population density and density of BC Housing units. In an ideal world, each part of the City would have an equal proportion of BC Housing units to that of its total dwelling stock. However, we all know that is not the case. We ran some analysis on this which is presented in the scatter-plot chart below. The left axis is BC Housing dwelling density and the bottom axis is population density.  Areas that are below the trendline (the dotted line that represents the relationship between Units and Population) are seeing less BC housing units than would be expected for their populations given the relationship depicted in the graph and areas above the line are showing more BC housing units than expected. In this instance we see that Grandview Woodlands is punching a bit above its weight in terms of BC Housing units versus population density, but it is in a similar league to Killarney in Southeast Vancouver, and is totally dwarfed by Downtown and Strathcona, which have the bulk of BC Housing units in the City

    Figure 1: Graph showing the relationship between densities of BC Housing units and overall population density.

    Figure 1: Graph showing the relationship between densities of BC Housing units and overall population density.


    The next thing to look at was whether or not we could draw any causal links between the existing Daytox/Detox site and non-violent crime rates in the area. This was to address the statement that the new location of the site may lead to concerns with regards to the safety of children and seniors due to the proximity of addiction-related services. The two questions to answer are: Does the current facility generate a lot of crime and what is the current crime baseline at the location of the proposed site?

    Image 2: Density of Reported Crimes/ha

    Image 2: Density of Reported Crimes/ha


    In the above visualization, it is of note that there is no real crime "hot-spot" around the current site (red blobs indicate high crimes per hectare). While the density of crimes is generally higher in the area compared to Mount Pleasant as a whole, we could not draw any conclusions that they were being driven by the Detox/Daytox site. We should also note, that this a very high-level analysis, indeed a whole thesis can be written on the effects of addiction-related services and criminal activities (or any mislabeled "driver" and criminal activity for that matter). However, at this high-level it is inconclusive to suggest that there will be a reduction to personal safety were the site to be moved. 


    The following analysis is to explore the shade that the proposed building will cast on the neighbouring parcels and if and how much it would "dwarf" the neighbouring buildings. In the following images you will see our very rough 3d model of the proposed development, as well as a solar modeling based on angle of the sun and daylight hours and other objects that currently cast shade (namely trees and buildings) on surrounding properties.


    Image 3: Before and after sketch of location and height of proposed building.


    First Avenue between Clark and McLean is a very steep street. Based on the only high level sketch we could find of the site, it appears as if the structure will be approximately five stories at Clark and maintain a uniform roof line towards to McLean. In terms of massing, the site will be bigger, but the slope of the street and the presence of mature full foliage trees will do much to blunt this impact.

    In terms of shading, the analysis is a bit more interesting. The two images below show a before and after sketch of what the total hours of sunshine will be at the location based on a solar model run for May 20th (a theoretical sunny day in spring/summer). Red colours indicate higher levels of sunshine per day and blue colours indicate fewer hours of sunshine per day. For example, with a quick glance it is easy pick out the shade cast by trees as dark blue and the red as open areas that get many more hours of sunlight.


    Image 4: Before and after prediction of building shadow based on the height of the proposed building at 5 stories.


    Based on the analysis, it was noted that there was increased shading mostly in the alleyway directly behind the proposed development and and to the west of the site on Clark Drive. There is not a lot of shading and infringement on neighboring properties due to two factors: first the site slopes off very steeply to the East, as shadows mainly fall in a Northeast to Southeast arc, and the shadows are basically eaten up by the hill. Second, the trees along 1st are very tall and have quite full foliage. These (if they are retained) already block out significant amounts of sunlight in this area.

    To get a a more complete understanding of the impact, the next step is to compare the two cases directly by estimating the total loss of direct sunlight on May 20th (Image 5 below). In the image below, lighter colours indicate fewer hours of sunlight lost and bluer colours indicate greater amounts of sunlight lost. As has been mentioned, there will not be a tremendous amount of change on any neighbouring properties. Indeed, in terms of placing a big blocky building anywhere in Vancouver, this would have to be one of the best sites for reducing impacts to shading and sunlight.


    Image 5: Estimation of total loss of direct sunlight hours.


    From the above analyses the following outcomes were gathered:

    • Another BC Housing development is less than 100m away from the proposed site and within 2 blocks there are almost 200 existing BC Housing units:  True but this is a drop in the bucket of BC Housing units in the City overall. Second, there are many other areas that have higher densities of BC Housing units.
    • Safety for seniors, children and property due to proximity to addiction related services: We did not note any large crime hot spots around the existing facility, therefore we cannot determine if there will be a negative impact to the safety of seniors, children and property due to the proximity of addiction related services.
    • The building height shadow and potential to dwarf adjacent buildings: Given the site conditions, the building will certainly mass larger than adjacent buildings but will have a lowered impact with regards to shading

    In summary, what was attempted here is to include some data and analysis to answer potential community concerns. Many of these will be addressed in the coming days and months by project stakeholders as the project moves forward (note: we are not part of this project at all), but at the outset it is hoped that analyses like these will be employed by all parties to better craft the design process for this site. As always, questions, concerns and comments are welcome and appreciated!

    Exploring Urban Change Through Population Density

    So, after an epic break from blogging, Licker Geospatial Consulting is back at it, with a nice new post on our favorite topic, Urban Change!

    Part of this has been spurred on by our recent collaboration with the fine folks at Renewable Cities. With them, we've been looking at changes in population dynamics over time in Metro Vancouver, British Columbia and other Major Canadian Municipalities. This post will show off something similar but will be more related to how we can possibly understand multi-temporal, multi-variate changes through some nifty mapping.   

    Now as many of our past and current collaborators know, Licker Geospatial Consulting cut their teeth in urban planning and then did a right angle turn into environmental planning and earth sciences (and then some sort of squiggle into geospatial consulting!). One of the coolest things about the earth sciences (i.e. geotech) is the use of cross sections to comprehend and visualize multi-dimensional data. Now because urban planners need to fancy things up all the time, they took the humble cross section and renamed it: The Transect (Thanks DPZ) The transect is, of course, totally awesome and very useful to help planners systemize urban environments. Very rarely, however, do we see the transect used as a tool for urban analysis and information synthesis.  Even more rarely do we see transects used to understand temporal change. What we want to achieve with this post is to show how a transect, or cross section can be employed to understand urban spatial-temporal change and possibly the influence of mass transit on urban development.

    Let's Talk Data

    (Non GIS nerds please skip to the next heading) As mentioned, through my collaboration with Renewable Cities, I've been amalgamating an awesome longitudinal set of census data (specifically population) for all of Canada. These data are great because they represent a controlled and assured set of measured data that is mostly comparable across multiple years. For this little post, I've focused my efforts on the lower mainland, but there is nothing stopping us from seeing how things have changed in any part of urban Canada, really. What we are using for inputs are Census Enumeration Points, Census Dissemination Areas, or Census Dissemination Blocks, depending on the year. Comparing these data is not as easy as just overlaying all these polygons into a massive set of longitudinal greatness, indeed what's really annoying (but inevitable) is that all of these blocks or areas are not the same size, shape or even types due to the fact they were created to administer Census data not to allow for cutting edge analysis, alas...

    A big data jumble, 1971 data are light blue polygons, 1981 and 1986 data are light and dark blue points respectively, and 1991, 1996, 2001, 2006, 2011 and 2016 data are purple, blue, red, black and green respectively... Nothing matches up!!

    A big data jumble, 1971 data are light blue polygons, 1981 and 1986 data are light and dark blue points respectively, and 1991, 1996, 2001, 2006, 2011 and 2016 data are purple, blue, red, black and green respectively... Nothing matches up!!

    Transforming these data into information that we can actually use requires some generalization and interpolation. The quickest and easiest technique out there is to use a kernel density function on the centrepoints of each dataset so at least everything is on the same scale and in area density (which is what we wanted anyway). In plainer  English, we made everything into density surfaces. Once I had these generated, we got even more clever and interpolated between years to generate this mesmerizing beauty below (but that's another blog post)....

    Where's the analysis already?

    So we got the density by year and you'll note we found some Skytrain lines somewhere. It's time to run some sections! Cross sections are pretty cool because they allow us to view overlaid data along a common axis, which greatly enhances our ability to synthesize data at a glance (In English again: lots of data quickly). What we did was: first, measure the change in population density between 2016 and 1976 (40 years of change: superb!) to develop an overall understanding of change, and second we used some GIS wizardry (go to the very end of this post for the method) to develop sections by Skytrain line. The results, with a little bit of interpretation are displayed below for your amusement and edification (click to expand all figures).

    The Expo Line

    Let's walk through this slowly. First the rainbow of colours on the top figure represent change in population density, as expressed by the average number of people per hectare within an 800m neighborhood. Areas that are red are where the population has actually declined in the past 40 years and areas in brown are where it has increased (sometimes a lot!). The bottom graph shows the population density along the line starting at Waterfront Station to the left and ending at King George Station to the right. Each line represents the population density at that particular year. The Expo line was more or less completely built out by 1995, but change along the route has varied tremendously by station location. First note that between 1976 and 1986 there was almost no growth along the line! (astounding in this day in age!) However, post expo things started to change mostly around Joyce Station and New Westminster. After 1996 there was a ton of development around the Edmonds and Joyce Skytrain stops as well as in Downtown Vancouver (certainly related to de-industrialization and the Skytrain). After that development boomlet, you'll notice that the next big changes were both in Downtown Vancouver and in Surrey which saw the most growth in the 2006-2016 period. There are some other cool things to note: population density has not materially changed much at Nanaimo station, 29th Avenue, 22nd Avenue, and Scott Road (I would love to look at changes to employment though!). 

    The Millennium Line

    It's a different story for density along the M line (and the sneaky extension I added in there) than the E line, that is for certain. First, you'll note that residential density increased very little in the City of Vancouver in the past 40 years along this line (likely because most of the existing M line route is still surrounded by active Industrial Land, for the most part, as well as by low density residential lands and the new M Line extension had not been built yet). However, Burnaby is a different (and interesting story). First, Skytrain induced development caused population density at both Gilmore, Brentwood, and Holdom to increase from effectively 0 people per hectare in 1996 to about 75 persons per hectare in 10 years! There's been a similar rate of change in Central Coquitlam as well. Another interesting density spurt is at Loughheed Town Centre which had a huge boom between 1976 and 1986 that didn't happen anywhere else along the line (this was basically due to an attempt at highway oriented multi-family development!). Finally, it looks like Moody Centre and Coquitlam Centre are due for booms given the recent Evergreen line extensions. 

    The Canada Line

    So, a drawback from similar scales between these three figures means that population density at the Yaletown Station is literally off the chart! To properly understand this change just note that in 20 years, the population density at Yaletown Roundhouse has increased from 100 persons per hectare to 245! (and was 0 in 1986!!!) Nothing else in the lower mainland even comes close. Take, for instance, the stretch between King Edward and 41st Avenue, basically zero change in 40 years. Richmond has seen some pretty big changes in the past 20 years but an order of magnitude less than Vancouver (likely flight path/flood plain induced). Now, more than any other graph we've looked at in this little assessment, this one will change the most in the next 5-10 years as there are big changes underfoot in the Cambie Corridor area, so stay tuned for a follow up blog post in 2022 ;) .

    Some Sort of Conclusion

    As with all of our posts here, we are trying to highlight an application of geospatial analysis that can help us make better urban planning decisions and understand our urban environments. The next time someone questions the transformative impact of mass transit coupled with de-industrialization then all you need to do is show them these graphs and explain what a cross-section is. (if only it were that easy). That being said, all this work is exploratory in nature, but super fun to do, so if you feel the need to conduct some longitudinal urban analysis then feel free to drop a line to  If you want to pick this post or our methods apart, the comment section is below!

    Finally, Nerdy method for making the graphs.

    Simply put the method is to: first interpolate the vertices of a line against a surface and then plot those those interpolated values as y values on an xy graph where x values are measured and scaled against the length of the line!


    Metro Vancouver 1968 - An Amazing Window Into Regional Urban Evolution

    Because I cut my teeth as young GIS analyst supporting land use planners, I am huge sucker for old land use maps.   Recently, my old colleague Peter Russel from the City of Richmond found an amazing copy of Development in the Western Portion of the Lower Mainland Region, 1968.   How amazing is this map? Well for starters, it is completely packed with information, its super well designed, and it was drawn up almost exactly 50 years ago!

    While it's unlikely that the young draftsperson who constructed this map in 1968 actually reads LGeo's blog, if you are out there and reading this, then please know that your work has stood the test of time! Take a look at the gorgeous map below and tell me if you disagree. (full size 20mb version can be found here)

    Now the reason why I really love this map, is that it provides an extremely valuable perspective on long range land use planning and the evolution of our urban environments.  That is to say, if we know how much things have changed in the last 50 years, we can start to grapple with the profound challenge of figuring out the next 50.  To do this, we can use a bit of fancy GIS and can run some fairly cool analysis on this map to figure out how things have changed.

    The western portion of the lower mainland region was a different world compared to Metro Vancouver

    The first thing you notice is how much influence the Fraser River had on the development of our region.  In 1968, the original Port Mann Bridge had only been constructed four years prior in 1964, the Massey Tunnel had only been around since 1957, and only the venerable Pattullo Bridge had been standing since 1937.  These lack of connections were likely one reason why the population south of the Fraser River was so small.   Second, you can notice how agricultural lands are relatively unchanged since 1968, likely that is due to the implementation of the Agricultural Land Reserve which was established in 1974.  Finally, notice the primacy of roads and highways on this figure.  By the time this map was produced, our region was completely ensconced in the world of motordom. Cars were the mode of choice on this figure and it shows.  Rail lines are shown but faintly and only fragments of the interurban lines can be inferred from the very interesting place names scattered throughout Metro's suburban communities.

    Contrast this map with Metro Vancouver's Regional Growth Strategy map here.  You'll note that roads and highways are completely de-emphasized with a focus instead on transit and multi-nodal development has supplanted land uses. 

    Use the simple application below to explore the figure. I've found that by fiddling around with opacity of the figure (or the extracted data), it becomes really easy to see what has changed.  Once you are done panning zooming and overlaying, check out the discussion below for some insights into the evolution of our region.

    adjust overlay opacity:
    • Swap Overlay

    Spatial analysis & Discussion

    As mentioned, this figure is full of information.  The clear colors, well positioned labels and highly accurate mapping render this map well positioned to produce informational champagne.  However, old figures like this one do not yield their information without a digital fight! I had to spend a fair bit of time, extracting, digitizing and correcting the data to transform the information from paper to silicon.  All that being said and done, I've managed to create a reasonable dataset from this figure with the following standard (and very important caveats):

    • Extracting digital data from old figures is a profession in of itself. I'm not an expert in this area and I am sure that others couple likely do a better job. That being said I used a simple interactive supervised classification system coupled with some aggregation and manual correction to try and extract all the land use types. If you can't read GIS, in English what I did was pull the colours of the map and make some assumptions about things I couldn't see.
    • There is no way for me to easily verify the veracity of this figure.  That is to say, some of the information could just be plain wrong, out of place or simply ambiguous.  I just don't know because I was neither alive nor present in  the Lower Mainland in 1968. So, calling all baby boomers: I insist that you check to see if Sullivan Station and Essondale were places.  Also take a look at Sea Island, note the mystery community there?
    • All area totals are super approximate and based on my digitization. Therefore, please do not live or die on the fact that I've noticed there was approximately  427.5 sq km of agricultural land depicted on this figure in 1968.  By the same token, please enjoy the fact that there was apparently 487.4 sq km of agricultural land in 2011 but do not quote the 546.3 sq. km total I've used that corrected for right of ways (more on that below).

    So, what do we know about the Lower Mainland Land use in 1968 (note, this is chopped  down to MV boundaries, and does not include the Northern Parts of West and North Vancouver as well as Bowen Island):

    Designation Total Area (Sq. Km.) Percent of Area
    Agricultural 427.6 20.1%
    Civic and Institutional 43.0 2.0%
    Commercial 21.8 1.0%
    Industrial 35.3 1.7%
    Residential 262.5 12.4%
    No Designation 1,201.3 56.6%
    Parks and Recreation 131.3 6.2%

    Somewhat interesting... But the temporal analysis is even more interesting.  For instance, how much has the residential footprint grown?  Have we really deindustrialized?  what about outdoor space?  To answer this, as mentioned I've done some work to get the 2011 MV Land Use data in line with the 1968 version.  Some notes.

    • For both 1968 and 2011, I've conflated parks and recreation with no designation as MV 2011 has created this unfortunate category: Recreation, Open Space and Protected Natural Areas
    • Because the 1968 dataset does not have road right-of-ways (ROWS) as a designation, I've had to roll ROWs into all other categories proportionately in the 2011 dataset and inflate land use numbers by approximately 200 sq. km.
    • 2011 mixed use res/commercial has been reclassified to residential; and
    • 2011 extractive industries has been reclassified into no designation because that's how they were treated in 1968...

    With those additional caveats in mind. treat yourself to 50 (...err 45 ) years of land use change!

    Designation 1968 Area % Land Base Modified 2011 Area % Land Base % change in area (1968-2011) Change in area
    Agricultural 427.6 20.1% 546.3 25.6% 27.8% 118.7
    Civic and Institutional 43.0 2.0% 53.0 2.5% 23.4% 10.1
    Commercial 21.8 1.0% 33.2 1.6% 52.3% 11.4
    Industrial 35.3 1.7% 82.3 3.9% 133.3% 47.0
    Residential 262.5 12.4% 473.7 22.2% 80.5% 211.2
    No Designation 1,332.6 62.8% 945.4 44.3% -29.1% -387.2

    So here are some fun takeaways for you to debate with me:

    • Residential land has increased by 211sq. km. or 80% Population increased by 1.5m (about  900,000 to 2.43m) or 170%, ergo we've sprawled out but we are also more dense than 1968 - despite an addiction to motordom!
    • Industrial land area has increased considerably, Notably, Vancouver's industrial areas have shrunk while Surrey's and NE Sector(especially along the Fraser) have grown dramatically. 
    • The ratio of commercial to residential lands has slipped somewhat from 8% to 7% (this may be offset by an increase in industrial and mixed land uses), suggesting that commercial land use demand is linked to residential growth.
    • Lands considered as agricultural (who knows what the Non-designated lands were in 1968!) appears to have increased; suggesting that the ALR has been effective in preserving agricultural lands... (I would love to see more data on this to see if this is the case!)

    I could go on, and there are probably many more facts and nuggets that you can glean from the data.  So put on your analysis hat because I want to hear them! Please send me your comments, corrections and considerations; because information like what I've exposed above starts conversations that will inevitably allow for better planning and decision making.




    How Large and Dense Are Canadian Cities? A Visual Comparison

    So, certain parties have recently let me know that some of my blog posts are slightly too nerdy for the general populace.  Considering how much I love extra complex analysis this isn't surprising. However, my goal is to bring GIS to the general public, and I don't want to miss that goal due to some excessive detail.  Therefore, I've tried to make this week's blog post  by focusing on something that we've all thought about, but never mapped:

    How big is my city anyway??

    Why this is an interesting question is that there is lots of information on how big or populated a Canadian city is (for instance here), but the units: square kilometers and persons per square kilometers are not so comprehensible to your average human.  

    Second, its hard to relate these data without an comparison, so what if Vancouver has 5,491 people per km2, what does that actually mean and look like and more importantly how does that compare to say, Regina?

    After some noodling around on the interwebs trying to answer this question, I stumbled on this excellent website which allows for country to country comparisons of size . And then I realized what I had to do: Show the true size of Canadian municipalities by using Vancouver as the lucky comparison town.

    What I've done then, is simply overlay Vancouver (respecting projections and the such) on various Canadian cities to show how huge and comparatively underpopulated they are compared to my favorite city.  I've presented the results below: you can click on each thumbnail to get a larger version for your viewing pleasure.

    The coolest part of this little project was, at the outset, I had no idea how small Vancouver was compared to some other Canadian cities.  Or more to the point: how big are other Canadian Cities!  You'll also note that Ottawa and Halifax are slightly odd.  That is because they are regional municipalities that encompass A LOT of underdeveloped space.  Comparing areas and densities to these monsters isn't really an apples-to-apples comparison, so I've tried to chop them down to size using some older municipal boundaries.

    All data sources are from the current Census of population. Also if you notice any errors or omissions let me know and I'll update the maps quickly. Happy map viewing!


    Safe Access To Every Playground in Toronto

    So after a reasonably long hiatus, I'm back to blogging; this time about population access and playgrounds in Toronto. 

    Why I am keen on this topic is: (1) As a new parent, I am starting to get interested in play and play spaces.  Seeing as how I will be visiting Toronto in June, I (non-altruistically) wanted to find out where is the best place to visit with regards to playground access for my energetic toddler; (2) I wanted to showcase some of the new (and awesome) Census data; and (3) I wanted to draw attention to what can be accomplished with Toronto Open Data. 

    So given the above interest, I was able to generate some very interesting questions around playgrounds in the City. For instance:

    1. Where are all the playgrounds in the City of Toronto and how do I get that data?
    2. Where are the best and worst parts of the City for play access for young people (0-14yrs old)?
    3. Which parts of the City are the particularly challenging from a play access standpoint (ie where is there much potential walking travel along busy roads)?
    4. Which areas of the City may benefit from new infrastructure?

    Thankfully, getting this information mapped and analysed was not too great of a challenge, thanks, once again to the good folks at open data Toronto.  In any event, I needed a few things to get started with this analysis:

    First, I searched for a playground dataset - which I found here.  However, this was not all the playgrounds in the City, only ones located on City land.  To complete my set, I added in all  of the non-overlapping locations of junior or elementary schools in the City. (operating on the assumption that most, if not all, elementary schools have playgrounds).  I combined the two datasets, and spent about 10 minutes reviewing the data.  Check out the map below, (and please let me know if I missed any or added in an unnecessary locations).  

    Where Are The Children

    Once I had the playgrounds mapped, I then set about figuring out how kids would possibly walk to these play spaces. Safe walking to school is a big deal these days, however, safe walking to playgrounds - because they are often co-located on school grounds - is less well analyzed.  Nevertheless, the general consensus is that a safe walk to a playground should be short, protected and accessible.  Given the rising number of pedestrian fatalities in the City of Toronto, I thought that by taking an overview level approach to access, I may be able to isolate less safe areas for walking and see how these intersected with potential walks to playgrounds.

    To generate these walks, I used the newest release of census data (Age by dissemination areas!), and mapped out the concentration of young people (age 0-14) in the City.   In response to some other commentators out there, there are still A LOT of young people in the City of Toronto, with the highest densities being located in the Yorkville, Thorncliffe, and Woodbine Gardens Areas...

    MINIMUM Access

    The next step is to get "geo-nerdy" and figure out access.  As mentioned in previous blog posts, this is best accomplished through the creation of pedestrian walking network and running a nearest location algorithm.  Thankfully open data Toronto to the rescue once again, a great singleline road and trail network set exists here.  Building the network was a snap.  and from that I was able calculate how far each population point was in time (as the kid walks - 77m/minute) from each playground location.   The findings are heartening. 44% of Children live within a 5 minute walk of a playground and 88% of all children in Toronto Live within a 10 minute walk of a playground. These are excellent numbers... but there is more to analyze here!

    Diversity of Access

    As we all know children do not walk to their closest playground but typically pick from what is local.  I therefore also mapped which parts of the City have the access to highest number of playgrounds in the City (see figure below). The findings are pretty interesting: 

    • 88% of children aged 0-14 live within a 10 minute walk of at least 1 play facility;
    • 66% of children live within a 10' walk of at least 2 play facilities;
    • 42% of children live within a 10' walk of at least 3 play facilities;
    • 10% of children live within a  10' walk of at least 5 play facilities; and
    • 0.7% of children live within a 10' walk of 8 or more play facilities

    Safe Access

    So, now we have a reasonable idea of access. But as I mentioned, what I am really after is safe access to playgrounds.   What I wanted to highlight then was the shortest paths to playgrounds that run alongside, or cross a major arterial.  Thankfully there are not many of these but they bear investigation. First, based on the theoretical 3,702 trips to their closest playgrounds, I noticed that 10% of all these trips in terms of distance run alongside major arterial roads, 17% along collectors, 52% along local roads and only 7% along trails. In terms of trips, 18% of all shortest path trips travel some appreciable distance (50m+) along major arterial roads.  

    That being said, walking alongside a major arterial, is not nearly as dangerous as completing a crossing.  I recently read an interesting article that basically states that Children up to their early teenage years had difficulty consistently crossing the street safely.  I'll let you read the article, but suffice to say, crossings are important... Therefore, based on my preliminary analysis, it seems that 15% of all trips involve at least one major arterial crossing to get to a playground.  Now, full caveat here, I am looking at theoretical shortest path routes and not actual routes.  In reality, many children will not take the shortest path to their local park but the safest path... However, with that in mind the figure below is still indicative of potentially dangerous crossings.

    bonus: which areas are spoiled for choice and where could the City benefit from a new play facility or two

    If you managed to read this far, then you are certainly into geospatial analysis, so here is one more for you. Basically, with all of these data we can also find out which areas of Toronto have more playgrounds to access within 10 minutes given the population of children in the City.  If that didn't make any sense, let's try this way: I am trying to locate neighborhoods where the expected density of playgrounds is less than the expected density of children using a 10 minute walkshed.

    To make this analysis happen, I found out for each dissemination area what is the total population of young people within a 10 minute walk as well as the total number of playgrounds.  I then divided these two numbers (and divided population by 100) to get a measure of playgrounds per 100 children within a 10 minute walking distance.  I then layered on locations of under-serviced densities to gain a full picture of access plus playground and population density. The output is pretty cool,  if a little busy.  To read the map, you can either look for green areas that have many playgrounds per 100 children (these could be areas with too many facilities), or look for the black areas that have no playgrounds and therefore have under-serviced populations (these are ares that may require facilities).   Areas that are orange are basically at the mean of 0.7 playgrounds per 100 children within a 10 minute walk!

    As with all of my work, please let me underscore that this all preliminary analysis, subject to change.  yes, it looks professional and cool, but this is work done on my own time, between projects, and therefore may be subject to validation and analytical errors that I have not been able to suss out.  Please recognize this when you review or share this work. As always, comments are more than welcome! 

    Every Sunny Patio in Toronto - Mapped

    Now that, for the most part, the horrible months of winter are behind us, we can turn our sun starved gazes towards the most cherished of civics amenities.  Yes, I am referring to those unique public/private spaces: our Canadian patios.

    You see, I have simple goal here at lgeo and that is to get GIS information to the masses as quickly and as efficiently as possible.  And by GIS information, I mean: Beer, in the sunshine. So, with that lofty goal in mind, I've managed to make a good start on this, and will have an app to help sort out thirsty Canadians in the medium term.  

    For right now though, I'll walk you through one case study of patios, sunshine and all good things GIS.

    The Toronto Case Example

    To find sunny patios anywhere, we need some data to start with.  Fortunately for us, the open data revolution is making this easier than ever before.  Presented below is the sunny patio recipe that I've cooked up to make this happen:

    • 1 Massive buildings dataset with heights that is reasonably up-to-date;
    • 1 digital elevation model of reasonable accuracy and precision;
    • 1 list of every patio in town;
    • and the capacity to build a solar shading model for an entire day at regular intervals; and
    • some GIS wizadry to put it all together!

    See, so easy! Now, thanks to the very good folks at open data Toronto,  I've managed to locate  a great list of businesses with patios, an awesome buildings dataset and the aforementioned elevation model.  I've got the last two bullets down pat so here we go.

    The hardest part of all of this was getting the patios in the right spot.  Patios come in many flavors including roof patios, back patios, side and front patios, arcades and random corporate office balconies.  And in case you were wondering, Toronto has like 1,400 of these so that took some time.  Thankfully, GIS is really good at automating data management stuff like moving patios off of the middle of buildings to the block face so it wasn't too bad. Just in case you wanted to get an idea of the level of accuracy that I needed, here are some shots of how well these things are located (Torontonians see if you can guess the street in the comments):

    Side Patios

    Side Patios

    Front and back patios

    Front and back patios

    Anyway, once I had the patios down, it was time to tackle the buildings and the associated shadow model. Full disclosure, there is some IP in here so let's just assume this was more or less magically created. However, the takeaway for how do this can be found on this amazing link here (full disclosure I am not as excellent as the NY times).  In any event, I've managed to create the map below for the June 6th prime patio day (use the sliders to change time of day, scroll wheel zooms in and out, click to pan):

    Select the time of day:
    adjust shadow opacity:

    Once the shadows were completed, the next step was to figure out at what time of day any patio would be in the sunshine.  Some more semi-secret GIS later, we have  all of the data ready to play with in the map below.  Reddish circles mean that the patio is in full sun, blue circles mean the patio is in partial sun. Have fun with it, you can use the street view links to hopefully find the patios (I'm working on the view angle that will be added later).  

    Select the time of day:
    Patio Solar Exposure
    adjust shadow opacity:

    As always, I need some help with the exact location of these patios so any crowd sourcing of errors is appreciated.  And if you wondering, the beta app of this mapping will be released on android and iphone before summer kicks off.  Just in time to help you find your sunny patio as easy as possible.


    #SakuraMap - A Cherry Guide To Vancouver's Bodacious Blossoms

    As I have mentioned previously, I am a hopeless romantic who can't stop mapping intriguing things.  So, while developing new analytical approaches for measuring urban vitality is interesting, perhaps far more approachable is mapping and analyzing Vancouver's abundant and life-affirming cherry blossom trees. 

    Now, while the fine folks over at the Vancouver Cherry Blossom Festival, have an excellent website and a great map of some favorite trees, they don't have any handy cartography that can be used to tour the blossoms. So, much like the map I made to help folks ride the ales, I figured I would use the integrative power of GIS to make some figure that would help people find the trees they love at the right time of year.

    Every Flowering Cherry and Plum Tree in Vancouver...

    This is actually, less easy then you might imagine.  Many do not know this, but there are more than 29,000 cherry (and plum) trees in this fine City. Viewing all of these trees on one map, at one time, is almost impossible.  However, from a little bit of research, we do know when most species have historically bloomed in the City. Using blooming period averages I found at VCBF, I was able to determine, on average, how long after the first blossoms of spring every other tree followed.  The results are a basic blooming timeline that can then be sequenced into an animation, slide show or movie for easy review and use in the field. 

    The result are the slides and movie below.   What I've tried to do is use "best-available" data to create a best guess at when and where you can find blossoms this spring.  Now, I know that this map will not be accurate, so I want to try some participatory GIS to make it better. If you see a tree that is, or is not blooming according to my map, take a photo with your phone's GPS turned on, email it to me, and I will use that information to make my maps better.

    In the meantime, enjoy the #SakuraMaps and happy blossom viewing!

    UPDATE --- Please use this map here, to review in detail where things are blooming. Drop me an email if you find something out of whack.

    Blooming Gallery

    Blooming Movie (download here, animated gif available here)

    Bonus Analysis

    The maps above are great, but I wouldn't be doing my job as an analyst if I couldn't mix in a bit of decision support:  Therefore, I ran a quick analysis to find the best bike routes for each day of #VanSakura based on total number of trees and blossom trees per km/bike lane.  Please be advised that the list below is contingent upon a nicely spaced blooming schedule.  I'll update it as real data becomes available.

    ID Date Bike Route Name Total Sakura Count Bike Route Name Trees / KM
    1 March 19th North Arm Trail 221 Haro 31.3
    2 March 20th North Arm Trail 220 Haro 31.3
    3 March 21st North Arm Trail 220 Haro 31.3
    4 March 22nd North Arm Trail 220 Haro 31.3
    5 March 23rd North Arm Trail 220 Haro 31.3
    6 March 24th North Arm Trail 220 Haro 31.3
    7 March 25th North Arm Trail 220 Haro 31.3
    8 March 26th North Arm Trail 220 Haro 31.3
    9 March 27th N/A 0 N/A 0.0
    10 March 28th N/A 0 N/A 0.0
    11 March 29th Bute 2 Bute 2.6
    12 March 30th Bute 2 Bute 2.6
    13 March 31st Bute 2 Bute 2.6
    14 April 1st 63rd Ave 22 63rd Ave 17.2
    15 April 2nd 63rd Ave 22 63rd Ave 17.2
    16 April 3rd 63rd Ave 22 63rd Ave 17.2
    17 April 4th 63rd Ave 22 63rd Ave 17.2
    18 April 5th 63rd Ave 22 63rd Ave 17.2
    19 April 6th 63rd Ave 22 63rd Ave 17.2
    20 April 7th 63rd Ave 22 63rd Ave 17.2
    21 April 8th Off-Broadway / 7th Ave 16 Richards 3.9
    22 April 9th Midtown/Ridgeway 81 Rupert St 28.5
    23 April 10th Midtown/Ridgeway 81 Rupert St 28.5
    24 April 11th Midtown/Ridgeway 81 Rupert St 28.5
    25 April 12th Midtown/Ridgeway 81 Rupert St 28.5
    26 April 13th Midtown/Ridgeway 81 Rupert St 28.5
    27 April 14th Midtown/Ridgeway 80 Rupert St 28.5
    28 April 15th Midtown/Ridgeway 82 Rupert St 28.5
    29 April 16th Off-Broadway / 7th Ave 45 Chilco 8.6
    30 April 17th Off-Broadway / 7th Ave 45 Chilco 8.6
    31 April 18th Off-Broadway / 7th Ave 45 Inverness 7.4
    32 April 19th Seaside 53 Inverness 7.7
    33 April 20th Seaside 53 Inverness 7.7
    34 April 21st Seaside 53 Inverness 7.7
    35 April 22nd Seaside 53 Inverness 7.7
    36 April 23rd Seaside 53 Inverness 7.7
    37 April 24th Seaside 53 Inverness 7.7
    38 April 25th Seaside 53 63rd Ave 7.8
    39 April 26th Off-Broadway / 7th Ave 215 Rupert St 39.9
    40 April 27th Off-Broadway / 7th Ave 215 Rupert St 39.9
    41 April 28th Off-Broadway / 7th Ave 215 Rupert St 39.9
    42 April 29th Off-Broadway / 7th Ave 215 Rupert St 39.9
    43 April 30th Off-Broadway / 7th Ave 191 Rupert St 37.7
    44 May 1st Off-Broadway / 7th Ave 191 Rupert St 37.7
    45 May 2nd Off-Broadway / 7th Ave 195 Rupert St 42.7
    46 May 3rd Off-Broadway / 7th Ave 195 Rupert St 42.7
    47 May 4th Off-Broadway / 7th Ave 191 Rupert St 42.7
    48 May 5th Off-Broadway / 7th Ave 191 Rupert St 42.7
    49 May 6th Off-Broadway / 7th Ave 191 Rupert St 42.7
    50 May 7th Off-Broadway / 7th Ave 191 Rupert St 42.7
    51 May 8th Off-Broadway / 7th Ave 175 Rupert St 42.7
    52 May 9th Off-Broadway / 7th Ave 9 Rupert St 5.0
    53 May 10th Off-Broadway / 7th Ave 9 Rupert St 5.0
    54 May 11th Off-Broadway / 7th Ave 9 Rupert St 5.0
    55 May 12th Off-Broadway / 7th Ave 9 Rupert St 5.0
    56 May 13th Off-Broadway / 7th Ave 9 Rupert St 5.0
    57 May 14th Off-Broadway / 7th Ave 9 Rupert St 5.0
    58 May 15th Rupert St 7 Rupert St 5.0
    59 May 16th Rupert St 7 Rupert St 5.0
    60 May 17th Rupert St 7 Rupert St 5.0
    61 May 18th Rupert St 7 Rupert St 5.0

    Is Vancouver Dying? A Restaurant Vitality Perspective

    There has been much attention these days focused on claims that we have reached "Peak Vancouver" and our gorgeous city is now on the decline.  Stories of millennial migrations, absurd property valuations, potential bubbles, and of course, the million dollar teardown trend highly in our local news cycle to the delight of news organizations in our otherwise dull city.  

    But how much of this is media hyperbole and how much is fact?  Personally, I don't believe that Vancouver is dying and by two gross measures: our population and our economy, this City is doing very well. And more importantly, can we lump all of Vancouver into one giant failure bubble, or are there nuances to the vitality of this City?

    Perhaps a better question is: Are there geographic expressions to Vancouver's vitality? I've already commented on population dynamics in the City, locations of alienated desire and of course where to find good beer.  What else can we map then?

    Naturally, my thoughts turn to the service industry (restaurants) where two good ideas come to mind:

    1. We can measure the health of a neighbourhood's local economy through its retention of established business, specifically in this case, local restaurants. The theory here being that neighbourhoods with high restaurant survival rates are good places to do business (and therefore are nice to live in as well); and
    2. We can also measure local economic health through an analysis of economic growth.  In this case, we can look at the rate of formation for new restaurants in the City. The theory here being that neighbourhoods with high business formation rates speak to growing markets and exiting places to be.

    Before we go any further let's nail down these two concepts:

    • Restaurant Survival Rate - Percentage of all restaurants that were open in 2011 still open in more or less the same location in 2016; and
    • Restaurant Formation Rate - Percentage change in total number of active restaurants by 2011-2016

    Now, let's suppose that these two factors: restaurant survival rates and new restoraunt formation rates are not correlated.  If that's the case (and it is: r-squared of 0.0034!), then we can create a simple two variable model to classify the City:

    1. Areas where survival rates are low and formation rates are negative are likely areas that are, for lack of a better word, in decline. This means that in these areas long term businesses are failing and no new ones are taking their spots.  These are the doomsday neighbourhoods predicted by Vancouver haters.
    2. Areas where survival rates are low and formation rates are positive are likely areas that are experiencing rapid change.  In Vancouver the four letter term for this would be: gentrification (gtfn?). 
    3. The third category is where we have negative rates of new business formation, but high survival rates for established restaurants.  I don't have a great term for these hoods but we can call them static zones.  That is to say, existing places do well, but its tough to get a foothold in these areas
    4. Finally, we have areas where we have a growing number of restaurants and high survival rates of existing establishments.  These areas can be considered by any definition as being economically healthy.

    OK! Map it out already!

    The figure below shows the state of all of Vancouver's 1,498 class 1 and class 2 restaurants in business today plus the 196 that were in business in 2011 but were not replaced by another business at that location. Overall, Vancouver has a 62% five year survival rate which is pretty good. Vancouver also has a 9.2% overall growth rate in restaurants, which is excellent considering our population only went up by 5% (cheap credit perhaps?).

    Note the patches of green in International Village and Olympic Village...

    Some Analysis...

    To do some analysis, I made a layer comprised of Business Improvement Areas (BIAs) and the remainder of neighbourhoods based on some logical groupings to give me analytical samples of reasonable size.   Once this was done, I completed a simple overlay to get the following info:

    There is a lot going on in the image above, so let's discuss quadrant by quadrant (please note that I use the question mark here "?" to indicate that this is just my off-the-cuff analysis of the data. In no way am I placing value judgement on any of these neighbourhoods or BIAs):

    • Economically Healthy? By my definition, most areas in Vancouver have healthy economics for restaurants. Overall, most areas of the City are seeing greater than 60% five-year survival rates and within these areas, most are seeing growth through the generation of new establishments.  Really interesting is the Chinatown BIA - which ranks as the best place to have a restaurant in the City (68% survival rate and an astounding 55% increase in new restaurants over 5 years).  Second to the Chinatown BIA, the Victoria Drive BIA (at Vic and 41st) has a 70% survival rate and has seen a 40% increase in new establishments!  Rounding out the "super growth" category are Hastings Crossing BIA, Other Mount Pleasant (ie Olympic Village and SE False Creek) and areas in the West End outside of the West End BIA (ie Coal Harbour).  All of these can be considered as gentrification candidates where suvival is low (RIP Crime Lab), but that is offset by tremendous growth.  
    • Gentrifying? Speaking of gentrification, the next quadrant certainly speaks to this occurrence... The Strathcona BIA (which stretches from Gore to Clark along Hastings, is seeing all sorts of new restaurants come (and go), but also has extremely low survival rates at 50%.   The "Other Downtown" area (ie International Village and North False Creek) has the worst survival rate in the City at 43% despite positive growth of 12%.  In this area, I suspect that the pace of rapid change has displaced many prior establishments and new ones cannot seem to succeed in this market (the same can be said for that mall....).  Finally we have the Hastings North BIA, the land of breweries is less kind to restaurants with only 50% of establishments surviving from 2011 to 2016.  Something tells me however, that this trend will stabilize as development along Hastings finally slows down.
    • Static? In my opinion these three areas (Point Grey Village BIA, Marpole BIA and Kits outside of the BIA) are the most interesting.  One the one hand they have very high business survival rates, on the other hand all have seen an 8% drop in the number of restaurants in the 2011-2016 time period.  Perhaps these are ultra-competitive markets, or perhaps some of these surviving restaurants simply persist with an older clientele.  Either way, if Point Grey Village BIA can find a way to grow, it would seem to be a great place to do business.
    • Declining? Something is going on in the Kits 4th Aveneue BIA and on Robson Street.  My current theory is that restaurants are being displaced by clothing stores. and other restaurants simply can't handle the rent shock of these newly minted "high-end" streets. I would welcome any other theories that explain a 48% five year survival rate and an 8% decline is restaurants over five years.


    I would encourage folks who have read this far, to start to think about what this data means and view it in the context of other economic trends in the City.  Personally, if we take a look at Vancouver dining scene, it appears to be vibrant growing and remarkably stable for most of the City. Taken this way, I would say that Vancouver is a long way from dying.  some small parts may be sick, but the rest of the City seems to be thriving in the foodie arena.

    As always I welcome comments, feedback and differing points of view.  If you like this type of analysis, feel free to contact me and I can probably customize for it your needs.  Next week I promise to get back to beer and love, I promise.


    Bonus Dynamic Map

    I'm playing around with mapbox for some of my online figures. Let me know what you think of this as well.


    Analytical data below:

    Area Name New restaurant at new location - 2016 Business from 2011 - not replaced New Business Replacing one from 2011 - same location Still In Business at same location 2011-2016
    Kitsilano Fourth Ave. BIA 3 6 15 20
    Other Downtown 12 7 15 17
    Robson St. BIA 6 7 8 16
    Dunbar Village BIA 0 2 3 7
    Hastings - North BIA 6 3 18 21
    Other Fairview 13 15 31 65
    Strathcona Area BIA 4 1 6 7
    Downtown Vancouver BIA 63 58 63 176
    Other Kitsilano 6 11 16 46
    Collingwood BIA 6 3 7 13
    South Granville BIA 2 1 7 13
    West End BIA 23 9 42 77
    West Broadway BIA 7 3 9 18
    Mount Pleasant BIA 8 6 12 36
    Marpole BIA 1 2 2 10
    Other SE Van 6 4 6 20
    Other West Side 8 5 10 32
    Other Kingsway 15 10 18 61
    Fraser St. BIA 2 1 4 11
    Other NE Van 12 6 7 24
    Yaletown BIA 8 3 13 35
    Kerrisdale BIA 6 4 5 21
    Point Grey Village BIA 1 2 2 13
    Other Marpole 7 2 4 10
    Commercial Dr. BIA 19 5 16 43
    Other South Main St 13 3 13 34
    Other West End 7 1 5 9
    Cambie Village BIA 8 3 7 26
    Gastown BIA 11 2 11 32
    Other Mount Pleasant 24 5 11 25
    Victoria Drive BIA 11 2 5 16
    Hastings Crossing BIA 13 0 8 12
    Chinatown BIA 16 4 3 15

    Ride the Ales! A Brewery Map for Modern Times

    Taking a break from romance, I thought I would blog this week about my other favorite geographic topic: Beer!

    As many of you know, I have two forthcoming apps that will use GIS and geospatial technology to make the world a more fun and interesting place.  In case you couldn't guess, one of the apps will involve dating.  The other is going to help everyone get a bit tipsier.  Indeed, I will be creating an application that helps people to get to sunny patios faster and in the nick of time to catch some rays.

    While my PatioFinder app is in progress, I'll share with you folks a homage to one of my favorite cartographic styles: the Beck's London Tube Map of 1931.  I simply love this style and have seen it applied to so many maps and diagrams so excellently. I also love touring around Vancouver by bike sampling our diverse array of craft breweries. So....

    The set up:

    • I sourced the most current list of breweries that I could get my hands on from beermebc here;
    • I devised some logical groupings of breweries based on geographic location (and cut out anything south of Dageraad);
    • I plotted and connected the dots using a shortest path route finding algorithm to determine my routing combinations;
    • I then plotted the breweries and the routes and then transferred them to a hexagonal grid to start the schematic process;
    • With a bit of artistic license, I ended up with the top figure;
    • I then used some fancy GIS to figure out timing along each route and used something called linear referencing to build the timetable for the bottom figure; and
    • You can see the results from the real world data and my transfer to "creative space" from left-to-right in the slider image below. (note: creative space can be easily accessed after only a few pints)

    The results:

    Well this worked out well, I would say.  I didn't have any overarching analytical goal except to use some skills I obtained building strip maps for pipeline alignments and applying them to something enjoyable like trip planning.  There are some notes and caveats that go with this map:

    • Schematic diagrams in GIS are hard to do.  Everything in GIS-land is made to be accurate and precise.  Building a schematic is neither.  Thus, I had to "force" my software to conform to my hexagonal wishes and requirements for reference lines... no easy task
    • I didn't include breweries to the south of Dageraad.  I'm only a little sorry about this, because my page size didn't work with the kind of scaling and I wasn't up to schematizing all of the arms of the Fraser. maybe next week....
    • If this has been done before, please let me know how you did it, as I am sure there are better ways to create a schematic diagram than the method I outlined above.

    And with all of those out of the way, please check out and enjoy the final product.  If you want to suggest alternate names for the routes please feel free to do so in the comments below, and I will update the map. A downloadable version is available here.

    Finally, I can't help but do some more analysis of population change and things that are cool and interesting in Vancouver.  Take a look at the interposition of breweries and population change over the last five years in Vancouver... notice anything?

    Breweries and population change hmm....

    Breweries and population change hmm....