Accomplishment Statement

Performed an environmental impact assessment using 3D surface analysis and overlay commands to determine suitability of a potential ski resort.

Introduction

In this lab, I was tasked to produce an objective analysis through maps at a higher elevation than the original 555 m for snow of the proposed Garibaldi at Squamish ski resort. I also needed to include an analysis of the appropriate mandated environmental implications, which includes protected old growth forests, protected riparian management zones around rivers and streams and protected ungulate habitat areas.

Analysis

I acquired data from many sources to complete my analysis. I used DataBC for protect areas, rivers, roads and contours, UBC Geography G:Drive for the project and park boundary and NRCan for the DEM of BC. I then had to parse my data to keep it organized by using consistent name conventions. I then mined my data using different tools in ArcMap such as clip, buffer, overlay, and dissolve.

Memo

To: Municipality of Squamish

I have done an environmental impact assessment on the proposed area for the Garibaldi Ski Resort project and I have deduced many reasons as to why this may not be a suitable area for this project.

The proposed project boundary has many potential effects on vegetation and fish and wildlife habitat. I analyze these effects using the areas of ungulate habitat, old growth forests and riparian management zones around rivers and streams. These areas are highly fragile and building a ski resort here could have major impacts. The rivers cover 29% and altering the rivers could change the river network and therefore could make the land more susceptible to landslides and debris flows. These areas account for almost 40% of the project boundary and will see severe impacts if a resort is built here. I also analyzed the snowline and discovered that almost 32% of the project boundary will have potential issues with not having enough snow. Although this may not seem like an issue now, it will become an issue as global warming trends suggest that this snowline will keep increasing as we see warming trends. This resort will not be completed for 20 years and by that time, the snowline will be much higher and more issues with not having enough snow. Sources of error in my analysis would be that the landscape is changing and more complex and my data may not be up-to-date and does not include any economical data. Further datasets and analysis I would suggest is including economic data to provide more information as to how costly it would be to the habitats if a ski resort would be built here. I would also suggest field data to be acquired to get more information on the environment of the area.

This project has many issues with the habitat and may not be feasible considering how much may be lost as a result. Many factors will be changing in the 20 year period of its building and will bring many of environmental issues. I have included maps of the project area and snow line/high elevation and protect areas and also a 3D hillshade representation to further illustrate these issues.

Map 1: Environmental Impact Assessment

Map 2: Environmental Impact Assessment 3D

Accomplishment Statement

Gained knowledge on parsing and filtering Census data to analyze housing affordability in Vancouver and Montreal.

Introduction

In this lab, I analyzed rental housing cost and affordability in Metro Vancouver and Montreal. I used census data from 2016 with the scale of Census Tracts(CT) and Census Dissemination Areas(DA). I created 3 different maps to show how different methods of data classification influence the interpretation of data on maps, the cost of rent in Vancouver and Montreal and the affordability of shelter in Vancouver and Montreal.

Analysis

In the first map, I have depicted 4 data classification methods for cost of median monthly rent in Vancouver. The 4 data classifications are natural breaks, equal interval classification, manual breaks and standard deviation classification. Natural breaks classifies the data using intervals that will minimize the variation within the classes and find the most optimal breaks so that the difference between the classes is maximized. Equal interval divides the data into equal size classes which is a difference of 676 in the map below. This method is not great for Vancouver rent as data is skewed to one end. Manual breaks allows  you to set your own class breaks. This is a good classification method to use when comparing different maps as it makes it much easier to compare when the same breaks are on both maps. Standard deviation classifies the data by how much the data differs from the mean. This is a good method to figure out which areas are above and below the average cost of rent in Vancouver.

Map 1

In the second map, I compare the median monthly cost of rent for Vancouver and Montreal using census tracts. Census tracts are areas represented by approximately 2500-8000 people. I used median over mean for this analysis because the mean is heavily influenced by outliers which would not accurately represent rental costs. I acquired this data from the Abacus Dataverse Network and downloaded Census Canada Cartographic boundary files. I also acquired 2016 census data for monthly rent from CHASS site using its Canadian Census Analyser. The data included many areas with no data or zero as monthly rent. This is because many dwellings are not rentals but owned, unofficial such as basement suites. Some areas are also Aboriginal lands, or Indian Reservations which are not part of the Census and thus have zeros. I used manual breaks to classify my data since my audience would be the general public and choosing breaks that make sense helps the viewer visualize the data and compare both of the cities. During this analysis, I excluding all data with zero or no data as this would have produced error in my data classification.

Map 2

In the third map, I compare the affordability of shelter in Vancouver and Montreal census tracts using manual breaks classification. I do this by acquiring data that shows the percentage of households that spend more than 30% of their income on rent. Affordability measures how much of a total household income goes towards rent and if this is above a certain threshold. According to the Canada Mortgage and Housing Corporation, any household which spends 30% or more of its gross income on rent has affordability issues. This is a better indicator of shelter affordability than rental cost alone because it considers the cost of shelter in relation to income and not only the cost of shelter for individuals. Affordability is a good indicator of a cities ‘livability’ because many households would determine whether they want to move to a certain city by their ability to afford shelter. If rent is high and income is low, households will not find this place ‘livable’.

Map 3

Conclusion

During my analysis, I found that Vancouver has a much higher rent compared to Montreal. Vancouver had many more areas in which rent was above $1000 while Montreal had many areas with rent in between $500-$1000. When comparing affordability, I also found that Montreal was much more affordable compared to Vancouver. Montreal had many more areas in which rent was between 20-40% of income compared to Vancouver.

Accomplishment Statement

Learned to use proximity analysis and other analysis tools to assess the risk of Metro Vancouver to flooding during a storm surge event.

Introduction

In Lab 3, I created 4 maps to highlight areas in Metro Vancouver that are at risk to flooding during a storm surge. In this analysis, I only looked at the immediate danger zone which is at an elevation area at, or below, 5 metres that lies up to 1 kilometre inland from the shoreline.

Analysis

In the first map, I used a DEM from Open data Canada with 25m resolution which is clipped to show just Metro Vancouver. I then classified this to display low elevation flooding by grouping the pixels into 8 categories of elevations. There could be data error as the resolution is 25m, but all categories except one represented anything over 20 metres.

Map 1

In the second map, I created a map of potential flood from storm surge of low elevations within 1km of the shoreline by adding and then buffering the shoreline by 1km and then combining this with 5m and under elevations.

Map 2

In the third map, I added a roads layer and highlighted which roads intersected flooding areas. I then created a table summarizing the total length of each road type that is affected by potential flooding.

Map 3

In the fourth map, I added an another DEM layer of False Creek with a resolution of 1m. I also added City of Vancouver schools and an outline of the new site for St. Paul’s Hospital. I used this to analyze if any schools or the new site for the hospital fall within the potential flooding areas.

Map 4

Error

The school points were in Lat/Lon but the system defaulted the projection to UTM 10 N. Since I had to change the coordinate system and re-project the layer, this may have caused error in the school points. There could also be error in the accuracy of the representation of the elevations as the resolution for the DEM was 25m.

Data