Environmental Impact Assessment – Lab #5: EIA

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As part of a ski development analysis for Garibaldi Resort in Squamish, I was asked to create 2 maps outlining the potential impacts on the environment (i.e. the ungulate winter habitats, old growth management areas) and the potential elevation/hill shade (such as the snowline contour, which is determined as 555m). The consequential assessment is essential in analysing environmental risks, natural hazards, as well as affects on the development and the land itself.

Map 1: Map of Ecological Areas (preserved areas) in the proposed project area of Garibaldi Resort

Map 2: Map of Hillshade, Contour and Elevation in the proposed project area of Garibaldi Resort (including snowline contour, and the previously illustrated ecological areas)

Full resolution of the maps can be found below:

I was also asked to include a 1-2 page memo report on my findings, analysed results and processes in compiling these maps. The report also included recommendations based on what I evaluated, and suggestions for other potential studies (i.e. climate change/temperate changes). Here is the report below:

Memo Report:

Whilst analyzing the proposed development of Garibaldi Resort on Brohm Ridge (at Squamish), there are a number of analysis results that are worth evaluating prior to construction. Many of them included potential threats to ecological areas, certain environmental threats and impact from hill elevation. Throughout the course of this report, I will aim to outline all the potential implications to Garibaldi Ski Resort development in 2018.

In order to generate a comprehensive analysis to identify necessary components for an environmental impact assessment, there were a number of steps I undertook in order to acquire and verify the data. First, I gathered open sourced data from DataBC (specifically Ungulate Winter Range and Old Growth Management Areas), as both layers indicated the areas covered under the Forest Practices Code, Forest Ranges Practices Act and forest licenses found under the legally established Old Growth Management Areas. These layers would thus provide necessary information on ecologically preserved habitats and conserved old growth forest regions. I then made use of data outlining the project boundary, the digital elevation, contours, park boundaries, roads and rivers of the site. As a number of these layers made use of different co-ordinate systems, I configured the main data frame coordinate system as NAD 1983 UTM Zone 10N – hence, the resulting maps would be projected the same way. For the next step, I calculated the areas lower than 555m (i.e. elevation at 555m would be deemed as the snowline contour) in order to identify the areas which have limited snow availability and thus not be suitable for a ski resort. I also studied the regions that would be omitted from the construction of the resort, including the old growth forest, winter habitats and fish bearing streams found in Brohm Ridge (it is critical to note that these areas are legally protected, thus construction is completely restricted). As a final step, I constructed two maps, one outlining the ecological areas under protection (as aforementioned above) and another depicting the elevation (using hill shade/contour) and its impact on those ecological areas.

After thorough quantitative analysis, my results outlined the possible areas for development and the impact on certain protect areas (as outlined below):

Type Area (sqm) Area of Project Boundary Area Percentage of Project Boundary Area (to 3 significant figures)
Project Boundary Area 54717275.030137 / /
Below Snowline Contour (under 555m elevation) 16371095.01165 0.299194267306498 29.9%
Old Growth Forest/Management Areas 3710331.429332 0.067809141213418 6.78%
Ungulate Habitat Areas (Mule Deer species) 2317859.136008 0.042360646335757 4.23%
Ungulate Habitat Areas (Mountain Goat species) 1997299.753625 0.0365021787457 3.65%
Total Ungulate Habitat Areas 7.88%
Fish Bearing Streams (50m) 8006619.665446 0.146327090686 14.63%
Fish Bearing Streams (100m) 7588594.574394 0.138687362816 13.86%
Total Fish Bearing Streams 28.49%

As illustrated in the table, the areas below the snowline contour (i.e. under 555m elevation) is presumed to have limited snow availability. Thus, 29.9% of the project boundary area is not suitable for ski resort construction as it is under the 560m elevation line. The old growth management areas (mostly forest areas), retain 6.78% of the overall project boundary area, whilst ungulate habitat areas – in both mule deer and mountain goat species, consist of 4.23% and 3.65% respectively. Consequently, equating to a total of 7.88% of ungulate habitat areas within the proposed project boundary. Fish bearing streams would also need to be taken into consideration during development, as the river buffer of protected fisheries (i.e. protected lakes/streams) make up a total of 28.49% of the project boundary. Notably, regions below the snowline contour and fish bearing streams would make the most impact to potential areas for the ski resort. Though both ungulate habitat areas and old growth management areas should not be undermined, as it also makes a significant contribution to ecological areas, totaling to 14.66%.

From the findings in this report, there are a number of recommendations that I would like to recommend for Garibaldi resort. As seen on the map showcasing the ecological areas under protection by Canada’s legal board, a number of the old growth management areas and ungulate habitat areas coincide with the proposed project boundary areas (especially on the regions with snow – above 555m/ the snowline contour). There are also a number of fish bearing streams (according to the river buffers), which would need to be accommodated during allocation of certain ski amenities. Thus, it is critical to select a location that does not intersect with any of the previously mentioned ecological areas. Perhaps, certain areas could be introduced as part of a tourist attraction or part of a resort activity. For instance, fish bearing streams could be utilized as a fishing activity (although further data has to be gathered on the level of protection for those particular fish species). Likewise, ungulate winter habitats and old growth forest management areas could also be incorporated as the natural scenery of the resort, with strict rules outlining the limits of the boundaries to ensure the wildlife area is well protected. Transportation systems and road networks are not an issue for the ski resort, as there are an abundance of roads interconnecting the project boundary area. Whilst examining the second map of hill shade within the project boundary area, it is critical to note much of this elevation may interchange throughout seasons (as a consequence of climate change and seasonality), i.e. the snowline contour may depreciate or there are substantial risks of avalanches. Thus, resort infrastructure/facilities would need to accommodate for these natural shifts and ensure the safety of visitors and the neighboring animal habitats. The proposed resort should also avoid any elevation below 555m, as this would pose certain risks due to fluctuating and unstable climates.

I believe that the two most major environmental factors to ski resort development are the ongoing affects of climate change, and the eradication of the ecologically preserved areas. As climate change is particularly unstable and consistently fluctuating, it has become difficult and risky to plan ski resorts – a tourist attraction that is entirely dependent on the provision of cold climates. Thus, they should be considered the most major concerns for the project. In order to address these concerns, I propose that a number of other analysis reports to be investigated before proceeding with the Garibaldi resort development. Including those of seasonal temperature changes throughout the area, potential impacts by transportation (e.g. how would continuous trips by public transport/private vehicles contribute to emissions, or how these vehicles would affect the landscape?), land slope stability (in order to identify avalanche/natural hazard risks, as well as potential sites for structural construction), annual snowfall (to analyze the density of snow coverage and thus provide better preparation), potential tourist density/maximum capacity for the resort, as well as annual changes to the snowline contour (indicating the affects of climate change). All of these evaluations would provide a more extensive outlook and a more efficient environmental impact assessment.

Housing Affordability – Lab #4: Housing Affordability

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As illustrated below, the maps depict the shelter costs in Metro Vancouver from 2011 to 2016 (as taken from Statistics Canada as a data source). Both maps compare how housing affordability has shifted from 2011 to 2016, with a specific focus on shelter costs.

Shelter costs could be defined as costs that households are paying (monthly) in order to reside/rent/own their dwelling. These costs are showcased throughout these maps in order to indicate the prices induced by households to live in Vancouver. Although this variable is effective in portraying housing affordability throughout Vancouver, there may be issues in areas of economic disparity. For instance in Main Street, the same region has a large transition between cheaper and more expensive housing, thus shelter costs would vary immensely. As shelter costs only look at the price of residing in a dwelling, it does not necessarily represent the price of purchasing private housing, thus may not include critical information.

For more information on the Lab scenario, please see the following link: https://blogs.ubc.ca/caseychun/2018/03/05/quantitative-data-classification-lab-4-housing-affordability/

Maps 1, 2: Shelter Costs in Metro Vancouver from 2011-2016

Full Resolution of the maps can be found below:

Quantitative Data Classification – Lab #4: Housing Affordability

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Whilst completing Lab #4 on Housing Affordability, I was able to create a series of maps that demonstrated the different classification methods GIS software provides. Including those of natural breaks, equal interval, manual breaks and standard deviation. As each type of classification method yields visually different maps, I utilised all 4 types to analyse housing affordability in Metro Vancouver. The scenario was as follows:

Scenario: Often geographers need to work with census data that is gathered, analyzed and displayed by national government organizations (example Statistics Canada). Census data is utilized in many geographic analysis research projects: urban planning, immigration, social geography, environmental justice, crime prevention, transportation planning, policy analysis, etc., and all of these topics can be explored using GIS. Many of you will use Canadian Census Data for your final projects.

Every 5 years, Canadians are surveyed. Previous to the 2011 survey, 80% of the population completed the ‘short form’ and 20% of the population completed the ‘long form’, where more detailed information is captured. In particular, the ‘long form’ included socio-economic data including income, dwelling type and value (the topic of this lab), transportation data such (modes of transportation for commuting) and immigration data. The former Canadian conservative government changed census policy for 2011; the long form was not mandatory but voluntary. This has impacted the quality of the data, and makes it challenging to compare to previous years. The 2011 Census is referred to now as 2011 NHS for national household survey. The next survey was conducted in 2016, with the long form reinstated for 20% of the population, and the data was finally all released in the fall of 2017. For this lab, we will use 2011 and 2016 data on cost of dwelling, or housing cost, to visualize change over 5 years. To note is the 2011 data is not as reliable as 2006 and 2016.

Statistics Canada creates different census map areas based upon population. In Metro Vancouver, for this lab, we will be using 2 different census areas: Census Tracts (CT) and Census Dissemination Areas (DA). Statistics Canada draws census boundaries on maps for CT and DA based upon the number of people living in the area. DAs are finer resolution with a DA being sometimes less than a city block, sometimes just an apartment building, whereas CTs are coarser resolution, and one CT makes up a few city blocks.

Maps 1, 2, 3, 4: Natural Breaks, Equal Interval, Manual Breaks, Standard Deviation

 

Full resolution of the maps can be found below:

Planning for Flooding/Storm Surge – Lab #3

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Throughout the course of ‘Planning for Flooding/Storm Surge’ Lab Assignment (Lab #3), I was asked to create a series of maps to accurately depict potential storm surge floods in Metro Vancouver. Specifically, the scenario was as follows:

Scenario: As Metro Vancouver had undergone a series of climatic/hydrological events throughout this current time period, create maps to document the storm surges that may affect certain areas of Metro Vancouver. Storm Surges could be defined as “the rising of the sea as a result of atmospheric pressure changes and wind associated with a storm” (as quoted from Lab #3 instructions hand-out). Hence, storm surges could significantly affect areas of Metro Vancouver due to the risks that it accompanies, including flooding (which is affected by winds, tides, waterways, elevation and etc). The purpose of these maps is to outline the potential danger zone of the storm surge at low elevation (where the storm zone would be most impacting), below 10 meters or less and lie up to 1 kilometer of the shore line.

I have created the following maps in order to accurately represent the risks of storm surge below:

Maps 1: Map of Metro Vancouver and all the areas of potential flooding via storm surge, depicts the elevation from 0-10 meters

Maps 2: Another map of Metro Vancouver showing areas of potential flooding with legend

Map 3: Map of potential flooding within 1km of shoreline

Map 4: Map of potential flooding on all the roads in Metro Vancouver, with a table summarising the total length being affected

Map 5: Map of False Creek tidal flats area, showing potential flooding and it’s effect on nearby schools, new St. Paul’s Hospital location and elevation

Full Resolution of the maps can be found below: