The goal of our final project was to find the total area of the Greater Vancouver agricultural land reserve that is suitable for agricultural use based on the most current data available. The data we used was soil types and capabilities, land cover, rivers and lakes, roads, and parks and golf courses. map1 shows the total agricultural land reserve within Greater Vancouver which equals 21% of the census metropolitan area.

map1

We decided that it was best to break up the group work into chronological sections based on the project outline questions given to us for the report. We communicated by Facebook chat and Google Docs to make sure everyone was on track. Looking back, it might have been better to have everyone do all the lab work together instead of sequentially so everyone was familiar with everyone’s steps in creating the maps and the analysis that they did.

My most valuable contribution to the group was the maps I made since they were the base maps for the rest of the maps and analysis that had to be done in the ALR area. I also spent hours in the lab recovering work after it was not saved properly to ensure that the rest of the group could finish their analysis and did not have to start over. All my group members did interesting research for the final report section of the project.

Again, I think the only way to do a project together is for all group members to show up together in the lab and work on the maps together. Google Docs is a great resource to share open information for team members. However, it is not the same as everyone participating in all steps of map making and analysis in terms of quality and outcome of material learned by all group members.

I think it is interesting that so many roads run through the agricultural land reserve. I think in order to ensure full productivity of the land reserve there would be limitations on development within the area. However there is still almost 70% of the designated area that is useable for agriculture, which is 14% of the Greater Vancouver census metropolitan area. For a highly developed area with such a large population it is impressive that 14% of the area can still be used for agriculture.

The most useful and interesting GI analysis technique I learned in this project was how to create a query to select multiples values within one field in an attribute table. This query is:

NAME OF FIELD IN (unique value, unique value, unique value)

This query is important when there are many different classifications of data that can be grouped into one. For example when creating a map of land cover there were 3 different types of forest that can all be grouped into one. map2 shows different types of land classification. map7 shows all features taken out of the agricultural land reserve to determine the total area of unusable land. map 8 visualizes unusable vs usable land for agriculture.

map2

map7

map8

Lab 1

• Gained basic knowledge of GIS terms and ArcMap software to cultivate an understanding of geospatial analysis to be used in future labs and research in and after this course.

Lab 2

• Learned how to manipulate data in ArcMap for example using ArcTooxbox application to transform different projection systems in order to conduct a more accurate analysis of data.

Lab 3

• Practiced calculating statistics to find areas affected in the case of a tsunami by summarizing attribute table to show which healthcare and educational institutions would be affected if a tsunami hit.

Lab 4

• Manipulated visual outcomes of maps by using various breaks to show ethical implications of using different data classification methods in maps.

Lab 5

• Found and retrieved data from reliable sources online to conduct an environmental impact analysis within a proposed ski hill area to determine the severity of impact the project would have on the area.

Final Project

• Cultivated team-working skills by conducting a team analysis of a specific agricultural land reserve area to see how much of the area could still currently be used for agriculture, and the implications and reasons for our findings.

After conducting a geo-analysis on the area, it is quite clear to me that the costs of going through with this project would outweigh the benefits. The proposed project is for a ski resort to be built in Squamish in the pristine Garibaldi area. As a primary analyst for this project, I would say when taking into account the quantity of protected areas within the proposed project boundary, building a ski resort here would not be worth it. If you are concerned about protection of old growth forests, ungulate winter habitat, and red-listed ecosystems and marine life in the area, you must review my data before proceeding with the development. Not to mention, the portion of the proposed project area that is below 555m, the snow level in this area.

To conduct this analysis I retrieved data from BC government websites about ungulate habitat patterns, red-listed ecosystems, old growth forest management, and riparian ecosystems. I also got data to show existing roads, rivers, contours, park boundaries, and elevation to produce a full analysis of the area in terms of elevation and accessibility. By clipping all these data layers within the project boundary I was able to clearly visualize how much of the area would be affected by this project. By manipulating the data further, I was able to show specifics of which types of red-listed ecosystems and rivers would be affected. I was also able to create a layer showing how much of the proposed area is under the regular snow line.

My analysis found that 44.6 % of the total project area falls within protected areas and 29.9 % of the area is under 555m of elevation, which means snow rarely sticks below that level. 6.8 % of the project area has old growth forest areas. 7.9 % of the project area has mule deer and mountain goat winter habitat. 24.8 % of the project area is red listed species habitat. Finally, 1.5 % of the project area affects streams and riparian areas. All of these areas are areas, which should be protected to preserve biodiversity and old growth forests in this area. If it were not almost half of the project area that is habitat of these at risk species, it may be more excusable.

The environmental impacts that this project will have highly outweigh the benefits for many reasons. The ecosystems housed by the area take up almost half of the project; therefore it would be truly devastating to this ecosystem to disturb these habitats. Secondly, there are four other ski resorts within an hour and a half of the proposed area. With almost 30 % of the project area under the snow level and with such great competition in the area, it may not be economically beneficial to build a resort here. Perhaps it would be more productive to look at an area that is already more trafficked by backcountry skiers. Maybe a more trafficked area will have less biodiversity within it.

In ArcMap there are different ways to classify the data you are showing in a map. These different classifications appear differently when represented visually on a map, as shown on my classifications methods map. Different classifications can be useful for different purposes.

Classification Methods

If I were a journalist, I would use natural breaks because it shows more red census tracts in the city, business district, and West Vancouver. This creates more response from readers of a journal because it highlights the unaffordability of housing in Vancouver.

If I were a real estate agent trying to sell to buyers near UBC, I would also use natural break or standard deviation because it makes the desired area seem less expensive relatively since it is the same colour as most of the rest of Vancouver.

Both these decisions have ethical implications because they are both choices to manipulate data that will change viewers’ opinions and response to something, like convincing them Vancouver is extremely unaffordable, or that buying close to UBC is relatively inexpensive compared to the rest of Vancouver.

Housing Affordability

In this map, affordability of housing in Vancouver and Montreal is compared based on median shelter costs and family earnings in a certain census tract. It is necessary to take earnings into account when thinking about affordability of housing because it is likely that families who earn more live in more expensive houses. This map rates affordability of housing based on rating categories from a housing affordability journal. Although this map obviously shows that Montreal’s housing is much more affordable when taking median house cost and familial earnings into account, what does this indicate about Montreal versus Vancouver’s livability? Many people would argue that this pegs Vancouver as less livable since housing is simply too unaffordable. After all, most census tracts in Vancouver are shown in this map as severely unaffordable.

Reflection

In completing these labs it is important to reflect on the knowledge and transferable skills acquired in doing so. Each lab has taught me a new skill and given me the opportunity to familiarize myself further with the ArcMap program. Using this program to solve mapping problems that I had never before envisioned myself doing is a valuable experience that can someday transfer into practical skills that will be desirable in the workforce.

Lab 1

Before completing the first lab I had absolutely no knowledge of GIS Software. Therefore the whole lab was important for me. Getting time to begin navigating the interface of ArcMap was useful because like any program, you must use it routinely to be familiar with it. Learning about the different types of data and how they are used and displayed in Arc systems was a comprehensive part of the online training.

Lab 2

The second lab was important to practice using different types of data, learning how to change data files when necessary, and knowing when it is necessary to do so. One of the most important things from this lab was learning how to change projection systems using the ArcToolbox application. This is important because data is not always represented in the same projection but in order for a map to be useful, all data should be in the same projection. Learning about specific uses of Landsat data was another valuable part of this lab. It is interesting to think about how many practical uses there are in looking at the world from these satellite images.

Lab 3

This lab was much more difficult than the first two as it went into more specific skills and data analysis within the ArcMap program. The thing I found the most interesting was being able to determine which specific healthcare and educational institutions would be in danger if a tsunami of a certain size hit Vancouver by manipulating layers of data and then looking at the new overlays’ attribute tables to tell me the names of the institutions that would be affected. The result of this lab was a map of Vancouver showing the area within 1km of the shoreline and under 10m elevation that would be in danger if the tsunami hit (if Vancouver island weren’t in the way). It also shows the specific roads that would be in danger (unfortunately my map shows all of the roads, not just the main ones making it a bit difficult to see). This type of geoanalysis is important for cities that are at risk of tsunamis when planning a city or planning for evacuation routes if a tsunami is predicted.

Danger Zone in Vancouver

12 percent of the city of Vancouver would be in danger if the tsunami hits. To calculate this, first I found the area of each layer: Vancouvermask_danger and Vancouvermask. To do so I found the area of the layers by creating an AREASQKM field in the attribute table, then calculating the geometry of the area in square kilometers.

Vancouvermask_danger: 15.8 sqkm

Vancouvermask: 131.0 sqkm

15.8/131= 0.120

= 12% of Vancouver in the danger zone!

Facilities Within the Zone

False Creek Residence, Villa Cathay Care Home, Broadway Pentecostal Lodge, and Yaletown House Society are the healthcare institutions that are in danger if the tsunami hits.

The educational institutions in danger are Emily Carr Institute of Art and Design, Henry Hudson Elementary, False Creek Elementary, St. Anthony of Padua, and Ecole Rose Des Vents.

To find these I used the select by attributes tool and selected healthcare and education where it intersects with Vancouver_dangerzone. I found the specific institutions by looking in the highlighted area of the healthcare attribute table, then the education attribute table.

Vancouver Danger Zone with Signage

Projection Problems

In this lab I practiced fixing misaligned and improperly referenced spatial data. Area, angles, direction, and distance are affected when data is projected into a different coordinate system and this can sometimes cause issues in how it is displayed when added to a map. Sometimes you need to change the layer’s coordinate system. To do this you launch ArcToolbox and use the data management tool to change the layer’s projection.

Landsat Data

Landsat is a remote sensing program that has been continuously scanning the earth since 1972, using sunlight as its energy source to measure the response of objects and surfaces on earth. Satellites use wavelengths to produce images of these objects and surfaces.

It is used to measure land change estimates due to natural disasters, for example the effects of a hurricane on land-water conditions before and after a storm. The question of geographical analysis in an example like this would be: What effects did the natural disaster have on the land and on the water in a specific area? The location you would choose would be the specific location that the disaster happened in (everywhere in which water and land was effected by the hurricane). The interval you would select would be a period of a week or so from the day before the hurricane to the week after. You could also look at other data from previous years to see the normal variations that occur because of seasonal factors in the land and water in this area. Season can also affect land and water patters so this is something you would want to take into account when looking at the data.

Example of Landsat Data

Introduction

After three hours of training, I’m a certified GIS operator! This intro course to GIS provided me with lots of knowledge necessary to complete the subsequent lab assignment.