Lab 4: I learned the working knowledge of Canadian Census Data, and understanding quantitative data classification. Also, using ratios to compare dataset and determine housing affordability, then creating maps to display the results.
Lab5: Learn how to independently acquire spatial datasets online, and write memo to summarize results for a non-technical audience. Also, I leaned how to evaluate and use different spatial analysis tools.
Submitted this late due to medical reasons, and already sent doctor notes to TA.
Q9:
As a natural resource planner, I evaluate the percentage of the proposed project area that “lower 600m of vertical”, also the percentage of proposed project that has old growth forest, Mule Deer, Mountain Goat winter habit, red-listed, and fish bearing stream, along with the total percentage of protected area that falls in projected area. Also I should make recommendation to the proponents that what the priorities are in order to be preceded. Therefore I made two maps, and some calculations to point out my perspectives. From the calculation results I get, we could see that the percentage of protected area that has old growth forest, Mule Deer and Mountain Goat winter habitat are less than other categories, which should be give more attention on it.
To analyze data, first I found data layers from DataBC, and create geodatabase to organize the data. Giving data layers a proper name is very important too, so we will very directly know the basic property of each data layer. “Clip” needs to be done to select the area that useful for my case. Then, cleaning some data that not useful for the case. Classify the types of data we are looking for, so we can get detail information about it. In this case, we can get the area of different species to calculate the percentage of the total project area.
The total area of old growth forest, ungulate habitat, red-listed ecosystems and fish that falls in project area is 28845087.87754, which is 52.72%. Comparing the Sum of answers 2-5 which is 65.8%, this value is 13.08% smaller than the sum of answers 2-5. The area below 600m is 17392902.57026.
In my opinion, we should pay more attention on the old growth forest and Mule Deer and Mountain Goat winter habit. Due to the protected area that has these two categories are very small compare to other categories. That means the amount of old growth forest and Mule Deer and Mountain Goat are small. Also we could increase the total protected area, due to the sum of four protected areas is bigger than the total protected area.
When working on environmental projects, you sometimes become involved in proposals that you do not ethically believe in. Do you personally think the project should be allowed to continue? Does this differ from what you wrote in your memo?
I personally don’t think the project should be allowed to continue, because I cannot entirely believe in the proposals. Its different from my memo. In the memo, i just described data analysis process, and give the result that i got.
affordability measuring: measure of housing that can be affordable with median household income by a place. It reflects more information than just housing cost alone, which not shows about household income, etc.
affordability is a good indicator for “livability.” That’s because it show lots of information about household, imcomes, and the data can be trusted.
Lab1: Understanding basic information about GIS, and get the bigger certificate for GIS.
Lab2: Managing and previewing the data, understanding Coordinate systems and projections, Then evaluating geospatial data and identifying the map from Spatial data models.
Lab3: Using data to do the Geographic analysis, create a map about the land use with potential Tsunami Risk in Vancouver.
Q7: percentage in dager is 12.1%. Use the statistics tool to get the sum of shape_area in the
Q8: Healthcare facilities in danger: villa cathay care home, false creek residence, broadway pentecostal lodge, yaletown house society.
Educational facilities in danger: Emily carr institute of art and design, henry hudson elementary, false creek elementary, st anthony of padua, ecole rose des vents.
Use select by location. Select from “Vancouver_health” and “Vancouver_edu”, Source layer”Vancouver_danger”. Export the selected data as “danger health” and “danger_edu”. Check the attribute table of the exported layers.