The study area includes the City of Vancouver region, which was displayed as a Vancouver Census Tract boundary in ArcGIS Pro. We have taken into account the fact that we used Census Tracts (CT) over Dissemination Areas (DA), meaning that it has the potential to generalize our data onto a larger scale.  CTs are larger, relatively stable geographic areas that usually have a population between 2,500 and 8,000 persons (Tru Libraries, 2021). This is comparable to DAs where we would be working with smaller neighborhoods composed of one or more neighboring dissemination blocks. Dissemination blocks consist of a population of 400 to 700 persons (Tru Libraries, 2021). Hence, using CT may have caused us to miss small nuances in the data. However, we decided to use Census Tract data as our count of how many Greenest City projects are present within a CT resulted in a higher number of points and presented usable data for us to continue our spatial analyses. If we were to use DA data, we would have many areas that were blank and would present many holes in our data values. Therefore, using CA data would leave our data with fewer empty values. Considering what type of geographic boundary area to utilize for our analysis was crucial given that it would dictate the quantitative results of our spatial analysis. 

Secondly, we are aware that obtaining and utilizing Census data from 2016 may cause a higher potential for error and uncertainty within the results of our data. This is because, since 2016, there have likely been updates and changes in the data collected which may have not been evident in our results. It would have been optimal to obtain data that was most recently updated from this year to present the most accurate results, and we have attempted to compensate for this by obtaining the most up-to-date data for Greenest City Projects within Vancouver. This, we argue, was most important for conducting our analyses given our goals in seeing the current spatial distribution of Greenest City Projects in order to propose further developable areas for more to be built in the future. Hence, we were able to minimize some errors and uncertainty by obtaining 2021 data for Greenest City projects from the City of Vancouver Open Data Portal. It is also important to note that the dataset includes a large majority of Greenest City projects in Vancouver, however, projects including community gardens, privately installed charging stations (or private projects that may fall in line with Greenest City Project initiatives) prior to 2010 are not included within the dataset. This is generally not seen as a setback in our analyses as we believe the data obtained for Greenest City Projects are sufficient enough to draw conclusions and make suggestions for future research. 

As our project aligns with addressing concerns related to social variables against Greenest City Project initiatives within Vancouver, we found that social data recorded for Vancouver was quite scarce and challenging to obtain. Hence, any social-based data utilized may have the risk of inaccuracy and bias. As all of our census data was obtained from Statistics Canada, we are aware that Canada tends to have greater amounts of quantitative, non-social-based data. Many have critiqued Canada’s data deficit when it comes to social and health data. According to Globe and Mail reporters Eric Andrew-Gee and Tavia Grant, the government of Canada has the provincial responsibility for health and education (2019). They keep crucial data locked up in “silos” and gives governments no incentive to preserve easily comparable figures; a paranoid zeal on the part of our statistical authorities to protect personal privacy; a level of complacency about the scope of our problems that prevents us from demanding government transparency and action; and a fear of race and class that prevents us from learning everything we can about disparities between the privileged and the poor (Gee & Grant 2019). Therefore, while acknowledging that there is a prevalent issue with gaps in Canadian public data, we are advocating to bridge this gap through considering visible minority and income levels to see whether there is a spatial correlation with the presence of Greenest City Projects.  We hope that this can serve as the basis for future research which will be discussed on the following page. 

Furthermore, the residential and non-residential areas we have used as a basis to conduct our advanced spatial methods against Greenest City projects may present some uncertainties and limitations when considering our proposed project locations. It may not be entirely accurate as the data we obtained and parsed had not taken into consideration how land use is spatially distributed when considering proposed project locations. For instance, South Vancouver is considered a heavily industrialized area, meaning that regardless of marginalization, sustainable project implementation may not be accurately feasible. Hence, the proportion of open land use available for our Greenest City project proposal may be false due to the lack of available land in one CT affecting where proposed Greenest City Project areas can be. Therefore, we must recognize that some regions of Vancouver have low areas of potential whilst some areas may not have any space for Greenest City Projects at all. This opens up room for improvement in future projects as the data collected for land use can be more intricately analyzed to provide a more accurate and detailed analysis.