When beginning the analysis, first we downloaded and extracted all the layers into a working folder then created a project geodatabase and imported the downloaded feature classes into the working default geodatabase.
We renamed the feature classes starting with “Surrey” to allow us to organize our classes for the wildcard option when using Model Builder. For the first step with the Model Builder, we made sure all our layers were projected using the same coordinate system. We then set the output layers to be projected in UTMZONE 10 NAD 1983. We then added another tool using clip, then dragged the clip tool into the Model Builder under the projected feature we previously made. The clip tool was set to the Surrey City Boundary layer in order to automate the process so it applied the same clipping feature to all our layers. We had the Model Builder loop through the geodatabase using the iterator feature – a for loop. Finally to save the model, we saved it in a toolbox outside our geodatabase.
We downloaded Plot Divisions of Greater Vancouver and clipped them right away because it was too large. Then we took the agricultural land and reserved agricultural land layers and erased reserved agricultural land from agricultural land to get potential locations to build the mall on.
The potential mall polygons at first did not show the areas for each of those individual polygons because it was still a multipart polygon. So we used the Multipart to Singlepart tool to break down the polygons so it would show us the area of each of those potential mall location polygons. The three polygons with a minimum size of 41,704 m2 were extracted to give the table of the three potential mall locations big enough to fit a mall larger than Metrotown mall. This table was joined back to the Surrey_Single_Mall_Locations layer and only matching records were kept to display the three potential mall locations as polygons on the map. To save the join, the matching records were exported as a new layer called Surrey_ThreeSingle_Mall_locations.
We also analyzed how many parcels of land were present on the potential mall locations. We displayed them on the map of our 3 potential mall locations and recorded how many parcels of land were present in each of the mall location areas. The less number of parcels, the less land developers have to buy off from other owners or the less transactions they have to make.
We afterwards conducted an income analysis of neighbourhoods surrounding the potential mall locations. We decided that the higher the income of the neighbourhood, the more profitable it will be building a mall there. Steps taken for income analysis involved downloading Canada wide CT and DA layers from Abacus Dataverse Network. Then we used the intersection tool to select Metro Vancouver regions only within the Canada CT and DA layers. To extract City of Surrey CT and DA layers, the search tool was used to find areas outside of the Surrey boundary layer and unselect them from the Metro Vancouver CT and DA layers. After the areas outside of the Surrey boundary polygon were removed, the remaining selected areas were exported into separate layers, SurreyCT_2016 and SurreyDA_2016. We later joined SurreyDA_2016 and SurrreyCT_2016 tables back to CanadaDA_2016 and CanadaCT_2016 respectively and kept only matching records to get polygons of Surrey.
Finally, we wanted to see which mall location would take the least amount of time to travel to by car from a specific skytrain station in Surrey. The method of Network Analysis was chosen because Metrotown is known to be profitable because of its close proximity to a skytrain station. Therefore we wanted to know how long it would take to drive to each of the potential locations from Surrey Central skytrain station given traffic intersection data (the speed limit at which cars can travel along these intersections). Steps taken to conduct the Network Analysis involved first adding Minutes and Meters to our Roads layer in the attribute table so that we would be able to determine the shortest distance from a point of interest to one of the three potential malls. From the GDB we created a new dataset called “RoadsNetwork” and then added the roads layers into this as a new dataclass. Then we created the network layer; using the Network Analyst toolbar, we clicked on create New Route and clicked on Create Network Location Tool and chose our start and end point (starting from the Surrey Central Skytrain Station to one of the three mall locations). After completing this for all three mall locations we are able to get a route with minutes and distance in meters.