Research Findings - Objectives 1 and 2
Objective 1: Identify relevant criteria and limitations from literature related to siting approved marijuana dispensaries.
This objective was achieved through the use of both academic literature and current government legislation in order to determine which criteria would be important for consideration when siting a marijuana dispensary. These accredited sources helped determine that proximity to schools, public transportation, public parks, places of worship, and existing LCBO’s, are all important criteria when siting the location of a newly approved dispensary, and were incorporated into the MCE model. The remaining criteria that were used in the MCE are population density, underage population density, and lastly, that it must be situated in a zone designated for commercial use.
Objective 2: Establish an MCE model to determine the most suitable location for incoming dispensaries in approved municipalities.
In order to complete this objective and establish a GIS model, the ModelBuilder was used through Arc Catalog to produce a model that can be easily manipulated to suit municipalities other than Guelph. To do so, the model was divided into two main components, factors and constraints.
The constaints used in the model effectively determined either where, or where not a dispensary would be suitable for development and eliminated the dissemination areas that fell within the constraint buffers for consideration.The constraints implemented into the model were proximity to schools, places of worship, parks, existing LCBO’s, commercial zoning, and accessiblity to public transportation. The factors that were used in the model helped determine which dissemination areas would score higher based on their distance to other existing locations. The factors included that will impact that suitability of the dispensary are proximity to schools, parks, places of worship, existing LCBO’s, accessible public transportation, population density, and underage population density.
To ensure that the model is run properly, the factor criteria must be given a standardized ranking before being incorporated with the constraints. These standardized rankings were derived from Euclidean distances based on a 1-100 scale, factors that greatly met the required criteria were assigned a higher ranking. The specific weights were determined using the pairwise ranking chart found in Objective 3 of the research approach.
The constraint layers were further divided into two parts, one being areas that development was not permitted and areas where development was permitted. These two types of constraints were combined to create a final suitability layer that determines all areas that are suitable for a marijuana dispensary.
By devising a model that outputs a constraint layer along with a layer based on weighted factors creates a situation where the factors weights can be easily manipulated to better accommodate different scenarios without compromising our constraint layers. This makes the model easily applicable to other regions attempting to site a marijuana dispensary.