For many Canadians, attention regarding food insecurity is focused on distant countries, without recognizing that Canada itself experiences insecurity issues. Many food insecure situations in Canada have a tight relationship to the remoteness of communities. Although Canada is a developed country, there are few transport mechanisms that are able to deliver food resources to these remote communities, resulting in overpriced goods to compensate for the costs (Lem, 2012). Along with the cost of goods increasing due to transportation mechanisms, less goods arrive to these remote communities. Distribution routes are often more complex and have longer travel times, resulting in goods having a higher chance of damage to occur during transportation (Connie et al, 2017). This has resulted in costs for goods being approximately 48% higher than southern, less remote communities (Veerarghavan et al., 2016). In turn, locals living in these remote communities cannot afford an adequate diet. A better means of transportation is needed to lower the costs of goods in order to help these remote communities afford a nutritious diet.
Current Canadian research, through organizations such as Food Secure Canada (FSC), has begun to bring attention to create a national policy that will support zero hunger, more sustainable food and a healthier food system (Veerarghavan et al., 2016). The Canadian government has assigned the Ministry of Agriculture and Agri-Food to create a national policy on food security. With this new policy, an element that should be considered is finding alternative transportation methods for the delivery of goods. Some communities are in a food insecure state not because they cannot access goods, but because they cannot afford the prices of these goods. Therefore, it would be ideal to find a lower cost alternative for the transportation of goods to accommodate food insecure regions.
To help these remote communities gain access to receiving transported goods, blimp-sized unmanned aerial vehicles (UAVs) could bring substantial amounts of goods to these areas without the need of road and supporting infrastructure. Ultimately, these UAVs will help lower transportation costs, and are more environmentally sustainable (Shavarani, Nejad, Rismanchian, & Izbirak, 2017). The current state of research for blimp UAVs is quite novel and little research on them in this context exists. The discussions and research thus far have surrounded the use of UAVs for emergency medicinal deliveries and for the quick delivery of packages by the company Amazon. The appealing factor about using UAVs for deliveries is that they are less expensive than current trucking methods, are not limited to road infrastructure, are faster to deliver and can deliver in rough terrain. In addition to UAVs appeal, the batteries and global positioning systems (GPS) used in drones have been getting more accessible (Dorling et al, 2017). With carbon fiber and lithium polymer batteries decreasing in price, and the GPSs used have improved accuracy, these accessibilities are making the possibility of blimp-sized UAVs feasible (Dorling, et al., 2017). Shavarani et al., 2017, predicted that blimp-sized UAVs will be approximately 12 thousand times the size of current UAVs. This means that the blimp itself will cost an estimated 6 million dollars and will be able to carry over 36 thousand kg of goods. Conversely, transport trucks cost roughly 150 thousand dollars and carry on average 80 thousand kg of goods (Truck Reporters, 2013). Although transport trucks seem to be the better option, they require roads to be built for transportation to occur. The City of Barrie (2010) states in a road construction document that two-lane, non-divide roads in rural areas cost approximately 2 million dollars per kilometer (City of Barrie, 2010). UAVs however do not require vast kilometers of roads for transportation but instead only require recharge ports to service the UAVs battery-driven energy. Blimp-sized UAVs can help can lower costs of transportation as large quantity amounts can be taken in one trip, as well can eliminate certain transportation costs such as vast amounts of road construction.
With the benefits of blimp-sized UAVs discussed, there are two phases to servicing remote communities with these UAVs: identify the best location for the launch station, and to identify the routes that the UAV will take. For the purpose of this study, finding the location for the launch station will be examined. To follow this, the best route to connect this launch station to the nearest main receiving city.
There has been significant effort into the development of UAV technology, yet like any technological advancement gaps in knowledge exist. The first gap in UAV delivery research regards the identification of the distance from North-western communities in Ontario to the launch station. Two distances must be accounted for, a main receiving city and the remote communities needing to be served. For the purpose of this research, the main receiving city identified is Thunder Bay. This site is key as it is the largest city in North-Western Ontario. It has many means of receiving goods including the trans-Canada highway, Thunder Bay International Airport, Canada National and Canada Pacific railways, as well as the Thunder Bay port. The launch station must be close to Thunder Bay to receive goods for the delivery to remote communities. However the launch station cannot be extremely far from the remote communities that will be benefiting from the UAV deliveries. As of now, the appropriate distance from these remote communities is unknown due to factors such as how often delivery trips will occur, exactly how much individual UAVs can carry, how many UAVs there will be and the flight range. For example, the most common UAVs are small quadcopters that are for recreational use and surveillance, which currently have a short-range carrying flight technology being approximately 20 minutes (Lin, Shah, Mauntel & Shah, 2017). This technology would have to majorly improve before carrying an estimated 36 thousand kg of goods. The second gap in UAV delivery research is the lack of information around the cost of building highways to the launch station. This lack of information is crucial to the overall discussion of UAV deliveries being more cost efficient than road transportation. As well this information provides numbers for this research regarding the cost of the road needing to be built from Thunder Bay to the launch station will be. In summary, the launch station location variable of distance from receiving city and serving remote communities remains unknown, as well as the cost of constructing highways in rural areas. With this information absent, research is showing that it is feasible in the near future to do major deliveries to remote cities with UAVs, and will be a great alternative to delivery transportation of goods.
To conduct a research analysis regarding the placement of a UAV launch station, this spatial problem can be examined with the software of Geographic Information Systems (GIS). GIS is a set of tools that collects, stores, retrieves and transforms spatial data to solve spatial problems such as transportation routes and infrastructure planning (Burrough, et al., 2015).
Purpose of Research
The purpose of this research is to provide remote communities in North-Western Ontario better access to transported goods through the use of UAVs. This will be achieved by utilizing a multi-criteria evaluation as well as a least cost pathway, to create a model that determines the most suitable location for a UAV launch station and access route near Thunder Bay, Ontario.
Objective 1: To identify social and biophysical factors involved for determining UAV launch site and access route that benefits as many remote communities as possible, without disturbing sensitive landscape or interfering with surrounding communities.
Objective 2: To develop a GIS based multi-criteria evaluation (MCE) model to determine the best site for UAV launch station.
Objective 3: To develop a least cost pathway (LCP) model that identifies the least cost route from weighted major transportation locations, to the most suitable site for UAV launch station.
Objective 4: To apply models to North-Western Ontario to determine an overview of most the suitable UAV launch site and transportation route in relation to the Trans-Canada Highway in Thunder Bay.
Objective 5: To evaluate the strengths and limitations of the GIS based models.