Koen, Hildegarde S2017-10-092017-10-092017-02Koen, H.S. 2017. Predictive Policing in an Endangered Species Context: Combating Rhino Poaching in the Kruger National Park. Submitted in partial fulfillment of the requirements for the degree Philosophiae Doctor (Electronics) in the Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Built Environment and Information Technology, University of Pretoriahttps://repository.up.ac.za/handle/2263/61301http://hdl.handle.net/10204/9645Thesis submitted in partial fulfillment of the requirements for the degree Philosophiae Doctor (Electronics) in the Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Built Environment and Information Technology, University of PretoriaApproximately three rhinos are poached daily in South Africa. Rhino poaching is a serious problem that affects not only the rhino population of South Africa, but also the rhino population of the world. South Africa has the largest rhino population and of those rhinos the largest number can be found in the Kruger National Park (KNP). The KNP has been hit the hardest by the poaching epidemic, losing 1,175 rhinos in 2015 alone. Two big challenges are the size of the park and the unknown locations of both the poachers and new poaching events. The KNP is the size of a small country and there are simply not enough rangers to patrol this area effectively. A costly solution would be to employ more rangers, but a proposed alternative is to reduce the search space and thus ensure that the rangers are allocated to the high risk areas first. A mathematical model was developed in the form of a Bayesian network (BN) to infer the most important factors contributing to poaching events and to model the rhino poaching problem. This model can be used to predict the area in which a future poaching attack could take place and thereby reduce the search area of rangers. The model also serves as a vehicle to enhance the understanding of the problem and encourage reasoning and discussion amongst decision makers. The map of the KNP is divided into cells and each cell is given a poaching probability, based on the outcome of the BN. This probability map forms a heat map that can be shown to the control centre and rangers can then be sent to the respective hotspots on the map. This is a proactive approach, which is in stark contrast to the numerous reactive approaches attempted thus far. This is the first BN modelling approach to the rhino poaching problem, and it is also the first BN application to wildlife crime. Previous applications of BN have only gone so far as environmental modelling, but not wildlife crimes. In this study the rhino poaching problem was shifted from a complex, ill-structured space to a position where researchers can begin to address the underlying problems by using a causal model as the vehicle for understanding the complex interplay between the factors affecting poaching events.enRhino poachingPredictive modellingShared awarenessCausal networksReportKoen, H. S. (2017). <i>Predictive Policing in an Endangered Species Context: Combating Rhino Poaching in the Kruger National Park</i> (Worklist;18573). Retrieved from http://hdl.handle.net/10204/9645Koen, Hildegarde S <i>Predictive Policing in an Endangered Species Context: Combating Rhino Poaching in the Kruger National Park.</i> Worklist;18573. 2017. http://hdl.handle.net/10204/9645Koen HS. Predictive Policing in an Endangered Species Context: Combating Rhino Poaching in the Kruger National Park. 2017 [cited yyyy month dd]. Available from: http://hdl.handle.net/10204/9645TY - Report AU - Koen, Hildegarde S AB - Approximately three rhinos are poached daily in South Africa. Rhino poaching is a serious problem that affects not only the rhino population of South Africa, but also the rhino population of the world. South Africa has the largest rhino population and of those rhinos the largest number can be found in the Kruger National Park (KNP). The KNP has been hit the hardest by the poaching epidemic, losing 1,175 rhinos in 2015 alone. Two big challenges are the size of the park and the unknown locations of both the poachers and new poaching events. The KNP is the size of a small country and there are simply not enough rangers to patrol this area effectively. A costly solution would be to employ more rangers, but a proposed alternative is to reduce the search space and thus ensure that the rangers are allocated to the high risk areas first. A mathematical model was developed in the form of a Bayesian network (BN) to infer the most important factors contributing to poaching events and to model the rhino poaching problem. This model can be used to predict the area in which a future poaching attack could take place and thereby reduce the search area of rangers. The model also serves as a vehicle to enhance the understanding of the problem and encourage reasoning and discussion amongst decision makers. The map of the KNP is divided into cells and each cell is given a poaching probability, based on the outcome of the BN. This probability map forms a heat map that can be shown to the control centre and rangers can then be sent to the respective hotspots on the map. This is a proactive approach, which is in stark contrast to the numerous reactive approaches attempted thus far. This is the first BN modelling approach to the rhino poaching problem, and it is also the first BN application to wildlife crime. Previous applications of BN have only gone so far as environmental modelling, but not wildlife crimes. In this study the rhino poaching problem was shifted from a complex, ill-structured space to a position where researchers can begin to address the underlying problems by using a causal model as the vehicle for understanding the complex interplay between the factors affecting poaching events. DA - 2017-02 DB - ResearchSpace DP - CSIR KW - Rhino poaching KW - Predictive modelling KW - Shared awareness KW - Causal networks LK - https://researchspace.csir.co.za PY - 2017 T1 - Predictive Policing in an Endangered Species Context: Combating Rhino Poaching in the Kruger National Park TI - Predictive Policing in an Endangered Species Context: Combating Rhino Poaching in the Kruger National Park UR - http://hdl.handle.net/10204/9645 ER -