Evaluation of Predictive Models forWildlife Poaching Activity through Controlled Field Test in Uganda - Gholami, Shahrzad; Ford, Benjamin; Kar, Debarun; Fang, Fei; Tambe, Milind; Plumptre, Andrew; Driciru, Margaret; Wanyama, Fred; Rwetsiba, Aggrey; Nsubaga, Mustapha; Mabonga, Joshua (AAAI Conference on Artificial Intelligence, 2018)
Worldwide, conservation agencies employ rangers to protect conservation areas from poachers. However, agencies lack the manpower to have rangers effectively patrol these vast areas frequently. While past work modeled poachers behavior so as to aid rangers in planning future patrols, those models predictions were not validated by extensive field tests.We conducted two rounds of field tests in Ugandas Queen Elizabeth Protected Area to evaluate our proposed spatio-temporal model that predicts poaching threat levels. In the first round, a one-month field test was conducted to test the predictive power of the model and in the second round an eight-month test was conducted to evaluate the selectiveness power of the model. To our knowledge, this is the first time that a predictive model is evaluated through such an extensive field test in this domain. These field tests will be extended to another park in Uganda, Murchison Fall Protected Area. Once such models are evaluated in the field, they can be used to generate efficient and feasible patrol routes for the park rangers.