Computer Science 5th Year Masters Thesis Presentation

  • Remote Access - Zoom
  • Virtual Presentation - ET
  • Masters Student
  • Computer Science Department
  • Carnegie Mellon University
Master's Thesis Presentation

Reducing Poaching Risk through Land Use and Patrol Routes Planning using Data Driven Optimization

The forest, along with the many products it provides, is an important source of income to the local population of the Congo Basin. Specifically, legal logging generates revenue for the local government and creates jobs for residents. However, the increase of human intrusion on the forest threatens the livelihood of ecosystems. Studies have found that the roads built by logging companies to transport logs have facilitated poaching activity in the area. Adequate land zoning can be a solution to this issue. Through zoning a forest, different areas with their respective levels of suitability for various objectives can be assigned specific usages such that an optimal value in suitability and compatibility with the local environment and economy can be achieved. In our work, we identify logging activity as a pertinent feature towards predicting poaching risk in the Congo, and propose a data-driven zoning method to determine the optimal land use for sub-regions within the area.

Thesis Committee:
Fei Fang (Chair)
George Chen

Zoom Participation. See announcement.

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