Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test in Uganda

Domaine:

peace and security
Créateur:
Sha
Éditeur:
Ass
Hôte:
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 has modeled poachers’ behavior so as to aid rangers in planning future patrols, those models’ predictions were not validated by extensive field tests. In my thesis, I present a spatio-temporal model that predicts poaching threat levels and results from a five-month field test in Uganda’s Queen Elizabeth Protected Area (QEPA). To my knowledge, this is the first time that a predictive model has been evaluated through such an extensive field test in this domain. These field test will be extended to another park in Uganda, Murchison Fall Protected Area, shortly. Main goals of my thesis are to develop the best performing model in terms of speed and accuracy and use such model to generate efficient and feasible patrol routes for the park rangers.

Visit

doi.org

Similaires

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test EvaluationsA Hybrid GPR-GAM Model for Enhanced Spatio-Temporal Climate Prediction in KenyaCAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protectionekiru111/Uganda-Malaria-Spatio-temporal-MLEcoCast: A Spatio-Temporal Model for Continual Biodiversity and Climate Risk ForecastingExploiting Data and Human Knowledge for Predicting Wildlife Poaching

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations

Illegal wildlife poaching threatens ecosystems and drives endangered species toward extinction. Howe

A Hybrid GPR-GAM Model for Enhanced Spatio-Temporal Climate Prediction in Kenya

International audience Climate change presents growing challenges in regions like Ken

CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection

Wildlife poaching presents a serious extinction threat to many animal species. Agencies ("defenders"

ekiru111/Uganda-Malaria-Spatio-temporal-ML

ML-based spatio-temporal analysis of malaria risk factors in Uganda integrating survey, household, g

EcoCast: A Spatio-Temporal Model for Continual Biodiversity and Climate Risk Forecasting

Increasing climate change and habitat loss are driving unprecedented shifts in species distributions

Exploiting Data and Human Knowledge for Predicting Wildlife Poaching

Poaching continues to be a significant threat to the conservation of wildlife and the associated eco