TY - JOUR
T1 - Modeling illegal logging in Brazil
AU - Chen, Bohan
AU - Peng, Kaiyan
AU - Parkinson, Christian
AU - Bertozzi, Andrea L.
AU - Slough, Tara Lyn
AU - Urpelainen, Johannes
N1 - Funding Information:
This research is funded by NSF grant DMS-1737770 and an academic grant from the National Geospatial-Intelligence Agency (Award No. # HM0210-14-1-0003, Project Title: ?Sparsity models for spatiotemporal analysis and modeling of human activity and social networks in a geographic context?), approved for public release, 20-578. The authors thank Raymond Chu, Yixuan (Sheryl) He, and Joseph McGuire for valuable discussions and for performing work related to modeling of Brazilian deforestation during the UCLA Mathematical Modeling REU in the summer of 2019. The authors would like to thank Alexander Vladimirsky for very helpful and thorough comments which improved the methodology and the exposition of the manuscript. The elevation data was downloaded from the Shuttle Radar Topography Mission [13]. This data was processed using the Quantum Geographic Information System [30], and imported to MATLAB using TopoToolbox [31 , 32]. On behalf of all authors, the corresponding author states that there is no conflict of interest.
Funding Information:
This research is funded by NSF grant DMS-1737770 and an academic grant from the National Geospatial-Intelligence Agency (Award No. # HM0210-14-1-0003, Project Title: “Sparsity models for spatiotemporal analysis and modeling of human activity and social networks in a geographic context”), approved for public release, 20-578. The authors thank Raymond Chu, Yixuan (Sheryl) He, and Joseph McGuire for valuable discussions and for performing work related to modeling of Brazilian deforestation during the UCLA Mathematical Modeling REU in the summer of 2019. The authors would like to thank Alexander Vladimirsky for very helpful and thorough comments which improved the methodology and the exposition of the manuscript. The elevation data was downloaded from the Shuttle Radar Topography Mission []. This data was processed using the Quantum Geographic Information System [], and imported to MATLAB using TopoToolbox [, ]. On behalf of all authors, the corresponding author states that there is no conflict of interest.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/6
Y1 - 2021/6
N2 - Deforestation is a major threat to global environmental wellness, with illegal logging as one of the major causes. Recently, there has been increased effort to model environmental crime, with the goal of assisting law enforcement agencies in deterring these activities. We present a continuous model for illegal logging applicable to arbitrary domains. We model the practice of criminals under influence of law enforcement agencies using tools from multiobjective optimal control theory and consider non-instantaneous logging events and load-dependent travel velocity. We calibrate our model using real deforestation data from the Brazilian rainforest and demonstrate the importance of geographically targeted patrol strategies.
AB - Deforestation is a major threat to global environmental wellness, with illegal logging as one of the major causes. Recently, there has been increased effort to model environmental crime, with the goal of assisting law enforcement agencies in deterring these activities. We present a continuous model for illegal logging applicable to arbitrary domains. We model the practice of criminals under influence of law enforcement agencies using tools from multiobjective optimal control theory and consider non-instantaneous logging events and load-dependent travel velocity. We calibrate our model using real deforestation data from the Brazilian rainforest and demonstrate the importance of geographically targeted patrol strategies.
KW - Fast sweeping method
KW - Hamilton–Jacobi–Bellman equation
KW - Illegal logging
KW - Optimal control
KW - Optimal path planning
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U2 - 10.1007/s40687-021-00263-6
DO - 10.1007/s40687-021-00263-6
M3 - Article
AN - SCOPUS:85105143749
VL - 8
JO - Research in Mathematical Sciences
JF - Research in Mathematical Sciences
SN - 2522-0144
IS - 2
M1 - 29
ER -