prioritizr - Systematic Conservation Prioritization in R

Systematic conservation prioritization using mixed integer linear programming (MILP). It provides a flexible interface for building and solving conservation planning problems. Once built, conservation planning problems can be solved using a variety of commercial and open-source exact algorithm solvers. By using exact algorithm solvers, solutions can be generated that are guaranteed to be optimal (or within a pre-specified optimality gap). Furthermore, conservation problems can be constructed to optimize the spatial allocation of different management actions or zones, meaning that conservation practitioners can identify solutions that benefit multiple stakeholders. To solve large-scale or complex conservation planning problems, users should install the Gurobi optimization software (available from <https://www.gurobi.com/>) and the 'gurobi' R package (see Gurobi Installation Guide vignette for details). Users can also install the IBM CPLEX software (<https://www.ibm.com/products/ilog-cplex-optimization-studio/cplex-optimizer>) and the 'cplexAPI' R package (available at <https://github.com/cran/cplexAPI>). Additionally, the 'rcbc' R package (available at <https://github.com/dirkschumacher/rcbc>) can be used to generate solutions using the CBC optimization software (<https://github.com/coin-or/Cbc>). For further details, see Hanson et al. (2024) <doi:10.1111/cobi.14376>.

Last updated 2 months ago

biodiversityconservationconservation-planneroptimizationprioritizationsolverspatialcpp

11.62 score 123 stars 2 dependents 604 scripts 1.3k downloads

prepr - Automatic Repair of Spatial Polygons

Automatically repair broken spatial polygons using constrained triangulation. The computational methodology is derived from Ledoux et al. (2014) <doi:10.1016/j.cageo.2014.01.009>.

Last updated 8 months ago

gisspatialgdalgmpcpp

3.48 score 6 stars 17 scripts