What is ESTTO?

      The regional landscape pattern determines various ecological processes within the ecosystem. Currently, landscape pattern optimization is generally based on policy and planning requirements, and multiple optimization scenarios are set up. Commonly used models such as cellular automata, CLUE-S, and agents are used to redistribute landscape patterns spatially. However, multi-scenario optimization has limited improvement on the trade-offs of ecosystem services. The challenge remains in how to adjust landscape patterns to maximize current ecosystem services and find the optimal solution for regional ecosystem services. This still poses a difficulty in ecological service trade-off research.

     ESTTO was developed by "Ecosystem services and landscape sustainability Group" led by Prof. Xiao Sun. It innovatively converts raster data and constraints into abstract linear programming mathematical problems and implements them through a plug-in architecture. It conveniently utilize various solvers for commercial (GUROBI, IBM ILOG CPLEX) and open-source/free (SCIP, CBC) purposes to assist in generating production possibility frontier and then finding the optimal solution and landscape spatial patterns for reducing trade-offs between ecosystem services or socio-ecological indicators, or achieving win-win outcomes.