1. SIMO SIMulation and Optimization ”New generation forest planning system” 13.02.2006 Antti Mäkinen Dept. of Forest Resource Management / University of Helsinki

2. 2 Forest planning systems Analytical tools for forest planning and decision making Used for analyzing production potentials, forest trends, forest managament practices, conflict management etc. Systems create different future ’scenarios’ that are used to evaluate consequences of different actions in the unknown future Planning systems range from small-scale and short-term to large-scale and long-term forestry models

3. 3 Need for new planning system? Forestry databases maintained in Finland mostly collected either with National Forest Inventory compartment-wise inventory Current forest management planning systems are designed to suit these two data sets Stand volume, timber assortments and growth are predicted using single tree models In the future the data sources are much more variable, including data from several grain levels → Need for new planning tools

4. 4 SIMO project Collaboration of different finnish forestry organizations (UPM- Kymmene, Tornator, Metsämannut, Metsähallitus, Tapio, Forestry Centres and University of Helsinki) 3-year project, started october 2004 At the moment, a lot of background work has been done in order to build an appropriate planning system: Data system analysis Model collection and evaluation System design and software development Stand simulator with J software development tool Actual simulator is under development at the moment

5. 5 Aims of SIMO ”FLEXIBLE with respect to data it demands and models that it uses” ”ADAPTABLE to the planning problem” “EXTENDABLE for possible future needs” “provide decision support for different grain levels”

6. 6 Aims of SIMO continued To produce a set of lightweight program modules, which the users can interface into their planning systems Modules should be adaptable to different planning tasks and needs Simulation parameters can be (easily) controlled by the user Simulations can be locally calibrated Uncertainty in the data can be taken into account

7. 7 Aims of SIMO continued New models can be implemented by the user Possibility to utilize different data sources Planning system is not a ”black box” – user should know what happens inside the program Inconsistent or erroneus data can be handled, but the user will be informed precisely

8. 8 SIMO software development The core modules of the planning system will be produced in this project (no user interfaces) All of the modules will be open-source code (MIT license) The users will handle the integration into their own systems At the moment the simulator module is well underway and other modules are being developed

9. 9 System structure SIMULATOR module, produces the alternative management scenarios OPTIMIZER module, finds the optimal scenario from the scenarios with given constraints DATA INPUT/OUTPUT interfaces, connection to the database & data storage REPORTER module, data visualizations & formatting SPATIAL OPERATIONS module, handles the spatiality of the simulations

10. 10 Development tools etc. Simulator programming with Python Model library programming in C/C++ Data, simulation control & logic, model chains, model metadata etc. in XML (eXtended Markup Language)

11. 11 How the simulation process works in SIMO? XML Files SIMULATOR MODEL LIBRARY Reporter Module IN: data, simulation control, modelchains, model definitions OUT: results IN: modelname, input variables OUT: model result, warnings & errors IN: XML data OUT: transformed XML, graphs SIMULATION PROCESS

12. 12 What is missing? XML Files SIMULATOR MODEL LIBRARY Reporter Module Optimizer Module MODEL LIBRARY Validator Module Spatial Module Input/output interface

13. 13 Strengths of SIMO XML Simulator  Virtually any kind of model can be used in the simulations and added to the model library  User can define correction/rectification factors for the models, (eg. different factors for geographical areas)  Data levels are not confined to strict predifined standard  User can define the model chains freely for different kinds of simulations  SIMO is ADAPTABLE, EXTENDABLE and FLEXIBLE

14. 14 More on SIMO Documentation, software components, presentations, log of the project etc. can be found at: http://honeybee.helsinki.fi/mmvar/simo Department home: http://honeybee.helsinki.fi/mmvar