Difference between revisions of "Heureka/PlanWise"
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== General System description == | == General System description == | ||
System name: Heureka PlanWise | System name: Heureka PlanWise | ||
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*Economic analysis | *Economic analysis | ||
*Find solutions to future shortage problems. | *Find solutions to future shortage problems. | ||
| − | *Exploration of | + | *Exploration of different management opportunities. |
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=== Related systems === | === Related systems === | ||
| − | PlanWise if part of the [[Heureka]] system software suite. It shares the same core as [[Heureka/StandWise | StandWise]] and [[Heureka/RegWise | RegWise]]. Plans or scenarios generated in PlanWise can be compared and ranked in [[Heureka/PlanEval | PlanEval]] which is a multi-criteria decision making tool. PlanEval is currently | + | PlanWise if part of the [[Heureka]] system software suite. It shares the same core as [[Heureka/StandWise | StandWise]] and [[Heureka/RegWise | RegWise]]. Plans or scenarios generated in PlanWise can be compared and ranked in [[Heureka/PlanEval | PlanEval]] which is a multi-criteria decision making tool. PlanEval is currently being further developed to support participatory planning with multiple stakeholders. |
== Data and data models == | == Data and data models == | ||
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==Output== | ==Output== | ||
===Types of outputs=== | ===Types of outputs=== | ||
| − | + | {{Heureka_Types_of_Outputs}} | |
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===Spatial analysis capababilities=== | ===Spatial analysis capababilities=== | ||
| − | PlanWise has built-in functions for computing | + | PlanWise has built-in functions for computing adjacencies (polygon pairs), shared border lengths, enumeration of feasible harvest clusters whose total area do not succeed a certain opening size constraint, and so-called cliques (combinations of mutually adjacent polygons). |
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| + | These functions are invoked when using the special feature of PlanWise to automatically add opening size constraints. PlanWise can automatically generate a so called EARM model (see Goycoolea et al 2005) <ref name="Goycoolea"> Goycoolea, M., Murray, A. T., Barahona, F., Epstein, R., Weintraub, A. 2005. Harvest scheduling subject to maximum area restrictions: Exploring exact approaches. Operations Research, 2005. Volume 53. Number 3.[http://mgoycool.uai.cl/papers/mgw04.pdf]</ref>. | ||
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| + | Results from PlanWise can also be evaluated with a GIS-tool called Heureka Habitat Prognois Model, which, however, has not been released yet. | ||
== System == | == System == | ||
Latest revision as of 06:42, 14 October 2012
General System description
System name: Heureka PlanWise
Contents
Brief overview
PlanWise is a software for forestry planning, especially adapted to boreal forests in Sweden. It is part of the Heureka system. It can be used for both small-scale and large-scale planning. The two main components are a built-in optimization modeling system for LP and MIP problems, and a treatment program generator for enumerating alternative management regimes. All tools and models needed for an analysis are included. Doing an analysis with PlanWise is a quite straight forward process, starting with data import, followed by defining treatment rules, generating alternatives, formulating and solving an optimization problem, and finally generating reports.
Scope of the system
PlanWise exploits a wide range of management options to create forestry plans that meet the goals of the decision maker in the best possible way. A decision maker can discover new opportunities by letting the system propose what kind of management to apply for different stands, and the timing of treatments. A multitude of both timber and non-timber values can be addressed.
System origin
The first version was developed by the Heureka Reserach Program in 2001-2009 by the Swedish University of Agricultural Sciences (SLU) and Skogforsk. Since 2009 the system is maintained and developed by | SLU.
Support of specific issues
PlanWise aims to be a flexible forestry planning tool that can handle several different ecosystems functions and services.
Support for specific thematic areas of a problem type
- Tactical and strategical planning.
- Identify sustainable harvest levels (annual allowable cuts)
- Analysis of long-term supply or availability of different wood products and other non-timber forest values.
- Evaluation of different management strategies and policies, including nature conservation.
- Generate input for multi-critera decision making (see below).
- Tradeoff analysis
- Economic analysis
- Find solutions to future shortage problems.
- Exploration of different management opportunities.
Related systems
PlanWise if part of the Heureka system software suite. It shares the same core as StandWise and RegWise. Plans or scenarios generated in PlanWise can be compared and ranked in PlanEval which is a multi-criteria decision making tool. PlanEval is currently being further developed to support participatory planning with multiple stakeholders.
Data and data models
Forest data input
The Heureka system includes a database that stores areas, stands, cells, sample plots, and tree-level data (sample trees). Functions are available to import NFI data, compartment register data, GIS shape files, kNN data, and some other data sources. In case tree-level data is not available, the system can simulate trees lists from theoretical diameter and height distribution models.
User input
There are extensive options for the user to control how computations are made. For example, the user can choose what growth model to use, the timing (range) of harvest activities, how thinnings should be performed, whether a certain part of a stand should be set aside for nature conservation, etc.
Models
The "driving force" in Heureka is the growth, mortality, regeneration and cutting of trees. There models constitute the growth-and-yield models, on which most of the other models in the system depend. An exception is the soil model which predicts the amout of soil carbon and soil nitrogen, using litter as one input.
PlanWise supports forest planning problems of Model 1 type[1], meaning that the developement of each stand is projected over the entire planning horizon.
Decision Support
The built-in optimization modeling system makes the system quite comprehensive with respect to what kind of analysis that can be done. The optimization modeling language is ZIMPL, to which a graphical user interface has been developed, with direct links to the output variables calculated by system.
Decision making processes and models
PlanWise is a tool for generating plans that contain a wide variaty of out put data. Optimization is used to obtain optimal solution to given problem. By varying input assumptions in the optimization problems, for example on the opening size allowed, differtn plans can be obtained. These plans can then be used as input alternatives to PlanEval for multi-criteria decision making process with one or more stake-holders.
Output
Types of outputs
A report builder allows the user to make both detailed and summary reports (tables and graphs) for almost any variable. All results are stored in a SQL Server database, so ordinary SQL Queries can also be made directly to the database. A map viewer is also built-in and can display thematic maps for a sequence of time periods. The following results categories can be reported:
- Costs and revenues
- Net present values
- Recreation indices
- Growth and mortality
- Biomass contents
- Species-level outputs and states
- Carbon storage
- Dead wood
Spatial analysis capababilities
PlanWise has built-in functions for computing adjacencies (polygon pairs), shared border lengths, enumeration of feasible harvest clusters whose total area do not succeed a certain opening size constraint, and so-called cliques (combinations of mutually adjacent polygons).
These functions are invoked when using the special feature of PlanWise to automatically add opening size constraints. PlanWise can automatically generate a so called EARM model (see Goycoolea et al 2005) [2].
Results from PlanWise can also be evaluated with a GIS-tool called Heureka Habitat Prognois Model, which, however, has not been released yet.
System
System requirements
PlanWise runs under Windows (XP or later). Access to an SQL Server (2005 or later) database is required for storing input data and results.
Architecture and development plattform
see Heureka
Linear programming solvers are LP_Solve, SCIP/Soplex, and CPLEX. LP_Solve is free, and the other solvers require a license.
Usage
The system is used by researchers, students, forest owners, forest companies, and other organizations.
Computational limitations
There are no explicit limitations on the number of timer periods or number of stands that can be handled, but problem size is constrained by computer memory size and processing capacity. The largrest problem solved so far had 25 000 stands and a planning horizon of 20 five-year periods (2011), using a 64-bit version of PlanWise on a PC with 8 GB RAM and an Intel I7 processor. The generation of treatment program alternatives can be quite time-consuming and increases exponentially with the number of time periods (20 hours for the case mentioned).
User interface
PlanWise has a quite comprehensive graphical user interface.
- The optimization programming model has syntax checking and higllighting.
- The user can define so called forest domains for classifying stands into management groups, where stands in a group can be assigned certain management strategies, which are also defined by the user.
- A report builder allows the user to make reports and maps for almost any any variable. The map viewer is bulit-in and can display thematic maps for a sequence of time periods.
Documentation and support
Documentation and user's guides are available at the Heureka Wiki website.
Installation
The program is freely available after registration. The program is available as a ClickOnce application, with possibility to get automatic upgrades when new version are released.
References
Cited references
- ↑ Johnson, K. Norman, and Scheurman, H. Lynn. Techniques for Prescribing Optimal Timber Harvest and Investment Under Different Objectives - Discussion and Synthesis. 1977. Forest Science Monograph.
- ↑ Goycoolea, M., Murray, A. T., Barahona, F., Epstein, R., Weintraub, A. 2005. Harvest scheduling subject to maximum area restrictions: Exploring exact approaches. Operations Research, 2005. Volume 53. Number 3.[1]
