Hugin
General System description
System name: HUGIN
Brief description
HUGIN is a DSS used to derive the timber production possibilities at national and regional level for Sweden, associated to different forest management strategies and environmental policies.
Contents
Scope of the system
HUGIN is based on the Swedish National Forest Inventory. Together with individual tree growth prognosis and a management programme, the forecasts for both the state of the forest, growth and potential cutting level are made.
System origin
- HUGIN's development started in the late 70's
- Despite being an old DSS, it is still in use[1]. It has been used for two forest harvest projections for the whole Sweden. Also, it has been used by large forest companies to make harvest projections and to calculate the supply of biomass for fuel in order to allocate heating plants.
Support for specific issues
It can study the consequences of different management regimes with regard to the output of timber and forest fuels, and issues like carbon sequestration in forests[2].
Support for specific thematic areas of a problem type
- Silvicultural
- Certification
- Conservation
- Restoration
- Transportation
- Development choices / land use zoning
- Policy/intervention alternatives
Related systems
Data and data models
Typical spatial extent of application
HUGIN system aims to make forecasts at the regional and national scale of the forest.
Forest data input
The input data unit is the individual tree. Data for the HUGIN system are tree, stand and site variables from the sample plots of the Swedish National Forest Inventory (NFI), including ownership and geographic variables.
Models
Forest models
Growth is calculated at the individual tree level. Management is assigned to a certain share of the sample plots, according to priority rules based on what is considered to be good management, but some of them, a small number, are selected more or less random.
HUGIN also contains total tree biomass functions (for Swedish conditions) with which the total forest biomass development over time can be studied.
Decision Support
Definition of management interventions
The following treatments can be studied using the HUGIN system:
- regeneration methods (planting, sowing, natural regeneration),
- pre-commercial thinning,
- fertilisation,
- final felling,
- drainage of peatland, and
- thinning (weight, species, diameter distribution).
Typical temporal scale of application
Strategic level. Growth is calculated on five year periods, but the results are presented over 10-year periods. Projections are usually done over 100 years.
Types of decisions supported
- Management level
- strategic decisions
- administrative decisions
- Management function
- planning decisions
- organizing decisions
- decision making situation
- unilateral
- collegial
- Bargaining / participative decision making
Decision-making processes and models
HUGIN is a deterministic simulation model, though containing some stochastic elements. No optimization is used.
Output
Types of outputs
Result consists of standard tables that present each 10 years the state of the forest, harvested volume (both over bark and solid), growth and mortality by tree species, clear-cut area, composition of fellings, and timber quality.
Spatial analysis capabilities
Some adjacency constraints can be taken into account. For example, plots close to roads, lakes or houses can be given a special treatment.
System
System requirements
- Operating Systems: VAX-VMS, UNIX
Architecture and major DSS components
HUGIN was developed in FORTRAN programming language, It is compatible with MIMER, EXCEL and INGRESS.
Usage
It has been used for state forests, by forest companies, national and local Boards of Forestry, various organizations, and researchers.
User interface
Although being handled by only a few persons in the department, the system is rather user-friendly.
References
Cited references
- ↑ ANDERSSON, M., B. DAHLIN et M. MOSSBERG (2005): The Forest Time Machine — a multi-purpose forest management decision-support system. Computers and Electronics in Agriculture, 49, 114–128.
- ↑ BÅÅTH, H., A. GÄLLERSPÅNG, G. HALLSBY, A. LUNDSTRÖM, P. LÖFGREN, M. NILSSON et G. STÅHL (2002): Remote sensing, field survey, and long-term forecasting: an efficient combination for local assessments of forest fuels. Biomass and Bioenergy, 22, 145-157.
External resources
- NABUURS G.J. et R. PÄIVINEN (1996): Large Scale Forestry Scenario Models - a compilation and review. European Forest Institute Working Paper No. 10. Joensuu, Finland.
