Difference between revisions of "GAYA"
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== General System description == | == General System description == | ||
| − | System name: GAYA | + | System name: GAYA |
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=== Brief overview === | === Brief overview === | ||
| − | + | GAYA is a forest simulator that may be applied to stands or sample plots. Different optimization tools can be connected to the simulator.The first version of GAYA was developed by Prof. Ljusk Ola Eriksson at the Swedish University of Agricultural Sciences. GAYA was "imported" to Norway and transferred to Norwegian conditions by the professors Hans Fredrik Hoen and Tron Eid at the Norwegian University of Life Sciences around 1990. | |
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[[Category:Decision support system]] | [[Category:Decision support system]] | ||
[[Category:Swedish DSS]] | [[Category:Swedish DSS]] | ||
| − | [[Category: | + | [[Category:Norwegian DSS]] |
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__TOC__ | __TOC__ | ||
=== Scope of the system === | === Scope of the system === | ||
| − | GAYA- | + | GAYA is a forest simulator describing the forest dynamics according to silvicultural treatments. The simulations are based on predefined forest treatments and area-based models describing growth, mortality, prices and costs. Calculations and ”book-keeping” is carried out for up to 20 periods of 5 or 10 years. GAYA is used both for long term forest management planning at forest level based on information for individual forest stands, and for analyses based on sample plots e.g. from the national forest inventory. |
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=== System origin === | === System origin === | ||
| − | * GAYA | + | * GAYA was developed for long-term economic analysis of forest production it is used for research and education in Sweden and Norway. |
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=== Support for specific issues === | === Support for specific issues === | ||
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=== Related systems === | === Related systems === | ||
| − | It has a strong resemblance to the Finish [[MELA]] model. | + | It has a strong resemblance to the Finish [[MELA]] model and GAYA is a major part in the [[SGIS]] system. |
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== Data and data models == | == Data and data models == | ||
=== Typical spatial extent of application === | === Typical spatial extent of application === | ||
| − | + | GAYA is using stand level growth models. | |
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=== Forest data input === | === Forest data input === | ||
| − | + | About 30 state variables are used for defining the forest stand. They are divided between species, biologically, and economically related variables. | |
* Species is defined by tree number, basal are, height, age and volume. | * Species is defined by tree number, basal are, height, age and volume. | ||
* Stand is further defined by area, site index, and e.g. earlier treatments in the rotation. | * Stand is further defined by area, site index, and e.g. earlier treatments in the rotation. | ||
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=== Type of information input from user === | === Type of information input from user === | ||
| − | The following control variables can be user-specified | + | The following control variables are examples of variables that can be user-specified when defining potential treatments: |
* basal area of the removal as a percentage of total basal area; | * basal area of the removal as a percentage of total basal area; | ||
* basal area in the remaining stand; | * basal area in the remaining stand; | ||
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* number of trees in the remaining stand; | * number of trees in the remaining stand; | ||
* diameter ratio between removed trees and remaining stand; | * diameter ratio between removed trees and remaining stand; | ||
| − | * type of | + | * type of fertilizer; |
| − | * intensity of | + | * intensity of fertilizer. |
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== Models == | == Models == | ||
=== Forest models === | === Forest models === | ||
| − | GAYA | + | GAYA simulates alternative forest management treatment schedules for each calculation unit. Up to three species per stand can be simulated, projecting its development separately. Development is simulated based on area-based models describing diameter, basal area, height, spacing and natural mortality. The time dimension of the calculations is user controlled, i.e. a discrete number of time periods of uniform length of 5 or 10 years may be applied. Costs, revenues and a net present value are calculated for all treatment schedules of each calculation unit. |
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== Decision Support == | == Decision Support == | ||
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=== Definition of management interventions === | === Definition of management interventions === | ||
Silvicultural treatments, fertilization, regeneration methods, thinnings, harvesting. | Silvicultural treatments, fertilization, regeneration methods, thinnings, harvesting. | ||
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=== Decision-making processes and models === | === Decision-making processes and models === | ||
| − | The | + | The simulated treatment schedules can be exported to an optimization module to solve the planning problem. The [[JLP]]-package and the [[J]]-package is commonly used and they both use [[:Category:Linear programming|linear programming]]. |
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== Output == | == Output == | ||
=== Types of outputs === | === Types of outputs === | ||
| − | Outputs are displayed in tables, showing | + | Outputs are displayed in tables, showing a number of defined variables for each time period. They are divided in periodic and non-periodic variables. |
Periodic variables | Periodic variables | ||
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Non-periodic variables | Non-periodic variables | ||
:For the treatment schedule: NPV at time zero, ending inventory value (EIV; NPV at the end of the last period). NPV and EIV of CO<sub>2</sub>-flow, total NPV in case CO<sub>2</sub>-flow is priced. | :For the treatment schedule: NPV at time zero, ending inventory value (EIV; NPV at the end of the last period). NPV and EIV of CO<sub>2</sub>-flow, total NPV in case CO<sub>2</sub>-flow is priced. | ||
| − | :Variables for the calculation unit: number of schedules, area, site, vegetation type, altitude, | + | :Variables for the calculation unit: number of schedules, area, site, vegetation type, altitude, rentability, slope, and a GIS-specified treatment code. |
=== Spatial analysis capabilities === | === Spatial analysis capabilities === | ||
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=== System requirements === | === System requirements === | ||
| − | Operating Systems: | + | Operating Systems: Windows XP and above. |
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=== Usage === | === Usage === | ||
| − | + | Developed for research and educational level. However, GAYA is also used at some Norwegian forest inventory companies as a part of [[SGIS]]. | |
=== Computational limitations === | === Computational limitations === | ||
| − | + | GAYA is developed using FORTRAN. | |
=== User interface === | === User interface === | ||
| − | Command line interface | + | Command line interface and defining potential treatments in a command file are laborious. However, sample command files are available. And graphical user interface developed in MS Excel is also available. |
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== References == | == References == | ||
Latest revision as of 07:00, 14 October 2012
General System description
System name: GAYA
Brief overview
GAYA is a forest simulator that may be applied to stands or sample plots. Different optimization tools can be connected to the simulator.The first version of GAYA was developed by Prof. Ljusk Ola Eriksson at the Swedish University of Agricultural Sciences. GAYA was "imported" to Norway and transferred to Norwegian conditions by the professors Hans Fredrik Hoen and Tron Eid at the Norwegian University of Life Sciences around 1990.
Contents
Scope of the system
GAYA is a forest simulator describing the forest dynamics according to silvicultural treatments. The simulations are based on predefined forest treatments and area-based models describing growth, mortality, prices and costs. Calculations and ”book-keeping” is carried out for up to 20 periods of 5 or 10 years. GAYA is used both for long term forest management planning at forest level based on information for individual forest stands, and for analyses based on sample plots e.g. from the national forest inventory.
System origin
- GAYA was developed for long-term economic analysis of forest production it is used for research and education in Sweden and Norway.
Support for specific issues
It provides support for forest management planning, through harvesting scheduling, economic evaluation, CO2-flow evaluation, yield prediction, and its optimization.
Support for specific thematic areas of a problem type
- Silvicultural
- Certification
- Conservation
- Development choices / land use zoning
- Policy/intervention alternatives
Related systems
It has a strong resemblance to the Finish MELA model and GAYA is a major part in the SGIS system.
Data and data models
Typical spatial extent of application
GAYA is using stand level growth models.
Forest data input
About 30 state variables are used for defining the forest stand. They are divided between species, biologically, and economically related variables.
- Species is defined by tree number, basal are, height, age and volume.
- Stand is further defined by area, site index, and e.g. earlier treatments in the rotation.
- Economical stand related variables are the terrain transportation distance, several difficulty parameters related to felling operations and a wood quality parameter.
Type of information input from user
The following control variables are examples of variables that can be user-specified when defining potential treatments:
- basal area of the removal as a percentage of total basal area;
- basal area in the remaining stand;
- number of trees in the removal;
- number of trees in the remaining stand;
- diameter ratio between removed trees and remaining stand;
- type of fertilizer;
- intensity of fertilizer.
Models
Forest models
GAYA simulates alternative forest management treatment schedules for each calculation unit. Up to three species per stand can be simulated, projecting its development separately. Development is simulated based on area-based models describing diameter, basal area, height, spacing and natural mortality. The time dimension of the calculations is user controlled, i.e. a discrete number of time periods of uniform length of 5 or 10 years may be applied. Costs, revenues and a net present value are calculated for all treatment schedules of each calculation unit.
Decision Support
Definition of management interventions
Silvicultural treatments, fertilization, regeneration methods, thinnings, harvesting.
Decision-making processes and models
The simulated treatment schedules can be exported to an optimization module to solve the planning problem. The JLP-package and the J-package is commonly used and they both use linear programming.
Output
Types of outputs
Outputs are displayed in tables, showing a number of defined variables for each time period. They are divided in periodic and non-periodic variables.
Periodic variables
- Treatment undertaken in the period.
- For stand after treatment: total tree number, standing volume by species, basal area, dominant height, age, and NAI (Net Area Increment).
- Removal: total tree number, volume for each species., basal area, mean diameter, sawwood and pulpwood proportions, price and cost information (including haulage costs), cash flow, total biomass, and net CO2 flow.
Non-periodic variables
- For the treatment schedule: NPV at time zero, ending inventory value (EIV; NPV at the end of the last period). NPV and EIV of CO2-flow, total NPV in case CO2-flow is priced.
- Variables for the calculation unit: number of schedules, area, site, vegetation type, altitude, rentability, slope, and a GIS-specified treatment code.
Spatial analysis capabilities
Spatial constraints such as adjacency cannot be taken into account. However, a GIS integration implementation is operative.
System
System requirements
Operating Systems: Windows XP and above.
Usage
Developed for research and educational level. However, GAYA is also used at some Norwegian forest inventory companies as a part of SGIS.
Computational limitations
GAYA is developed using FORTRAN.
User interface
Command line interface and defining potential treatments in a command file are laborious. However, sample command files are available. And graphical user interface developed in MS Excel is also available.
References
Cited references
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.
