Code and data for: Integrating wind disturbances into Forest planning: A stochastic programming approach
Authors/Creators
- 1. NMBU
- 2. LUKE
- 3. TUM
Contributors
Contact person:
Description
The dataset archived here is the aggregation of 204 projections of forest land according to a selection of forest management alternatives and wind events. The data has been simulated using the SIMO forest planning software (Rasinmäki et al. 2008), which incorporates the HWind model based on Heinenen et al. (2009). The scenarios represent a specific wind intensity (14 m/s, 18 m/s and 22 m/s, representing low, moderate and high intensity), at a variety of frequencies.
The code archived here extracts specific information from the datasets, produces a stochastic programming formulation and solves using open sourced software (python, pyomo), and creates figures to represent the information in a logical and interpretable fashion. For specific information, readers are refered to the readme text found in the code zip file. Relates to https://github.com/eyvindson/WindRiskGraphing
Files
WindRisk_Data.zip
Files
(2.0 GB)
| Name | Size | Download all |
|---|---|---|
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md5:1ca95e34be29173a90cbe745554089f3
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2.0 GB | Preview Download |
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md5:4480c9d35441eedd5d5d24af58cad29f
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3.5 MB | Preview Download |
Additional details
Dates
- Available
-
2024-05-24
Software
- Repository URL
- https://github.com/eyvindson/WindRiskGraphing
- Programming language
- Python
References
- Rasinmäki, J., Mäkinen, A., and Kalliovirta, J. 2009. SIMO: An adaptable simulation framework for multiscale forest resource data. Computers and Electronics in Agriculture 66(1): 76–84. doi:10.1016/j.compag.2008.12.007.
- Heinonen, T., Pukkala, T., Ikonen, V.-P., Peltola, H., Venäläinen, A., and Dupont, S. 2009. Integrating the risk of wind damage into forest planning. Forest Ecology and Management 258(7): 1567–1577. doi:10.1016/j.foreco.2009.07.006