Description
Climate change is a growing concern in the Forestry Industry. Trees are adapted to growing in certain conditions and changes in these conditions can lead to changes in productivity. Coillte, Ireland’s national forestry company, have data that shows the productivity at different locations of various tree species under different climatic scenarios. In this study, we attempt to incorporate this spatial data into Coillte’s strategic planning system. Our approach integrates GIS data with recursive linear programming (LP) and involves creating decision variables that reflected the composition of a forest. This approach allows us to reflect the changing growth rates of tree species in the LP model, where the model aims to maximise the Net Present Value (NPV) of the forest over a planning horizon. The goal of the study is to compare varying values of NPV under different climate change scenarios.
Recommended Citation
Keenan, Peter; Carroll, Paula; Conway, Henry; and Lee, Stephen, "Spatial modelling of climate change in Irish forestry" (2017). AMCIS 2017 Proceedings. 25.
https://aisel.aisnet.org/amcis2017/DataScience/Presentations/25
Spatial modelling of climate change in Irish forestry
Climate change is a growing concern in the Forestry Industry. Trees are adapted to growing in certain conditions and changes in these conditions can lead to changes in productivity. Coillte, Ireland’s national forestry company, have data that shows the productivity at different locations of various tree species under different climatic scenarios. In this study, we attempt to incorporate this spatial data into Coillte’s strategic planning system. Our approach integrates GIS data with recursive linear programming (LP) and involves creating decision variables that reflected the composition of a forest. This approach allows us to reflect the changing growth rates of tree species in the LP model, where the model aims to maximise the Net Present Value (NPV) of the forest over a planning horizon. The goal of the study is to compare varying values of NPV under different climate change scenarios.