Assessment of the Importance of Spatial Scale in Long-Term Land Use Modeling of the Midwestern United States

TitleAssessment of the Importance of Spatial Scale in Long-Term Land Use Modeling of the Midwestern United States
Publication TypeJournal Article
Year of Publication2015
AuthorsKyle, Page, Thomson Allison, Wise Marshall, and Zhang Xuesong
JournalEnvironmental Modelling and Software
Volume72
Pages261-271
Date Published08/2015
Abstract / Summary

This study assesses the value of enhanced spatial resolution in the agriculture and land use component of an integrated assessment (IA) model. IA models typically represent land use decisions at finer resolution than the energy and economic components, to account for spatial heterogeneity of land productivity and use. However, increasing spatial resolution incurs costs, from additional input data processing, run time, and complexity of results. This study uses the Global Change Assessment Model (GCAM) to analyze land use in the Midwestern United States in three levels of spatial aggregation, and three climate change mitigation scenarios. For visualization and simplification of higher resolution model output, we use non-metric multidimensional scaling. We find that the level of spatial aggregation influences the magnitude but not the direction of land use change in response to the modeled drivers, and in the examples analyzed, increasing spatial resolution reduces the extent of land use change.

URLhttp://www.sciencedirect.com/science/article/pii/S1364815215001711
DOI10.1016/j.envsoft.2015.06.006
Funding Program: 
Journal: Environmental Modelling and Software
Year of Publication: 2015
Volume: 72
Pages: 261-271
Date Published: 08/2015

This study assesses the value of enhanced spatial resolution in the agriculture and land use component of an integrated assessment (IA) model. IA models typically represent land use decisions at finer resolution than the energy and economic components, to account for spatial heterogeneity of land productivity and use. However, increasing spatial resolution incurs costs, from additional input data processing, run time, and complexity of results. This study uses the Global Change Assessment Model (GCAM) to analyze land use in the Midwestern United States in three levels of spatial aggregation, and three climate change mitigation scenarios. For visualization and simplification of higher resolution model output, we use non-metric multidimensional scaling. We find that the level of spatial aggregation influences the magnitude but not the direction of land use change in response to the modeled drivers, and in the examples analyzed, increasing spatial resolution reduces the extent of land use change.

DOI: 10.1016/j.envsoft.2015.06.006
Citation:
Kyle, P, A Thomson, M Wise, and X Zhang.  2015.  "Assessment of the Importance of Spatial Scale in Long-Term Land Use Modeling of the Midwestern United States."  Environmental Modelling and Software 72: 261-271, pp. 261-271.  https://doi.org/10.1016/j.envsoft.2015.06.006.