Assessment of the importance of spatial scale in long-term land use modelling of the Midwestern United States
Abstract
The purpose of this study is to assess the value of enhanced spatial resolution in the agriculture and land use component of an integrated assessment model. While these models have historically represented land use decisions at the scale of geopolitical regions, the present generation uses regions defined by climatic or environmental characteristics, to better represent the spatial heterogeneity of land productivity and potential uses. However, increasing a model’s spatial resolution incurs costs, including input data processing, structural modifications, increased run time, and increased 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 sub-regional aggregation and three scenarios of future climate mitigation. We demonstrate benefits of enhanced spatial resolution, and to facilitate the assessment of higher resolution model output we apply non-metric multidimensional scaling on a pair-wise distance matrix for visualization and analysis.
- Authors:
-
- Pacific Northwest National Laboratory (PNNL), College Park, MD (United States)
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1229958
- Alternate Identifier(s):
- OSTI ID: 1251295
- Report Number(s):
- PNNL-SA-106492
Journal ID: ISSN 1364-8152; KP1703030
- Grant/Contract Number:
- AC05-76RL01830
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Environmental Modelling and Software
- Additional Journal Information:
- Journal Volume: 72; Journal ID: ISSN 1364-8152
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; 60 APPLIED LIFE SCIENCES; integrated assessment; multivariate statistics; non-metric multidimensional scaling; agriculture and land use
Citation Formats
Kyle, G. Page, Thomson, Allison M., Wise, Marshall A., and Zhang, Xuesong. Assessment of the importance of spatial scale in long-term land use modelling of the Midwestern United States. United States: N. p., 2015.
Web. doi:10.1016/j.envsoft.2015.06.006.
Kyle, G. Page, Thomson, Allison M., Wise, Marshall A., & Zhang, Xuesong. Assessment of the importance of spatial scale in long-term land use modelling of the Midwestern United States. United States. https://doi.org/10.1016/j.envsoft.2015.06.006
Kyle, G. Page, Thomson, Allison M., Wise, Marshall A., and Zhang, Xuesong. Wed .
"Assessment of the importance of spatial scale in long-term land use modelling of the Midwestern United States". United States. https://doi.org/10.1016/j.envsoft.2015.06.006. https://www.osti.gov/servlets/purl/1229958.
@article{osti_1229958,
title = {Assessment of the importance of spatial scale in long-term land use modelling of the Midwestern United States},
author = {Kyle, G. Page and Thomson, Allison M. and Wise, Marshall A. and Zhang, Xuesong},
abstractNote = {The purpose of this study is to assess the value of enhanced spatial resolution in the agriculture and land use component of an integrated assessment model. While these models have historically represented land use decisions at the scale of geopolitical regions, the present generation uses regions defined by climatic or environmental characteristics, to better represent the spatial heterogeneity of land productivity and potential uses. However, increasing a model’s spatial resolution incurs costs, including input data processing, structural modifications, increased run time, and increased 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 sub-regional aggregation and three scenarios of future climate mitigation. We demonstrate benefits of enhanced spatial resolution, and to facilitate the assessment of higher resolution model output we apply non-metric multidimensional scaling on a pair-wise distance matrix for visualization and analysis.},
doi = {10.1016/j.envsoft.2015.06.006},
journal = {Environmental Modelling and Software},
number = ,
volume = 72,
place = {United States},
year = {Wed Aug 12 00:00:00 EDT 2015},
month = {Wed Aug 12 00:00:00 EDT 2015}
}
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