gcamland v1.0 – An R Package for Modelling Land Use and Land Cover Change

Katherine Calvin; Robert Link; Marshall Wise

doi:10.5334/jors.233

gcamland v1.0 – An R Package for Modelling Land Use and Land Cover Change

Journal of Open Research Software

Volume 7 (2019): Issue 1

By: Katherine Calvin , Robert Link and Marshall Wise

Open Access

|Oct 2019

Abstract

gcamland v1.0 is an open source R package that was built to allocate land across a variety of uses based on changes in agricultural yield and commodity price. The land allocation algorithm is based on the one included in the Global Change Assessment Model (GCAM). gcamland v1.0 includes the ability to run in a historical mode, enabling model validation and parameter estimation, or in a future mode, simulating changes in land use/land cover in the future. For both modes, gcamland v1.0 can run a single simulation or a large ensemble of simulations with different parameters. When ensembles are generated in the historical mode, gcamland v1.0 calculates the likelihood of a given parameter set by comparing to observational data. gcamland v1.0 is publicly available via GitHub and has can be adjusted to represent alternative scenarios or configured to different regions and land types.

Funding statement: This research was supported by the Office of Science of the U.S. Department of Energy as part of the Multi-Sector Dynamics Program. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830.

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Articles in this issue

DOI: https://doi.org/10.5334/jors.233 | Journal eISSN: 2049-9647

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Language: English

Submitted on: Jun 4, 2018

Accepted on: Oct 7, 2019

Published on: Oct 22, 2019

Published by: Ubiquity Press

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

Global Change Assessment Model (GCAM),

Land-use land-cover change (LULCC),

integrated assessment modelling,

© 2019 Katherine Calvin, Robert Link, Marshall Wise, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 7 (2019): Issue 1