Model:GLUDM

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GLUDM




Metadata

Also known as
Model type Single
Model part of larger framework
Incorporated models or components:
Spatial dimensions 2D
Spatial extent Global
Model domain Terrestrial
One-line model description Global future agricultural land use dynamics model
Extended model description The model calculates a unique regression equation for each grid-cell between a the relative area of a specific land use (e.g. cropland) and global population. The equation is used to extrapolate that land use are into the future in each grid cell with predicted global population predictions. If the relative area of a land use reach a value of 95%, additional expansion is migrated to neighboring cells thus allowing spatial expansion. Geographic limitations are imposed on land use migration (e.g. no cropland beyond 60 degree latitude).

For more information: Haney, N., Cohen, S. (2015), Predicting 21st century global agricultural land use with a spatially and temporally explicit regression-based model. Applied Geography, 62: 366-376.

Keywords:

land use, agriculture, Future,


First name Sagy
Last name Cohen
Type of contact Project manager
Institute / Organization University of Alabama
Postal address 1
Postal address 2
Town / City Tuscaloosa
Postal code 35487
State Alabama
Country United States
Email address sagy.cohen@ua.edu
Phone
Fax


Supported platforms Unix, Linux, Mac OS, Windows
Other platform
Programming language Java
Other program language
Code optimized Single Processor
Multiple processors implemented
Nr of distributed processors
Nr of shared processors
Start year development 2013
Does model development still take place? No
If above answer is no, provide end year model development 2014
Code development status As is, no updates are provided
When did you indicate the 'code development status'? 2020
Model availability As code
Source code availability
(Or provide future intension)
Through CSDMS repository
Source web address
Source csdms web address https://github.com/csdms-contrib/gludm
Program license type GPL v2
Program license type other
Memory requirements
Typical run time Minutes


Describe input parameters Rasters containing the relative area of a specific land use (e.g. cropland) in the past (e.g. 1960, 1980, 1990, 2005).

A table of historic and predicted global population.

Input format ASCII
Other input format text file
Describe output parameters Rasters containing the relative area of a specific land use in the future.
Output format ASCII
Other output format
Pre-processing software needed? Yes
Describe pre-processing software GIS
Post-processing software needed? Yes
Describe post-processing software GIS
Visualization software needed? Yes
If above answer is yes ESRI
Other visualization software Any GIS


Describe processes represented by the model Regression based interpolation. Different regression equation type can be used.

Land use area in each grid cell is the dependent variable and global population is the independent variable.

Describe key physical parameters and equations Global population values is assumed to be the most important controlling factor on the area of a specific agricultural land use area.
Describe length scale and resolution constraints At the moment the resolution of the input controls the resolution of the output. This is a global model but can be applied to smaller domains.
Describe time scale and resolution constraints Yearly, 1960-2100.
Describe any numerical limitations and issues


Describe available calibration data sets We used the HYDE 3.1 dataset and the USDA's CropScape dataset for validation.

See: Haney, N., Cohen, S. (2015), Predicting 21st century global agricultural land use with a spatially and temporally explicit regression-based model. Applied Geography, 62: 366-376.

Upload calibration data sets if available:
Describe available test data sets Cropland area for ...
Upload test data sets if available:
Describe ideal data for testing


Do you have current or future plans for collaborating with other researchers?
Is there a manual available? Yes
Upload manual if available:
Model website if any http://sdml.ua.edu/models/
Model forum / discussion board
Comments See model description, validation and analysis in:

Haney, N., Cohen, S. (2015), Predicting 21st century global agricultural land use with a spatially and temporally explicit regression-based model. Applied Geography, 62: 366-376.

http://sdml.ua.edu/publications/


This part will be filled out by CSDMS staff

OpenMI compliant No but possible
BMI compliant No but possible
WMT component No but possible
PyMT component
Can be coupled with:
Model info
Citation indices GLUDM
Nr. of pubs: 1
Citations: 6
h-index: 1
Qrcode GLUDM.png
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Introduction

History

References




Citation indices GLUDM
Nr. of pubs: 1
Citations: 6
h-index: 1



Featured publication(s)YearModel describedType of ReferenceCitations
Haney, Nicholas; Cohen, Sagy; 2015. Predicting 21st century global agricultural land use with a spatially and temporally explicit regression-based model. Applied Geography, 62, 366–376. 10.1016/j.apgeog.2015.05.010
(View/edit entry)
2015GLUDM
Model application 6
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Input Files

Output Files