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Synthesis of a Complete Land Use/Land Cover Dataset for the Conterminous United States


Neil Best


Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP); Computation Institute, University of Chicago

Joshua Elliott


University of Chicago; Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP)

Ian Foster


University of Chicago; Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP)

May 4, 2012

RDCEP Working Paper No. 12-08

Abstract:     
We present a new land cover dataset for the conterminous USA called “PEELo.” It is designed for climate change impact analysis based on land use change at 5 arc-minute resolution. The procedure described herein is adaptable for generating similar datasets for other regions and requirements. PEELo is derived from existing data products – the MODIS Land Cover Type (MLCT) and National Land Cover Database (NLCD) – but its design overcomes certain limitations that hinder their use for climate change impact analysis. First, while other products that focus on agriculture neglect non-agricultural land use/land cover (LULC) categories, PEELo contains eight distinct LULC classes in addition to a “crop” class. PEELo features subcell area fractions for each class, increasing its depth of information over traditional single-category LULC maps. Second, PEELo offers improved accuracy in characterizing cultivated lands, important for quantifying agriculturalactivity. PEELo provides a more accurate spatial distribution of cultivated lands over MLCT as compared to reference datasets and improved totals for cultivated land relative to USDA Major Land Uses census data. We present here landcover data for 2001 plus PEELos synthesis methodology, which combines information from multiple sources by establishing a common classification scheme at lower spatial resolution. PEELo was developed as an initialization dataset for a partial-equilibrium economic land use model (PEEL) that simulates land use/land cover change in response to exogenous agricultural prices and climate change scenarios. We anticipate that similar landcover data products will be of use to other modeling efforts worldwide.

Number of Pages in PDF File: 32

Keywords: land-use/land-cover, remote sensing, MODIS, NLCD, high-performance data processing, agriculture

JEL Classification: Q15, C89

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Date posted: May 5, 2012  

Suggested Citation

Best, Neil and Elliott, Joshua and Foster, Ian, Synthesis of a Complete Land Use/Land Cover Dataset for the Conterminous United States (May 4, 2012). RDCEP Working Paper No. 12-08. Available at SSRN: http://ssrn.com/abstract=2051158 or http://dx.doi.org/10.2139/ssrn.2051158

Contact Information

Neil Best (Contact Author)
Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP) ( email )
5735 S. Ellis Street
Chicago, IL 60637
United States

Computation Institute, University of Chicago ( email )
5735 S Ellis Ave
Chicago, IL 60637
United States
7738348912 (Phone)
Joshua Elliott
University of Chicago ( email )
1101 East 58th Street
Chicago, IL 60637
United States
Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP) ( email )
5735 S. Ellis Street
Chicago, IL 60637
United States

Ian Foster
University of Chicago ( email )
1101 East 58th Street
Chicago, IL 60637
United States
Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP) ( email )
5735 S. Ellis Street
Chicago, IL 60637
United States

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