<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Jordan Dornbierer</dc:contributor>
  <dc:contributor>Steve Wika</dc:contributor>
  <dc:contributor>Kristi L. Sayler</dc:contributor>
  <dc:contributor>Robert Quenzer</dc:contributor>
  <dc:creator>Terry L. Sohl</dc:creator>
  <dc:date>2017</dc:date>
  <dc:description>&lt;p&gt;&lt;span&gt;Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land use change model to project parcel-based agricultural change across a large region in the United States Great Plains. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using real parcel boundaries based on contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. The conceptual approach is practical and scalable, with potential use for national-scale projections.&lt;/span&gt;&lt;/p&gt;</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1080/1747423X.2017.1340525</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Taylor &amp; Francis</dc:publisher>
  <dc:title>Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>