Main Logo of Southern Research Station, Stating: Southern Research Station - Asheville, NC, with a saying of 'Science you can use!'
[Images] Five photos of different landscape

Publication Information

Mail this page   Give us your feedback on this publication

Title: Agro-ecoregionalization of Iowa using multivariate geographical clustering
Author(s): Williams, Carol L.; Hargrove, William W.; Leibman, Matt; James, David E.
Date: 2008
Source: Agriculture, Ecosystems and Environment, Vol. 123: 161-174
Description: Agro-ecoregionalization is categorization of landscapes for use in crop suitability analysis, strategic agroeconomic development, risk analysis, and other purposes. Past agro-ecoregionalizations have been subjective, expert opinion driven, crop specific, and unsuitable for statistical extrapolation. Use of quantitative analytical methods provides an opportunity for delineation of agro-ecoregions in a more objective and reproducible manner, and with use of generalized crop-related environmental inputs offers an opportunity for delineation of regions with broader application. For this study, raster (cell-based) environmental data at 1 km scale were used in a multivariate geographic clustering process to delineate agroecozones. Environmental parameters included climatic, edaphic and topographic characteristics hypothesized to be generally relevant to many crops. Clustering was performed using five a priori grouping schemes of 5–25 agroecozones. Non-contiguous geographic zones were defined representing areas of similar crop-relevant environmental conditions. A red–green–blue color triplet was used for visualization of agroecozones as unique combinations of environmental factors. Concordance of the agroecozones with other widely used datasets was investigated using MapCurves, a quantitative goodness-of-fit method. The 5- and 25-agroecozone schemes had highest concordance with a map of major land resource areas and a map of major landform regions, with degree of fit judged to be good. The resulting agroecozones provide a framework for future rigorous hypothesis testing. Other applications include: quantitative evaluation of crop suitability at the landscape scale, environmental impact modeling and agricultural scenario building.
Key Words: agroecopause, agroecozone, mapcurves, multivariate geographic clustering
[ PDF Icon ] View and Print this Publication (428 KB)
Publication Notes:
  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
  • Our on-line publications are scanned and captured using Adobe Acrobat. During the capture process some typographical errors may occur. Please contact the SRS Webmaster, srswebmaster@fs.fed.us if you notice any errors which make this publication unuseable.
[ Get Acrobat ] Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility




Publication Links:

FIA Resource Bulletins

Publications Search


Search for on-line publications
containing the following:

 


(Uncheck this box to search all R&D Publications.)

Small logo of the USDASmall logo of the Forest Service