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Journal of Applied Remote Sensing

Historic land cover change in the agricultural Midwest using an object-based approach for classification of high-resolution imagery
Author(s): Sarah Porter; Marc Linderman
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Paper Abstract

A semiautomated classification methodology was implemented using historic, high-resolution aerial photography in a dominant agricultural landscape. An object-based segmentation approach was applied to study land cover change from 1930 through 1990 in Johnson County, Iowa, in the Midwestern United States. A critical analysis of the approach is discussed, emphasizing the ability of the methodology to generate landscape metrics that can accurately characterize the quality of the landscape, particularly the high-resolution landscape features that are so important in a highly modified landscape. Landscape analysis includes a discussion of both the changes in the areal composition of land cover types and also the structural changes that are captured using both patch- and landscape-level metrics. Results were compared with countywide statistics from the United States Department of Agriculture as well as similar landscape studies, and provide evidence of agricultural intensification. Results also indicate some counterintuitive processes occurring from what is expected of a landscape undergoing this type of transformation, suggesting that altering the scale of study may provide different insight into land cover change dynamics.

Paper Details

Date Published: 12 September 2013
PDF: 21 pages
J. Appl. Remote Sens. 7(1) 073506 doi: 10.1117/1.JRS.7.073506
Published in: Journal of Applied Remote Sensing Volume 7, Issue 1
Show Author Affiliations
Sarah Porter, Agricultural Research Service (United States)
Marc Linderman, The Univ. of Iowa (United States)

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