Historic land cover change in the agricultural Midwest using an object-based approach for classification of high-resolution imagery

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 county-wide statistics from the United States Department of Agriculture as well as similar landscape studies, and provide evidence of agricultural intensification. Results also indicate some counter-intuitive 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. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)