Estimating error and uncertainty in change detection analyses of historical aerial photographs

Joanne N. Halls 1 and Lindsey Kraatz 2
1 University of North Carolina Wilmington
Department of Earth sciences
601 S. College Road, NC 28403, USA
Tel.: + 001 910 962 7614; Fax: + 001 910 962 7077
2 Virginia Institute of Marine Science
Rt. 1208 Greate Rd., Gloucester Point, Virginia, 23062

By gathering, rectifying, interpreting, and digitizing historical aerial photography (from 1938 to 1998) we computed the rate of change of back-barrier land cover types and used GIS spatial analysis tools to compute the degree of fragmentation  of marshes through time and place. To quantify the significance of this historical change, a series of tests were designed and conducted to describe the amount of spatial variability and  accuracy of the rectified photographs, the digitized polygons, and the quantification of change. A digitizing accuracy assessment was conducted where randomly chosen  locations were identified on the aerial photographs and compared with the digitized  data. The accuracy assessment resulted in greater than 80 percent accurate which is acceptable. Second, the digitized polygons were tested for degree of crenulation, or curviness, and also line generalization tests were conducted which indicated that the interpretation of the photographs was not a factor in the results. Third, we incorporated a fuzziness test (using derived epsilon bands) into the GIS data to identify and quantify true changes in the marsh habitats versus positional changes, or sliver polygons. Results indicate that rectification of aerial photography (although an RMS error of less than 1), interpretation, and digitizing can  lead to erroneous results however by using fuzziness techniques we can minimize the errors and predict which areas are changing through time.

Keywords: change detection, aerial photography, digitizing accuracy

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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