The objective of this study was to develop a digital procedure to measure the amount of urban change that has occurred in an area since the publication of its corresponding 1:24,000-scale topographic map. Traditional change detection techniques are dependent upon the visual comparison of high-altitude aerial photographs or, more recently, satellite image data to a corresponding map. Analytical change detection techniques typically involve the digital comparison of satellite images to one another. As a result of this investigation, a new technique has been developed that analytically compares the most recently published map to a corresponding digital satellite image. Scanned cartographic and satellite image data are combined in a single file with a structural component derived from the satellite image. This investigation determined that with this combination of data the spectral characteristics of urban change are predictable. A supervised classification was used to detect and delimit urban change. Although it was not intended to identify the specific nature of any change, this procedure does provide a means of differentiating between areas that have or have not experienced urbanization to determine appropriate map revision strategies.
|Title||Automated urban change detection using scanned cartographic and satellite image data|
|Authors||Jeffrey D. Spooner|
|Publication Type||Conference Paper|
|Publication Subtype||Conference Paper|
|Record Source||USGS Publications Warehouse|