Multiple source imagery and linear features for detection of urban expansion in Aqaba City,Jordan

Aqaba is one of the most strategic cities in Jordan and the entire region, as it is the only seaport for Jordan and has a special economic zone as the only window to global markets. The main purpose of this study is to detect urban development in Aqaba region by detecting and registering linear features in images with various geometric and radiometric properties taken at different times. This article used linear features for image registration that were chosen since they can be reliably extracted from imagery with significantly different geometric and radiometric properties. The modified iterated Hough transform (MIHT) is used as the matching strategy for automatically deriving an estimate of the parameters involved in the transformation function relating the images to be registered as well as the correspondence between conjugate lines. Derived edges from the registered images are used as the basis for change detection. The utilization of edges is motivated by the fact that they are invariant with respect to possible radiometric differences between the images in question. Linear features extraction, feature matching, image registration and pixel–pixel subtraction have been implemented using SPOT, Landsat, Ikonos and aerial photographs that have different radiometric, spatial and temporal resolutions. It has been shown that linear features (straight-line segments) have high semantics and can be reliably extracted from the images. These linear features can be used for accurate co-registration as an essential prerequisite for a reliable change detection procedure. For the purpose of change detection, image–image registration is more crucial than image–ground registration, where corresponding features in images are registered with respect to each other regardless of the associated absolute errors. The results illustrate that using edges as the base for change detection in urban areas is efficient and reliable.