الفهرس 
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Abstract
Change detection is one of the most important inherent capabilities of remote
sensing images. The availability of new satellite sensors such as WorldView and
GeoEye, provides new data for better detection, delineation, and visualization of
changes. Numerous techniques have been proposed and developed for automated
change detection.
The main aim of this study is to assess the use of very high-resolution satellite
images in monitoring land cover changes for large scale map updating in Egypt.
For achieving that aim, the pre-processing of satellite images which includes data
fusion, geometric correction and shadow correction were carried out. Two study
areas were selected; the first one was in Assiut city and the second was in Sohag
city. The first study area (secondary study area) was selected to emphasis the
importance of image to image change detection technique for remote sensing
applications. In this study area, two very high resolution satellite images were
used; IKONOS-2 image of 2006 and WorldView-2 image of 2016. Five change
detection techniques were tested for detecting changes that occurred between 10
years. The change detection techniques considered are image differencing, image
ratio, principal component analysis, post-classification comparison, and multi-date
direct classification. The accuracy of each technique was evaluated through an
overall accuracy and kappa coefficient. In the second study area (main study area),
the data used were GeoEye-1 image of 2014 and Sohag map (2006) of scale
1:5000. The change detection between the GeoEye-1 image and Sohag map was
carried out using the post-classification comparison technique. After that the
change map result was divided into two classes: building and non-building. All
objects were transformed from raster to vector format. For building objects, the
height was estimated. A python code was written to calculate relief displacement
using buildings height and shadow length. The vector layer was added to update
the reference map. The results of this work showed that, for the Egyptian
Abstract
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environment, the principal component analysis method generated accurate change
detection map compared to other methods with overall accuracy (92.24%) . Also,
it was found that the area of agricultural lands was significantly decreased due to
the increase in population and urban growth. The second study area (main study
area) was selected to assess the use of very high resolution satellite images for
large scale map updating. Studying of the information content of GeoEye-1
images shows the capability of VHR satellite images with resolution of 0.5 m for
updating 1:5000 maps. Also, the approximated method for building relief
displacement correction is a promising method. It has RMSE accuracy of 0.95m.
The reference map was updated by 9.39%.
Keywords: change detection, very high resolution, object-based, map updating.