Sinai peninsula is considered an important region for Egypt at both the national and strategic levels. Roads network is necessary for urban planning. Also base maps forms a base for determination of the soil suitability for reclamation, urban development and selection of the suitable type of development and investment that could be made in the area.
An accurate and up-to-date road network database is essential for GIS (Geographic Information System) based applications such as urban and rural planning, transportation management, vehicle navigation, emergency response, etc. Since Sinai have rough terrain (hilly and mountainous areas), when producing base maps (orthoimages) the topography should be taken into consideration. DTM and DSM will be produced from the stereo satellite images of SPOT4 so we will get a representation of height.
The production of DSM and DTM have been performed on the digital photogrammetric workstation (Leica Photogrammetric Suite) LPS. The digital photogrammetric procedures include collection of GCPs,tie point measurements, aerial triangulation,block adjustment,manual DTM creation for the bare land, automatic DSM creation andDEM editing. The quality of the generated DTM has been validated. After that orthorectification of stereo satellite images has been performed on the digital photogrammetric workstation LPS.
Orthorectification of mono multispectral images that is available for the study area has been implemented on the Erdas imagine. This has been followed by assessment of the quality of orthorectification using
check points after that a mosaic of images has been made which has been used as base map. The results of producing the orthoimage from digital photogrammetric workstation and from image processing software have been evaluated. Spectral Angler Mapper and maximum likelihood classification algorithms have been comparedfor classifying fused SPOT4 mosaic and SPOT5 imagewith and without incorporation of DSM as an additional channel. It was found that Spectral Angler Mapper was considerably more accurate thanmaximum likelihood classification.
After producing base maps roads have been extracted from manual digitizing of orthoimages and from automatic classification usingSAM taking into consideration DSM that have been produced Assessment of cartographic potential of EgyptSat-1 satellite image (case study in flat areas) Ayman Rashad Elshehaby &
Lamyaa Gamal El-deen Taha Abstract Egypt has launched its first Earth remote sensing satellite EgyptSat-1 in 2007. A series of evaluations of the usefulness and limitations of EgyptSat-1 images for different applications are required. This research is concerned with the investigation of the geometric and cartographic potential of EgyptSat-1 image in order to know to what scale EgyptSat-1 image is suitable for map production and map updating. The geometrical accuracy of rectification of EgyptSat-1 based on non-parametric rectification (polynomial approach and rubber sheeting) has been evaluated. Four methods of rectification have been compared: different orders of 2D polynomials (first-order polynomial, second-order polynomial, third-order polynomial) and rubber sheeting method. Different sets of ground control points (observed with differential global positioning system) have been tested. Several experiments were performed to rectify EgyptSat-1 image using the four rectification methods. For each method, different numbers of ground control points (GCPs) were used starting at 15 points, and then the number was reduced each time till the minimum number of GCPs for each method is reached and with three different GCP distributions. Various issues such as the solutions, feasibility, accuracy, and requirements for control information are addressed. The results show that rubber sheeting followed by third-order polynomial then
second-order polynomial then first-order polynomial gives the best root mean square error. Actually, a serious mapping should be based on a satisfying by the theory justified mathematical model so that rubber sheeting should not be used for a serious mapping even it shows smaller discrepancies, but for the flat test area, an approximate 2D transformation can be accepted. Also although third-order polynomial is accurate in the proximity of GCPs and shows smaller discrepancies compared to the first- and the second order
polynomials, they can lead to significant errors for regions outside the GCP range and should not be used for a serious mapping. One can be considered the best resulted rectified image that obtained from second-order polynomial followed by the first-order polynomial. It was found in our study area that the minimum number of control points for each method gives accuracy better than a pixel. The first order polynomial and rubber sheeting are good from the economical cost that they use minimum number of control points (three). It was found that the planimetric accuracy of rectified EgyptSat image met the 1:25,000 mapping standard (National Map Accuracy Standards). Also from the assessment of the information content of the EgyptSat
image, it was found that it is consistent with the map scale of 1:25,000. In conclusion by analysis of the results, it is obvious that EgyptSat images are able to produce and update map of scale 1:25,000.
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