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Prof. Ahmed Abdel Sattar Shaker :: Publications:

Multiple polynomial-based generation of DEM from topographic contour data
Authors: Shaker, A.1, Saad, Abdullah1, Salah, Mahmoud.1, Salama, Ibrahim2 1Department of Surveying Engineering, Shoubra Faculty of Engineering, Benha University, Egypt,, 2Construction and
Year: 2015
Keywords: : Polynomial, interpolation, DEM, elevation, slope.
Journal: Regional Conference on Surveying & Development Sharm El-Sheikh, Egypt, 3-6 October 2015
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: International
Paper Link: Not Available
Full paper Ahmed Abdel Sattar Shaker_Multiple polynomial-based generation.pdf
Supplementary materials Not Available

The purpose of this paper is to introduce a methodology for DEM generation from 1/100,000 topographiccontoursbased on multiple polynomial interpolations. Sinai Peninsula, in Egypt, was chosen as a study area for its size and topographic diversity. The selected test area stretches north south from gently-slope flat land in northern part to rugged mountainous region in Sothern part. The proposed modeling scheme comprises five steps. In the first step, contours for Sinai Peninsulawere manually digitized from 1:100,000 scale topographic maps. The obtained data is about 940,624 points. As well, SRTM DEMs were downloaded and processed to be used for comparison. In the second step, theSRTM DEMs were classified into three classes: flat; rolling; and mountainous depicts slopes of less than 5%, from 5 to12% and greater than 12% respectively. In the third step, three DEMs with a 30m horizontal resolution were derived from the digitized contours using linear; quadratic; and cubic polynomial equations in a least-square fashion.In the fourth step, flat, rolling and mountainous areas were extracted from linear, quadratic and cubic-based DEMs respectively.A refined DEM was constructed by combining the three extracted areas in one scene. Finally, the reconstructed DEMwere compared withvariety of existing interpolation techniques. The comparison is based on four criteria: RMSE; systematic errors; derived slope; and computational cost. Statistics show that for the reconstructed DEM, the RMSE was 2.38m with no systematic errors. The derived slope and computational cost were comparable to the well known interpolation technique, Kriging, with simpler implementation

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