EXECUTIVE SUMMARY:The monitoring of building activity (erection of new buildings, demolishing buildings and especially the change of building heights) by manual inspection of space and aerial images is time consuming and a source of errors. A detection of building changes based on the comparison of digital surface models (DSMs) is more reliable. For this study DSMs have been generated based on aerial images, an IKONOS and a GeoEye-1 stereo pair taken from 2007 up to 2009. By pixel based matching with dynamic programming, semiglobal matching and least squares matching the visible surface has been determined. Semiglobal matching leads to sharp building shapes, while the area based least squares matching smoothes the height model and has more problems in areas with little or without contrast. As is shown in the investigation building changes and building height changes in the range of one floor can in many cases be determined with all methods, however building shapes are better determined using semiglobal matching.
ABSTRACT:Despite of valuable efforts from working groups and research organizations towards flood hazard reduction through its program, still minimal diminution from these hazards has been realized. This is mainly due to the fact that with rapid increase in population and urbanization coupled with climate change, flood hazards are becoming increasingly catastrophic. Therefore there is a need to understand and access flood hazards and develop means to deal with it through proper preparations, and preventive measures. To achieve this aim, Geographical Information System (GIS), geospatial and hydrological models were used as tools to tackle with influence of flash floods in the Kingdom of Saudi Arabia due to existence of large valleys (Wadis) which is a matter of great concern. In this research paper, Digital Elevation Models (DEMs) of different resolution (30m, 20m,10m and 5m) have been used, which have proven to be valuable tool for the topographic parameterization of hydrological models which are the basis for any flood modelling process. The DEM was used as input for performing spatial analysis and obtaining derivative products and delineate watershed characteristics of the study area using ArcGIS desktop and its Arc Hydro extension tools to check comparability of different elevation models for flood Zonation mapping. The derived drainage patterns have been overlaid over aerial imagery of study area, to check influence of greater amount of precipitation which can turn into massive destructions. The flow accumulation maps derived provide zones of highest accumulation and possible flow directions. This approach provide simplified means of predicting extent of inundation during flood events for emergency action especially for large areas because of large coverage area of the remotely sensed data.
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