الفهرس 
Methodological framework for early hazard warning of coastal sea level rise on urban development using geomatics technologies
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Abstract
The Egyptian coastal areas are a natural and economic resource of extraordinary value which are highly influenced by global climate change and sea-level rise. The absence of precise quantitative estimation of sea-level rise impacts is considered one of the major challenges. This research aims to formulate an early warning methodological framework of coastal hazards on urban development by using geomatics to support the decision-makers in planning the needed adaptation strategies. The research methodology consists of four phases. In the first phase, the recently available tide gauges measurements were compared with the emission scenarios by the recent Intergovernmental Panel on Climate Change (IPCC) for setting sea level rise planning scenarios taking into consideration the local and global factors. As the results of coastal flood risk assessments are largely relying on the accuracy of digital elevation model data. Therefore, in the second phase, a mathematical scale factor formula was derived to obtain higher vertical accuracy of one of the freely available digital elevation models (SRTM) to achieve the requirements for coastal inundation studies with a minimum volume of field measurements. The proposed methodological framework was applied to two -study areas with different environmental and terrains characteristics along the Mediterranean and the Red Seas in Egypt. In the third phase, the accuracy of different automatic shoreline extraction methods from different satellite sensors was evaluated, and then the latest information regarding coastal erosion rates is detected for both study areas. In the last phase, Hotspot’s areas are identified and the impact of SLR on SDGs progress at the local level was investigated. The findings of this research confirm that the integration of geomatics technologies provides coastal disaster managers, engineers, and planners with an opportunity for more efficient utilization of spatial data for hazard assessments and adaptation strategies determination