Mechanism of flood forecasting is a complex system, which involves precipitation, drainage characterizes, land use/cover types, ground water and runoff discharge. The application of flood forecasting model require the efficient management of large spatial and temporal datasets, which involves data acquisition, storage, pre-processing and manipulation, analysis and display of model results. The ...

With 6.5 million households in the United States located in areas prone to storm surge, assessing the vulnerability of structures and residential communities to coastal flooding is an important concern. Of particular interest is understanding how the performance of structures during surge events is influenced by flood conditions, coastal defenses, and building design at both the house and commu...

Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as waterm...

Remote sensing technology serves as a powerful tool for analyzing geospatial characteristics of flood inundation events at various scales. However, the performance of remote sensing methods depends heavily on the flood characteristics and landscape settings. Difficulties might be encountered in mapping the extent of localized flooding with shallow water on riverine floodplain areas, where patch...

To support the transition from traditional flood defence strategies to a flood risk management approach at the basin scale in Europe, the EU has adopted a new Directive (2007/60/EC) at the end of 2007. One of the major tasks which member states must carry out in order to comply with this Directive is to map flood hazards and risks in their territory, which will form the basis of future flood ri...

Year 2010 massive flood hit the northern region of Peninsular Malaysia particularly Perlis and Kedah involved several districts and destroyed many agricultural areas and the infrastructure. This study focuses on the comparison between pixel-based classification and object-based classification of five machine learning algorithms including Parallelepiped (PP), Minimum Distance (MD), Maximum Likel...

Remotely sensed flood extents obtained in near real-time can be used for emergency incident management and as observations assimilation into forecasting models. High-resolution synthetic aperture radar (SAR) sensors have the potential to detect urban areas through clouds during both day- night-time. This paper considers a method detecting flooding by merging SAR with model-derived hazard maps. ...

Flood inundation modelling generally involves two steps. The first involves the use of a hydrologic model, such as RORB, to estimate the design flood hydrograph for a given design storm event. These models require several inputs, such as design rainfalls (i.e. duration, intensity & temporal pattern), losses, baseflow and routing parameters; each of which has an associated degree of uncertainty ...

Natural disasters are one of the things that have risks and hazards to population. This study aims simulate flood hazard calculate its impact on Hitoyoshi area, Japan residential areas. was chosen as case because area experienced a catastrophic in 2020 destroyed city. The calculation this is also based mapping land function, damage buildings, building materials, especially areas affected by flo...

This thesis is an outcome of the project “Flood and damage assessment using very high resolution SAR data” (SAR-HQ), which is embedded in the interdisciplinary oriented RIMAX (Risk Management of Extreme Flood Events) programme, funded by the Federal Ministry of Education and Research (BMBF). It comprises the results of three scientific papers on automatic near real-time flood detection in high ...