Abstract
With the publication of eight original research articles, four types of advances in the remote sensing of floods are achieved. The uncertainty of modeled outputs using precipitation datasets derived from in situ observations and remote sensors is further understood. With the terrestrial laser scanner and airborne light detection and ranging (LiDAR) coupled with high resolution optical and radar imagery, researchers improve accuracy levels in estimating the surface water height, extent, and flow of floods. The unmanned aircraft system (UAS) can be the game changer in the acquisition and application of remote sensing data. The UAS may fly everywhere and every time when a flood event occurs. With the development of urban structure maps, the flood risk and possible damage is well assessed. The flood mitigation plans and response activities become effective and efficient using geographic information system (GIS)-based urban flood vulnerability and risk maps.
Highlights
Once water in a stream or river overflows its banks, the water submerges nearby dry uplands.A flood event occurs
The objective has been met with the publication of eight original research articles
The articles or studies furthered the understanding of the uncertainty of modeled outputs using the precipitation datasets derived from in situ observations and remote sensors
Summary
Once water in a stream or river overflows its banks, the water submerges nearby dry uplands. As humans are facing ever-changing environments and advancing in science and technology, especially with remote sensing, we as scientists are obligated to predict and to capture the extent of flooding in an efficient and effective manner This type of information is essential to decision-makers and emergency responders, as well as concerned citizens. Great attention is paid to assessing the extent of a flood using remotely sensed optical, radar, digital elevation model (DEM), and river gauge data. The exploration of the technological means and combined use of multiple remotely sensed datasets improved the mapping results of flood events, and advanced our understanding of the flood vulnerability in local communities. The overall accuracy for the flood mapping was 87.3%, and the Kappa coefficient 0.746 Their results demonstrate that the UAS is an ideal platform for remote sensing data acquisition and application in urban flood assessment. The developed method is able to extract the inundated and non-inundated areas satisfactorily, which in turn results in additional applications of remote sensing technology to aid emergency responders and decision-makers
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