scholarly journals Integration of Crowdsourced Images, USGS Networks, Remote Sensing, and a Model to Assess Flood Depth during Hurricane Florence

2020 ◽  
Vol 12 (5) ◽  
pp. 834
Author(s):  
Carolynne Hultquist ◽  
Guido Cervone
Keyword(s):  
Remote Sensing ◽  
Sensor Networks ◽  
Cross Sections ◽  
Satellite Remote Sensing ◽  
Environmental Data ◽  
Data Sources ◽  
Remote Sensing Imagery ◽  
Flood Depth ◽  
Crowdsourced Data ◽  
Automated Methods

Crowdsourced environmental data have the potential to augment traditional data sources during disasters. Traditional sensor networks, satellite remote sensing imagery, and models are all faced with limitations in observational inputs, forecasts, and resolution. This study integrates flood depth derived from crowdsourced images with U.S. Geological Survey (USGS) ground-based observation networks, a remote sensing product, and a model during Hurricane Florence. The data sources are compared using cross-sections to assess flood depth in areas impacted by Hurricane Florence. Automated methods can be used for each source to classify flooded regions and fuse the dataset over common grids to identify areas of flooding. Crowdsourced data can play a major role when there are overlaps of sources that can be used for validation as well providing improved coverage and resolution.

Estimations for Percentage of Impervious Area by the Use of Satellite Remote Sensing Imagery

1994 ◽  
Vol 29 (1-2) ◽  
pp. 135-144 ◽  
Author(s):  
C. Deguchi ◽  
S. Sugio
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Satellite Imagery ◽  
Satellite Remote Sensing ◽  
Aerial Photographs ◽  
Estimation Errors ◽  
Remote Sensing Imagery ◽  
Impervious Area ◽  
Urbanized Areas

This study aims to evaluate the applicability of satellite imagery in estimating the percentage of impervious area in urbanized areas. Two methods of estimation are proposed and applied to a small urbanized watershed in Japan. The area is considered under two different cases of subdivision; i.e., 14 zones and 17 zones. The satellite imageries of LANDSAT-MSS (Multi-Spectral Scanner) in 1984, MOS-MESSR(Multi-spectral Electronic Self-Scanning Radiometer) in 1988 and SPOT-HRV(High Resolution Visible) in 1988 are classified. The percentage of imperviousness in 17 zones is estimated by using these classification results. These values are compared with the ones obtained from the aerial photographs. The percent imperviousness derived from the imagery agrees well with those derived from aerial photographs. The estimation errors evaluated are less than 10%, the same as those obtained from aerial photographs.

Transportation Routes in Soils Susceptible to Ground Failure: New Madrid Seismic Zone

2000 ◽  
Vol 1736 (1) ◽  
pp. 127-133
Author(s):  
Salome Romero ◽  
Glenn J. Rix ◽  
Steven P. French
Keyword(s):  
Remote Sensing ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Data Sources ◽  
New Madrid Seismic Zone ◽  
Seismic Zone ◽  
Remote Sensing Imagery ◽  
Geologic Maps ◽  
Transportation Routes

Geologic deposits susceptible to ground motion amplification under seismic loading in the New Madrid Seismic Zone are delineated using multiple data sources including in situ measurements, geologic maps, and remote-sensing imagery. Soils are classified on the basis of the recommendations from the National Earthquake Hazards Reduction Program, which recommends a classification based on the average shear wave velocity of the geologic material in the upper 30 m. Measurements of shear wave velocity were obtained from Central United States Earthquake Consortium state geologists, the U.S. Geological Survey, and several researchers. However, since this is a predominantly rural area, limited field test data are available. Therefore, several other data sources are introduced including geologic maps and remote-sensing imagery to extrapolate dynamic properties in areas lacking extensive field measurements. Each data source was incorporated into a geographic information system for subsequent analysis. Bridges susceptible to failure from amplification of seismic waves and located on key transportation routes are identified for subsequent risk assessment or seismic retrofitting since the performance of these structures affects disaster planning and rescue efforts and may have severe consequences for the national economy.

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