scholarly journals Panchromatic Satellite Image Classification for Flood Hazard Assessment

2012 ◽  
Vol 10 (6) ◽  
Author(s):  
Ahmed Shaker ◽  
Wai Yeung Yan ◽  
Nagwa El-Ashmawy
Keyword(s):  
Maximum Likelihood ◽  
Hazard Assessment ◽  
Flood Hazard ◽  
Satellite Image ◽  
Image Data ◽  
Maximum Likelihood Classifier ◽  
Flood Hazard Assessment ◽  
Before And After ◽  
High Flood ◽  
Occurrence Matrix

The study aims to investigate the use of panchromatic (PAN) satellite image data for flood hazard assessment with anaid of various digital image processing techniques. Two SPOT PAN satellite images covering part of the Nile River inEgypt were used to delineate the flood extent during the years 1997 and 1998 (before and after a high flood). Threeclassification techniques, including the contextual classifier, maximum likelihood classifier and minimum distanceclassifier, were applied to the following: 1) the original PAN image data, 2) the original PAN image data and grey-levelco-occurrence matrix texture created from the PAN data, and 3) the enhanced PAN image data using an edgesharpeningfilter. The classification results were assessed with reference to the results derived from manualdigitization and random checkpoints. Generally, the results showed improvement of the calculation of flood area whenan edge-sharpening filter was used. In addition, the maximum likelihood classifier yielded the best classificationaccuracy (up to 97%) compared to the other two classifiers. The research demonstrates the benefits of using PANsatellite imagery as a potential data source for flood hazard assessment.

scholarly journals Integration of GIS-Based Multicriteria Decision Analysis and Analytic Hierarchy Process for Flood-Hazard Assessment in the Megalo Rema River Catchment (East Attica, Greece)

2021 ◽  
Vol 13 (18) ◽  
pp. 10232
Author(s):  
Efthimios Karymbalis ◽  
Maria Andreou ◽  
Dimitrios-Vasileios Batzakis ◽  
Konstantinos Tsanakas ◽  
Sotirios Karalis
Keyword(s):  
Analytic Hierarchy Process ◽  
Decision Analysis ◽  
Hazard Assessment ◽  
Flood Risk ◽  
Flood Hazard ◽  
Analytic Hierarchy ◽  
Flood Hazard Assessment ◽  
High Flood ◽  
Hierarchy Process ◽  
Very High

This study deals with the flood-hazard assessment and mapping in the catchment of Megalo Rema (East Attica, Greece). Flood-hazard zones were identified utilizing Multi-Criteria Decision Analysis (MCDA) integrated with Geographic Information System (GIS). Five factors were considered as the most influential parameters for the water course when high storm-water runoff exceeds drainage system capacity and were taken into account. These factors include slope, elevation, distance from stream channels, geological formations in terms of their hydro-lithological behavior and land cover. To obtain the final weights for each factor, rules of the Analytic Hierarchy Process (AHP) were applied. The final flood-hazard assessment and mapping of the study area were produced through Weighted Linear Combination (WLC) procedures. The final map showed that approximately 26.3 km2, which corresponds to 22.7% of the total area of the catchment, belongs to the high flood risk zone, while approximately 25 km2, corresponding to ~15% of the catchment, is of very high flood risk. The highly and very highly prone to flooding areas are located mostly at the southern and western parts of the catchment. Furthermore, the areas on both sides of the channel along the lower reaches of the main stream are of high and very high risk. The highly and very highly prone to flooding areas are relatively low-lying, gently sloping and extensively urbanized, and host the densely populated settlements of Rafina-Pikermi, Penteli, Pallini, Peania, Spata, Glika Nera, Gerakas and Anthousa. The accuracy of the flood-hazard map was verified by correlating flood events of the last 30 years, the Hydrologic Engineering Center’s River Analysis System (HEC–RAS) simulation and quantitative geomorphological analysis with the flood-hazard level. The results of our approach provide decision makers with important information for land-use planning at a regional scale, determining safe and unsafe areas for urban development.

scholarly journals Flood hazard assessment in large plain basins with a scarce slope in the Pampean Plain, Argentina

2021 ◽  
Vol 193 (4) ◽  
Author(s):  
Guido Borzi ◽  
Alejandro Roig ◽  
Carolina Tanjal ◽  
Lucía Santucci ◽  
Macarena Tejada Tejada ◽  
...  
Keyword(s):  
Hazard Assessment ◽  
Flood Hazard ◽  
Pampean Plain ◽  
Flood Hazard Assessment

scholarly journals Risk Analysis and Flood Hazard Assessment in the Hornád River Basin

2021 ◽  
Vol 656 (1) ◽  
pp. 012010
Author(s):  
M Zeleňáková ◽  
M Šugareková ◽  
P Purcz ◽  
S Gałaś ◽  
M M Portela ◽  
...  
Keyword(s):  
Risk Analysis ◽  
River Basin ◽  
Hazard Assessment ◽  
Flood Hazard ◽  
Flood Hazard Assessment

scholarly journals Safer_RAIN: a Fast-Processing DEM-Based Algorithm for Pluvial Flood Hazard Assessment Across Large Urban Areas

2019 ◽  
Author(s):  
Attilio Castellarin ◽  
Caterina Samela ◽  
Simone Persiano ◽  
Stefano Bagli ◽  
Valerio Luzzi ◽  
...  
Keyword(s):  
Hazard Assessment ◽  
Urban Areas ◽  
Flood Hazard ◽  
Flood Hazard Assessment ◽  
Fast Processing

scholarly journals Compounding effects of sea level rise and fluvial flooding

2017 ◽  
Vol 114 (37) ◽  
pp. 9785-9790 ◽  
Author(s):  
Hamed R. Moftakhari ◽  
Gianfausto Salvadori ◽  
Amir AghaKouchak ◽  
Brett F. Sanders ◽  
Richard A. Matthew
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Hazard Assessment ◽  
Failure Probability ◽  
River Flow ◽  
Flood Hazard ◽  
High Tide ◽  
Probability Method ◽  
Flood Hazards ◽  
Flood Hazard Assessment

Sea level rise (SLR), a well-documented and urgent aspect of anthropogenic global warming, threatens population and assets located in low-lying coastal regions all around the world. Common flood hazard assessment practices typically account for one driver at a time (e.g., either fluvial flooding only or ocean flooding only), whereas coastal cities vulnerable to SLR are at risk for flooding from multiple drivers (e.g., extreme coastal high tide, storm surge, and river flow). Here, we propose a bivariate flood hazard assessment approach that accounts for compound flooding from river flow and coastal water level, and we show that a univariate approach may not appropriately characterize the flood hazard if there are compounding effects. Using copulas and bivariate dependence analysis, we also quantify the increases in failure probabilities for 2030 and 2050 caused by SLR under representative concentration pathways 4.5 and 8.5. Additionally, the increase in failure probability is shown to be strongly affected by compounding effects. The proposed failure probability method offers an innovative tool for assessing compounding flood hazards in a warming climate.

scholarly journals Multi-Mechanism Flood Hazard Assessment: Critical Review of Current Practice and Approaches

2020 ◽  
Author(s):  
Michelle Bensi ◽  
Somayeh Mohammadi ◽  
Shih-Chieh Kao ◽  
Scott T. DeNeale
Keyword(s):  
Hazard Assessment ◽  
Critical Review ◽  
Current Practice ◽  
Flood Hazard ◽  
Flood Hazard Assessment
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