The use of satellite remote sensing for flood risk management

Franci, Francesca (2015) The use of satellite remote sensing for flood risk management , [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Ingegneria civile, ambientale e dei materiali, 27 Ciclo. DOI 10.6092/unibo/amsdottorato/7181.
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Abstract

Over the last decades the impact of natural disasters to the global environment is becoming more and more severe. The number of disasters has dramatically increased, as well as the cost to the global economy and the number of people affected. Among the natural disaster, flood catastrophes are considered to be the most costly, devastating, broad extent and frequent, because of the tremendous fatalities, injuries, property damage, economic and social disruption they cause to the humankind. In the last thirty years, the World has suffered from severe flooding and the huge impact of floods has caused hundreds of thousands of deaths, destruction of infrastructures, disruption of economic activity and the loss of property for worth billions of dollars. In this context, satellite remote sensing, along with Geographic Information Systems (GIS), has become a key tool in flood risk management analysis. Remote sensing for supporting various aspects of flood risk management was investigated in the present thesis. In particular, the research focused on the use of satellite images for flood mapping and monitoring, damage assessment and risk assessment. The contribution of satellite remote sensing for the delineation of flood prone zones, the identification of damaged areas and the development of hazard maps was explored referring to selected cases of study.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Franci, Francesca
Supervisore
Dottorato di ricerca
Scuola di dottorato
Ingegneria civile ed architettura
Ciclo
27
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Satellite remote sensing Flood risk management Geographic Information System Geographic Information System Change detection analysis Object-based classification
URN:NBN
DOI
10.6092/unibo/amsdottorato/7181
Data di discussione
21 Maggio 2015
URI

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