Flood Hazard Assessment Supported by Reduced Cost Aerial Precision Photogrammetry

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Flood Hazard Assessment Supported by Reduced Cost Aerial Precision Photogrammetry

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Título: Flood Hazard Assessment Supported by Reduced Cost Aerial Precision Photogrammetry
Autor: Zazo, Santiago;Rodríguez-Gonzálvez, Pablo;Molina, Jose Luis;González-Aguilera, Diego;Agudelo-Ruiz, Carlos Andres;Hernandez-Lopez, David
Facultad/Centro: Escuela Superior y Tecnica de Ingenieros de Minas
Area de conocimiento: Ingeniería Cartografica, Geodesica y Fotogrametria
Resumen: Increasing flood hazards worldwide due to the intensification of hydrological events and the development of adaptation-mitigation strategies are key challenges that society must address. To minimize flood damages, one of the crucial factors is the identification of flood prone areas through fluvial hydraulic modelling in which a detailed knowledge of the terrain plays an important role for reliable results. Recent studies have demonstrated the suitability of the Reduced Cost Aerial Precision Photogrammetry (RC-APP) technique for fluvial applications by accurate-detailed-reliable Digital Terrain Models (DTMs, up to: 100 point/m2; vertical-uncertainty: 0.06 m). This work aims to provide an optimal relationship between point densities and vertical-uncertainties to generate more reliable fluvial hazard maps by fluvial-DTMs. This is performed through hydraulic models supported by geometric models that are obtained from a joint strategy based on Structure from Motion and Cloth Simulation Filtering algorithms. Furthermore, to evaluate vertical-DTM, uncertainty is proposed as an alternative approach based on the method of robust estimators. This offers an error dispersion value analogous to the concept of standard deviation of a Gaussian distribution without requiring normality tests. This paper reinforces the suitability of new geomatic solutions as a reliable-competitive source of accurate DTMs at the service of a flood hazard assessment.
Descripción física: 1566 p.
Revisión por pares: SI
Editor: MDPI
Datos: Remote Sensing 2018, 10, 1566
URI: http://hdl.handle.net/10612/9278
Fecha: 2018-10-01
Tipo: info:eu-repo/semantics/article
Materia: Cartografía
Palabras clave: flood risk assessment
RC-APP technique
Flood risk
Assessment
Ground filtering algorithm
Derechos de acceso: info:eu-repo/semantics/openAccess
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