Application of machine learning techniques for the estimation of seismic vulnerability in the city of Port-au-Prince (Haiti)

Arredondo Parra, Álvaro (2019). Application of machine learning techniques for the estimation of seismic vulnerability in the city of Port-au-Prince (Haiti). Thesis (Master thesis), E.T.S.I. en Topografía, Geodesia y Cartografía (UPM).

Description

Title: Application of machine learning techniques for the estimation of seismic vulnerability in the city of Port-au-Prince (Haiti)
Author/s:
  • Arredondo Parra, Álvaro
Contributor/s:
  • Torres Fernández, Yolanda
  • Arranz Justel, José Juan
Item Type: Thesis (Master thesis)
Masters title: Ingeniería Geodésica y Cartografía
Date: 11 September 2019
Subjects:
Freetext Keywords: machine learning, aprendizaje automático, obia, computer vision, riesgo sísmico, haití
Faculty: E.T.S.I. en Topografía, Geodesia y Cartografía (UPM)
Department: Ingeniería Topográfica y Cartografía [hasta 2014]
UPM's Research Group: Subgrupo (SISMO) del Grupo de Ingeniería Sísmica: Dinámica de Suelos y Estructuras
Creative Commons Licenses: Recognition

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (6MB) | Preview

Abstract

High resolution, city-level exposure databases are important tools for risk planning and damage assessment. However, this kind of information is not always available, especially in developing countries where cities have grown rapidly without excessive planning or oversight, and sending a team of engineers to manually generate such a database by traditional means can be prohibitively costly. In recent years, we have seen tremendous growth in the availability of Earth Observation (EO) data, such as multispectral imagery or LiDAR point clouds, and also the processing capabilities of said data, not just in raw computing power but also in novel statistical modeling and analytical techniques known as Machine Learning (ML) and Computer Vision (CV). The aim of this work is to apply Machine Learning methods to aid in the generation of such databases as a case study in Port-au-Prince, Haiti, and to expose these methods in a comprehensible, reproducible fashion, as a series of open-source programming scripts.

More information

Item ID: 56628
DC Identifier: http://oa.upm.es/56628/
OAI Identifier: oai:oa.upm.es:56628
Deposited by: Álvaro Arredondo Parra
Deposited on: 02 Oct 2019 05:58
Last Modified: 02 Oct 2019 05:59
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM