Using remote sensing for exposure and seismic vulnerability evaluation: is it reliable?

Autor: Yolanda Torres, Sandra Martínez-Cuevas, Sergio Molina-Palacios, José Juan Arranz, Álvaro Arredondo

Publikováno v: GIScience & Remote Sensing, Vol 60, Iss 1 (2023)

Conducting field surveys for exposure and seismic vulnerability evaluation is the most costly, resource-intensive task when assessing earthquake risk. During the past decade, risk analysts have been trying to alleviate this using remote sensing for b

Externí odkaz: https://doaj.org/article/50dd87cfa16d4f52964ff7110f13d55b

Assessing the Accuracy of Digital Surface Models Derived from Optical Imagery Acquired with Unmanned Aerial Systems

Autor: Salvatore Manfreda, Petr Dvorak, Jana Mullerova, Sorin Herban, Pietro Vuono, José Juan Arranz Justel, Matthew Perks

Publikováno v: Drones, Vol 3, Iss 1, p 15 (2019)

Small unmanned aerial systems (UASs) equipped with an optical camera are a cost-effective strategy for topographic surveys. These low-cost UASs can provide useful information for three-dimensional (3D) reconstruction even if they are equipped with a

Externí odkaz: https://doaj.org/article/12220a7c0d9d48dcb17648cc28d292c6

AUTOMATIC SEGMENTATION OF POINT CLOUDS IN THE ARCHITECTURE ENVIRONMENT

Autor: L. Navas-Sánchez, José Juan Arranz, Belén Benito, R. Romero-Jarén, Sandra Martínez-Cuevas, E. Erduran

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2021, Pp 215-221 (2021)
International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences

Correct and reliable identification and classification of different structures and infrastructures that make up a city (e.g. residential buildings, school buildings, hospitals, power stations, routes of communication, etc.) are of great importance fo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a1e2e5be5391e79d2a73d098ec1514c
https://doi.org/10.5194/isprs-archives-xliii-b2-2021-215-2021

Optimizing the Recognition and Feature Extraction of Wind Turbines through Hybrid Semantic Segmentation Architectures

Autor: Miguel-Ángel Manso-Callejo, Ramón Alcarria, Calimanut-Ionut Cira, José-Juan Arranz-Justel

Publikováno v: Remote Sensing; Volume 12; Issue 22; Pages: 3743
Remote Sensing, ISSN 2072-4292, 2020-11-30, Vol. 12, No. 22
Archivo Digital UPM
instname

Updating the mapping of wind turbines farms—found in constant expansion—is important to predict energy production or to minimize the risk of these infrastructures during storms. This geoinformation is not usually provided by public mapping agenci

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89047eddc8f9ba771ce87a91d2196e4d

The New Methods for Rapid Exposure and Seismic Vulnerability Assessment. How Do They Adapt to Different Scenarios?

Autor: Jorge M. Gaspar-Escribano, Alejandra Staller, Igor Gómez, José Juan Arranz, Y. Torres, Belén Benito, Sandra Martínez-Cuevas

Publikováno v: Proceedings, Vol 19, Iss 1, p 14 (2019)
Proceedings, 2019, CIGeo 2019, ISSN 2504-3900, 2019-07, Vol. 19, No. 1
Archivo Digital UPM
instname
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)

We present a procedure for exposure and vulnerability evaluation that integrates LiDAR, orthophotos, and other ancillary datasets. It comprises three phases: (1) city stratification into homogeneous regions; (2) exposure database compilation; and (3)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df238bac2d06fabf17086d3833ce8461
https://www.mdpi.com/2504-3900/19/1/14