Autor segons l'article: Vavassori, Alberto; Carrion, Daniela; Zaragozi, Benito; Migliaccio, Federica
Departament: Geografia
Autor/s de la URV: Zaragozí Zaragozí, Benito Manuel
Paraules clau: Crisis map; Flood detection; Optical satellite imagery; Qfield; Semi-automatic processing; Social media; Vgi; Volunteered geographic information; Water
Resum: Timely mapping of flooded areas is critical to several emergency management tasks including response and recovery activities. In fact, flood crisis maps embed key information for an effective response to the natural disaster by delineating its spatial extent and impact. Crisis mapping is usually carried out by leveraging data provided by satellite or airborne optical and radar sensors. However, the processing of these kinds of data demands experienced visual interpretation in order to achieve reliable results. Furthermore, the availability of in situ observations is crucial for the production and validation of crisis maps. In this context, a frontier challenge consists in the use of Volunteered Geographic Information (VGI) as a complementary in situ data source. This paper proposes a procedure for flood mapping that integrates VGI and optical satellite imagery while requiring limited user intervention. The procedure relies on the classification of multispectral images by exploiting VGI for the semi-automatic selection of training samples. The workflow has been tested with photographs and videos shared on social media (Twitter, Flickr, and YouTube) during two flood events and classification consistency with reference products shows promising results (with Overall Accuracy ranging from 87% to 93%). Considering the limitations of social media-sourced photos, the use of QField is proposed as a dedicated application to collect metadata needed for the image classification. The research results show that the integration of high-quality VGI data and semi-automatic data processing can be beneficial for crisis map production and validation, supporting crisis management with up-to-date maps.
Àrees temàtiques: Biodiversidade; Ciência da computação; Ciências agrárias i; Ciências ambientais; Computer science, information systems; Computers in earth sciences; Earth and planetary sciences (miscellaneous); Engenharias i; Geociências; Geografía; Geography, physical; Geography, planning and development; Medicina veterinaria; Remote sensing; Saúde coletiva; Zootecnia / recursos pesqueiros
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: benito.zaragozi@urv.cat
Data d'alta del registre: 2025-02-24
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://www.mdpi.com/2220-9964/11/12/611
Referència a l'article segons font original: Isprs International Journal Of Geo-Information. 11 (12): 611-
Referència de l'ítem segons les normes APA: Vavassori, Alberto; Carrion, Daniela; Zaragozi, Benito; Migliaccio, Federica (2022). VGI and Satellite Imagery Integration for Crisis Mapping of Flood Events. Isprs International Journal Of Geo-Information, 11(12), 611-. DOI: 10.3390/ijgi11120611
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
DOI de l'article: 10.3390/ijgi11120611
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2022
Tipus de publicació: info:eu-repo/semantics/article