Detection of Flood Extent Using Sentinel-1A/B Synthetic Aperture Radar: An Application for Hurricane Harvey, Houston, TX

Autor: Kristy F. Tiampo, Lingcao Huang, Conor Simmons, Clay Woods, Margaret T. Glasscoe

Publikováno v: Remote Sensing, Vol 14, Iss 9, p 2261 (2022)

The increasing number of flood events combined with coastal urbanization has contributed to significant economic losses and damage to buildings and infrastructure. Development of higher resolution SAR flood mapping that accurately identifies flood fe

Externí odkaz: https://doaj.org/article/362c85bbd3bf49ef9b4bcb0c10b7bfac

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Characterization of the 2014 Indus River Flood Using Hydraulic Simulations and Satellite Images

Autor: Aqil Tariq, Hong Shu, Alban Kuriqi, Saima Siddiqui, Alexandre S. Gagnon, Linlin Lu, Nguyen Thi Thuy Linh, Quoc Bao Pham

Publikováno v: Remote Sensing, Vol 13, Iss 11, p 2053 (2021)

Rivers play an essential role to humans and ecosystems, but they also burst their banks during floods, often causing extensive damage to crop, property, and loss of lives. This paper characterizes the 2014 flood of the Indus River in Pakistan using t

Externí odkaz: https://doaj.org/article/63796f30895b4334ba91683f12e3eb4e

Flood Hazard and Risk Zonation in North Bihar Using Satellite-Derived Historical Flood Events and Socio-Economic Data

Autor: Gaurav Tripathi, Arvind Chandra Pandey, Bikash Ranjan Parida

Publikováno v: Sustainability, Vol 14, Iss 1472, p 1472 (2022)
Sustainability; Volume 14; Issue 3; Pages: 1472

North Bihar is one of the most flood-affected regions of India. Frequent flooding caused significant loss of life and severe economic damages. In this study, hydroclimatic conditions and historical flood events during the period of 2001 to 2020 were

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0209c1851438eb414eaea5661a143cb4
https://www.mdpi.com/2071-1050/14/3/1472

Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility

Autor: Simon Mason, Humberto Vergara, Juan Bazo, Alex de Sherbinin, Andrew Kruczkiewicz, Agathe Bucherie, Fernanda Ayala, Carolynne Hultquist

Publikováno v: Remote Sensing, Vol 13, Iss 2764, p 2764 (2021)
Remote sensing, 13(14):2764, 1-21. MDPI
Remote Sensing; Volume 13; Issue 14; Pages: 2764
Repositorio Institucional-UTP
Universidad Tecnológica del Perú
UTP-Institucional
instacron:UTP

The analysis of historical disaster events is a critical step towards understanding current risk levels and changes in disaster risk over time. Disaster databases are potentially useful tools for exploring trends, however, criteria for inclusion of e

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0791fbb5961ec675f76b048fa375dfc2
https://doi.org/10.3390/rs13142764