Remote Sensing and Early Warning of Natural Hazards. Questo articolo non è disponibile.
Lingua: inglese
Editore: Amer Geophysical Union, 2022
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- Nuovo

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EUR 190,57
Descrizione dell’articolo da parte del venditore
350 pages. 10.75x8.25x0.75 inches. In Stock. This item is printed on demand.
Codice articolo __1119159121
- Titolo
- Remote Sensing and Early Warning of Natural Hazards
- Autore
- Hong, Yang/ Kirschbaum, Dalia B./ Aghakouchak, Amir/ Zhang, Ke
- Editore
- Amer Geophysical Union
- Anno di pubblicazione
- 2022
- Condizione
- Brand New
- Rilegatura
- Hardcover
- Lingua
- inglese
- ISBN 10
- 1119159121
- ISBN 13
- 9781119159124
- Peso dell'articolo
- 0,94 chilogrammi
- Serie
- Libro 246 di 266: Geophysical Monograph
Applications of remote sensing technology for monitoring and predicting water-related hazards
Water-related hazards such as floods and droughts have serious impacts on society. Their incidence has increased in recent decades, a trend set to continue with ongoing climate change. Adaptation and mitigation measures require accurate detection, monitoring, and forecasting, much of which comes from remote sensing technologies.
Remote Sensing of Water-Related Hazards takes an interdisciplinary approach, presenting recent advances in the available data, sensors, models, and indicators developed for monitoring and prediction.
Volume highlights include:
- Progress in remote sensing of precipitation, storms, and tornados
- Different techniques for flood mapping, forecasting, and early warning
- Integrated approach for predicting flood and landslide cascading hazards
- Satellite monitoring of water cycle variation, water scarcity, and drought conditions
- Multi-indicator and multi-sensor approaches for quantifying drought impacts
The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
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Informazioni sull’autore
Ke Zhang, Hohai University, China.
Yang Hong, University of Oklahoma, USA.
Amir AghaKouchak, University of California, Irvine, USA.
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