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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 tornadosDifferent techniques for flood mapping, forecasting, and early warningIntegrated approach for predicting flood and landslide cascading hazardsSatellite monitoring of water cycle variation, water scarcity, and drought conditionsMulti-indicator and multi-sensor approaches for quantifying drought impactsThe 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.
Ke Zhang, Hohai University, China.Yang Hong, University of Oklahoma, USA.Amir AghaKouchak, University of California, Irvine, USA.
List of Contributors viiPreface xi1. Interdisciplinary Perspectives on Remote Sensing for Monitoring and Predicting Water-Related Hazards 1Ke Zhang, Yang Hong, and Amir AghaKouchakPart I Remote Sensing of Precipitation and Storms2. Progress in Satellite Precipitation Products over the Past Two Decades: Evaluation and Application in Flash Flood Warning 13Guoqiang Tang, Tsechun Wang, Meihong Ma, Wentao Xiong, Feng Lyu, and Ziqiang Ma3. Observations of Tornadoes and Their Parent Supercells Using Ground-Based, Mobile Doppler Radars 31Howard B. BluesteinPart II Remote Sensing of Floods and Associated Hazards4. Remote Sensing Mapping and Modeling for Flood Hazards in Data-Scarce Areas: A Case Study in Nyaungdon Area, Myanmar 71Ke Zhang, Zaw Myo Khaing, and Zhijia Li5. Multisensor Remote Sensing and the Multidimensional Modeling of Extreme Flood Events: A Case Study of Hurricane Harvey--Triggered Floods in Houston, Texas, USA 87Mengye Chen, Zhi Li, and Shang Gao6. A Multisource, Data-Driven, Web-GIS-Based Hydrological Modeling Framework for Flood Forecasting and Prevention 105Zhanming Wan, Xianwu Xue, Ke Zhang, Yang Hong, Jonathan J. Gourley, and Humberto Vergara7. An Ensemble-Based, Remote-Sensing-Driven, Flood-Landslide Early Warning System 123Ke Zhang, Guoding Chen, Yi Xia, and Sheng Wang8. Detection of Hazard-Damaged Bridges Using Multitemporal High-Resolution SAR Imagery 135Wen Liu, Kazuki Inoue, and Fumio YamazakiPart III Remote Sensing of Droughts and Associated Hazards9. Drought Monitoring Based on Remote Sensing 151Xin Li, Ran Tao, and Ke Zhang10. Remote Sensing of Vegetation Responses to Drought Disturbances Using Spaceborne Optical and Near-Infrared Sensors 169Ke Zhang, Linxin Liu, Yunping Li, and Ran Tao11. Recent Advances in Physical Water Scarcity Assessment Using GRACE Satellite Data 187Emad Hasan and Aondover Tarhule12. Study of Water Cycle Variation in the Yellow River Basin Based on Satellite Remote Sensing and Numerical Modeling 203Meixia Lv and Zhuguo Ma13. Assessing the Impact of Climate Change-Induced Droughts on Soil Salinity Development in Agricultural Areas Using Ground and Satellite Sensors 223Dennis L. Corwin and Elia ScudieroIndex 245
Robert D. van der Hilst, Jay D. Bass, Jan Matas, Jeannot Trampert, at Urbana-Champaign) Bass, Jay D. (Department of Geology, University of Illinois, Robert D. Van Der Hilst, Robert D van der Hilst, Jay D Bass
Martin J. Siegert, Mahlon C. Kennicutt II, Robert A. Bindschadler, II Kennicutt, Mahlon C., Mahlon C. Kennicutt, Martin J Siegert, Mahlon C Kennicutt, Robert A Bindschadler
Yang Hong, Yu Zhang, Sadiq Khan, USA) Hong, Yang (University of Oklahoma, Norman, USA) Zhang, Yu (Princeton University, New Jersey, USA) Khan, Sadiq (University of Oklahoma, Norman
Yang Hong, Jonathan J. Gourley, China) Hong, Yang (University of Oklahoma, Norman, USA and Tsinghua University, Beijing, USA) Gourley, Jonathan J. (NOAA/National Severe Storms Laboratory, Norman, Oklahoma, Jonathan J Gourley
Ni-Bin Chang, Yang Hong, USA) Chang, Ni-Bin (University of Central Florida, Orlando, China) Hong, Yang (University of Oklahoma, Norman, USA and Tsinghua University, Beijing
Ni-Bin Chang, Yang Hong, USA) Chang, Ni-Bin (University of Central Florida, Orlando, China) Hong, Yang (University of Oklahoma, Norman, USA and Tsinghua University, Beijing