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Flood Inundation Mapping from Optical Satellite Images Using Spatiotemporal Context Learning and Modest AdaBoost

Xiaoyi Liu, Hichem Sahli, Yu Meng, Qingqing Huang, Lei Lin
2017 Remote Sensing  
In this work, we propose a novel procedure combining spatiotemporal context learning method and Modest AdaBoost classifier, which aims to extract inundation in an automatic and accurate way.  ...  The availability of multi-date images makes it possible to monitor the progress of floods. Satellites used for mapping floods can be divided into those that are optical and those that are microwave.  ...  A novel inundation mapping approach based on spatiotemporal context learning and Modest AdaBoost is proposed and verified in this paper.  ... 
doi:10.3390/rs9060617 fatcat:umjc75zyz5cgdduu6wyrfsyy6i

Computer Vision and IoT-Based Sensors in Flood Monitoring and Mapping: A Systematic Review

Bilal Arshad, Robert Ogie, Johan Barthelemy, Biswajeet Pradhan, Nicolas Verstaevel, Pascal Perez
2019 Sensors  
Interestingly, the last decade has presented great opportunities with a series of scholarly activities exploring how camera images and wireless sensor data from Internet-of-Things (IoT) networks can improve  ...  This paper presents a systematic review of the literature regarding IoT-based sensors and computer vision applications in flood monitoring and mapping.  ...  Acknowledgments: Special thanks to the Illawarra-Shoalhaven Smart Water Management team for their support and guidance. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s19225012 pmid:31744161 pmcid:PMC6891459 fatcat:4jnir477ajfwjnqm6eznbipx2a