Contributions of Operational Satellites in Monitoring the Catastrophic Floodwaters Due to Hurricane Harvey

Abstract

Hurricane Harvey made landfall as a Category-4 storm in the United States on 25 August 2017 in Texas, causing catastrophic flooding in the Houston metropolitan area and resulting in a total economic loss estimated to be about $125 billion. To monitor flooding in the areas affected by Harvey, we used data from sensors aboard the Suomi National Polar-Orbiting Partnership Satellite (SNPP) and the new Geostationary Operational Environmental Satellite (GOES)-16. The GOES-16 Advanced Baseline Imager (ABI) observations are available every 5 min at 1-km spatial resolution across the entire United States, allowing for the possibility of frequent cloud free views of the flooded areas; while the higher resolution 375-m imagery available twice per day from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the SNPP satellite can observe more details of the flooded regions. Combining the high spatial resolution from VIIRS with the frequent observations from ABI offers an improved capability for flood monitoring. The flood maps derived from the SNPP VIIRS and GOES-16 ABI observations were provided to the Federal Emergency Management Agency (FEMA) continuously during Hurricane Harvey. According to FEMA’s estimate on 3 September 2017, approximately 155,000 properties might have been affected by the floodwaters of Hurricane Harvey.

Toward a more effective hurricane hazard communication

“…This study can be also expanded by adding the exposure/vulnerability components and also advanced techniques for estimation of risk (Dewan 2013). Also, remotely sensed data can be used in both hazard estimation (Tessler et al 2015) and exposure/vulnerability assessment (Wang and Xu 2010, Goldberg et al 2018. Worth noted that, there are uncertainties in the reported TC damage estimates.…”

Preface: Remote Sensing for Flood Mapping and Monitoring of Flood Dynamics

“…For flood disaster monitoring, two case studies of Hurricane Harvey were contributed. Goldberg et al [8] leveraged the combination of image data from sensors aboard the Suomi National Polar-Orbiting Partnership Satellite (SNPP) and the new Geostationary Operational Environmental Satellite (GOES)-16 to produce timely flood maps that were provided to the Federal Emergency Management Agency (FEMA) continuously during the Harvey event. For the same event, Chini et al [9] tested Sentinel-1 InSAR Coherence to detect flood waters in the urban areas of Houston (TX, USA).…”

Identifying Dynamic Changes in Water Surface Using Sentinel-1 Data Based on Genetic Algorithm and Machine Learning Techniques

“…Sensor networks monitoring rainfall and river flow [8] cannot cover many parts of the world, and these ground-based systems are expensive [9]. In recent years, satellite remote sensing technology has developed rapidly that can provide timely, objective, accurate, regional and global geographic information data [10][11][12]. Among them, Sentinel-1 remote sensing data…”