Abstract
For disaster emergency response, timely information is critical and satellite data is a potential source for such information. High-resolution optical satellite images are often the most informative, but these are only available on cloud-free days. For some extreme weather disasters, like cyclones, access to cloud-free images is unlikely for days both before and after the main impact. In this situation, Synthetic Aperture Radar (SAR) data is a unique first source of information, as it works irrespective of weather and sunlight conditions. This paper shows, in the context of the cyclone Idai that hit Mozambique in March 2019, that Change Detection between pairs of SAR data is a perfect match with weather data, and therefore captures impact from the severe cyclone. For emergency operations, the filtering of Change Detections by external data on the location of houses prior to an event allows assessment of the impact on houses as opposed to impact on the surrounding natural environment. The free availability of SAR data from Sentinel-1, with further automated processing of it, means that this analysis is a cost-effective and quick potential first indication of cyclone destruction.
Highlights
Monitoring and assessing impact from natural disasters continues to be a difficult task
Despite progress on automated identification of disaster damages based on optical images, the emergency response for the cyclone Idai in Beira was guided by trained operators that manually tagged optical images, similar to the method presented in Reference [1]
This highlights the advantage of the Synthetic Aperture Radar (SAR) data, as opposed to the analysis based on optical images or unmanned aerial vehicles (UAVs), that were not available until much later
Summary
Monitoring and assessing impact from natural disasters continues to be a difficult task. Despite progress on automated identification of disaster damages based on optical images, the emergency response for the cyclone Idai in Beira was guided by trained operators that manually tagged optical images, similar to the method presented in Reference [1]. There are at least three alternative remote sensing methods to use combined with automatic processing—(i) images from unmanned aerial vehicles (UAVs), (ii) optical satellite images, and (iii) Synthetic Aperture Radar (SAR), each with different advantages and disadvantages. The main advantage of SAR data, compared to optical images and UAVs, is that it is available irrespective of any weather condition and acquisitions are possible day and night. Most applications of disaster response based on optical satellite images rely on substantial human processes, involving trained operators, that can be time consuming and costly. SAR data on the other hand is freely available and does not rely on weather or local human and physical resources
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
