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Mapping Localized subsidence of Lagos, Nigeria with Sentinel-1A/B Satellite Coverage
Joel Johnson, CIRES Boulder Colorado, United States. firstname.lastname@example.org
Kristy Tiampo, CIRES Boulder CO Colorado, United States. email@example.com
Mike Willis, CIRES BOULDER Colorado, United States. firstname.lastname@example.org
Over 10 percent of the worlds’ population lives less than 10 meters above sea level(McGranahan et al,. 2007), putting them at risk for rising seas and sinking coasts. Additionally, coastal inhabitants preferentially live in locations that are subsiding (Nicholls et al,. 2012), representing a flooding threat to people and infrastructure in coastal cities. Findings from the Intergovernmental Panel on Climate Change (IPCC 2018) outline the risks and impacts of sea level rise on flooding, and go on to identify a knowledge gap regarding the combined effects with coastal subsidence. When drivers of subsidence combine, they can generate sinking rates of 6-100mm/yr, significantly more than the 3-10mm/yr for sea level rise alone (Erkens et al,. 2015), making subsidence an order of magnitude more threatening to coastal cities.
The recent growth in access to C-band Synthetic Aperture Radar (SAR) data through the European Space Agency (ESA) Sentinel-1A/B satellites and the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission provide increased opportunities for differential interferometric synthetic aperture radar (DInSAR) monitoring. Here we developed a dockerized supercomputer workflow that allows us to rapidly generate InSAR pairs from Sentinel 1 imagery using ISCE processing software(Rosen et al., 2012) at ~10 meter resolution.Results from this workflow are used to create a timeseries of subsidence for Lagos, Nigeria, where rapid urban growth has led to accelerated subsidence throughout the city. This growth has resulted in various flash floods due to infiltration and drainage issues in the last fifteen years(Atufu 2018), and the city is also vulnerable to coastal flooding. Next steps will include inputting our time series to determine how future flood events may impact specific areas of Lagos. Understanding where floods are a higher risk can allow for better distribution of rescue resources, and allow for targeted remediation and recovery efforts.