Using Remote Sensing to Determine the Spatial Scales of Estuaries

One challenge facing Earth system science is to understand and quantify the complexity of rivers, estuaries, and coastal zone regions. Earlier studies using data from airborne hyperspectral imagers (Bissett et al., 2004, Davis et al., 2007) demonstrated from a very limited data set that the spatial scales of the coastal ocean could be resolved with spatial sampling of 100 m Ground Sample Distance (GSD) or better. To develop a much larger data set (Aurin et al., 2013) used MODIS 250 m data for a wide range of coastal regions. Their conclusion was that farther offshore 500 m GSD was adequate to resolve large river plume features while nearshore regions (a few kilometers from the coast) needed higher spatial resolution data not available from MODIS. Building on our airborne experience, the Hyperspectral Imager for the Coastal Ocean (HICO, Lucke et al., 2011) was designed to provide hyperspectral data for the coastal ocean at 100 m GSD. HICO operated on the International Space Station for 5 years and collected over 10,000 scenes of the coastal ocean and other regions around the world. Here we analyze HICO data from an example set of major river delta regions to assess the spatial scales of variability in those systems. In one system, the San Francisco Bay and Delta, we also analyze Landsat 8 OLI data at 30 m and 15 m to validate the 100 m GSD sampling scale for the Bay and assess spatial sampling needed as you move up river.