<p>Satellite based flood detection can enhance understanding of risk to humans and infrastructures, geomorphic processes, and ecological effects.&#160; Such application of optical satellite imagery has been mostly limited to the detection of water exposed to sky, as plant canopies tend to obstruct water visibility in short electromagnetic wavelengths.&#160; This case study evaluates the utility in multi-temporal thermal infrared observations from Landsat 8 as a basis for detecting sub-canopy fluvial inundation resulting in ambient temperature change.</p><p>We selected three flood events of 2016 and 2019 along sections of the Mississippi, Cedar, and Wapsipinicon Rivers located in Iowa, Minnesota, and Wisconsin, United States.&#160; Classification of sub-canopy water involved logical, threshold-exceedance criteria to capture thermal decline within channel-adjacent vegetated zones.&#160; Open water extent in the floods was mapped based on short-wave infrared thresholds determined parametrically from baseline (non-flooded) observations.&#160; Map accuracy was evaluated using higher-resolution (0.5&#8211;5.0 m) synchronic optical imagery.</p><p>Results demonstrate improved ability to detect sub-canopy inundation when thermal infrared change is incorporated: sub-canopy flood class accuracy was comparable to that of open water in previous studies.&#160; The multi-temporal open-water mapping technique yielded high accuracy as compared to similar studies.&#160; This research highlights the utility of Landsat thermal infrared data for monitoring riparian inundation and for validating other remotely sensed and simulated flood maps.</p>
Practical retrieval of land surface emissivity spectra in 8-14μm from hyperspectral thermal infrared data
