Modeling the impact of future Landsat spectral capabilities for monitoring water quality and harmful algal blooms
Research Team Members
Nina Raqueño, Ryan Ford
This project focuses on using spectral imagery to retrieve concentrations of waterbody components using modeled Look-Up-Tables (LUTs) to determine how imaging systems could be improved for this task, e.g., Landsat. This work extends the LUT retrieval method to assess its ability to retrieve pigments related to harmful cyanobacteria blooms. Imagery from Landsat satellites, as well as multi and hyperspectral unmanned aerial system (UAS) is used for this assessment.
In the past year we have determined the factors of the LUT retrieval pro- cess that affect retrieval error, the largest being atmospheric compensation, sensor noise, and the inputs/design of the LUT, which gives us direction for future work. Some of our improved mapping results are shown below for Owasco Lake. However, the spectral response of a sensor remains critical for water applications and our results demonstrate the value of an imaging spectrometer whether that sensor is on a satellite or a UAS.
Our modeling approach was used to test various future Landsat spectral configurations (below) and demonstrated clear improvements when the spectrum is more finely sampled. Ryan Ford will defend his dissertation in summer 2019.
Figures and Images