Multiple Images Improve Lake CDOM Estimation: Building Better Landsat 8 Empirical Algorithms across Southern Canada

Coloured dissolved organic matter (CDOM) is an important water property for lake management. Remote sensing using empirical algorithms has been used to estimate CDOM, with previous studies relying on coordinated field campaigns that coincided with satellite overpass. However, this requirement reduces the maximum possible sample size for model calibration. New satellites and advances in cloud computing platforms offer opportunities to revisit assumptions about methods used for empirical algorithm calibration. Here, we explore the opportunities and limits of using median values of Landsat 8 satellite images across southern Canada to estimate CDOM. We compare models created using an expansive view of satellite image availability with those emphasizing a tight timing between the date of field sampling and the date of satellite overpass. Models trained on median band values from across multiple summer seasons performed better (adjusted R-2 = 0.70, N = 233) than models for which imagery was constrained to a 30-day time window (adjusted R-2 = 0.45). Model fit improved rapidly when incorporating more images, producing a model at a national scale that performed comparably to others found in more limited spatial extents. This research indicated that dense satellite imagery holds new promise for understanding relationships between in situ CDOM and satellite reflectance data across large areas.

Automated summary

This study explores the opportunities and limitations of using median values of Landsat 8 satellite images to estimate CDOM, comparing models created with a broad view of satellite image availability versus those emphasizing a tight timing between field sampling and satellite overpass dates. The research found that models trained on median band values from multiple summer seasons performed better than those constrained to a 30-day time window, indicating the potential of dense satellite imagery for understanding relationships between in situ CDOM and satellite reflectance data at a national scale.