Remote sensing of lake CDOM using noncontemporaneous field data

Abstract

There are perhaps millions of lakes in Canada, and remote sensing is a crucial tool for making regional estimates of carbon stocks. Estimation using existing platforms has been hampered by both spatial and spectral resolution, but a new generation of sensors promises greatly improved image quality with broad-scale repeat coverage. Nearly all remote sensing studies in aquatic environments include carefully coordinated field campaigns with satellite overpasses, but this greatly limits the number of lakes that can be used in model development. We explored the opportunities and limits for combining high-quality Advanced Land Imager imagery with legacy lake samples to estimate colored dissolved organic matter (CDOM), a lake characteristic of high value in constructing lake carbon budgets. The passage of time produces somewhat greater scatter than in the standard model with timed field campaign, but there is no indication of a bias toward an incorrect model when using field samples from a variety of dates. Because many thousands of older field samples exist for Canadian lakes, existing limnological databases hold considerable value for estimating CDOM from satellite with sensors of sufficient radiometric depth and signal quality. This study reveals a substantial opportunity for creating and refining estimates of fundamental lake parameters in one of the world's great storehouses of aquatic carbon.