COS 19-7
Prospects and progress in understanding carbon stocks in northern lakes with the new Landsat 8 platform
As increasing attention is paid to the storage and flux of carbon in and around boreal lakes, strategies to make and refine credible region-wide estimates of stocks and fluxes will be increasingly important. Given that there are hundreds of thousands of lakes in the world’s lake-rich regions, concerted field campaigns can reach only a minuscule fraction of the lakes. Although remote sensing would appear to be of obvious potential, ecologists interested in understanding lake carbon have been limited by many factors, primarily (1) the low spectral and radiometric resolution of earlier Landsat imagery; (2) the limited coverage of the experimental ALI sensor; and (3) the high cost of alternative imagery. We have recently shown that multi-temporal imagery from the similar ALI sensor can be used for a high-quality estimation of colored dissolved organic matter (CDOM), an important lake property. For that relation we used a legacy field data set collected at irregular times over more than a decade, which greatly expanded the amount of field observation available for building the model. In this study we ask whether comparable results can be found for the initial imagery of the newly launched Landsat 8 sensor.
Results/Conclusions
We have created an automated protocol for treating and refining an ongoing series of imagery-driven estimates. The workflow is intended to automatically incorporate new evidence to continually sharpen the estimates of lake carbon content across a vast area. With minimal atmospheric correction and an estimate of carbon content in continual refinement, we demonstrate that long-term wide-area monitoring is possible with the new Landsat platform. Built on the demonstrated potential of the ALI sensor for sensing carbon stocks, the prospect of long-term observation of lake properties is arriving, and it promises a much clearer picture of one of the world’s great storehouses of carbon.