A comparison of chlorophyll a values obtained from an autonomous underwater vehicle to satellite-based measures for Lake Michigan
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Abstract
Accurate methods to track changes in lake productivity through time and space are critical to fisheries management. Chlorophyll a is the most widely studied proxy for ecosystem primary production, and has been the topic of many studies. The main sources of chlorophyll a measurements are ship-based measures or multi-spectral satellite data. Autonomous underwater vehicles can survey large spatial extents approaching the scale of satellite data, but with the accuracy of ship-based water sampling methods. We use several statistical measures to compare measures of chlorophyll a collected in Lake Michigan with spatiotemporally matched satellite-derived measures of chlorophyll a from the MODIS Aqua multi-spectral sensor using NASA’s OC3 and the Great Lakes Fit algorithms. Our findings show a near one to one relationship between AUV data and both satellite-derived data sets when the AUV data are coarsened to the resolution of the satellite data. A comparison of satellite-based chlorophyll a to AUV-derived chlorophyll summarized in discrete water depth bins suggested that, based on decreasing coefficients of determination, satellite estimates of chlorophyll accounted for the most variability in chlorophyll a concentrations in the upper 10 m of the water column, even though satellite sensors may detect past this depth.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | A comparison of chlorophyll a values obtained from an autonomous underwater vehicle to satellite-based measures for Lake Michigan |
| Series title | Journal of Great Lakes Research |
| DOI | 10.1016/j.jglr.2019.04.003 |
| Volume | 45 |
| Issue | 4 |
| Year Published | 2019 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Great Lakes Science Center |
| Description | 9 p. |
| First page | 726 |
| Last page | 734 |
| Country | United States |
| Other Geospatial | Lake Michigan |