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Evaluating the Portability of Satellite Derived Chlorophyll-a Algorithms for Temperate Inland Lakes using Airborne Hyperspectral Imagery and Dense Surface Observations
Citation:
Johansen, R., R. Beck, J. Nowosad, C. Nietch, M. Xu, S. Shu, B. Yang, H. Liu, E. Emery, M. Reif, J. Harwood, J. Young, D. Macke, M. Martin, G. Stillings, R. Stumpf, AND H. Su. Evaluating the Portability of Satellite Derived Chlorophyll-a Algorithms for Temperate Inland Lakes using Airborne Hyperspectral Imagery and Dense Surface Observations. Harmful Algae. Elsevier B.V., Amsterdam, Netherlands, 76:35-46, (2018). https://doi.org/10.1016/j.hal.2018.05.001
Impact/Purpose:
This study recreated and reevaluated the performances of twenty-nine satellite derived chlorophyll-a algorithms for temperate inland lakes to serve as a proxy for algal bloom detection. The aim was to confirm the use of moderate resolution satellite imagers as a “red flag” detection system to identify potential problem areas for harmful algae that can be then verified by in situ measurements.
Description:
This study recreated and reevaluated the performances of twenty-nine satellite derived chlorophyll-a algorithms for temperate inland lakes to serve as a proxy for algal bloom detection. The performances of these algorithms were compared over two study areas, Harsha Lake in Southwest Ohio and Taylorsville Lake in central Kentucky. The datasets utilized for an estimation of chlorophyll-a concentrations were the airborne derived CASI-1500 hyperspectral imagery, and the spatially resampled and spectrally binned synthetic datasets designed to mimic the configurations of WorldView-2/3, Sentinel-2, Landsat-8, MODIS, and MERIS. This study demonstrates promising results for the use of CASI and Sentinel-2, and to a lesser degree WorldView-2 and Landsat-8 for the identification of algal blooms with r2 values 0.678, 0.707, 0.499, and 0.317, respectively for correlations tested with coincident lake surface chlorophyll measurements in Taylorsville Lake, Kentucky. The results confirm the portability and efficacy of utilizing a suite of algorithms across multiple sensors in order to detect potential hotspots for algal blooms through the use of chlorophyll-a as a proxy. Furthermore, the strong performance of the Sentinel-2 algorithms is exceptionally promising, due to the recent launch of the second satellite in the constellation, which will provide higher temporal resolution for temperate inland water bodies susceptible to algal blooms. In addition, much of the data processing has been automated using the open-source statistical software R, resulting in reduced processing time, and allowing for the integration of numerous algorithms across multiple sensors for the near real-time monitoring required for detecting algal blooms and mitigating their adverse impacts.
URLs/Downloads:
DOI: Evaluating the Portability of Satellite Derived Chlorophyll-a Algorithms for Temperate Inland Lakes using Airborne Hyperspectral Imagery and Dense Surface Observations
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