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Comparison of Satellite Reflectance Algorithms for Estimating Turbidity and Cyanobacterial Concentrations in Productive Freshwaters Using Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations
Citation:
Beck, R., M. Xu, S. Zhan, R. Johansen, H. Liu, S. TONG, B. Yang, S. Shu, Q. Wu, S. Wang, K. Berling, A. Murray, E. Emery, M. Reif, j. Harwood, J. Young, C. Nietch, D. Macke, M. Martin, G. Stillings, R. Stumpf, H. Su, Z. Ye, AND Y. Huang. Comparison of Satellite Reflectance Algorithms for Estimating Turbidity and Cyanobacterial Concentrations in Productive Freshwaters Using Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations. JOURNAL OF GREAT LAKES RESEARCH. Elsevier B.V., Amsterdam, Netherlands, 45(3):413-433, (2019). https://doi.org/10.1016/j.jglr.2018.09.001
Impact/Purpose:
This research is focused on comparing relatively simple, and, therefore, portable, semi-analytical, and reflectance-signature-based algorithms that provide reasonable estimates of turbidity and/or phytoplankton biomass with current and near-future multispectral satellite imagers. The ultimate goal of this research is to explore and expand remote sensing-based options that could be used for near-real-time monitoring of inland water quality
Description:
We analyzed 37 satellite reflectance algorithms and 321 variants for five satellites for estimating turbidity in a freshwater inland lake in Ohio using coincident real hyperspectral aircraft imagery and dense coincident surface observations as part of an effort to develop simple proxies for turbidity and algal blooms and to evaluate their performance and portability between satellite imagers for regional operational turbidity and algal bloom monitoring. Turbidity algorithms were then applied to synthetic satellite images and compared to calibrated turbidity, chloropyll-a (Chl-a), total suspended solids (TSS) and cyanobacterial/blue green algal (BGA) coincident surface observation measurements. Several turbidity algorithms worked well with real Compact Airborne Spectrographic Imager (CASI) and synthetic WorldView-2, Sentinel-2 and Sentinel-3/MERIS/OLCI imagery. A simple red band algorithm had the best but limited performance with MODIS imagery and a new fluorescence line height algorithm yielded the best but limited turbidity estimates with simulated Landsat-8 imagery. Blue-Green Algae/Phycocyanin (BGA/PC) and chlorophyll algorithms were the most widely applicable algorithms for turbidity estimation because strong co-variance of turbidity, TSS, Chl-a, and BGA made them mutual proxies in this experiment.
URLs/Downloads:
DOI: Comparison of Satellite Reflectance Algorithms for Estimating Turbidity and Cyanobacterial Concentrations in Productive Freshwaters Using Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations
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