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Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations
Citation:
Beck, R., S. Zhan, H. Liu, S. Tong, B. Yang, M. Xu, Z. Ye, Y. Huang, 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, AND H. Su. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations. REMOTE SENSING OF ENVIRONMENT. Elsevier Science Ltd, New York, NY, 178:15-30, (2016).
Impact/Purpose:
Several promising algorithm/satellite imager combinations for routine Chl-a estimation in smaller inland water bodies were found with operational and near-future satellite systems from a multi-agency flyover and water truth effort. The effort helps to validate remote sensing algorithms for algae blooms in inland lakes.
Description:
We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop simple proxies for algal blooms and to facilitate portability between multispectral satellite imagers for regional algal bloom monitoring. Narrow band hyperspectral aircraft images were upscaled spectrally and spatially to simulate 5 current and near future satellite imaging systems. Established and new Chl-a algorithms were then applied to the synthetic satellite images and then compared to calibrated Chl-a water truth measurements collected from 44 sites within one hour of aircraft acquisition of the imagery. Masks based on the spatial resolution of the synthetic satellite imagery were then applied to eliminate mixed pixels including vegetated shorelines. Medium-resolution Landsat and finer resolution data were evaluated against 29 coincident water truth sites. Coarse-resolution MODIS and MERIS-like data were evaluated against 9 coincident water truth sites. Each synthetic satellite data set was then evaluated for the performance of a variety of spectrally appropriate algorithms with regard to the estimation of Chl-a concentrations against the water truth data set. The goal is to inform water resource decisions on the appropriate satellite data acquisition and processing for the estimation of Chl-a at the water surface for near-real-time monitoring of algal blooms in temperate inland reservoirs. We found several promising algorithm/satellite imager combinations for routine Chl-a estimation in smaller inland water bodies with operational and near-future satellite systems.
