Assessing and refining the satellite-derived massive green macro-algal coverage in the Yellow Sea with high resolution images

Abstract

During over the past 10 years, the massive green macro-algal bloom has regularly occurred in the Yellow Sea, the spatial coverage of which is mainly derived by the remote sensing community from satellite images with moderate/low resolution (30-m–1000-m), such as the 250-m-resolution MODIS (Moderate Resolution Imaging Spectroradiometer). In this paper, the MODIS estimates are compared for the first time with the concurrent high resolution (3-m) airborne Synthetic Aperture Radar (SAR) data. We find that the MODIS results are overestimated by more than a factor of 3 when each algae pixel is assumed to be pure (i.e. 100% algae cover), whereas the overestimation is significantly reduced to 1.14 when the pure pixel assumption is abandoned and the genuine (fractional) algae coverage is derived with the linear pixel un-mixing method. These results, together with the re-sampling processing of the high resolution images, indicate that the mixed pixel effect, that is inherent with images with moderate and low resolutions, is the key factor for the satellite extraction of the macro-algae coverage, and these findings are further confirmed by the satellite data with different resolutions. Besides, significant correlations (R2 > 0.9) are found between the macro-algae coverage from 3-m resolution SAR images and those from concurrent satellite images with various resolutions (30-m–1000-m) under the pure pixel assumption, which provides an alternative statistics-based method (in addition to the linear pixel un-mixing) for the accurate macro-algae coverage extraction from satellite images with coarse resolution (e.g. HJ-1 CCD, AQUA MODIS, COMS GOCI). This new method is independently validated with high resolution optical images, and applied to derive the annual maxima of the massive green macro-algal bloom areas (fractional coverage) in the Yellow Sea from 2007 to 2016, which ranges from 45.6 to 732.9-km2 with an average of 247.9 ± 199.3-km2.