QUANTITATIVE ULVA PROLIFERA BLOOM MONITORING BASED ON MULTI-SOURCE SATELLITE OCEAN COLOR REMOTE SENSING DATA

摘要

Since 2007, a large-scare green macroalgae bloom of Ulva prolifera has occurred every year in the Yellow Sea, and satellite ocean color remote sensing monitoring of such event is an effective technical method with important application value. For the Moderate Resolution Imaging Spectroradiometer (MODIS), Geostationary Ocean Color Imager (GOCI), Sentinel-3 Ocean and Land Colour Instrument (OLCI), Landsat8 Operational Land Imager (OLI) and Gaofen satellite (GF1) multispectral satellite data of the study area, the bloom was monitored based on spectral band difference algorithms and band-ratio algorithms. In view of the threshold selection of the detection, the scaled algae index (SAI) is less sensitive to the environment and shows accurate stability. For the five satellite ocean color sensors, this study compared their ability to monitor algal bloom on spatial and temporal scales. On the spatial scale, quantitative results of each data are specifically compared. Low spatial resolution data was found to overestimate the blooming area. On the time scale, GOCI can best monitor the dynamic changes of bloom, and the composites of algae and sea surface wind shows the dynamic evolution of blooming event in the range from May to July 2017.