Geosynchronous Satellite GF-4 Observations of Chlorophyll-a Distribution Details in the Bohai Sea, China

Abstract

We analyzed the distribution of chlorophyll-a (Chla) in the Bohai Sea area based on data from the geosynchronous orbit optical satellite Gaofen-4 (GF-4), which was launched in 2015, carrying a panchromatic multispectral sensor (PMS). This is the first time the geosynchronous orbit optical satellite GF-4 remote-sensing data has been used in China to detect the Chla change details in the Bohai Sea. A new GF-4 retrieved model was established based on the relationship between in situ Chla value and the reflectance combination of 2 and 4 bands, with the R2 of 0.9685 and the total average relative error of 37.42%. Twenty PMS images obtained from 2017 to 2019 were applied to analyze Chla in Bohai sea. The results show that: (1) the new built Chla inversion model PMS-1 for the GF-4 PMS sensor can extract Chla distribution details in the Bohai Sea well. The high Chla content in the Bohai Sea is mainly located in coastal areas, such as the top of Laizhou Bay, Bohai Bay and Liaodong Bay, with the value being around 13 µg/L. The concentration of Chla in the Bohai Strait and northern Yellow Sea is relatively low with the value being around 5 µg/L. (2). Taking full advantage of the continuous observation of geostationary orbit satellite, GF-4 with a high-resolution sensor PMS of 50 m can effectively detect short-term change (changes within 10 min) in Chla concentration. The changes mainly appear at the southwest and northeast costal area as well as in the center of Bohai Sea with the change value of around 3 µg/L. (3) The change of Chla concentration in the Bohai sea is related to the environmental factors such as seawater temperature, salinity, illumination and nutrient salts, as well as the dynamic factors such as wind, flow field and tidal current.

Inversion of Chlorophyll-a Concentrations in Chaohu Lake Based on GF-1 WFV Images

“…The red band showed the highest correlation with the chlorophyll-a concentrations, with a coefficient of determination of 0.570 (Fig. 2c) but still did not meet the accuracy requirements of the inversion study [35]. In addition to those of the red band, the coefficients of determination of the blue (Fig.…”

“…2d) bands were 0.277, 0.392 and 0.367, respectively, with the blue band having the lowest correlation with the chlorophyll-a concentrations. Therefore, inversion modeling of chlorophyll-a concentrations using a single band is inappropriate, and inversion modeling using a combination of bands should be considered [35,36].…”

Monitoring the Chl-a Distribution Details in the Yangtze River Mouth Using Satellite Remote Sensing

“…These problems have drawn the attention of many scholars [17]. Given the former problem, many scholars proposed to use red and near-infrared bands to avoid the above defects of blue-green bands in the inversion algorithm of type II water bodies [11,12,[18][19][20]. In addition to the traditional twoband ratio method, some scholars have proposed a three-band algorithm for the medium muddy water [21].…”

Comprehensive Evaluation of the GF-4 Satellite Image Quality from 2015 to 2020

“…Ground control points are essential when high geo-positioning accuracy images are required [6,7]. To examine the quantitative retrieval, radiometric and atmospheric corrections should be performed with calibration coefficients [8,9]. These coefficients can also be obtained from the CRESDA website.…”