Remote sensing retrieval of chlorophyll-a concentration in the coastal waters of Hong Kong based on Landsat-8 OLI and Sentinel-2 MSI sensors. Issue 1 (February 2021)

• Record Type: Journal Article
• Authors: Dong, Shundan; He, Hongchang; Fu, Bolin; Fan, Donglin; Wang, Taotao
• Is Part Of: IOP conference series. Volume 671:Issue 1(2021)
• Publication Date: 2021-02
• Subjects: Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/671/1/012033
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: Using Landsat-8 OLI remote sensing data and Sentinel-2 MSI remote sensing data as data sources, selecting the coastal waters of Hong Kong as the study area, using semi-analytical model as the method, selecting the same time as the measured chlorophyll-a concentration at the monitoring point and the cloud coverage rate of remote sensing images two types of remote sensing images with clear images less than 10%. For the two types of remote sensing images, two thirds of the remote sensing image data are selected after preprocessing, and the remote sensing reflectance of the monitoring point location corresponding to the actual date is extracted for correlation analysis, and the most relevant inversion factor is obtained for modeling. Meanwhile the remaining 1/3 of the data is used to test the accuracy of its inversional regression model. The best inversional regression model based on Landsat-8 remote sensing data is Y=6.8x2-20.77x+17.02, R 2 =0.906 which is slightly higher than the best inversional regression model based on Sentinel-2 remote sensing data Y=-3.345e +05x2+3826x-3.44, R 2 =0.801, which proves the feasibility of inverting the two types of remote sensing data for the chlorophyll-a concentration in the Hong Kong offshore waters, and the inversional results of the two types of data show that the chlorophyll-a concentration in the internal waters of the Hong Kong offshore waters is higher than the phenomenon of external chlorophyll-a concentration.