Publications

Zhan, J; Zhang, DJ; Zhou, GQ; Zhang, GY; Cao, LJ; Guo, Q (2021). MODIS-Based Research on Secchi Disk Depth Using an Improved Semianalytical Algorithm in the Yellow Sea. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 14, 5964-5972.

Abstract
Secchi disk depth is a commonly measured parameter representing the optical properties of water bodies. Assessment of water transparency in seas is highly significant to marine-environment monitoring. In this study, an improved Secchi disk depth (Z(SD)) inversion algorithm was proposed based on the Poole-Atkins model by determining the parameter A in the original model. The Forel-Ule index (FUI) is a water color parameter that can be obtained from remote sensing data. Through the analysis of the International Ocean Color Coordinating Group dataset, it was found that there are strong logarithmic and quadratic correlations between the FUI and parameter A, whose R-2 values are 0.929 and 0.925, respectively. Comparing the results derived from MODIS product data with the in situ measured data in the Yellow Sea showed that the RMSE and MRE of the quadratic formula are 1.83 m and 43.74%, respectively, which reflect better performance than the other empirical formulas. Thus, parameter A can be expressed in quadratic form with FUI as a variable. Finally, we mapped the Z(SD) inversion results for the Yellow Sea and analyzed the spatial changes. This study provides new insight for inverting Z(SD) transparency algorithms and highlights the value of marine transparency monitoring.

DOI:
10.1109/JSTARS.2021.3085556

ISSN:
1939-1404