Evaluation of the Crosta method for the retrieval of water quality parameters from remote sensing data in the Pearl River estuary

Yunpeng Wang,Yuanzhi Zhang,Feng Gao

doi:10.2166/wqrj.2020.024

Abstract

Abstract In recent decades, many algorithms have been developed for the retrieval of water quality parameters using remotely sensed data. However, these algorithms are specific to a certain geographical area and cannot be applied to other areas. In this study, feature-orientated principal component (PC) selection, based on the Crosta method and using Landsat Thematic Mapper (TM) for the retrieval of water quality parameters (i.e., total suspended sediment concentration (TSM) and chlorophyll a (Chla)), was carried out. The results show that feature-orientated PC TSM, based on the Crosta method, obtained a good agreement with the MERIS-based TSM product for eight Landsat TM images. However, the Chla information, selected using the feature-orientated PC, has a poor agreement with the MERIS-based Chla product. The accuracy of the atmospheric correction method and MERIS product may be the main factors influencing the accuracy of the TSM and Chla information identified by the Landsat TM images using the Crosta method. The findings of this study would be helpful in the retrieval of spatial distribution information on TSM from the long-term historical Landsat image archive, without using coincident ground measurements. This article has been made Open Access thanks to the kind support of CAWQ/ACQE (https://www.cawq.ca).

Highlights

In recent years, global studies have shown that it is possible to pair in-situ data collected at discrete stations with remotely sensed data, with the aim of retrieving water quality parameters
The results show that the PC1 generated from the Landsat Thematic Mapper (TM), taken on Oct. 17, 2003, and the MERIS TSM product are strongly correlated, with a highly significant linear relationship (R2 1⁄4 0.83, p-value < 0.0001, RMSE 1⁄4 4.77 g/m3) (Figure 6(a))
The Crosta method was used to investigate the applicability of water quality parameters (TSM and Chla) identified by Landsat TM images

Summary

Introduction

Global studies have shown that it is possible to pair in-situ data collected at discrete stations with remotely sensed data, with the aim of retrieving water quality parameters. These algorithms ranged from linear relationships between satellite remote sensing reflectance and field measurements of water quality parameters (e.g., total suspended sediment concentration (TSM) and chlorophyll a (Chla)) in the estuary and inland waters to region-specific algorithms, explicitly developed for coastal waters, using in-situ measured reflectance and TSM or Chla. Xi & Zhang ( ) established an empirical two-band model using the ratio of remote sensing reflectance at 629 and 671 nm to retrieve the TSM concentration in the Pearl River estuary (PRE) They used a MERIS image and in-situ remote sensing reflectance to map the distribution of the TSM in the PRE.

Objectives

Methods

Results

Conclusion