Optical Classification of the Remote Sensing Reflectance and Its Application in Deriving the Specific Phytoplankton Absorption in Optically Complex Lakes

Kun Xue,Ming Shen,Dian Wang,Ronghua Ma

doi:10.3390/rs11020184

Abstract

Optical water types (OWTs) were identified from remote sensing reflectance (Rrs(λ)) values in a field-measured dataset of several large lakes in the lower reaches of the Yangtze and Huai River (LYHR) Basin. Four OWTs were determined from normalized remote sensing reflectance spectra (NRrs(λ)) using the k-means clustering approach, and were identified in the Sentinel 3A OLCI (Ocean Land Color Instrument) image data over lakes in the LYHR Basin. The results showed that 1) Each OWT is associated with different bio-optical properties, such as the concentration of chlorophyll-a (Chla), suspended particulate matter (SPM), proportion of suspended particulate inorganic matter (SPIM), and absorption coefficient of each component. One optical water type showed an obvious characteristic with a high contribution of mineral particles, while one type was mostly determined by a high content of phytoplankton. The other types belonged to the optically mixed water types. 2) Class-specific Chla inversion algorithms performed better for all water types, except type 4, compared to the overall dataset. In addition, class-specific inversion algorithms for estimating the Chla-specific absorption coefficient of phytoplankton at 443 nm (a*ph(443)) were developed based on the relationship between a*ph(443) and Chla of each OWT. The spatial variations in the class-specific model-derived a*ph(443) values were illustrated for 2 March 2017, and 24 October 2017. 3) The dominant water type and the Shannon index (H) were used to characterize the optical variability or similarity of the lakes in the LYHR Basin using cloud-free OLCI images in 2017. A high optical variation was located in the western and southern parts of Lake Taihu, the southern part of Lake Hongze, Lake Chaohu, and several small lakes near the Yangtze River, while the northern part of Lake Hongze had a low optical diversity. This work demonstrates the potential and necessity of optical classification in estimating bio-optical parameters using class-specific inversion algorithms and monitoring of the optical variations in optically complex and dynamic lake waters.

Highlights

Inland lakes supply fresh water and food, and influence the regional climate and ecological environment, such as the hydrological cycle and nutrient dynamics [1]
Class-specific inversion algorithms for estimating the Chla-specific absorption coefficient of phytoplankton at 443 nm (a*ph(443)) were developed based on the relationship between a*ph(443) and Chla of each optical water type (OWT)
A number of local and regional bio-optical inversion algorithms have been developed to estimate the concentrations of suspended particulate matter (SPM) and chlorophyll-a (Chla), and the inherent optical properties (IOPs) in optically complex lakes [2,3,4,5]

Summary

Introduction

Inland lakes supply fresh water and food, and influence the regional climate and ecological environment, such as the hydrological cycle and nutrient dynamics [1]. The following studies have treated the partition of oceanic, coastal, and lake waters into different optical classes based on field-measured or satellite remote sensing reflectance [10,12], inherent optical properties [13], or specific absorption coefficients [14]. This study aims to 1) identify the optical water types of the lakes in the LYHR Basin using field-measured and OLCI-derived Rrs(λ) data; 2) characterize the bio-optical properties and IOP variations in each OWT; and 3) develop class-specific models to improve the estimation of the Chla content and Chla-specific phytoplankton absorption at 443 nm (aph*(443))

Field-Measured Datasets

Bio-Optical Algorithms Under Evaluation

Results

Bio-Optical Characteristics of OWTs

Findings

Discussion