**1. Introduction**

Lakes are valuable freshwater resources, and they are used for drinking water, fishing, agriculture, industry, and tourism [1]. Lakes also record regional environmental changes, and play important roles in regulating the regional climate and maintaining ecological balance [2]. However, the water quality of many lakes is being threatened by environmental problems that are caused by various natural and anthropogenic factors, such as eutrophication and organic and inorganic pollution [3]. Therefore, effective approaches are needed to monitor the water quality in lakes.

Laboratory analysis of lake water samples is among the main conventional methods that have been used to monitor water quality of lakes. However, this approach is time-consuming and expensive. When compared with conventional methods, satellite remote sensing technology has the advantages of providing multi-temporal and multi-spectral data with high spatial and temporal resolution [4]. Dynamic monitoring and analysis of aquatic environments while using satellite remote sensing technology have been applied in monitoring lake and wetland environments and provide warnings of aquatic environmental emergencies [5].

The monitoring of water quality while using remote sensing technology is of grea<sup>t</sup> importance for guiding lake management. The concentrations of chlorophyll-a (Chl-a) and total suspended matter (TSM) are important indicators for assessing the water quality of lakes [6,7]. The concentration of Chl-a can be used to estimate the degree of eutrophication and as a proxy of primary productivity in mesotrophic and eutrophic water environments. TSM directly a ffects the transmission of light in water and it is closely related to the optical properties of water transparency and turbidity. In the past 30 years, many studies have been reported to monitor concentrations of Chl-a and TSM in lakes while using satellite data [8–11]. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to observe algal blooms and monitor seasonal variations of Chl-a concentration in Lake Taihu, China [12,13]. Medium Resolution Imaging Spectrometer (MERIS) data were used to obtain time-series of Chl-a concentration for the 50 largest standing-water bodies in South Africa [14], and long-term patterns in Poyang Lake, China [15]. Another study determined the spatial and temporal changes in the concentration of TSM in Poyang Lake while using MODIS data from 2000–2010 [16]. Shi et al. [17] integrated MODIS data from 2003–2013 and in situ observations from a number of boat-based surveys to estimate the concentrations of TSM in Lake Taihu. Semi-analytical and empirical algorithms provide indices that are sensitive with Chl-a and TSM [13–19]. The retrieval of Chl-a and TSM concentration are mainly achieved through regression relationships between the measured parameter and sensitive indices while using linear [20,21], quadratic polynomial [22], exponential [16,17], and power-law [23] regression approaches. In recent years, the emergence and application of new satellite sensors, such as Landsat-8 and Sentinel-2, have further promoted the development of the assessment of inland water quality while using remote sensing data [23–25].

Poyang Lake is the largest freshwater lake in China. Its ecosystem services and functions, such as water and biodiversity conservations, have significant impacts on ecological security and sustainability of regional ecology. Poyang Lake has experienced increased urbanization and anthropogenic disturbances, which has greatly impacted the aquatic environment of the lake and wetland system [26,27]. The eutrophication condition in Poyang Lake has been observed to increase over the past decades [28]. High spatial and temporal heterogeneity characterize the water quality of the lake [29]. Determining the dynamic changes of water quality in Poyang Lake requires satellite data with a high spatial resolution and frequency of monitoring in repeated cycle. Data from China's Gaofen-1 (GF-1) satellite possess high-resolution resolution capacity and they have the aforementioned characteristics. However, while GF-1 data have been used for the analysis of terrestrial land features, a lack of study has been implemented for water quality analysis.

This study aimed to assess the applicability of GF-1 satellite data in retrieve information about the concentrations of Chl-a and TSM of Poyang Lake. This study consisted of three steps: (1) characterize and analyze in situ water reflectance spectra and concentrations of Chl-a and TSM to determine the spectral bands or band combinations that are sensitive to retrieve Chl-a and TSM; (2) establish and evaluate algorithms while using data from the GF-1 satellite to estimate the concentrations of Chl-a and TSM; and, (3) determine the spatial and seasonal variation of water quality in the highest and lowest annual water levels between 2015 and 2016.

#### **2. Materials and Methods**
