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Remote monitoring of trophic state for inland waters is a hotspot of water quality studies worldwide. However, the complex optical properties of inland waters limit the potential of algorithms. This research aims to develop an algorithm to estimate the trophic state in inland waters. First, the turbid water index was applied for the determination of optical water types on each pixel, and water bodies are divided into two categories: algae-dominated water (Type I) and turbid water (Type II). The algal biomass index (ABI) was then established based on water classification to derive the trophic state index (TSI) proposed by Carlson (1977). The results showed a considerable precision in Type I water (R2 = 0.62, N = 282) and Type II water (R2 = 0.57, N = 132). The ABI-derived TSI outperformed several band-ratio algorithms and a machine learning method (RMSE = 4.08, MRE = 5.46%, MAE = 3.14, NSE = 0.64). Such a model was employed to generate the trophic state index of 146 lakes (> 10 km2) in eastern China from 2013 to 2020 using Landsat-8 surface reflectance data. The number of hypertrophic and oligotrophic lakes decreased from 45.89% to 21.92% and 4.11% to 1.37%, respectively, while the number of mesotrophic and eutrophic lakes increased from 12.33% to 23.97% and 37.67% to 52.74%. The annual mean TSI for the lakes in the lower reaches of the Yangtze River basin was higher than that in the middle reaches of the Yangtze River and Huai River basin. The retrieval algorithm illustrated the applicability to other sensors with an overall accuracy of 83.27% for moderate-resolution imaging spectroradiometer (MODIS) and 82.92% for Sentinel-3 OLCI sensor, demonstrating the potential for high-frequency observation and large-scale simulation capability. Our study can provide an effective trophic state assessment and support inland water management.
Minqi Hu; Ronghua Ma; Zhigang Cao; Junfeng Xiong; Kun Xue. Remote Estimation of Trophic State Index for Inland Waters Using Landsat-8 OLI Imagery. Remote Sensing 2021, 13, 1988 .
AMA StyleMinqi Hu, Ronghua Ma, Zhigang Cao, Junfeng Xiong, Kun Xue. Remote Estimation of Trophic State Index for Inland Waters Using Landsat-8 OLI Imagery. Remote Sensing. 2021; 13 (10):1988.
Chicago/Turabian StyleMinqi Hu; Ronghua Ma; Zhigang Cao; Junfeng Xiong; Kun Xue. 2021. "Remote Estimation of Trophic State Index for Inland Waters Using Landsat-8 OLI Imagery." Remote Sensing 13, no. 10: 1988.
Poyang Lake is the largest freshwater lake connecting the Yangtze River in China. It undergoes dramatic dynamics from the wet to the dry seasons. A comparison of the hydrological changes between the wet and dry seasons may be useful for understanding the water flows between Poyang Lake and Yangtze River or the river system in the watershed. Gauged measurements and remote sensing datasets were combined to reveal lake area, level and volume changes during 2000–2020, and water exchanges between Poyang Lake and Yangtze River were presented based on the water balance equation. The results showed that in the wet seasons, the lake was usually around 1301.85–3840.24 km2, with an average value of 2800.79 km2. In the dry seasons, the area was around 618.82–2498.70 km2, with an average value of 1242.03 km2. The inundations in the wet seasons were approximately quadruple those in the dry seasons. In summer months, the lake surface tended to be flat, while in winter months, it was inclined, with the angles at around 10′′–16′′. The mean water levels of the wet and dry seasons were separately 13.51 m and 9.06 m, with respective deviations of around 0–2.38 m and 0.38–2.15 m. Monthly lake volume changes were about 7.5–22.64 km3 and 1–5.80 km3 in the wet and dry seasons, respectively. In the wet seasons, the overall contributions of ground runoff, precipitation on the lake surface and lake evaporation were less than the volume flowing into Yangtze River. In the dry seasons, the three contributions decreased by 50%, 50% and 65.75%, respectively. Therefore, lake storages presented a decrease (−7.42 km3/yr) in the wet seasons and an increase (9.39 km3/yr) in the dry seasons. The monthly exchanges between Poyang Lake and Yangtze River were at around −14.22–32.86 km3. Water all flowed from the lake to the river in the wet seasons, and the chance of water flowing from Yangtze River in the dry seasons was only 5.26%.
Fangdi Sun; Ronghua Ma; Caixia Liu; Bin He. Comparison of the Hydrological Dynamics of Poyang Lake in the Wet and Dry Seasons. Remote Sensing 2021, 13, 985 .
AMA StyleFangdi Sun, Ronghua Ma, Caixia Liu, Bin He. Comparison of the Hydrological Dynamics of Poyang Lake in the Wet and Dry Seasons. Remote Sensing. 2021; 13 (5):985.
Chicago/Turabian StyleFangdi Sun; Ronghua Ma; Caixia Liu; Bin He. 2021. "Comparison of the Hydrological Dynamics of Poyang Lake in the Wet and Dry Seasons." Remote Sensing 13, no. 5: 985.
More than 1100 lakes covering an area greater than 4500 km2 are located on the Tibetan Plateau, and these lakes are important regulators of several large and famous rivers in Asia. The determination of hydrological changes that have occurred in these lakes can reflect climate change and supply scientific data to plateau environmental research. Data from high frequency (moderate-resolution imaging spectro-radiometer) MODIS images, altimetry, and the Hydroweb database collected during 2000–2015 were integrated in this study to delineate the detailed hydrological changes of 15 lakes in three basins—Inner Basin, Indus Basin, and Brahmaputra Basin—on the southern Tibetan Plateau. Seven of the 10 lakes in the Inner Basin presented increasing trends with various intensities, and the increasing rates in the area of four lakes (Nam Co, Selin Co, Zhari-namco, and Ngangze) were 1.62, 28.81, 2.27, and 3.70 km2/yr, respectively. The yearly increases in volume of the four lakes were 3.6, 9.44, 6, and 2.36 km3, respectively. A water balance equation was established for the four lakes based on lake volume changes to illustrate the contributions of precipitation, ground runoff, evaporation, and other factors. The results revealed that surface runoff was the major contributor to expansion, and lake surface evaporation was almost 2.76–3.86 times that of lake surface precipitation. The two lakes in Indus Basin, Rakshastal and Mapam Yumco, presented a slight retreat. As a representative of Brahmaputra Basin, Yamzho Yumco underwent a retreat of –3.49 km2/yr in area, –0.39 m/yr in level, and –0.19 km3/yr in volume. Decreasing precipitation, increasing evaporation, and the operation of a hydrological project were the main causes of its constant retreat.
Fangdi Sun; Ronghua Ma; Bin He; Xiaoli Zhao; Yuchao Zeng; Siyi Zhang; Shilin Tang. Changing Patterns of Lakes on The Southern Tibetan Plateau Based on Multi-Source Satellite Data. Remote Sensing 2020, 12, 3450 .
AMA StyleFangdi Sun, Ronghua Ma, Bin He, Xiaoli Zhao, Yuchao Zeng, Siyi Zhang, Shilin Tang. Changing Patterns of Lakes on The Southern Tibetan Plateau Based on Multi-Source Satellite Data. Remote Sensing. 2020; 12 (20):3450.
Chicago/Turabian StyleFangdi Sun; Ronghua Ma; Bin He; Xiaoli Zhao; Yuchao Zeng; Siyi Zhang; Shilin Tang. 2020. "Changing Patterns of Lakes on The Southern Tibetan Plateau Based on Multi-Source Satellite Data." Remote Sensing 12, no. 20: 3450.
Landsat-8 Operational Land Imager (OLI) provides an opportunity to map chlorophyll-a (Chla) in lake waters at spatial scales not feasible with ocean color missions. Although state-of-the-art algorithms to estimate Chla in lakes from satellite-borne sensors have improved, there are no robust and reliable algorithms to generate Chla time series from OLI imageries in turbid lakes due to the absence of a red-edge band and issues with atmospheric correction. Here, a machine learning approach termed the extreme gradient boosting tree (BST) was employed to develop an algorithm for Chla estimation from OLI in turbid lakes. This model was developed and validated by linking Rayleigh-corrected reflectance to near-synchronous in situ Chla data available from eight lakes in eastern China (N = 225) and three coastal and inland waters in SeaWiFS Bio-optical Archive and Storage System (N = 97). The BST model performed well on a subset of data (N = 102, R2 = 0.79, root mean squared difference = 7.1 μg L−1, mean absolute percentage error = 24%, mean absolute error = 1.4, Bias = 0.9), and had better Chla retrievals than several band-ratio algorithms and a random forest approach. The performance of BST model was judged as appropriate only for the range of conditions in the training data. Given these limitations, spatial and temporal variations of Chla in hundreds of lakes larger than 1 km2 in eastern China for the period of 2013–2018 were mapped using the BST model. OLI-derived Chla indicated that small lakes (<50 km2) had greater Chla than the larger lakes. This research suggests that machine-learning models provide practical approaches to estimate Chla in turbid lakes via broadband instruments like OLI and that extending to other regions requires training with a representative dataset.
Zhigang Cao; Ronghua Ma; Hongtao Duan; Nima Pahlevan; John Melack; Ming Shen; Kun Xue. A machine learning approach to estimate chlorophyll-a from Landsat-8 measurements in inland lakes. Remote Sensing of Environment 2020, 248, 111974 .
AMA StyleZhigang Cao, Ronghua Ma, Hongtao Duan, Nima Pahlevan, John Melack, Ming Shen, Kun Xue. A machine learning approach to estimate chlorophyll-a from Landsat-8 measurements in inland lakes. Remote Sensing of Environment. 2020; 248 ():111974.
Chicago/Turabian StyleZhigang Cao; Ronghua Ma; Hongtao Duan; Nima Pahlevan; John Melack; Ming Shen; Kun Xue. 2020. "A machine learning approach to estimate chlorophyll-a from Landsat-8 measurements in inland lakes." Remote Sensing of Environment 248, no. : 111974.
Optical complexity and various properties of Case 2 waters make it essential to derive inherent optical properties (IOPs) through an appropriate method. Based on field measured data of Lake Chaohu between 2009 and 2018, the quasi-analytical algorithm (QAA) was modified for the particular scenario of that lake to derive absorption coefficients based on the moderate-resolution imaging spectroradiometer (MODIS) bands. By changing the reference wavelength to longer ones and building a relationship between the value of spectral power for particle backscattering coefficient (Y), suspended particulate matter (SPM), and above-surface remote-sensing reflectance (Rrs), we improved the accuracy of the retrieval of total absorption coefficients. The absorption coefficients of gelbstoff and non-algal particulates (adg) and absorption coefficients of phytoplankton (aph) in Lake Chaohu were also derived by changing important parameters according to Lake Chaohu. The derived aph tend to be bigger than measured aph in this study, while derived adg tend to be smaller than measured data. We also used the corrected MODIS surface reflectance product (MOD09/MYD09) to calculate the aph(443), aph(645), and aph(678) by the model proposed in this study. It shows that in summer and autumn, aph tended to be higher in the northwestern part of Lake Chaohu, and were relatively lower in the spring and winter, which is similar to previous studies. Overall, our study provides an algorithm that is effectively used in the case of Lake Chaohu and applicable to the data obtained by MODIS, which can be used for further study to investigate the change law of absorption coefficients in long time series by applying MODIS data.
Qiao Chu; Yuchao Zhang; Ronghua Ma; Ma Ronghua; Yuanyuan Jing. MODIS-Based Remote Estimation of Absorption Coefficients of an Inland Turbid Lake in China. Remote Sensing 2020, 12, 1940 .
AMA StyleQiao Chu, Yuchao Zhang, Ronghua Ma, Ma Ronghua, Yuanyuan Jing. MODIS-Based Remote Estimation of Absorption Coefficients of an Inland Turbid Lake in China. Remote Sensing. 2020; 12 (12):1940.
Chicago/Turabian StyleQiao Chu; Yuchao Zhang; Ronghua Ma; Ma Ronghua; Yuanyuan Jing. 2020. "MODIS-Based Remote Estimation of Absorption Coefficients of an Inland Turbid Lake in China." Remote Sensing 12, no. 12: 1940.
Pen aquaculture is the main form of aquaculture in some shallow lakes in eastern China. It is valuable to map the spatiotemporal changes of pen aquaculture in eutrophic lakes to assess its effect on water quality, thereby helping the relevant decision-making agencies to manage the water quality (WQ) of lakes. In this study, an automatic approach for extracting the pen aquaculture area was developed based on Landsat data. The approach integrates five algorithms, including grey transformation, discrete wavelet transform, fast Fourier transform, singular value decomposition and k-nearest neighbor classification. It was successfully applied in the automatic mapping of the pen aquaculture areas in Lake Yangcheng from 1990 to 2016. The overall accuracies were greater than 92%. The result indicted that the practice of pen aquaculture experienced five stages, with the general area increasing in the beginning and decreasing by the end of the last stage. Meanwhile, the changes of nine WQ parameters observed from 2000 to 2016, such as ammonia (NH3-N), pH, total nitrogen (TN), total phosphorus (TP), chlorophyll a, biochemical oxygen demand (BOD), chemiluminescence detection of permanganate index (CODMn), Secchi disk depth (SDD) and dissolved oxygen (DO), were analyzed in the lake sectors of Lake Yangcheng, and then their relationships were explored with the percentage of pen aquaculture area. The result suggested that the percentage of pen aquaculture area exhibits significantly positive correlations with NH3-N, TN, TP, chlorophyll a, BOD and CODMn, but significantly negative correlations with SDD and DO. The experimental results may offer an important implication for managing similar shallow lakes with pen aquaculture expansion and water pollution problems.
Juhua Luo; Ruiliang Pu; Ronghua Ma; Xiaolong Wang; Xijun Lai; Zhigang Mao; Li Zhang; Zhaoliang Peng; Zhe Sun. Mapping Long-Term Spatiotemporal Dynamics of Pen Aquaculture in a Shallow Lake: Less Aquaculture Coming along Better Water Quality. Remote Sensing 2020, 12, 1866 .
AMA StyleJuhua Luo, Ruiliang Pu, Ronghua Ma, Xiaolong Wang, Xijun Lai, Zhigang Mao, Li Zhang, Zhaoliang Peng, Zhe Sun. Mapping Long-Term Spatiotemporal Dynamics of Pen Aquaculture in a Shallow Lake: Less Aquaculture Coming along Better Water Quality. Remote Sensing. 2020; 12 (11):1866.
Chicago/Turabian StyleJuhua Luo; Ruiliang Pu; Ronghua Ma; Xiaolong Wang; Xijun Lai; Zhigang Mao; Li Zhang; Zhaoliang Peng; Zhe Sun. 2020. "Mapping Long-Term Spatiotemporal Dynamics of Pen Aquaculture in a Shallow Lake: Less Aquaculture Coming along Better Water Quality." Remote Sensing 12, no. 11: 1866.
The concentration and composition of suspended particulate matter provide important information for evaluating water quality and understanding the variability in the underwater light field in lakes. In this study, inherent optical property (IOP)-centered algorithms were developed to estimate the concentrations of chlorophyll-a (Chla, [mg/m3]) and suspended particulate matter (SPM, [g/m3]) and the Chla/SPM ratio (an indicator of the suspended particulate composition) of 118 lakes in the middle and lower reaches of the Yangtze and Huai Rivers (MLYHR) of China using Sentinel-3A/OLCI (Ocean and Land Colour Instrument) data collected from August 2016 to July 2018. The mean Chla concentration and Chla/SPM ratio were high in summer and low in winter, while the mean SPM peaked in winter and decreased in summer. The 94 lakes in the Yangtze River basin had a higher mean Chla concentration (30.94 ± 14.84) and Chla/SPM ratio (0.97 × 10−3 ± 0.60 × 10−3), but a lower mean SPM (44.87 ± 12.61) than the 24 lakes in the Huai River basin (Chla: 27.35 ± 12.18, Chla/SPM: 0.79 × 10−3 ± 0.48 × 10−3, SPM: 47.31 ± 13.40). Regarding the mean values of each lake, Chla and Chla/SPM ratio correlated well with temperature, whereas the wind speed and precipitation had little effect on the variations of suspended particulate matter. Moreover, shipping transportation and sand dredging activities affected the spatial distribution of Chla, SPM, and Chla/SPM in several large lakes (e.g., Lake Poyang and Lake Dongting). Chla/SPM related well with other proxies that express the suspended particulate composition, and had a significant correlation with the Chla-specific absorption coefficient of phytoplankton at 443 nm (aph⁎(443)). The remotely sensed concentration and composition of suspended particulate matter can provide a comprehensive reference for water quality monitoring and expand our knowledge of the trophic status of the lakes.
Kun Xue; Ronghua Ma; Ming Shen; Yao Li; Hongtao Duan; Zhigang Cao; Dian Wang; Junfeng Xiong. Variations of suspended particulate concentration and composition in Chinese lakes observed from Sentinel-3A OLCI images. Science of The Total Environment 2020, 721, 137774 .
AMA StyleKun Xue, Ronghua Ma, Ming Shen, Yao Li, Hongtao Duan, Zhigang Cao, Dian Wang, Junfeng Xiong. Variations of suspended particulate concentration and composition in Chinese lakes observed from Sentinel-3A OLCI images. Science of The Total Environment. 2020; 721 ():137774.
Chicago/Turabian StyleKun Xue; Ronghua Ma; Ming Shen; Yao Li; Hongtao Duan; Zhigang Cao; Dian Wang; Junfeng Xiong. 2020. "Variations of suspended particulate concentration and composition in Chinese lakes observed from Sentinel-3A OLCI images." Science of The Total Environment 721, no. : 137774.
The accurate estimate of surface chlorophyll a concentrations (Chla) by remote sensing presents a number of challenges where inherent and apparent optical properties have significant spatial or temporal variability. Indeed, Chla algorithms for Case 2 waters are often lake or region specific, and they are usually highly sensitive to changes in the dominant chromophoric constituents. This study develops and validates an absorption-specific approach to estimating Chla across an optically heterogeneous dataset. The approach is based on the classification of the optically dominant constituent. We tested this approach with in situ data from Taihu Lake, Poyang Lake, Chaohu Lake, Shitoukoumen Reservoir, Pearl River Estuary and Daya Bay as well as using HydroLight simulated data. The results show an improved performance when compared to most single Chla algorithms. We validated the approach with data from the Visible Infrared Imager Radiometer Suite (VIIRS). Results showed that this absorption-specific approach provided good Chla estimates over clear to very turbid waters with a wide range of optical conditions (R2 = 0.76, rRMSE = 35%, n = 230, p < 0.01).
Guangjia Jiang; Steven A. Loiselle; Dingtian Yang; Ronghua Ma; Wen Su; Changjun Gao. Remote estimation of chlorophyll a concentrations over a wide range of optical conditions based on water classification from VIIRS observations. Remote Sensing of Environment 2020, 241, 111735 .
AMA StyleGuangjia Jiang, Steven A. Loiselle, Dingtian Yang, Ronghua Ma, Wen Su, Changjun Gao. Remote estimation of chlorophyll a concentrations over a wide range of optical conditions based on water classification from VIIRS observations. Remote Sensing of Environment. 2020; 241 ():111735.
Chicago/Turabian StyleGuangjia Jiang; Steven A. Loiselle; Dingtian Yang; Ronghua Ma; Wen Su; Changjun Gao. 2020. "Remote estimation of chlorophyll a concentrations over a wide range of optical conditions based on water classification from VIIRS observations." Remote Sensing of Environment 241, no. : 111735.
The temporal resolution of satellite determines how well remote sensing products represent changes in the lake environments and influences the practical applications by end-users. Here, a resampling method was used to reproduce the suspended particulate matter (SPM) dataset in 43 large lakes (>50 km2) on the eastern China plain during 2003–2017 at different temporal resolutions using MODIS Aqua (MODISA) based on Google Earth Engine platform, then to address the impact of temporal resolution on the long-term SPM dataset. Differences between the MODISA-derived and reproduced SPM dataset at longer temporal resolution were higher in the areas with large water dynamics. The spatial and temporal distributions of the differences were driven by unfavorable observation environments during satellite overpasses such as high cloud cover, and rapid changes in water quality, such as water inundation, algae blooms, and macrophytes. Furthermore, the annual mean difference in SPM ranged from 5–10% when the temporal difference was less than 10 d, and the differences in summer and autumn were higher than that of other seasons and surpassed 20% when the temporal resolution was more than 16 d. To assure that difference were less than 10% for long-term satellite-derived SPM datasets, the minimal requirement of temporal resolution should be within 5 d for most of the inland lakes and 3 d for lakes with large changes in water quality. This research can be used to not only evaluate the reliability of historically remote sensing products but also provide a reference for planning field campaigns and applying of high spatial resolution satellite missions to monitor aquatic systems in the future.
Zhigang Cao; Ronghua Ma; Hongtao Duan; Kun Xue; Ming Shen. Effect of Satellite Temporal Resolution on Long-Term Suspended Particulate Matter in Inland Lakes. Remote Sensing 2019, 11, 2785 .
AMA StyleZhigang Cao, Ronghua Ma, Hongtao Duan, Kun Xue, Ming Shen. Effect of Satellite Temporal Resolution on Long-Term Suspended Particulate Matter in Inland Lakes. Remote Sensing. 2019; 11 (23):2785.
Chicago/Turabian StyleZhigang Cao; Ronghua Ma; Hongtao Duan; Kun Xue; Ming Shen. 2019. "Effect of Satellite Temporal Resolution on Long-Term Suspended Particulate Matter in Inland Lakes." Remote Sensing 11, no. 23: 2785.
Algal blooms in eutrophic lakes have been a global issue to environmental ecology. Although great progress on prevention and control of algae have been made in many lakes, systematic research on long-term temporal-spatial dynamics and drivers of algal blooms in a plateau Lake Dianchi is so far insufficient. Therefore, the algae pixel-growing algorithm (APA) was used to accurately identify algal bloom areas at the sub-pixel level on the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2000 to 2018. The results showed that algal blooms were observed all year round, with a reduced frequency in winter–spring and an increased frequency in summer–autumn, which lasted a long time for about 310–350 days. The outbreak areas were concentrated in 20–80 km2 and the top three largest areas were observed in 2002, 2008, and 2017, reaching 168.80 km2, 126.51 km2, and 156.34 km2, respectively. After deriving the temporal-spatial distribution of algal blooms, principal component analysis (PCA) and redundancy analysis (RDA) were applied to explore the effects of meteorological, water quality and human activities. Of the variables analyzed, mean temperature (Tmean) and wind speed (WS) were the main drivers of daily algal bloom areas and spatial distribution. The precipitation (P), pH, and water temperature (WT) had a strong positive correlation, while WS and sunshine hours (SH) had a negative correlation with monthly maximum algal bloom areas and frequency. Total nitrogen (TN) and dissolved oxygen (DO) were the main influencing factors of annual frequency, initiation, and duration of algal blooms. Also, the discharge of wastewater and the southwest and southeast monsoons may contribute to the distribution of algal blooms mainly in the north of the lake. However, different regions of the lake show substantial variations, so further zoning and quantitative joint studies of influencing factors are required to more accurately understand the true mechanisms of algae in Lake Dianchi.
Yuanyuan Jing; Yuchao Zhang; Minqi Hu; Qiao Chu; Ronghua Ma. MODIS-Satellite-Based Analysis of Long-Term Temporal-Spatial Dynamics and Drivers of Algal Blooms in a Plateau Lake Dianchi, China. Remote Sensing 2019, 11, 2582 .
AMA StyleYuanyuan Jing, Yuchao Zhang, Minqi Hu, Qiao Chu, Ronghua Ma. MODIS-Satellite-Based Analysis of Long-Term Temporal-Spatial Dynamics and Drivers of Algal Blooms in a Plateau Lake Dianchi, China. Remote Sensing. 2019; 11 (21):2582.
Chicago/Turabian StyleYuanyuan Jing; Yuchao Zhang; Minqi Hu; Qiao Chu; Ronghua Ma. 2019. "MODIS-Satellite-Based Analysis of Long-Term Temporal-Spatial Dynamics and Drivers of Algal Blooms in a Plateau Lake Dianchi, China." Remote Sensing 11, no. 21: 2582.
Eutrophication of inland freshwater bodies is a major threat to the ecosystem services. Many studies have focused on using surface or near surface phytoplankton biomass to determine trophic status or bloom conditions. However, surface phytoplankton biomass can change quickly due to the vertical migration of phytoplankton. A more appropriate indicator is column integrated biomass which considers the vertical distribution of the phytoplankton. In this study, we estimated the spatial and temporal dynamics of column integrated biomass in a shallow eutrophic lake, Lake Chaohu in China, using a biomass estimation algorithm and fourteen years of satellite data. The built algorithm was validated by in situ datasets with a significant correlation with the coefficient of determination (R2) of 0.89, mean absolute relative difference, MARD = 25.97%, the root-mean-square error, RMSE = 20.17 mg·m−2. We decomposed the temporal dynamics of the satellite-based time series into inter-annual trends, seasonal and irregular behaviors of biomass in different lake sections. We compared these individual dynamics to nutrients, meteorological and climate variables, in particular with respect to ongoing effort to manage nutrients in this complex lake and catchment. Nutrient concentrations were shown to be determinant in the inter-annual trends. Irregular variation of biomass was found to be sensitive to global climate change events (ENSO) which influence regional conditions of precipitation and temperature. By taking the vertical profile of phytoplankton into consideration, the derived temporal and spatial distribution of phytoplankton biomass, rather than surface biomass, provided new sights into lake conditions and were seen to be a good support for lake management efforts.
Jing Li; Ronghua Ma; Kun Xue; Steven Loiselle. Drivers to spatial and temporal dynamics of column integrated phytoplankton biomass in the shallow lake of Chaohu, China. Ecological Indicators 2019, 109, 105812 .
AMA StyleJing Li, Ronghua Ma, Kun Xue, Steven Loiselle. Drivers to spatial and temporal dynamics of column integrated phytoplankton biomass in the shallow lake of Chaohu, China. Ecological Indicators. 2019; 109 ():105812.
Chicago/Turabian StyleJing Li; Ronghua Ma; Kun Xue; Steven Loiselle. 2019. "Drivers to spatial and temporal dynamics of column integrated phytoplankton biomass in the shallow lake of Chaohu, China." Ecological Indicators 109, no. : 105812.
Inland lakes are essential components of hydrological and biogeochemical water cycles, as well as indispensable water resources for human beings. To derive the long-term and continuous trajectory of lake inundation area changes is increasingly significant. Since it helps to understand how they function in the global water cycle and how they are impacted by climate change and human activities. Employing optical satellite images, as an important means of lake mapping, has been widely used in the monitoring of lakes. It is well known that one of the obvious difficulties of traditional remote sensing-based mapping methods lies in the tremendous labor and computing costs for delineating the large lakes (e.g., Caspian Sea). In this study, a novel approach of reconstructing long-term and high-frequency time series of inundation areas of large lakes is proposed. The general idea of this method is to obtain the lake inundation area at any specific observation date by referring to the mapping relationship of the water occurrence frequency (WOF) of the selected shoreline segment at relatively slight terrains and lake areas based on the pre-established lookup table. The lookup table to map the links of the WOF and lake areas is derived from the Joint Research Centre (JRC)Global Surface Water (GSW) dataset accessed in Google Earth Engine (GEE). We select five large lakes worldwide to reconstruct their long time series (1984-2018) of inundation areas using this method. The time series of lake volume variation are analyzed, and the qualitative investigations of these lake changes are eventually discussed by referring to previous studies. The results based on the case of North Aral Sea show that the mean relative error between estimated area and actually mapped value is about 0.85%. The mean R2 of all the five lakes is 0.746, which indicates that the proposed method can produce the robust estimates of area time series for these large lakes. This research sheds new light on mapping large lakes at considerably deducted time and labor costs, and be effectively applicable in other large lakes in regional and global scales.
ShuangXiao Luo; Chunqiao Song; Kai Liu; Linghong Ke; Ronghua Ma. An Effective Low-Cost Remote Sensing Approach to Reconstruct the Long-Term and Dense Time Series of Area and Storage Variations for Large Lakes. Sensors 2019, 19, 4247 .
AMA StyleShuangXiao Luo, Chunqiao Song, Kai Liu, Linghong Ke, Ronghua Ma. An Effective Low-Cost Remote Sensing Approach to Reconstruct the Long-Term and Dense Time Series of Area and Storage Variations for Large Lakes. Sensors. 2019; 19 (19):4247.
Chicago/Turabian StyleShuangXiao Luo; Chunqiao Song; Kai Liu; Linghong Ke; Ronghua Ma. 2019. "An Effective Low-Cost Remote Sensing Approach to Reconstruct the Long-Term and Dense Time Series of Area and Storage Variations for Large Lakes." Sensors 19, no. 19: 4247.
Phosphorus (P) is an important substance for the growth of phytoplankton and an efficient index to assess the water quality. However, estimation of the TP concentration in waters by remote sensing must be associated with optical substances such as the chlorophyll-a (Chla) and the suspended particulate matter (SPM). Based on the good correlation between the suspended inorganic matter (SPIM) and P in Lake Hongze, we used the direct and indirect derivation methods to develop algorithms for the total phosphorus (TP) estimation with the MODIS/Aqua data. Results demonstrate that the direct derivation algorithm based on 645 nm and 1240 nm of the MODIS/Aqua performs a satisfied accuracy (R2 = 0.75, RMSE = 0.029mg/L, MRE = 39% for the training dataset, R2 = 0.68, RMSE = 0.033mg/L, MRE = 47% for the validate dataset), which is better than that of the indirect derivation algorithm. The 645 nm and 1240 nm of MODIS are the main characteristic band of the SPM, so that algorithm can effectively reflect the P variations in Lake Hongze. Additionally, the ratio of the TP to the SPM is positively correlated with the accuracy of the algorithm as well. The proportion of the SPIM in the SPM has a complex effect on the accuracy of the algorithm. When the SPIM accounts for 78%, the algorithm achieves the highest accuracy. Furthermore, the performance of this direct derivation algorithm was examined in two inland lakes in China (Lake Nanyi and Lake Chaohu), it derived the expected P distribution in Lake Nanyi whereas the algorithm failed in Lake Chaohu. Different water properties influence significantly the accuracy of this direct derivation algorithm, while the TP, Chla, and suspended particular inorganic matter (SPOM) of Lake Chaohu are much higher than those of the other two lakes, thus it is difficult to estimate the TP concentration by a simple band combination in Lake Chaohu. Although the algorithm depends on the dataset used in the development, it usually presents a good estimation for those waters where the SPIM dominated, especially when the SPIM accounts for 60% to 80% of the SPM. This research proposed a direct derivation algorithm for the TP estimation for the turbid lake and will provide a theoretical and practical reference for extending the optical remote sensing application and the TP empirical algorithm of Lake Hongze’s help for the local government management water quality.
Junfeng Xiong; Chen Lin; Ronghua Ma; Zhigang Cao. Remote Sensing Estimation of Lake Total Phosphorus Concentration Based on MODIS: A Case Study of Lake Hongze. Remote Sensing 2019, 11, 2068 .
AMA StyleJunfeng Xiong, Chen Lin, Ronghua Ma, Zhigang Cao. Remote Sensing Estimation of Lake Total Phosphorus Concentration Based on MODIS: A Case Study of Lake Hongze. Remote Sensing. 2019; 11 (17):2068.
Chicago/Turabian StyleJunfeng Xiong; Chen Lin; Ronghua Ma; Zhigang Cao. 2019. "Remote Sensing Estimation of Lake Total Phosphorus Concentration Based on MODIS: A Case Study of Lake Hongze." Remote Sensing 11, no. 17: 2068.
High spatial resolution satellite sensors provide opportunities to observe spatial variations of biogeochemical properties of small- and medium-sized inland water bodies. However, high spatial resolution sensors are usually equipped with wider spectral bandwidth (>50 nm) that diminishes the features of the spectrum. Therefore, the effects of the border bandwidth issue need to be evaluated prior to application in aquatic environments. Based on the in situ optical data [remote sensing reflectance (Rrs) and absorption coefficients] and the radiative simulations of hyperspectral remote sensing reflectance and using band specifics of common sensors (e.g., OLCI, VIIRS, MSI, OLI, ETM+ and WFV) as examples, the effects of bandwidth on optical properties of inland waters were analyzed. The results showed the followings. (1) The difference between values at center-wavelength and band-averaged values increased with increasing bandwidth for Rrs and the absorption coefficients. The difference was wavelength-dependent. The difference of Rrs at the visible band was within 0.25% but greater than 0.5% for the spectral bands near 710 nm and 665 nm. (2) The accuracy of the total absorption coefficient derived from QAA-750E, spectral match technique (SMT) and deep neural network (DNN) decreased with increasing bandwidth. The QAA-750E was more sensitive to bandwidth than SMT and DNN. Otherwise, the empirical algorithms for estimating chlorophyll-a (Chla) concentrations were significantly affected by bandwidth. The performance of algorithms for estimating cyanobacterial phycocyanin (PC) and suspended particulate matter (SPM) concentrations changed slightly with a wider bandwidth. Finally, the maximum bandwidth requirement for optical remote sensing in inland waters was proposed. For bandwidth options, it should be within 20 nm for 700–710 nm, ∼30 nm maximum for ∼560 nm and ∼665 nm, 60 nm for ∼620 nm, and ∼80 nm for ∼443 nm and ∼490 nm, respectively. The difference between the Rrs of narrow bands (10–20 nm) and the Rrs of the bands with the recommended bandwidth was within 0.25%. The corresponding bandwidth from MSI and OLI sensors meet this criterion for Chla and SPM. However, the lack of spectral coverage near 700–710 nm may present a challenge to retrieve Chla concentration from OLI images. This study provided helpful theoretical and practical references for the retrieval of inland water parameters by high spatial resolution satellite sensors and its prospective development.
Zhigang Cao; Ronghua Ma; Hongtao Duan; Kun Xue. Effects of broad bandwidth on the remote sensing of inland waters: Implications for high spatial resolution satellite data applications. ISPRS Journal of Photogrammetry and Remote Sensing 2019, 153, 110 -122.
AMA StyleZhigang Cao, Ronghua Ma, Hongtao Duan, Kun Xue. Effects of broad bandwidth on the remote sensing of inland waters: Implications for high spatial resolution satellite data applications. ISPRS Journal of Photogrammetry and Remote Sensing. 2019; 153 ():110-122.
Chicago/Turabian StyleZhigang Cao; Ronghua Ma; Hongtao Duan; Kun Xue. 2019. "Effects of broad bandwidth on the remote sensing of inland waters: Implications for high spatial resolution satellite data applications." ISPRS Journal of Photogrammetry and Remote Sensing 153, no. : 110-122.
Current water color remote sensing algorithms typically do not consider the vertical variations of phytoplankton. Ecolight with a radiative transfer program was used to simulate the underwater light field of vertical inhomogeneous waters based on the optical properties of a eutrophic lake (i.e., Lake Chaohu, China). Results showed that the vertical distribution of chlorophyll-a (Chla(z)) can considerably affect spectrum shape and magnitude of apparent optical properties (AOPs), including subsurface remote sensing reflectance in water (rrs(λ, z)) and the diffuse attenuation coefficient (Kx(λ, z)). The vertical variations of Chla(z) changed the spectrum shapes of rrs(λ, z) at the green and red wavelengths with a maximum value at approximately 590 nm, and changed the Kx(λ, z) from blue to red wavelength range with no obvious spectral variation. The difference between rrs(λ, z) at depth z m and its asymptotic value (Δrrs(λ, z)) could reach to ~78% in highly stratified waters. Diffuse attenuation coefficient of downwelling plane irradiance (Kd(λ, z)) had larger vertical variations, especially near water surface, in highly stratified waters. Three weighting average functions performed well in less stratified waters, and the weighting average function proposed by Zaneveld et al., (2005) performed best in highly stratified waters. The total contribution of the first three layers to rrs(λ, 0−) was approximately 90%, but the contribution of each layer in the water column to rrs(λ, 0−) varied with wavelength, vertical distribution of Chla(z) profiles, concentration of suspended particulate inorganic matter (SPIM), and colored dissolved organic matter (CDOM). A simple stratified remote sensing reflectance model considering the vertical distribution of phytoplankton was built based on the contribution of each layer to rrs(λ, 0−).
Kun Xue; Ronghua Ma. Evaluation of Weighting Average Functions as a Simplification of the Radiative Transfer Simulation in Vertically Inhomogeneous Eutrophic Waters. Applied Sciences 2019, 9, 1635 .
AMA StyleKun Xue, Ronghua Ma. Evaluation of Weighting Average Functions as a Simplification of the Radiative Transfer Simulation in Vertically Inhomogeneous Eutrophic Waters. Applied Sciences. 2019; 9 (8):1635.
Chicago/Turabian StyleKun Xue; Ronghua Ma. 2019. "Evaluation of Weighting Average Functions as a Simplification of the Radiative Transfer Simulation in Vertically Inhomogeneous Eutrophic Waters." Applied Sciences 9, no. 8: 1635.
Inherent optical properties (IOPs) play an important role in underwater light field, and are difficult to estimate accurately using satellite data in optically complex waters. To study water quality in appropriate temporal and spatial scales, it is necessary to develop methods to obtain IOPs form space-based observation with quantified uncertainties. Field-measured IOP data (N = 405) were collected from 17 surveys between 2011 and 2017 in the three major largest freshwater lakes of China (Lake Chaohu, Lake Taihu, and Lake Hongze) in the lower reaches of the Yangtze River and Huai River (LYHR). Here we provide a case-study on how to use in-situ observation of IOPs to devise an improved algorithm for retrieval of IOPs. We then apply this algorithm to observation with Sentinel-3A OLCI (Ocean and Land Colour Instrument, corrected with our improved AC scheme), and use in-situ data to show that the algorithm performs better than the standard OLCI IOP product. We use the satellite derived products to study the spatial and seasonal distributions of IOPs and concentrations of optically active constituents in these three lakes, including chlorophyll-a (Chla) and suspended particulate matter (SPM), using all cloud-free OLCI images (115 scenes) over the lakes in the LYHR basin in 2017. Our study provides a strategy for using local and remote observations to obtain important water quality parameters necessary to manage resources such as reservoirs, lakes and coastal waters.
Kun Xue; Ronghua Ma; Hongtao Duan; Ming Shen; Emmanuel Boss; Zhigang Cao. Inversion of inherent optical properties in optically complex waters using sentinel-3A/OLCI images: A case study using China's three largest freshwater lakes. Remote Sensing of Environment 2019, 225, 328 -346.
AMA StyleKun Xue, Ronghua Ma, Hongtao Duan, Ming Shen, Emmanuel Boss, Zhigang Cao. Inversion of inherent optical properties in optically complex waters using sentinel-3A/OLCI images: A case study using China's three largest freshwater lakes. Remote Sensing of Environment. 2019; 225 ():328-346.
Chicago/Turabian StyleKun Xue; Ronghua Ma; Hongtao Duan; Ming Shen; Emmanuel Boss; Zhigang Cao. 2019. "Inversion of inherent optical properties in optically complex waters using sentinel-3A/OLCI images: A case study using China's three largest freshwater lakes." Remote Sensing of Environment 225, no. : 328-346.
An absorption-based approach was used to determine surface particulate organic carbon (POC) concentrations in both inland and coastal waters. The improved performance of this approach was based on the specification of local POC absorption characteristics based on dominant POC sources; phytoplankton or detritus based. This specification was made using a new POC-Index (PI), developed and tested across a range of POC (300–10,000 mg/m3) conditions in temporally and spatially heterogeneous inland and coastal waterbodies. The POC model was based on remote sensing reflectance (Rrs, sr−1) in four wavebands: Rrs(751), Rrs(488) and Rrs(R/G), where R is the red band [Rrs(672)] for detritus dominated waters and G is the green band [Rrs(555)] in the phytoplankton dominated waters. The model provided a high R2 (0.74) and relatively low rRMSE (42.0%, N = 136, p < 0.01). Validation with independent datasets from Chaohu Lake and the Yangtze River Estuary produced a larger positive bias (R2 = 0.59, rRMSE = 83%, δ = 634 mg/m3, S = 0.63, I = 1439 mg/m3); nevertheless, the bias was reduced when tuned with local data (R2 = 0.80, rRMSE = 45%, δ = 72 mg/m3, S = 0.81, I = 327 mg/m3). Additionally, HydroLight simulations presented an independent correlation between PI and CDOM conditions and reasonable POC estimates from the new approach developed in this study. The approach was tested using data from Visible Infrared Imaging Radiometer Suite (VIIRS) in a range of optically complex conditions to quantify carbon dynamics. We indicate the advantages and challenges of using this approach in ecosystems where multiple organic carbon sources are present.
Guangjia Jiang; Steven A. Loiselle; Dingtian Yang; Changjun Gao; Ronghua Ma; Wen Su; Hongtao Duan. An absorption-specific approach to examining dynamics of particulate organic carbon from VIIRS observations in inland and coastal waters. Remote Sensing of Environment 2019, 224, 29 -43.
AMA StyleGuangjia Jiang, Steven A. Loiselle, Dingtian Yang, Changjun Gao, Ronghua Ma, Wen Su, Hongtao Duan. An absorption-specific approach to examining dynamics of particulate organic carbon from VIIRS observations in inland and coastal waters. Remote Sensing of Environment. 2019; 224 ():29-43.
Chicago/Turabian StyleGuangjia Jiang; Steven A. Loiselle; Dingtian Yang; Changjun Gao; Ronghua Ma; Wen Su; Hongtao Duan. 2019. "An absorption-specific approach to examining dynamics of particulate organic carbon from VIIRS observations in inland and coastal waters." Remote Sensing of Environment 224, no. : 29-43.
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.
Kun Xue; Ronghua Ma; Dian Wang; Ming Shen. Optical Classification of the Remote Sensing Reflectance and Its Application in Deriving the Specific Phytoplankton Absorption in Optically Complex Lakes. Remote Sensing 2019, 11, 184 .
AMA StyleKun Xue, Ronghua Ma, Dian Wang, Ming Shen. Optical Classification of the Remote Sensing Reflectance and Its Application in Deriving the Specific Phytoplankton Absorption in Optically Complex Lakes. Remote Sensing. 2019; 11 (2):184.
Chicago/Turabian StyleKun Xue; Ronghua Ma; Dian Wang; Ming Shen. 2019. "Optical Classification of the Remote Sensing Reflectance and Its Application in Deriving the Specific Phytoplankton Absorption in Optically Complex Lakes." Remote Sensing 11, no. 2: 184.
The OLI (Operational Land Imager) sensor on Landsat-8 has the potential to meet the requirements of remote sensing of water color. However, the optical properties of inland waters are more complex than those of oceanic waters, and inland atmospheric correction presents additional challenges. We examined the performance of atmospheric correction (AC) methods for remote sensing over three highly turbid or hypereutrophic inland waters in China: Lake Hongze, Lake Chaohu, and Lake Taihu. Four water-AC algorithms (SWIR (Short Wave Infrared), EXP (Exponential Extrapolation), DSF (Dark Spectrum Fitting), and MUMM (Management Unit Mathematics Models)) and three land-AC algorithms (FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes), 6SV (a version of Second Simulation of the Satellite Signal in the Solar Spectrum), and QUAC (Quick Atmospheric Correction)) were assessed using Landsat-8 OLI data and concurrent in situ data. The results showed that the EXP (and DSF) together with 6SV algorithms provided the best estimates of the remote sensing reflectance (Rrs) and band ratios in water-AC algorithms and land-AC algorithms, respectively. AC algorithms showed a discriminating accuracy for different water types (turbid waters, in-water algae waters, and floating bloom waters). For turbid waters, EXP gave the best Rrs in visible bands. For the in-water algae and floating bloom waters, however, all water-algorithms failed due to an inappropriate aerosol model and non-zero reflectance at 1609 nm. The results of the study show the improvements that can be achieved considering SWIR bands and using band ratios, and the need for further development of AC algorithms for complex aquatic and atmospheric conditions, typical of inland waters.
Dian Wang; Ronghua Ma; Kun Xue; Steven Arthur Loiselle. The Assessment of Landsat-8 OLI Atmospheric Correction Algorithms for Inland Waters. Remote Sensing 2019, 11, 169 .
AMA StyleDian Wang, Ronghua Ma, Kun Xue, Steven Arthur Loiselle. The Assessment of Landsat-8 OLI Atmospheric Correction Algorithms for Inland Waters. Remote Sensing. 2019; 11 (2):169.
Chicago/Turabian StyleDian Wang; Ronghua Ma; Kun Xue; Steven Arthur Loiselle. 2019. "The Assessment of Landsat-8 OLI Atmospheric Correction Algorithms for Inland Waters." Remote Sensing 11, no. 2: 169.
The number of reservoirs is rapidly increasing owing to the growth of the world’s economy and related energy and water needs. Yet, for the vast majority of reservoirs around the world, their locations and related information, especially for newly dammed reservoirs, are not readily available due to financial, political, or legal considerations. This study proposes an automated method of identifying newly dammed reservoirs from time series of MODIS-derived NDWI (normalized difference water index) images. Its main idea lies in the detection of abrupt changes in the NDWI time series that are associated with land-to-water conversion due to the reservoir impoundment. The proposed method is tested in the upper reach of the Yellow River that is severely regulated by constructed reservoirs. Our results show that five newly dammed reservoirs were identified in the test area during 2000–2018. Validated against high-resolution Google Earth imagery, our method is effective to determine both locations of the emerging medium-size reservoirs and the timing of their initial water impoundments. Such information then allows for a refined calculation of the reservoir inundation extents and storage capacities through the combination of higher-resolution Landsat imagery and SRTM DEM. The comparison of our estimated reservoir areas and capacities against documented information further indicates that the integration of multi-mission remote sensing data may provide useful information for understanding reservoir operations and impacts on river discharges. Our method also demonstrates a potential for regional or global inventory of emerging reservoirs, which is crucial to assessing human impacts on river systems and the global water cycle.
Wensong Zhang; Hang Pan; Chunqiao Song; Linghong Ke; Jida Wang; Ronghua Ma; Xinyuan Deng; Kai Liu; Jingying Zhu; Qianhan Wu. Identifying Emerging Reservoirs along Regulated Rivers Using Multi-Source Remote Sensing Observations. Remote Sensing 2018, 11, 25 .
AMA StyleWensong Zhang, Hang Pan, Chunqiao Song, Linghong Ke, Jida Wang, Ronghua Ma, Xinyuan Deng, Kai Liu, Jingying Zhu, Qianhan Wu. Identifying Emerging Reservoirs along Regulated Rivers Using Multi-Source Remote Sensing Observations. Remote Sensing. 2018; 11 (1):25.
Chicago/Turabian StyleWensong Zhang; Hang Pan; Chunqiao Song; Linghong Ke; Jida Wang; Ronghua Ma; Xinyuan Deng; Kai Liu; Jingying Zhu; Qianhan Wu. 2018. "Identifying Emerging Reservoirs along Regulated Rivers Using Multi-Source Remote Sensing Observations." Remote Sensing 11, no. 1: 25.