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24 pages, 5611 KiB

Open AccessArticle

Simulation and Assessment of the Capabilities of Orbita Hyperspectral (OHS) Imagery for Remotely Monitoring Chlorophyll-a in Eutrophic Plateau Lakes

by Runfei Zhang, Zhubin Zheng, Ge Liu, Chenggong Du, Chao Du, Shaohua Lei, Yifan Xu, Jie Xu, Meng Mu, Shun Bi and Jianzhong Li

Remote Sens. 2021, 13(14), 2821; https://doi.org/10.3390/rs13142821 - 18 Jul 2021

Cited by 15 | Viewed by 2999

Abstract

The chlorophyll-a (Chl-a) concentration of eutrophic lakes fluctuates significantly due to the disturbance of wind and anthropogenic activities on the water body. Consequently, estimation of the Chl-a concentration has become an immense challenge. Due to urgent demand and rapid development in high-resolution earth [...] Read more.

The chlorophyll-a (Chl-a) concentration of eutrophic lakes fluctuates significantly due to the disturbance of wind and anthropogenic activities on the water body. Consequently, estimation of the Chl-a concentration has become an immense challenge. Due to urgent demand and rapid development in high-resolution earth observation systems, it has become crucial to assess hyperspectral satellite imagery capabilities on inland water monitoring. The Orbita hyperspectral (OHS) satellite is the latest hyperspectral sensor with both high spectral and spatial resolution (2.5 nm and 10 m, respectively), which could provide great potential for remotely estimating the concentration of Chl-a for inland waters. However, there are still some deficiencies that are mainly manifested in the Chl-a concentration remote sensing retrieval model assessment and accuracy validation, as well as signal-to-noise ratio (SNR) estimation of OHS imagery for inland waters. Therefore, the radiometric performance of OHS imagery for water quality monitoring is evaluated in this study by comparing different atmospheric correction models and the SNR with several remote sensing images. Several crucial findings can be drawn: (1) the three-band model ((1/B15-1/B17)B19) developed by OHS imagery is most suitable for estimating the Chl-a concentration in Dianchi Lake, with the root-mean-square error (RMSE) and the mean absolute percentage error (MAPE) of 15.55 µg/L and 16.31%, respectively; (2) the applicability of the FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes) atmospheric correction model for OHS imagery in a eutrophic plateau lake (Dianchi Lake) was better than the 6S (Second Simulation of Satellite Signal in the Solar Spectrum) model, and QUAC (Quick Atmospheric Correction) model, as well as the dark pixel method; (3) the SNR of the OHS imagery was similar to that of Hyperion imagery and was significantly higher than SNR of the HSI imagery; (4) the spatial resolution showed slight influence on the SNR of the OHS imagery. The results show that OHS imagery could be applied to remote sensing retrieval of Chl-a in eutrophic plateau lakes and presents a new tool for dynamic hyperspectral monitoring of water quality. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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19 pages, 7638 KiB

Open AccessArticle

Satellite-Observed Multi-Scale Variability of Sea Surface Chlorophyll-a Concentration along the South Coast of the Sumatra-Java Islands

by Tengfei Xu, Zexun Wei, Shujiang Li, Raden Dwi Susanto, Nyoman Radiarta, Chao Yuan, Agus Setiawan, Anastasia Kuswardani, Teguh Agustiadi and Mukti Trenggono

Remote Sens. 2021, 13(14), 2817; https://doi.org/10.3390/rs13142817 - 17 Jul 2021

Cited by 19 | Viewed by 7528

Abstract

The southern coast of Java is known as one of the most productive fishing grounds for tuna, feeding by nutrient-rich water along the coast caused by the subsurface water upwelling. This primary productivity can be evidenced by the high sea surface chlorophyll-a concentration [...] Read more.

The southern coast of Java is known as one of the most productive fishing grounds for tuna, feeding by nutrient-rich water along the coast caused by the subsurface water upwelling. This primary productivity can be evidenced by the high sea surface chlorophyll-a concentration (SSC). Based on satellite remote sensing products, we investigate the multi-scale variability in SSC along the Sumatra-Java coast. The results show that seasonal variability of SSCs is primarily due to monsoon-driven upwelling and rainfall in the Indian Ocean and Indonesian seas sides of the Sumatra and Java Islands, respectively. Local Ekman pumping plays a secondary role, while rainfall input to the ocean has little effect. Coastally trapped Kelvin waves and mesoscale eddies are responsible for the intraseasonal SSC anomalies in regions along the south coast of Java and off the Sunda and Lombok Straits, respectively. The interannual variability in SSC is caused by the anomalous upwelling related to the Indian Ocean Dipole. There was a weak increasing trend of ~0.1–0.2 mg/m³ per decade, above the global averaged trend, which may be related to enhanced local Ekman pumping. These analyses provide an overall description of SSC variations based on satellite observations; however, further investigations based on in situ observations are needed to achieve better quantification. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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20 pages, 14653 KiB

Open AccessArticle

Continuous Sensing of Water Temperature in a Reservoir with Grid Inversion Method Based on Acoustic Tomography System

by Haocai Huang, Shijie Xu, Xinyi Xie, Yong Guo, Luwen Meng and Guangming Li

Remote Sens. 2021, 13(13), 2633; https://doi.org/10.3390/rs13132633 - 5 Jul 2021

Cited by 14 | Viewed by 2997

Abstract

The continuous sensing of water parameters is of great importance to the study of dynamic processes in the ocean, coastal areas, and inland waters. Conventional fixed-point and ship-based observing systems cannot provide sufficient sampling of rapidly varying processes, especially for small-scale phenomena. Acoustic [...] Read more.

The continuous sensing of water parameters is of great importance to the study of dynamic processes in the ocean, coastal areas, and inland waters. Conventional fixed-point and ship-based observing systems cannot provide sufficient sampling of rapidly varying processes, especially for small-scale phenomena. Acoustic tomography can achieve the sensing of water parameter variations over time by continuously using sound wave propagation information. A multi-station acoustic tomography experiment was carried out in a reservoir with three sound stations for water temperature observation. Specifically, multi-path propagation sound waves were identified with ray tracing using high-precision topography data obtained with ship-mounted ADCP. A new grid inverse method is proposed in this paper for water temperature profiling along a vertical slice. The progression of water temperature variation in three vertical slices between acoustic stations was mapped by solving an inverse problem. The reliability and adaptability of the grid method developed in this research are verified by comparison with layer-averaged water temperature results. The grid method can be further developed for the 3D mapping of water parameters over time, especially in small-scale water areas, where sufficient multi-path propagation sound waves can be obtained. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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23 pages, 29385 KiB

Open AccessEditor’s ChoiceArticle

Leveraging River Network Topology and Regionalization to Expand SWOT-Derived River Discharge Time Series in the Mississippi River Basin

by Cassandra Nickles and Edward Beighley

Remote Sens. 2021, 13(8), 1590; https://doi.org/10.3390/rs13081590 - 20 Apr 2021

Cited by 3 | Viewed by 3039

Abstract

The upcoming Surface Water and Ocean Topography (SWOT) mission will measure rivers wider than 50–100 m using a 21-day orbit, providing river reach derived discharges that can inform applications like flood forecasting and large-scale hydrologic modelling. However, these discharges will not be uniform [...] Read more.

The upcoming Surface Water and Ocean Topography (SWOT) mission will measure rivers wider than 50–100 m using a 21-day orbit, providing river reach derived discharges that can inform applications like flood forecasting and large-scale hydrologic modelling. However, these discharges will not be uniform in time or coincident with those of neighboring reaches. It is often assumed discharge upstream and downstream of a river location are highly correlated in natural conditions and can be transferred using a scaling factor like the drainage area ratio between locations. Here, the applicability of the drainage area ratio method to integrate, in space and time, SWOT-derived discharges throughout the observable river network of the Mississippi River basin is assessed. In some cases, area ratios ranging from 0.01 to 100 can be used, but cumulative urban area and/or the number of dams/reservoirs between locations decrease the method’s applicability. Though the mean number of SWOT observations for a given reach increases by 83% and the number of peak events captured increases by 100%, expanded SWOT sampled time series distributions often underperform compared to the original SWOT sampled time series for significance tests and quantile results. Alternate expansion methods may be more viable for future work. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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20 pages, 7670 KiB

Open AccessArticle

Retrieving Photometric Properties and Soil Moisture Content of Tidal Flats Using Bidirectional Spectral Reflectance

by Chen Gao, Min Xu, Hanzeyu Xu and Wei Zhou

Remote Sens. 2021, 13(7), 1402; https://doi.org/10.3390/rs13071402 - 6 Apr 2021

Cited by 5 | Viewed by 2715

Abstract

Moisture content in tidal flats changes frequently and spatially on account of tidal fluctuations, which greatly influence the reflectance of the tidal flat surface. Precise prediction of the spatial-temporal variation of tidal flats’ moisture content is an important foundation of surface bio-geophysical information [...] Read more.

Moisture content in tidal flats changes frequently and spatially on account of tidal fluctuations, which greatly influence the reflectance of the tidal flat surface. Precise prediction of the spatial-temporal variation of tidal flats’ moisture content is an important foundation of surface bio-geophysical information research by remote sensing. In this paper, we first measured the multi-angle reflectance of soil samples obtained from tidal flats in the northeastern Dongtai, Jiangsu Province, China, in the laboratory. Then, based on the particle swarm optimization (PSO) algorithm, we retrieved the photometric characteristics of the soil surface by employing the SOILSPECT bidirectional reflectance model. Finally, the soil moisture content was retrieved by introducing the equivalent water thickness of the soil. The results showed that: (i) A significant correlation existed between the retrieved equivalent water thickness and the measured soil moisture content. The SOILSPECT model is capable of estimating soil moisture with high precision by using multi-angle reflectance. (ii) Retrieved values of single scattering albedo (ω) were consistent with the variation of soil moisture content. The roughness parameter (h) and the asymmetry factor (Θ) were consistent with the structure and particle composition of the soil surface in dry soil samples. (iii) When the soil samples were soaked with water, the roughness parameter (h) and the type of scattering on the soil surface both showed irregular changes. These results support the importance of using the measured soil particle size as one of the parameters for the retrieval of soil moisture content, which is a method that should be used cautiously, especially in tidal flats. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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16 pages, 22384 KiB

Open AccessArticle

Impacts of the Kuroshio Intrusion through the Luzon Strait on the Local Precipitation Anomaly

by Wen-Pin Fang, Ding-Rong Wu, Zhe-Wen Zheng, Ganesh Gopalakrishnan, Chung-Ru Ho, Quanan Zheng, Chen-Fen Huang, Hua Ho and Min-Chuan Weng

Remote Sens. 2021, 13(6), 1113; https://doi.org/10.3390/rs13061113 - 15 Mar 2021

Cited by 2 | Viewed by 2744

Abstract

The Kuroshio Current has its origin in the northwestern Pacific, flowing northward to the east of Taiwan and the northern part of Luzon Island. As the Kuroshio Current flows northward, it quasi-periodically intrudes (hereafter referred to as Kuroshio intrusion (KI)) into the northern [...] Read more.

The Kuroshio Current has its origin in the northwestern Pacific, flowing northward to the east of Taiwan and the northern part of Luzon Island. As the Kuroshio Current flows northward, it quasi-periodically intrudes (hereafter referred to as Kuroshio intrusion (KI)) into the northern South China Sea (SCS) basin through the Luzon Strait. Despite the complex generation mechanisms of KI, the purpose of this study is to improve our understanding of the effects of KI through the Luzon Strait on the regional atmospheric and weather variations. Long-term multiple satellite observations, including absolute dynamic topography, absolute geostrophic currents, sea surface winds by ASCAT, multi-scale ultra-high resolution sea surface temperature (MURSST) level-four analysis, and research-quality three-hourly TRMM multi-satellite precipitation analysis (TMPA), was used to systematically examine the aforementioned scientific problem. Analysis indicates that the KI is interlinked with the consequential anomalous precipitation off southwestern Taiwan. This anomalous precipitation would lead to ~560 million tons of freshwater influx during each KI event. Subsequently, independent moisture budget analysis suggests that moisture, mainly from vertical advection, is the possible source of the precipitation anomaly. Additionally, a bulk formula analysis was applied to understand how KI can trigger the precipitation anomaly through vertical advection of moisture without causing an evident change in the low-level flows. These new research findings might reconcile the divisiveness on why winds are not showing a synchronous response during the KI and consequential anomalous precipitation events. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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19 pages, 39951 KiB

Open AccessArticle

Spatiotemporal Variation of Siberian Crane Habitats and the Response to Water Level in Poyang Lake Wetland, China

by Lin Zou, Bisong Hu, Shuhua Qi, Qianqian Zhang and Pan Ning

Remote Sens. 2021, 13(1), 140; https://doi.org/10.3390/rs13010140 - 4 Jan 2021

Cited by 22 | Viewed by 6020

Abstract

The Poyang Lake wetland in China is the largest wintering destination for Siberian cranes worldwide. Understanding the spatiotemporal characteristics of crane habitats is of great importance for ecological environment governance and biodiversity protection. The shallow water, grassland, and soft mudflat regions of the [...] Read more.

The Poyang Lake wetland in China is the largest wintering destination for Siberian cranes worldwide. Understanding the spatiotemporal characteristics of crane habitats is of great importance for ecological environment governance and biodiversity protection. The shallow water, grassland, and soft mudflat regions of the Poyang Lake wetland are ideal habitats for wintering Siberian cranes. Based on Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI) remote sensing images, habitat areas were extracted and associated with various water levels taken on multiple dates. Landscape metrics were applied to describe the spatial structural characteristics of the crane habitats, and spatial statistics are used to explore the cold and hot spots of their distribution. Moreover, three indicators including sustainability, stability, and variety were applied to evaluate the vulnerability of the crane habitats under different hydrological conditions. Our findings indicate: (a) The main crane habitats exhibit a gradual decreasing degree of fragmentation in time, an obvious uncertainty of shape complexity and a relatively stable connectivity. (b) The crane habitats have a consistent spatial pattern of highly aggregated distributions associated with various water levels. (c) The hot spots of the habitats formed multiple “sheet” belts centered on the “Lake Enclosed in Autumn” regions, while the cold spots indicate a spatial pattern of axial distributions. (d) The majority of the hot spots of the habitats were distributed in sub-lakes found in the southeast part of the Poyang Lake watershed and the Nanjishan and Wucheng nature reserves, while the cold spots were mainly distributed in the main channels of the basins of Poyang Lake. (e) The sustainable habitats were mainly distributed in the “Lake Enclosed in Autumn” regions and intensively aggregated in two national nature reserves. (f) Under conditions of extremely low to average water levels (5.3–11.46 m), an increase of water level causes a decrease of the stability and variety of the crane habitats and weakens the aggregation structure. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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18 pages, 4845 KiB

Open AccessArticle

Enhanced Estimation of Significant Wave Height with Dual-Polarization Sentinel-1 SAR Imagery

by Fabian Surya Pramudya, Jiayi Pan, Adam Thomas Devlin and Hui Lin

Remote Sens. 2021, 13(1), 124; https://doi.org/10.3390/rs13010124 - 1 Jan 2021

Cited by 17 | Viewed by 3382

Abstract

Sentinel-1 synthetic aperture radar (SAR) is one of the most advanced open-access satellite systems available, benefitting from its capability for earth observation under all-weather conditions. In this study, more than 280 Sentinel-1 SAR images are used to derive significant wave heights (H [...] Read more.

Sentinel-1 synthetic aperture radar (SAR) is one of the most advanced open-access satellite systems available, benefitting from its capability for earth observation under all-weather conditions. In this study, more than 280 Sentinel-1 SAR images are used to derive significant wave heights (H_s) of the sea surface using a polarization-enhanced methodology. Two study areas are selected: one is located near Hawai’i in a deep water region, and the other is in transitional water off the U.S. west coast, where the U.S. National Oceanic and Atmospheric Administration (NOAA) buoy data are available for validations. The enhanced H_s retrieval methodology utilizes dual-polarization SAR image data with strong non-Bragg radar backscattering, resulting in a better estimate of the cut-off wavelength than from those using single-polarization SAR data. The new method to derive H_s is applied to SAR images from 2017 taken from both deep water (near Hawai’i) and coastal water locations (off the U.S. West coast). The assessments of the retrieved H_s from SAR images suggest that the dual-polarization methodology can reduce the estimated H_s RMSE by 24.6% as compared to a single-polarization approach. Long-term reliability of the SAR image-derived H_s products based on the new methodology is also consolidated by large amount of in-situ buoy observations for both the coastal and deep waters. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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14 pages, 3713 KiB

Open AccessArticle

Remote Sensing and Argo Float Observations Reveal Physical Processes Initiating a Winter-Spring Phytoplankton Bloom South of the Kuroshio Current Near Shikoku

by Tongyu Wang, Fajin Chen, Shuwen Zhang, Jiayi Pan, Adam Thomas Devlin, Hao Ning and Weiqiang Zeng

Remote Sens. 2020, 12(24), 4065; https://doi.org/10.3390/rs12244065 - 11 Dec 2020

Cited by 5 | Viewed by 2670

Abstract

BIO-Argo float (chlorophyll a (Chl-a), temperature, and salinity profiles) and remote sensing data (Chl-a, photosynthetic available radiation (PAR), and wind) located south of the Kuroshio current near Shikoku from September 2018 to May 2019 were used to study phytoplankton bloom and their mechanisms [...] Read more.

BIO-Argo float (chlorophyll a (Chl-a), temperature, and salinity profiles) and remote sensing data (Chl-a, photosynthetic available radiation (PAR), and wind) located south of the Kuroshio current near Shikoku from September 2018 to May 2019 were used to study phytoplankton bloom and their mechanisms of development in open oceans. Results show that higher (lower) Chl-a concentrations are correlated with a deeper (shallower) mixed layer (R_Pearson = 0.77, R_crit = 0.12 (alpha = 0.05, n = 263)) compared to the average of Chl-a and mixed layer depth (0.13 mg/m³ and 105 m). The average net accumulation rates (r) of phytoplankton were close to 0.08 d⁻¹. An increasing r corresponds to a gradually increasing surface Chl-a (S (Chl-a): 0–20 m average Chl-a) and integrated Chl-a inventory (I (Chl-a): integrated Chl-a from surface to euphotic depth). These phenomena indicate that the mechanism of winter-spring phytoplankton blooms is consistent with the dilution-recoupling hypotheses (DRH). During the bloom formation, winter deep mixing and eddy-wind Ekman pumping are enhanced by a strong winter monsoon. The enhancement may disturb predator–prey interactions and dilute zooplankton in deep mixed layers. Moreover, winter deep mixing and eddy-wind Ekman pumping can cause the nutrients to be transported into the euphotic layer, which can promote the growth of phytoplankton and increase grazing. During the bloom extinction, the stratification strengthens and the intensity of light increases; this increases grazing and nutrient consumption, and decreases the phytoplankton bloom significantly (S (Chl-a) and I (Chl-a) increase by 0.3 mg/m³ and 27 mg/m², respectively). The output from a biogeochemistry model shows that nutrients are consistent with the temporal distribution of S (Chl-a) and I (Chl-a). Our results suggest that physical processes (deep winter mixing and eddy-wind Ekman pumping) under the DHR framework are critical factors for winter-spring blooms in open oceans with an anticyclone eddy. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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21 pages, 18625 KiB

Open AccessArticle

Autonomous Vehicles Mapping Plitvice Lakes National Park, Croatia

by Nadir Kapetanović, Branko Kordić, Antonio Vasilijević, Đula Nađ and Nikola Mišković

Remote Sens. 2020, 12(22), 3683; https://doi.org/10.3390/rs12223683 - 10 Nov 2020

Cited by 9 | Viewed by 4161

Abstract

Plitvice Lakes National Park is the largest national park in Croatia and also the oldest from 1949. It was added to the UNESCO World Natural Heritage List in 1979, due to the unique physicochemical and biological conditions that have led to the creation [...] Read more.

Plitvice Lakes National Park is the largest national park in Croatia and also the oldest from 1949. It was added to the UNESCO World Natural Heritage List in 1979, due to the unique physicochemical and biological conditions that have led to the creation of 16 named and several smaller unnamed lakes, which are cascading one into the next. Previous scientific research proved that the increased amount of dissolved organic matter (pollution) stops the travertine processes on Plitvice Lakes. Therefore, this complex, dynamic but also fragile geological, biological and hydrological system required a comprehensive limnological survey. Thirteen of the sixteen lakes mentioned above were initially surveyed from the air by an unmanned aircraft equipped with a survey grade GNSS and a full frame high-resolution full-screen camera. From these recordings, a georeferenced, high-resolution orthophoto was generated, on which the following surveys by a multibeam sonar depended. It is important to mention that this was the first time that these lakes had ever been surveyed both with the multibeam sonar technique and with such a high-resolution camera. Due to the fact that these thirteen lakes are difficult to reach and often too shallow for a boat-mounted sonar, a special autonomous surface vehicle was developed. The lakes were surveyed by the autonomous surface vehicle mounted with a multibeam sonar to create detailed bathymetric models of the lakes. The missions were planned for the surface vehicle based on the orthophoto from the preliminary studies. A detailed description of the methodology used to survey the different lakes is given here. In addition, the resulting high-resolution bathymetric maps are presented and analysed together with an overview of average, maximum depths and number of data points. Numerous interesting depressions, which are phenomena consistent with previous studies of Plitvice Lakes, are noted at the lake beds and their causes are discussed. This study shows the huge potential of remote sensing technologies integrated into autonomous vehicles in terms of much faster surveys, several orders of magnitude more data points (compared to manual surveys of a few decades ago), as well as data accuracy, precision and georeferencing. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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17 pages, 4815 KiB

Open AccessArticle

Recent Abnormal Hydrologic Behavior of Tibetan Lakes Observed by Multi-Mission Altimeters

by Pengfei Zhan, Chunqiao Song, Jida Wang, Wenkai Li, Linghong Ke, Kai Liu and Tan Chen

Remote Sens. 2020, 12(18), 2986; https://doi.org/10.3390/rs12182986 - 14 Sep 2020

Cited by 20 | Viewed by 3806

Abstract

Inland lakes in the Tibetan Plateau (TP) with closed catchments and minimal human disturbance are an important indicator of climate change. However, the examination of changes in the spatiotemporal patterns of Tibetan lakes, especially water level variations, is limited due to inadequate access [...] Read more.

Inland lakes in the Tibetan Plateau (TP) with closed catchments and minimal human disturbance are an important indicator of climate change. However, the examination of changes in the spatiotemporal patterns of Tibetan lakes, especially water level variations, is limited due to inadequate access to measurements. This obstacle has been improved by the development of satellite altimetry observations. The more recent studies revealed that the trend of central TP to grow decreased or reversed between 2010 and 2016. However, thus far, this trend has not been investigated to determine whether this pattern would last for the following years. This study aims to combine the traditional (launched before 2010, e.g., TOPEX/POSEIDON, ERS-1, ERS-2, Jason-1/-2, and Envisat) and recently advanced (launched after 2010, e.g., SARAL and Sentinel-3) altimetry observations to understand the Tibetan lake changes further in recent years. Therefore, we acquired information on the continuous lake level changes in Tibetan lakes using the lake level sequence integration method based on multisource altimetry satellites. The results revealed that water level changes in 22 examined lakes showed abrupt rises in 2016–2018, but the onsets and magnitudes of the rises varied among the lakes. During the study period, the water levels of the lakes (except Nam Co) revealed a drastic rising tendency with a mean rate of 0.74 m/a, which was remarkably higher than the average rate of water level rise over the period 2010–2015 (approximately 0.28 m/a). Specifically, the water level of the nine lakes in the Northern TP (NTP) displayed a significant rising trend, with an average rate of 0.82 m/a. In the Central TP (CTP), the lake level changes were generally divided into two categories. The water levels for the lakes in the Western CTP rose rapidly, while, in the Eastern CTP, the lake water levels rose slowly, with an average rising rate less than 0.40 m/a. The water levels for the lakes in the Northeastern TP (NETP) and Northwestern TP (NWTP) kept a stable rising tendency. According to the results of the climate analysis, the spatial differences of the lake level rise rates were primarily caused by the spatial and temporal changes of precipitation over the TP. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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35 pages, 22490 KiB

Open AccessArticle

A Semi-Empirical Chlorophyll-a Retrieval Algorithm Considering the Effects of Sun Glint, Bottom Reflectance, and Non-Algal Particles in the Optically Shallow Water Zones of Sanya Bay Using SPOT6 Data

by Yan Yu, Shengbo Chen, Wenhan Qin, Tianqi Lu, Jian Li and Yijing Cao

Remote Sens. 2020, 12(17), 2765; https://doi.org/10.3390/rs12172765 - 26 Aug 2020

Cited by 11 | Viewed by 3997

Abstract

Chlorophyll-a (Chl-a) concentration retrieval is essential for water quality monitoring, aquaculture, and guiding coastline infrastructure construction. Compared with common ocean color satellites, land observation satellites have the advantage of a higher resolution and more data sources for retrieving the concentration of Chl-a from [...] Read more.

Chlorophyll-a (Chl-a) concentration retrieval is essential for water quality monitoring, aquaculture, and guiding coastline infrastructure construction. Compared with common ocean color satellites, land observation satellites have the advantage of a higher resolution and more data sources for retrieving the concentration of Chl-a from optically shallow waters. However, the sun glint (R_sg), bottom reflectance (R_b), and non-algal particle (NAP) derived from terrigenous matter affect the accuracy of Chl-a concentration retrieval using land observation satellite image data. In this paper, we propose a semi-empirical algorithm based on the remote sensing reflectance (R_rs) of SPOT6 to retrieve the Chl-a concentration in Sanya Bay (SYB), considering the effect of R_sg, R_b, and NAP. In this semi-empirical algorithm, the Cox–Munk anisotropic model and radiative transfer model (RTM) were used to reduce the effects of R_sg and R_b on R_rs, and the Chl-a concentration was retrieved by the Chl-a absorption coefficient at 490 nm (a_phy(490)) to remove the effect of NAP. The semi-empirical algorithm was in the form of Chl-a = 43.3[a_phy(490)]^1.454, where a_phy (490) was calculated by the total absorption coefficient and the absorption coefficients of each component by empirical algorithms. The results of the Chl-a concentration retrieval show the following: (1) SPOT6 data are available for Chl-a retrieval using this semi-empirical algorithm in oligotrophic or mesotrophic coastal waters, and the accuracy of the algorithm can be improved by removing the effects of R_sg, R_b, and NAP (R² from 0.71 to 0.93 and root mean square error (RMSE) from 0.23 to 0.11 ug/L); (2) empirical algorithms based on the blue-green band are suitable for oligotrophic or mesotrophic coastal waters, and the algorithm based on the blue-green band difference Chl-a index (DCI) has stronger anti-interference in terms of the effects of sun glint and bottom reflectance than the algorithm based on the blue-green ratio (BGr); (3) in the case of ignoring R_sg unrelated to inherent optical properties (IOPs), NAP is the biggest interference factor when >9.5 mg/L and the effect of bottom reflectance should be considered when the water depth (H) <5 m in SYB; and (4) the inherent optical properties of the waters in SYB are dominated by NAP (Chl-a = 0.2–2.6 ug/L and NAP = 2.2–30.1 mg/L), and the nutrients are concentrated by enclosed terrain and southeast current. This semi-empirical algorithm for Chl-a concentration retrieval has the potential to monitor Chl-a in oligotrophic and mesotrophic coastal waters using other land observation satellites (e.g., Landsat8 OLI, ASTER, and GaoFen2). Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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20 pages, 7045 KiB

Open AccessArticle

Open Source Riverscapes: Analyzing the Corridor of the Naryn River in Kyrgyzstan Based on Open Access Data

by Florian Betz, Magdalena Lauermann and Bernd Cyffka

Remote Sens. 2020, 12(16), 2533; https://doi.org/10.3390/rs12162533 - 6 Aug 2020

Cited by 13 | Viewed by 3603

Abstract

In fluvial geomorphology as well as in freshwater ecology, rivers are commonly seen as nested hierarchical systems functioning over a range of spatial and temporal scales. Thus, for a comprehensive assessment, information on various scales is required. Over the past decade, remote sensing-based [...] Read more.

In fluvial geomorphology as well as in freshwater ecology, rivers are commonly seen as nested hierarchical systems functioning over a range of spatial and temporal scales. Thus, for a comprehensive assessment, information on various scales is required. Over the past decade, remote sensing-based approaches have become increasingly popular in river science to increase the spatial scale of analysis. However, data-scarce areas have been widely ignored so far, even if most remaining free flowing rivers are located in such areas. In this study, we suggest an approach for river corridor mapping based on open access data only, in order to foster large-scale analysis of river systems in data-scarce areas. We take the more than 600 km long Naryn River in Kyrgyzstan as an example, and demonstrate the potential of the SRTM-1 elevation model and Landsat OLI imagery in the automated mapping of various riverscape parameters, like the riparian zone extent, distribution of riparian vegetation, active channel width and confinement, as well as stream power. For each parameter, a rigor validation is performed to evaluate the performance of the applied datasets. The results demonstrate that our approach to riverscape mapping is capable of providing sufficiently accurate results for reach-averaged parameters, and is thus well-suited to large-scale river corridor assessment in data-scarce regions. Rather than an ultimate solution, we see this remote sensing approach as part of a multi-scale analysis framework with more detailed investigation in selected study reaches. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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16 pages, 5954 KiB

Open AccessArticle

WaterNet: A Convolutional Neural Network for Chlorophyll-a Concentration Retrieval

by Muhammad Aldila Syariz, Chao-Hung Lin, Manh Van Nguyen, Lalu Muhamad Jaelani and Ariel C. Blanco

Remote Sens. 2020, 12(12), 1966; https://doi.org/10.3390/rs12121966 - 18 Jun 2020

Cited by 37 | Viewed by 6174

Abstract

The retrieval of chlorophyll-a (Chl-a) concentrations relies on empirical or analytical analyses, which generally experience difficulties from the diversity of inland waters in statistical analyses and the complexity of radiative transfer equations in analytical analyses, respectively. Previous studies proposed the utilization of artificial [...] Read more.

The retrieval of chlorophyll-a (Chl-a) concentrations relies on empirical or analytical analyses, which generally experience difficulties from the diversity of inland waters in statistical analyses and the complexity of radiative transfer equations in analytical analyses, respectively. Previous studies proposed the utilization of artificial neural networks (ANNs) to alleviate these problems. However, ANNs do not consider the problem of insufficient in situ samples during model training, and they do not fully utilize the spatial and spectral information of remote sensing images in neural networks. In this study, a two-stage training is introduced to address the problem regarding sample insufficiency. The neural network is pretrained using the samples derived from an existing Chl-a concentration model in the first stage, and the pretrained model is refined with in situ samples in the second stage. A novel convolutional neural network for Chl-a concentration retrieval called WaterNet is proposed which utilizes both spectral and spatial information of remote sensing images. In addition, an end-to-end structure that integrates feature extraction, band expansion, and Chl-a estimation into the neural network leads to an efficient and effective Chl-a concentration retrieval. In experiments, Sentinel-3 images with the same acquisition days of in situ measurements over Laguna Lake in the Philippines were used to train and evaluate WaterNet. The quantitative analyses show that the two-stage training is more likely than the one-stage training to reach the global optimum in the optimization, and WaterNet with two-stage training outperforms, in terms of estimation accuracy, related ANN-based and band-combination-based Chl-a concentration models. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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18 pages, 12736 KiB

Open AccessArticle

Phenology-Based Rice Paddy Mapping Using Multi-Source Satellite Imagery and a Fusion Algorithm Applied to the Poyang Lake Plain, Southern China

by Mingjun Ding, Qihui Guan, Lanhui Li, Huamin Zhang, Chong Liu and Le Zhang

Remote Sens. 2020, 12(6), 1022; https://doi.org/10.3390/rs12061022 - 22 Mar 2020

Cited by 42 | Viewed by 5414

Abstract

Accurate information about the spatiotemporal patterns of rice paddies is essential for the assessment of food security, management of agricultural resources, and sustainability of ecosystems. However, accurate spatial datasets of rice paddy fields and multi-cropping at fine resolution are still lacking. Landsat observation [...] Read more.

Accurate information about the spatiotemporal patterns of rice paddies is essential for the assessment of food security, management of agricultural resources, and sustainability of ecosystems. However, accurate spatial datasets of rice paddy fields and multi-cropping at fine resolution are still lacking. Landsat observation is the primary source of remote sensing data that has continuously mapped regional rice paddy fields at a 30-m spatial resolution since the 1980s. However, Landsat data used for rice paddy studies reveals some challenges, especially data quality issues (e.g., cloud cover). Here, we present an algorithm that integrates time-series Landsat and MODIS (Moderate-resolution Imaging Spectroradiometer) images with a phenology-based approach (ILMP) to map rice paddy planting fields and multi-cropping patterns. First, a fusion of MODIS and Landsat data was used to reduce the cloud contamination, which added more information to the Landsat time series data. Second, the unique biophysical features of rice paddies during the flooding and open-canopy periods (which can be captured by the dynamics of the vegetation indices) were used to identify rice paddy regions as well as those of multi-cropping. This algorithm was tested for 2015 in Nanchang County, which is located on the Poyang Lake plain in southern China. We evaluated the resultant map of the rice paddy and multi-cropping systems using ground-truth data and Google Earth images. The overall accuracy and kappa coefficient of the rice paddy planting areas were 93.66% and 0.85, respectively. The overall accuracy and kappa coefficient of the multi-cropping regions were 92.95% and 0.89, respectively. In addition, our algorithm was more capable of capturing detailed information about areas with fragmented cropland than that of the National Land Cover Dataset (NLCD) from 2015. These results demonstrated the great potential of our algorithm for mapping rice paddy fields and using the multi-cropping index in complex landscapes in southern China. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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35 pages, 11674 KiB

Open AccessArticle

Optical Water Type Guided Approach to Estimate Optical Water Quality Parameters

by Kristi Uudeberg, Age Aavaste, Kerttu-Liis Kõks, Ave Ansper, Mirjam Uusõue, Kersti Kangro, Ilmar Ansko, Martin Ligi, Kaire Toming and Anu Reinart

Remote Sens. 2020, 12(6), 931; https://doi.org/10.3390/rs12060931 - 13 Mar 2020

Cited by 30 | Viewed by 6092

Abstract

Currently, water monitoring programs are mainly based on in situ measurements; however, this approach is time-consuming, expensive, and may not reflect the status of the whole water body. The availability of Multispectral Imager (MSI) and Ocean and Land Colour Instrument (OLCI) free data [...] Read more.

Currently, water monitoring programs are mainly based on in situ measurements; however, this approach is time-consuming, expensive, and may not reflect the status of the whole water body. The availability of Multispectral Imager (MSI) and Ocean and Land Colour Instrument (OLCI) free data with high spectral, spatial, and temporal resolution has increased the potential of adding remote sensing techniques into monitoring programs, leading to improvement of the quality of monitoring water. This study introduced an optical water type guided approach for boreal regions inland and coastal waters to estimate optical water quality parameters, such as the concentration of chlorophyll-a (Chl-a) and total suspended matter (TSM), the absorption coefficient of coloured dissolved organic matter at a wavelength of 442 nm (aCDOM(442)), and the Secchi disk depth, from hyperspectral, OLCI, and MSI reflectance data. This study was based on data from 51 Estonian and Finnish lakes and from the Baltic Sea coastal area, which altogether were used in 415 in situ measurement stations and covered a wide range of optical water quality parameters (Chl-a: 0.5–215.2 mg·m⁻³; TSM: 0.6–46.0 mg·L⁻¹; aCDOM(442): 0.4–43.7 m⁻¹; and Secchi disk depth: 0.2–12.2 m). For retrieving optical water quality parameters from reflectance spectra, we tested 132 empirical algorithms. The study results describe the best algorithm for each optical water type for each spectral range and for each optical water quality parameter. The correlation was high, from 0.87 up to 0.93, between the in situ measured optical water quality parameters and the parameters predicted by the optical water type guided approach. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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22 pages, 7550 KiB

Open AccessArticle

Monitoring of Fine-Scale Warm Drain-Off Water from Nuclear Power Stations in the Daya Bay Based on Landsat 8 Data

by Mengdi Liu, Xiaobin Yin, Qing Xu, Yuxiang Chen and Bowen Wang

Remote Sens. 2020, 12(4), 627; https://doi.org/10.3390/rs12040627 - 13 Feb 2020

Cited by 11 | Viewed by 3465

Abstract

Monitoring the drain-off water from nuclear power stations by high-resolution remote sensing satellites is of great significance for ensuring the safe operation of nuclear power stations and monitoring environmental changes. In order to select the optimal algorithm for Landsat 8 Thermal Infrared Sensor [...] Read more.

Monitoring the drain-off water from nuclear power stations by high-resolution remote sensing satellites is of great significance for ensuring the safe operation of nuclear power stations and monitoring environmental changes. In order to select the optimal algorithm for Landsat 8 Thermal Infrared Sensor (TIRS) data to monitor warm drain-off water from the Daya Bay Nuclear Power Station (DNPS) and the Ling Ao Nuclear Power Station (LNPS) located on the southern coast of China, this study applies the edge detection method to remove stripes and produces estimates of four Sea Surface Temperature (SST) inversion methods, the Radiation Transfer Equation Method (RTM), the Single Channel algorithm (SC), the Mono Window algorithm (MW) and the Split Window algorithm (SW), using the buoy and Minimum Orbit Intersection Distances (MOIDS) SST data. Among the four algorithms, the SST from the SW algorithm is the most consistent with the buoy, the MODIS SST, the ERA-Interim and the Optimum Interpolation Sea Surface Temperature (OISST). Based on the SST retrieved from the SW algorithm, the tidal currents calculated by the Finite-Volume Coastal Ocean Model (FVCOM) and winds from ERA-Interim, the distribution of the warm drain-off from the two nuclear power stations is analyzed. First, warm drain-off water is mainly distributed in a fan-shaped area from the two nuclear power stations to the center of the Daya Bay. The SST of the warm drain-off is about 1–4 °C higher than the surrounding water and exceeds 6 °C at the drain-off outfall. Second, the tide determines the shape and distribution characteristics of the warm drain-off area. The warm drain-off water flows to the northeast during the flood tide. During the ebb tide, the warm drain-off water flows toward the southwest direction as the tide flows toward the bay mouth, forming a fan-shaped area. Moreover, the temperature increase intensity in the combined discharge channel during the flood tide is lower than that during the ebb tide, and the low temperature rising area during the flood tide is smaller than that during the ebb tide. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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26 pages, 7316 KiB

Open AccessArticle

Spatiotemporal Dynamics and Driving Forces of Urban Land-Use Expansion: A Case Study of the Yangtze River Economic Belt, China

by Yang Zhong, Aiwen Lin, Lijie He, Zhigao Zhou and Moxi Yuan

Remote Sens. 2020, 12(2), 287; https://doi.org/10.3390/rs12020287 - 15 Jan 2020

Cited by 71 | Viewed by 4472

Abstract

It is important to analyze the expansion of an urban area and the factors that drive its expansion. Therefore, this study is based on Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) night lighting data, using the landscape index, spatial expansion strength index, [...] Read more.

It is important to analyze the expansion of an urban area and the factors that drive its expansion. Therefore, this study is based on Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) night lighting data, using the landscape index, spatial expansion strength index, compactness index, urban land fractal index, elasticity coefficient, the standard deviation ellipse, spatial correlation analysis, and partial least squares regression to analyze the spatial and temporal evolution of urban land expansion and its driving factors in the Yangtze River Economic Belt (YREB) over a long period of time. The results show the following: Through the calculation of the eight landscape pattern indicators, we found that during the study period, the number of cities and towns and the area of urban built-up areas in the YREB are generally increasing. Furthermore, the variations in these landscape pattern indicators not only show more frequent exchanges and interactions between the cities and towns of the YREB, but also reflect significant instability and irregularity of the urbanization development in the YREB. The spatial expansion intensity indices of 1992–1999, 1999–2006, and 2006–2013 were 0.03, 0.16, and 0.34, respectively. On the whole, the urban compactness of the YREB decreased with time, and the fractal dimension increased slowly with time. Moreover, the long axis and the short axis of the standard deviation ellipse of the YREB underwent a small change during the inspection period. The spatial distribution generally showed the pattern of “southwest-north”. In terms of gravity shift, during the study period, the center of gravity moved from northeast to southwest. In addition, the Moran's I values for the four years of 1992, 1999, 2006, and 2013 were 0.451, 0.495, 0.506, and 0.424, respectively. Furthermore, by using correlation analysis, we find that the correlation coefficients between these four driving indicators and the urban expansion of the YREB were: 0.963, 0.998, 0.990 and 0.994, respectively. Through the use of partial least squares regression, we found that in 1992-2013, the four drivers of urban land expansion in the YREB were ranked as follows: gross domestic product (GDP), total fixed asset investment, urban population, total retail sales of consumer goods. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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18 pages, 6530 KiB

Open AccessTechnical Note

Spatiotemporal Distributions of Ocean Color Elements in Response to Tropical Cyclone: A Case Study of Typhoon Mangkhut (2018) Past over the Northern South China Sea

by Junyi Li, Quanan Zheng, Min Li, Qiang Li and Lingling Xie

Remote Sens. 2021, 13(4), 687; https://doi.org/10.3390/rs13040687 - 13 Feb 2021

Cited by 14 | Viewed by 2896

Abstract

The ocean color elements refer to total suspended sediment (TSS) and chlorophyll-a (Chl-a), which are important parameters for the marine ecological environment. This study aims to examine the behavior of ocean color elements in response to a tropical cyclone in the case of [...] Read more.

The ocean color elements refer to total suspended sediment (TSS) and chlorophyll-a (Chl-a), which are important parameters for the marine ecological environment. This study aims to examine the behavior of ocean color elements in response to a tropical cyclone in the case of typhoon Mangkhut (2018), which passed over the northern South China Sea (NSCS) on 16 September 2018, using satellite multi-sensor observations, Argo float profiles, and tidal gauge sea level data. The results indicate that typhoon Mangkhut (2018) resulted in TSS and Chl-a concentrations increasing, with the spatial and timing behavior different in the offshore, shelf, and basin areas. In the offshore area from the coast to isobath 50 m, the mean TSS concentration, i.e., C_TSS, reached 13.9 mg/L on 18 September 2018, two days after typhoon landfall, against about 3.5 mg/L before typhoon landfall. In the shelf area with depths from 50 m to 100 m, the mean C_TSS reached 2.5 mg/L, against about 0.8 mg/L before typhoon landfall. In the basin area with depths of 100 m and beyond, the mean C_TSS had only a little fluctuation. On the other hand, in the offshore area, the mean Chl-a concentration, i.e., C_Chl-a, was 7.3 mg/m³ on 21 September, five days after typhoon landfall, against 2.4 mg/m³ as the monthly mean value. Furthermore, TSS concentrations favorable for Chl-a bloom range from 6 to 7 mg/L in this area. In the shelf area, the mean C_Chl-a increased from 0.2 mg/m³ to 0.6 mg/m³ in two days. In the basin area, the C_Chl-a increased from 0.1 mg/m³ to 0.2 mg/m³ during typhoon passage. Concurrent dynamic condition analysis results indicate that, in the offshore area, typhoon-induced solitary continental waves may play a dominant role in determining the spatial distribution features of the TSS originating from the Pearl River runoff. The Chl-a bloom delayed rather than concurrently occurred with the terrigenous nutrient peak, which is attributed to the nonlinear relation between C_Chl-a and C_TSS. In the shelf and basin areas, typhoon-enhanced vertical mixing and upwelling may play dominant roles in determining the spatiotemporal behavior of the TSS and the Chl-a. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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10 pages, 2028 KiB

Open AccessLetter

First Experiences with the Landsat-8 Aquatic Reflectance Product: Evaluation of the Regional and Ocean Color Algorithms in a Coastal Environment

by Majid Nazeer, Muhammad Bilal, Janet Elizabeth Nichol, Weicheng Wu, Mohammad M. M. Alsahli, Muhammad Imran Shahzad and Bijoy Krishna Gayen

Remote Sens. 2020, 12(12), 1938; https://doi.org/10.3390/rs12121938 - 15 Jun 2020

Cited by 9 | Viewed by 9690

Abstract

Since the launch of the Landsat-8 (L8) Operational Land Imager (OLI) on 11 February 2013, there has been a continuous effort to produce reliable ocean color products by taking the advantages of its medium spatial resolution (30 m) and higher Signal to Noise [...] Read more.

Since the launch of the Landsat-8 (L8) Operational Land Imager (OLI) on 11 February 2013, there has been a continuous effort to produce reliable ocean color products by taking the advantages of its medium spatial resolution (30 m) and higher Signal to Noise Ratio (SNR). A Provisional Aquatic Reflectance product for the L8 OLI (L8PAR) has been recently released to the public to explore its potential for ocean color applications. This study used a six-year data record of L8 for development of a regionally tuned algorithm (RTA20) for estimating Chlorophyll-a (Chl-a) concentrations around the complex coastal environment of Hong Kong, and is the first to report the usability of the L8PAR product for coastal areas. Furthermore, this study validated three previously developed algorithms, namely RTA16, RTA17 and RTA19, and two ocean color algorithms (OC2 and OC3) modified for L8 OLI by NASA’s Ocean Color group. Results indicate that the newly released L8PAR product has a high potential for estimating the coastal water Chl-a concentrations with higher detail and higher accuracy than previously. The RTA20 algorithm developed in this study outperformed the previous algorithms (RTA16, RTA17, RTA19, OC2 and OC3), e.g., with lower values for Root Mean Square Error (RMSE; 0.92 mg/m³), bias (−0.26 mg/m³) and mean ratio (1.29). Although inferior to the RTA20, the OC2 algorithm also performed well in terms of Pearson’s correlation coefficient (r; 0.84), slope (6.87) and intercept (−8.44) while for RTA20 the values for r, slope and intercept were 0.96, 0.77 and 0.27, respectively. This preliminary evaluation reveals that the OC2 algorithm can be used as an operational algorithm for L8 Chl-a product generation for global coastal areas while RTA20 can be used as a regional algorithm for the routine monitoring of Chl-a concentrations around the coastal areas of Hong Kong or for coastal areas with similar water quality elsewhere in the world. Full article

(This article belongs to the Special Issue Remote Sensing of Coastal Waters, Land Use/Cover, Lakes, Rivers and Watersheds)

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