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Since 2007, the Yellow Sea green tide has broken out every summer, causing great harm to the environment and society. Although satellite remote sensing (RS) has been used in biomass research, there are several shortcomings, such as mixed pixels, atmospheric interference, and difficult field validation. The biomass of green tide has been lacking a high-precision estimation method. In this study, high-resolution unmanned aerial vehicle (UAV) RS was used to quantitatively map the biomass of green tides. By utilizing experimental data from previous studies, a robust relationship was established to link biomass to the red-green-blue floating algae index (RGB-FAI). Then, the lab-based model for green tide biomass from visible images taken by the UAV camera was developed and validated by field measurements. Results show that the accurate and cost-effective method is able to estimate the green tide biomass and its changes in given local waters of the near and far seas. The study provided an effective complement to the traditional satellite RS, as well as high-precision quantitative techniques for decision-making in disaster management. [ABSTRACT FROM AUTHOR]

The chlorophyll fluorescence parameter Fv/Fm (maximum photosynthetic efficiency of optical system II) is an intrinsic index for exploring plant photosynthesis. Hyperspectral remote sensing technology can be used for rapid nondestructive detection of chlorophyll fluorescence parameters. Existing studies show that there is a good correlation between the vegetation index and Fv/Fm. However, due to the limited hyperspectral information reflected by the vegetation index, the established model often cannot reach the ideal accuracy. Therefore, this study took rice as the research object and explored the internal relationship between chlorophyll fluorescence parameters and spectral reflectance by setting different fertilization treatments. Spectral sensitive information was extracted by vegetation index and continuous wavelet transform (CWT) to explore a more suitable method for Fv/Fm hyperspectral estimation at the rice leaf scale. Then a monitoring model of Fv/Fm in rice leaves was established by the back propagation neural network (BPNN) algorithm. The results showed that: (1) the accuracy of univariate models constructed by Fv/Fm inversion based on 10 commonly used vegetation indices constructed by traditional methods was low; (2) The correlation between leaf hyperspectral reflectance and Fv/Fm could be effectively improved by using CWT, and the accuracy of the univariate model constructed by using the best wavelet coefficients could reach the level of rough evaluation of Fv/Fm; (3) The effect of wavelet transform using different mother wavelet functions as the basis function was different, and bior3.3 function was the best; R2, RMSE and RPD of the BPNN model constructed by using the first 10 best wavelet coefficients decomposed by the bior3.3 was 0.823 6, 0.013 2 and 2.304 3. In conclusion, this study proves that CWT can effectively extract sensitive bands of rice leaves for Fv/Fm monitoring, providing a reference for the follow-up rapid and nondestructive monitoring of chlorophyll fluorescence. [ABSTRACT FROM AUTHOR]

Under the influence of challenges posed by both human and natural factors, tidal wetlands in the Bohai Rim have been confronting severe threats. It is imperative to comprehend the evolution, as well as the losses and gains of tidal wetlands in the Bohai Rim, for effective coastal management and planning. However, the dynamic fluctuations in the losses and gains of tidal wetlands in this region are frequently overlooked. In this study, employing image data cubes and frequency method, we systematically monitored tidal wetlands in the Bohai Rim spanning the period from 1986 to 2022. Additionally, we performed an exhaustive analysis of the evolution, losses, and gains of tidal wetlands within the provinces and municipality surrounding the Bohai Rim, as well as a detailed analysis of typical areas. This study unveiled three key findings. Firstly, tidal wetlands in Liaoning, Hebei, Tianjin, and Shandong had experienced significant declines of 42%, 66.3%, 71.08% and 60.52% from 1986 to 2022, respectively; they had contracted spatially and changed from a contiguous complete distribution to a scattered fragmented distribution. Secondly, reclamation and erosion had led to the loss of tidal wetlands, while sedimentation had led to the gain of tidal wetlands. The loss area of tidal wetlands caused by reclamation and erosion, as well as the gain area of tidal wetlands caused by sedimentation, had exhibited fluctuating changes from 1986 to 2022. Finally, the area of tidal wetlands in the Liaohe River Delta, Tianjin Port, and Yellow River Delta had decreased by 46.48%, 74.96% and 22.36% from 1986 to 2022, respectively; and tidal wetlands in these three typical areas had spatially contracted. Our findings offer a fresh perspective and a solid scientific foundation for the effective management and strategic planning of tidal wetlands in the Bohai Rim region. • Extract tidal wetlands from image data cubes based on the method of inundation frequency. • Conduct a detailed analysis of tidal wetlands' evolution, tidal wetlands' losses and gains in the. • Bohai Rim region. • Conduct a detailed analysis of tidal wetlands' evolution at three typical areas. • Declaration of competing interest. [ABSTRACT FROM AUTHOR]

The reflectance anisotropy of land surface serves as an important bridge between surface biophysical parameters and remote sensing observations. It can characterize by the linear kernel-driven bidirectional reflectance distribution function (BRDF), which is the combination of several kernel functions and kernel weights. These kernel weights can be estimated by remote sensing; however, the stability of current kernel weights products is still challenging, especially in urban areas with complex aerosol properties and heterogeneous surfaces. In this paper, we propose a method for robust estimation of kernel weights from the Moderate Resolution Imaging Spectroradiometer (MODIS) surface spectral reflectance products (MxD09GA) data based on the constrained least-squares method (CLSM) and a priori knowledge. The kernel weights data were obtained by the CLSM from 2014 to 2017 in Beijing region of China. Validations were carried out using the MxD09GA and BRDF/Albedo products (MCD43A1). The results show that the time series of kernel weights by the CLSM show small variability over different land cover types. The kernel weights estimated by the CLSM can clearly show the phenological signal and fitting ability of surface spectral reflectance is better than that of the MCD43A1 products in Beijing urban area. Experimental results demonstrate that the CLSM has the potential for the robust estimation of kernel weights in urban areas. [ABSTRACT FROM AUTHOR]

The rising of the "claiming land from tidal wetlands and sea" has gradually reduced tidal wetlands, resulting in a huge damage to the coastal ecological environment. It is of great significance to monitor tidal wetlands by remote sensing technology. However, due to the influence of tides and weather, monitoring tidal wetlands by remote sensing technology is often inaccurate. In this study, using dense time series images data cube constructed by the spatio-temporal data fusion algorithm, we monitored tidal wetlands at the estuary of the Yellow River and Laizhou Bay; and we analyzed their evolution and driving forces in detail. This study revealed several findings. Firstly, the area of tidal wetlands had shown a decreasing trend; the tidal wetland at the new estuary of the Yellow River had extended to the sea from 1976 to 2021; other tidal wetlands had shrunk year by year. Secondly, a more important finding was that sedimentation, erosion and reclamation had led to the changes of the tidal wetlands; and there were no obvious changing trends of the tidal wetlands' area caused by these three factors in each time period. Finally, we confirmed that salt field driving force, salt field and harbor driving force, aquaculture pond driving force and the erosion of natural factor driving force had reduced tidal wetlands; while the sedimentation of the natural factor driving force had made the tidal wetlands increase; and the newly added area of all driving forces had had no obvious regular changing trends. Our proposing to monitor tidal wetlands by using dense time series images data cube provides a general approach for tidal wetlands' study and our results demonstrate the need for better coastal management of the estuary of the Yellow River and Laizhou Bay. • Propose to monitor tidal wetlands by the spatio-temporal data fusion algorithm. • Use the constructed dense time series images data cube to monitoring tidal wetlands. • Conduct a detailed analysis of the evolution and driving forces of tidal wetlands. [ABSTRACT FROM AUTHOR]

Tidal flats form boundaries between marine and terrestrial environments, and reported rapid decreases in their extent require improved measures of their status. Current methods for delineating tidal flats have low accuracy because of the limited precision of available imagery, and they cannot identify zones within tidal flats. Three zones within tidal flats are ecologically distinct due to their varied inundation. These include the supratidal, intertidal, and subtidal zones. In this study, we present a more precise method for mapping tidal flats. We used Chinese HJ-1A/B satellite images with a semiautomatic extraction method to generate a sufficient number of waterline estimates taken at various tide heights to delineate the full extent of tidal flats. Then, the full set of waterline estimates is analyzed with the Digital Shoreline Analysis System (DSAS) using Jenks Natural Breaks to identify three zones within tidal flats. We demonstrated the utility of this approach by mapping tidal flats of the Bohai Rim, China. In 2014, the estimate of available tidal flats in the region was 3093 km2, among which the area of supratidal, intertidal, and subtidal zones accounted for 5.0%, 84.3%, and 10.7%, respectively. A confusion matrix for accuracy assessment revealed a 93.8% overall accuracy for the resulting tidal flat map. Our method enables tidal flats to be mapped and monitored precisely and comprehensively, providing baseline data on the extent of this disappearing ecosystem that can be used to inform coastal planning and sustainable development. [ABSTRACT FROM PUBLISHER]

Land cover information of China was extracted using the supervised classification of remote sensing data and the carbon sink and carbon emissions of each province were calculated by combining the statistical data with the method of the Intergovernmental Panel on Climate Change (IPCC) 2006 listing. With the newly built 3E model, the three indexes of ESI (ecological support index), EDI (equitable distribution index) and EEI (economic efficiency index) were calculated and their spatial pattern characteristics and regional differences over time were analyzed. The research results indicated that as the forest coverage rate increased, the carbon sink of the ecosystem in China also increased. ESI in the central and western China was tending to decrease, while ESI in the eastern coast was growing. Although the EEI gap between eastern China and western China was large, their EDI value gap was becoming shrinking as the economic growth shifted towards the central China and western China. The 3E values which were calculated with the consideration of ecology, equity and efficiency for China's carbon emissions indicated that the carbon emissions in half provinces of China were in good conditions, with benign ecosystem circulation, fairness and high economic efficiency in the recent 11 years. These results could act as references for China's low carbon economic development and also could provide guidance for the spatial pattern planning of China's carbon emissions. [ABSTRACT FROM AUTHOR]

We obtained data from remotely sensed images using a two-phase preprocessing and retrieving approach. The spatial relationships between the Normalized Difference Vegetation Index (NDVI) and heat fluxes were studied, and the capability of monitoring indices [i.e., Normalized Difference Water Index (NDWI), Temperature Vegetation Dryness Index (TVDI), and Soil Moisture Monitoring Index (SMMI)] to depict regional soil moisture and monitor regional drought was analyzed. The following conclusions were obtained. The relationships between the NDVI and heat fluxes are significantly affected by land cover; specifically, these relationships depend on the density of vegetative cover. When monitoring regional soil moisture and drought, the appropriate index (TVDI, NDWI, or SMMI) should be selected based on drought severity and other associated characteristics. [ABSTRACT FROM PUBLISHER]

Since the reform and open-door policy in 1978, China coastal zone has experienced huge changes under a large number of coastal projects. However, there are few studies on the whole China coastline change and reclamation evolution during the period. For this reason, China's coastline and coastal reclamation change information were extracted from 1980 to 2010 period, from which four remote sensing images and the Chinese coastal survey data were used. In addition, Google Earth / Google Maps online remote sensing information was used as an auxiliary. Based on these, in-depth research on specific processes and driving forces of coastline change and reclamation evolution in the past 30 years were conducted. First, Chinese coastal zone was divided into nine regions combining with policy, economic, and natural factors as well as the administrative division. Then, we analyzed coastline change from five aspects which contained coastline length change, coastline change extent, coastline change area, coastline change direction and reasons of coastline change in combination with using two indicators: coastline change degree and coastline forward degree. Correspondingly, we also analyzed reclamation evolution from three aspects: reclamation added area, land use types of reclamation and reasons of reclamation evolution. The results demonstrated that China's coastline length showed an increasing trend and a drastic change degree in the past 30 years. The change direction of China's coastline has been promoting to the ocean and the trend became more and more obvious. Situations of coastline change varied with time and region. China's coastline length increment and trend to ocean were most remarkable from year 2000 to 2010. It had the largest change area in the 1980s, while the smallest change area was found in the 1990s. Shanghai - Jiangsu and Jing - Jin - Tang had significant coastline changes while the changes of Guangxi province and Hainan province were rather mild. The minimum increase of China's coastal reclamation area was found during the period of year 1990 to 2000, while the maximum area increase was found during the period of year 2000 to 2010 and much larger than the amount of area increase in other periods. The coastal reclamation for land use type had been changed from mainly agricultural land to the pond and then to unused water surface in the past 30 years. The unused water surface was the largest increased reclamation land use type. The proportion of port was increasing, while the proportion of agricultural land gradually decreased. China's coastline change was mainly induced by human factors for construction of ports, coastal aquaculture and etc. Natural and social factors such as economic development, population increase, coast type, distribution of tidal flat et al., together determined the evaluation of coastal reclamation. This paper can serve as the scientific foundation for management and sustainable development in the coastal areas of China. [ABSTRACT FROM AUTHOR]

This paper presents a new drought assessment method by spatially and temporally integrating temperature vegetation dryness index (TVDI) with regional water stress index (RWSI) based on a synergistic approach. With the aid of LANDSAT TM/ETM data, we were able to retrieve the land-use and land-cover (LULC), vegetation indices (VIs), and land surface temperature (LST), leading to the derivation of three types of modified TVDI, including TVDI_SAVI, TVDI_ANDVI and TVDI_MSAVI, for drought assessment in a fast growing coastal area, Northern China. The categorical classification of four drought impact levels associated with the RWSI values enables us to refine the spatiotemporal relationship between the LST and the VIs. Holistic drought impact assessment between 1987 and 2000 was carried out by linking RWSI with TVDIs group wise. Research findings indicate that: (1) LST and VIs were negatively correlated in most cases of low, medium, and high vegetation cover except the case of high density vegetation cover in 2000 due to the effect of urban heat island (UHI) effect; (2) the shortage of water in 1987 was more salient than that that in 2000 based on all indices of TVDI and RWSI; and (3) TVDIs are more suitable for monitoring mild drought, normal and wet conditions when RWSI is smaller than 0.752; but they are not suitable for monitoring moderate and severe drought conditions. [ABSTRACT FROM AUTHOR]

The seasonal cycles of sea surface Chlorophyll- a (Chl- a) concentration in the Bohai and Yellow Seas (BYS) were examined using new remotely sensed Chl- a products derived using a regional algorithm. Based on objective clustering analysis, two contrasting Chl- a seasonal patterns were delineated: 1) A nearshore pattern with a long-lasting Chl- a peak from spring to autumn, coinciding with sufficient nutrient supply and high light availability, and lower Chl- a values in winter due to the light-limitation as a consequence of low solar irradiance and high diffuse attenuation coefficient of light for the water column; 2) An offshore pattern with a strong spring bloom triggered by alleviated light limitation and abundant nutrients coinciding with high water column stability. A weak autumn peak induced by new nutrient replenishment from bottom re-suspension and horizontal transportation, a low Chl- a trough in winter mainly attributed to light-limitation, and a Chl- a trough in summer due to nutrient scarcity were observed. The linkages between the province-specific Chl- a seasonal patterns and the seasonal cycles of the corresponding environmental variables as well as other potential influencing factors are comprehensively delineated and discussed. Image 1 • Seasonal cycles of sea surface chlorophyll- a in the Bohai and Yellow Seas were analyzed using new satellite data. • The seasonal patterns of chlorophyll- a show contrasting patterns in the offshore and offshore waters. • A unimodal pattern present in the nearshore province and a bimodal presents in the offshore province. • The principal environmental drivers of the chlorophyll- a seasonal patterns were delineated based on various variables. [ABSTRACT FROM AUTHOR]

Accurate estimation of the biomass of raft-attached green algae is important for predicting the scale of green-tides in the Yellow Sea, China. In this study, two different biomass estimation methods are proposed: green algae attached to nursery-net (GAAN) and green algae attached to rope (GAAR). The GAAN method involves the use of images obtained using an unmanned aerial vehicle (UAV), high-resolution satellite images, and data from a statistical yearbook. The GAAR method uses high-resolution satellite images and data from a field sample survey. The results showed that the biomass of GAAN and GAAR in the Subei Shoal during 2017 was 8868 tons and 2974 tons respectively. A longer-term study of the biomass of GAAN and GAAR could provide quantitative information for the earnings forecasts of Porphyra yezoensis and for green-tide prevention. Image 1 • Two methods were proposed for estimating raft-attached macroalgal biomass. • Methods synthesized data from drone, satellite, field survey and statistics. • Biomass of algae attached to nursery-nets and rope was estimated, respectively. • Results showed potential for profit forecast of laver and green-tide prevention. [ABSTRACT FROM AUTHOR]

Green tides in the Yellow Sea have occurred in large-scale blooms since 2007. Originating in the southern Yellow Sea and drifting northward continuously, these green tides have severely affected the coastal ecological environment. To analyze the influence of green tides on marine aquaculture in the Rongcheng coastal water (the northernmost sea area influenced by green tide), we used the Moderate Resolution Imaging Spectrometer (MODIS), GaoFen-1 (GF-1) satellite imagery and the sea surface wind (SSW) data. We also used field investigation to analyze the drift trajectory, drift speed, dissipation speed and distribution density of green tides. The results show that the main body of a green tide will drift northeast and continue in this direction after crossing the Rongcheng Chengshanjiao coastal water. Between 2013 and 2018, the drift speeds of green tides to the north of this area were within 1–5 km/d, the drift speed in the east-west direction was 0.3–4 km/d, and the interannual difference was not significant. The dissipation speed of the green tide in the Rongcheng Sea is generally within the range of 1–5 km2/d and shows little interannual difference. The distribution density in the southern area of Rongcheng is the highest, ranging from 3% to 7%. The area with the highest frequency of influence is also the area with the greatest distribution density of green tides, and disasters are most severe here. A reasonable collection area is proposed, based on the above analysis. This research provides the basis for understanding the characteristics of green tides in the dissipation phase, and the prevention and control methods of green tide disasters in the Rongcheng coastal water. [ABSTRACT FROM AUTHOR]

The trends of sea surface chlorophyll-a (Chl-a) concentrations in the Bohai and Yellow Seas of China (BYS) were analysed based on the satellite-derived Chl-a dataset from August 2002 to December 2018. The result of linear trend analysis based on the seasonal Mann-Kendall test indicates a significant positive Chl-a trend during this period, with an average trend of ~1.15% year−1 (Slope: ~0.011 mg year −1). However, the linear trends of Chl-a varied seasonally, with strong and significant increases in spring and summer (about 2% year−1), and weak and non-significant increases in winter (lower than 1% year−1). The results of the ensemble empirical mode decomposition (EEMD) analysis revealed highly nonlinear and time-varying trends of Chl-a in the BYS, with gradually increased Chl-a during 2002–2011 and decreased Chl-a from 2012 to 2018. The instantaneous rate of Chl-a change was continuously reduced from 2002 to 2018, from a positive value of ~2.0% year−1 around the beginning year (2002) to a negative value of approximately −2.0% year−1 around the recent year (2018). The temporal evolution of the Chl-a trend was well in accordance with the changes in nutrient enrichment, suggesting that the status of eutrophication might be the primary driver of the long-term trends in Chl-a. The increase (decrease) in nutrient levels could alleviate (aggravate) the nutrient limitation for phytoplankton growth in spring and summer, thus regulating the changes in Chl-a. In contrast, the Chl-a trend seems to be unrelated to the trend of light intensity in this area. This is the first study aimed to discern and compare the linear and evolutionary nonlinear Chl-a trends in the BYS and provides a baseline against which future changes can be monitored. [Display omitted] • Linear and nonlinear trends of chlorophyll-a in the Bohai and Yellow Seas was compared during 2002–2018. • An overall significant positive trends in chlorophyll-a was obtained. • Non-linear trend revealed that chlorophyll-a increased before 2011 and decreased after. • The trend of chlorophyll-a was mainly driven by changes of nutrient enrichment, while light seems not a significant factor. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAV) equipped with high-resolution camera have been increasingly applied in environment monitoring as an important complement to traditional satellite remote sensing. An accurate extraction of marine green-tide regions still faces many technological challenges, such as the absence of centimeter-level orthophoto maps and a dedicated green-tide index based on red-green-blue (RGB) bands. In this study, a new green-tide index, namely, the red-green-blue floating algae index (RGB-FAI) using RGB images captured by ship-borne UAV, is developed for green-tide detection in the Yellow Sea, China. Specifically, RGB-FAI is defined to measure the green-reflectance height by using the red and blue bands as the baselines. Our results show that the RGB-FAI performs well in the detection of green-tide and the accuracy is satisfactory (kappa = 0.95). It is worthy to note that RGB-FAI has the highest extraction accuracy among these competing indices for green-tide in the declining phase under a hazy atmospheric condition. In addition, by combining the bi-temporal UAV images with RGB-FAI, the drift velocity of green-tide has also been estimated as 0.26 m/s in a 17.1° east by north during aerial photography. In conclusion, the proposed RGB-FAI is effective for green-tide detection and has more potential usage in marine environment monitoring. Image 1 • A novel index to detect green-tide was proposed for UAV RGB images. • First time used a ship-borne UAV to map green-tide. • The extraction method worked well, especially for declining green-tides. • The method helped estimate drift velocity and biomass of green-tide. [ABSTRACT FROM AUTHOR]