Algae bloom water body identification and classification method and device

Abstract

The invention provides an algae bloom water body identification and classification method and device. The algae bloom water body identification and classification method provided by the invention comprises the following steps: determining a target wavelength value reflecting algae fluorescence characteristics and a reference wavelength value not influenced by fluorescence; based on the spectrum parameters of the dinoflagellate and the diatom, determining a target parameter capable of distinguishing the dinoflagellate and the diatom and a threshold value when the target parameter distinguishes the dinoflagellate and the diatom; wherein the target parameter is the fluorescence quantum yield; the method comprises the following steps: acquiring a target remote sensing reflectivity value, a reference remote sensing reflectivity value and a seawater chlorophyll concentration from data when the data of a stationary orbit ocean water color imager is used for carrying out algae bloom water body identification and classification; calculating an algal bloom index according to the target remote sensing reflectivity value and the reference remote sensing reflectivity, and determining whether algal blooms exist or not according to the algal bloom index and the seawater chlorophyll concentration; and when determining that the algae bloom exists, determining the type of the algae bloom according to the specific value and the threshold value of the fluorescence quantum yield. According to the method provided by the invention, the algae bloom water body can be accurately identified.

Description

Technical Field

[0001] The present application relates to the field of marine environment monitoring technology, and in particular to a method and device for identifying and classifying algal bloom water bodies. Background Art

[0002] With the impact of climate change and human activities, harmful algal blooms (HABs) in the ocean occur frequently. Harmful algal blooms refer to the large-scale reproduction of certain algae in the marine environment in a short period of time to form high-density colonies. The metabolites produced by these algae will pose a threat to water quality, ecosystems and fisheries.

[0003] In the Yangtze River Estuary and the East China Sea, blooms of dinoflagellates and diatoms are common marine disasters. In order to cope with the rapidly changing water environment and monitor pollution sources in a timely manner, efficient and real-time water quality monitoring methods are needed. However, traditional water quality monitoring methods are often limited in terms of space and time. For example, traditional water quality monitoring methods usually only collect samples at certain specific locations and cannot fully reflect the changes in water quality in a large area of ​​water. Moreover, traditional water quality monitoring methods are cumbersome and require a lot of time to analyze sample data, making it impossible to respond to harmful algal blooms in a timely manner. How to accurately distinguish between dinoflagellates and diatom blooms and help coastal managers more effectively mitigate the harmful effects of algal blooms has become an urgent problem to be solved. Summary of the invention

[0004] In view of this, the present application provides a method and device for identifying and classifying algal bloom water bodies, which are used to accurately distinguish between dinoflagellate and diatom blooms, and help coastal managers effectively reduce the harmful effects of algal blooms.

[0005] Specifically, the present application is implemented through the following technical solutions:

[0006] The first aspect of the present application provides a method for identifying and classifying algal bloom water bodies, the method for identifying and classifying algal bloom water bodies is implemented based on data from a geostationary ocean color imager; the method comprises:

[0007] Determine a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence;

[0008] Based on the spectral parameters of dinoflagellates and diatoms obtained in the algae culture experiment, a target parameter capable of distinguishing dinoflagellates and diatoms for classification is determined, and a limit value of the target parameter when distinguishing dinoflagellates and diatoms is determined; wherein the target parameter is the fluorescence quantum yield;

[0009] When using the data of the geostationary ocean color imager to identify and classify algal bloom water bodies, the target remote sensing reflectance value at the target wavelength value, the reference remote sensing reflectance value at the reference wavelength value and the seawater chlorophyll concentration are obtained from the data of the geostationary ocean color imager;

[0010] Calculating an algal bloom index according to the target remote sensing reflectance value and the reference remote sensing reflectance value, and determining whether an algal bloom exists according to the algal bloom index and the seawater chlorophyll concentration;

[0011] When it is determined that an algal bloom exists, a specific value of the fluorescence quantum yield is determined based on the data of the geostationary ocean color imager, and the type of the algal bloom is determined based on the specific value and the boundary value.

[0012] A device for identifying and classifying algal bloom water bodies, the device comprising a determination module, a calculation module and an acquisition module, wherein;

[0013] The determination module is used to determine a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence;

[0014] The calculation module is used to determine the target parameter that can distinguish between dinoflagellates and diatoms based on the spectral parameters of dinoflagellates and diatoms obtained in the algae cultivation experiment, and determine the limit value of the target parameter when distinguishing between dinoflagellates and diatoms; wherein the target parameter is the fluorescence quantum yield;

[0015] The acquisition module is used to acquire the target remote sensing reflectance value at the target wavelength value, the reference remote sensing reflectance value at the reference wavelength value, and the seawater chlorophyll concentration from the data of the geostationary orbit ocean water color imager when using the data of the geostationary orbit ocean water color imager to identify and classify algal bloom water bodies;

[0016] The determination module is used to calculate the algal bloom index according to the target remote sensing reflectance value and the reference remote sensing reflectance value, and determine whether an algal bloom exists according to the algal bloom index and the seawater chlorophyll concentration;

[0017] The determination module is used to determine the specific value of the fluorescence quantum yield based on the data of the geostationary ocean color imager when determining the presence of algal bloom, and to determine the type of algal bloom based on the specific value and the boundary value.

[0018] The method and device for identifying and classifying algal bloom water bodies provided in the present application determine a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence. In this way, when using data from a geostationary ocean color imager to identify and classify algal bloom water bodies, the target remote sensing reflectance value at the target wavelength value, the reference remote sensing reflectance value at the reference wavelength value, and the seawater chlorophyll concentration are obtained from the data of the geostationary ocean color imager, and the algal bloom index is calculated based on the target remote sensing reflectance value and the reference remote sensing reflectance value. Then, based on the algal bloom index and the seawater chlorophyll concentration, it is determined whether there is an algal bloom. Since the algal bloom index is calculated based on the target remote sensing reflectance value and the reference remote sensing reflectance value, it reflects the change in the reflectance of algae in the water body and can sensitively capture the water color changes caused by algae, while the chlorophyll concentration is a direct sign of algal growth and reproduction and can provide an indication of the algal biomass in the water body. Quantitative data, the algal bloom index reflects the population characteristics of algae, pays more attention to the algae's reflection characteristics of light, and can detect the impact of algae on the color of water bodies. The chlorophyll concentration reflects the biomass of algae, which provides quantitative data on the number of algae. When the two are used together, they can improve the sensitivity to changes in algal growth, and can maintain high monitoring sensitivity and stability in different algal growth stages and different environmental conditions. Combining these two indicators to judge whether algal blooms exist can avoid misjudgments that may be caused by a single indicator, and can more accurately judge whether algal blooms occur in water bodies. Furthermore, the algal bloom index and chlorophyll concentration can be obtained through remote sensing technology, and have strong spatial resolution. Combining these two indicators can achieve efficient monitoring and classification in a wide range of waters, and can provide reliable algal growth status data at different time and spatial scales, facilitating a global assessment of water quality and ecological conditions. In addition, by obtaining the spectral parameters of dinoflagellates and diatoms in the algae cultivation experiment, the target parameter that can distinguish dinoflagellates from diatoms is determined to be the fluorescence quantum yield, and the boundary value of the fluorescence quantum yield in distinguishing dinoflagellates from diatoms is determined. In this way, when it is determined that there is an algal bloom, the specific value of the fluorescence quantum yield is determined based on the data of the geostationary ocean color imager, and the type of the algal bloom is determined according to the specific value and the boundary value. Since the fluorescence quantum yield reflects the efficiency of algae photosynthesis, the difference between dinoflagellates and diatoms in this indicator makes it an important feature for distinguishing the two. By comparing the spectral parameters, the difference in fluorescence quantum yield between the two types of algae can be accurately captured, which helps to improve the classification accuracy. Furthermore, the setting of the boundary value further clarifies the judgment standard, ensuring that when algae blooms, it is possible to accurately identify which type of algae dominates the changes in the water body. In addition, in the present application, the data obtained by the geostationary ocean color imager can achieve efficient algae monitoring over a large range with higher sensitivity and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flow chart of Example 1 of the method for identifying and classifying algal bloom water bodies provided in this application; Figure 2 A comparison diagram between data of a geostationary ocean color imager and measured data shown as an exemplary embodiment of the present application; Figure 3 Spectral curves of dinoflagellates and diatoms during algal blooms provided for this application; Figure 4 A comparison diagram of the fluorescence quantum yields of dinoflagellates and diatoms shown in an exemplary embodiment of the present application; Figure 5 This is a structural schematic diagram of Example 1 of the algal bloom water body identification and classification device provided in this application. DETAILED DESCRIPTION

[0020] Here, exemplary embodiments are described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application.

[0021] The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in this article refers to and includes any or all possible combinations of one or more associated listed items.

[0022] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0023] Specific embodiments are given below to introduce the technical solution of the present application in detail.

[0024] Figure 1 This is a flow chart of Example 1 of the algal bloom water body identification and classification method provided in this application. Please refer to Figure 1 The algal bloom water body identification and classification method provided in this embodiment is implemented based on data from a geostationary ocean color imager. The method may include:

[0025] S101, determining a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence.

[0026] Specifically, the target wavelength value that can reflect the fluorescence characteristics of algae is a specific spectral wavelength used to capture the fluorescence signal of algae. The light signal at this spectral wavelength can directly reflect the fluorescence characteristics of algae, including reflecting the algae biomass and photosynthetic activity. The reference wavelength value that is not affected by fluorescence includes a spectral wavelength range. The light signal within this spectral wavelength range is a non-algae fluorescence signal. This signal will not be affected by the fluorescence characteristics of algae and can characterize the background reflection characteristics of the water body where the algae are located.

[0027] In this step, by determining the target wavelength value that can reflect the fluorescence characteristics of algae and the reference wavelength value that is not affected by fluorescence, the accurate extraction of algae fluorescence signals and the effective elimination of non-fluorescence interference can be ensured. Through the joint application of the target wavelength value and the reference wavelength value, the precise separation and correction of real algae signals and non-algae signals in algae fluorescence signals can be achieved, providing reliable data support for the study of algae biomass and photosynthetic activity.

[0028] Optionally, in a possible implementation manner, the specific implementation process of this step may include:

[0029] S1011. Determine the correlation between the first remote sensing reflectivity data and the second remote sensing reflectivity data at different wavelengths based on the first type of remote sensing reflectivity data measured by the geostationary ocean color imager and the second remote sensing reflectivity data obtained by actual measurement, and determine the band with the strongest correlation as the candidate band for algal bloom identification; wherein the first remote sensing reflectivity data and the second remote sensing reflectivity data both include remote sensing reflectivity values ​​measured at multiple different locations in the same sea area at multiple different wavelengths.

[0030] It should be noted that in order to determine the first type of remote sensing reflectance data measured by the geostationary ocean color imager and the second type of remote sensing reflectance data obtained by actual measurement, two field measurement experiments were conducted. The experimental site was located in a coastal waters. The distribution of cruise sites was set according to actual needs, and the experimental time was from November 9 to 10, 2021 and April 9 to 18, 2024. The measurement was carried out under clear weather conditions, and a total of 28 sets of spectral data were obtained. In the actual measurement, the remote sensing reflectance (Rrs) was measured by a portable spectroradiometer manufactured by ASD, USA (spectral range: 350-2500 nm; spectral resolution: 3 nm). The measurement method follows NASA's ocean optical protocol (Mueller et al., 2003).

[0031] The remote sensing reflectance value of a given water body can be calculated by the following formula:

[0032] ;

[0033] Lt is the upward radiation above the water surface; Ls is the downward radiation from the sky; r is the reflectivity of the reference panel; Lr is the upward radiation of the reference panel; ρ is the surface reflectivity, which is 0.028.

[0034] Furthermore, the data of the Geostationary Ocean Color Imager were obtained from the National Ocean Satellite Center (https: / / www.nosc.go.kr / eng / main.do).

[0035] In this step, after obtaining the first type of remote sensing reflectivity data measured by the geostationary ocean color imager and the second type of remote sensing reflectivity data obtained by actual measurement, the correlation between the two can be obtained.

[0036] Figure 2 A comparison diagram between the data of the geostationary ocean color imager and the measured data is shown as an exemplary embodiment of the present application. Among them, (a) to (j) respectively represent the results of comparing the Rrs values ​​of different bands obtained from the GOCI-II data with the Rrs values ​​obtained from the in-situ measurement. Further, in (a) to (j), the horizontal axis represents the remote sensing reflectivity result measured in situ, and the vertical axis represents the remote sensing reflectivity result obtained by the GOCI-II satellite.

[0037] In this step, for different locations in the same sea area, the first type of remote sensing reflectivity data is measured according to the geostationary ocean color imager, and the second remote sensing reflectivity data is obtained by actual measurement. In this way, by comparing the correlation between the first remote sensing reflectivity data of different wavelengths at the same location and the measured second remote sensing reflectivity data, the alternative band that best reflects the characteristics of algal blooms can be screened out, thereby improving the accuracy of identifying algal bloom water bodies.

[0038] Specifically, refer to Figure 2 , the coefficients of determination (R²) of 620nm, 660nm, 680nm and 709nm are 0.849, 0.878, 0.878 and 0.892 respectively, while the R² values ​​of 412nm, 443nm, 490nm, 510nm and 555nm are 0.374, 0.454, 0.547, 0.441 and 0.537 respectively. In this step, the candidate bands are determined to be 620nm, 660nm, 680nm and 709nm.

[0039] S1012. Determine a first red-shift range of a fluorescence peak in a first spectral curve and a second red-shift range of a fluorescence peak in a second spectral curve according to first spectral curves of dinoflagellates at different growth stages and second spectral curves of diatoms at different growth stages; wherein the first spectral curve and the second spectral curve are obtained based on an algae cultivation experiment.

[0040] In this application, the spectral curves of dinoflagellates and diatoms during the algal bloom period in the ECS region were obtained through algae cultivation experiments.

[0041] The following is a brief introduction to the algae cultivation experiment:

[0042] Specifically, in the algae culture experiment, the algae species were placed in a transparent culture barrel in a constant temperature circulating water bath. The chlorophyll concentration in the algae solution was measured daily by a fluorescence meter, and the algae cell density was calculated by an optical microscope. The growth stage of phytoplankton was determined by the changes in chlorophyll concentration and cell density. In addition, the fluorescence intensity at the chlorophyll emission peak was measured by a fluorescence spectrophotometer, and the absorption coefficient of phytoplankton was measured by a UV spectrophotometer. The ratio of the two measured values ​​was used to calculate the fluorescence quantum yield of phytoplankton. The main steps are as follows:

[0043] I. Cultivate the algae species in a culture medium containing inactivated seawater, set appropriate light, temperature, salinity, pH and light-dark cycle conditions, and shake the flask to prevent the algae cells from settling to the bottom and affecting growth.

[0044] II. Under sterile conditions, an appropriate amount of penicillin was added to the algae mixture during the logarithmic growth phase, and streptomycin sulfate and kanamycin sulfate were added within 24 hours to remove contaminants. After the algae cells entered the logarithmic growth phase, they were inoculated into new flasks four times to activate the cells. The algae cells in the logarithmic growth phase were then inoculated into a transparent PVC culture bucket containing sterilized seawater and culture medium, and placed in a constant temperature circulating water bath. Each species was cultured in two parallel settings, under appropriate conditions, with natural light and daily shaking.

[0045] III. Sample algae liquid through centrifuge tubes every day, measure algae cell density through optical microscope, average the results, determine the growth stage based on cell density, and measure the fluorescence intensity at the emission peak through fluorescence spectrophotometer.

[0046] IV. Chlorophyll concentration was measured daily by filtration method and the spectral curve of algae mixture was measured by portable spectroradiometer.

[0047] Specifically, through algae cultivation, the spectral curves of dinoflagellates and diatoms during the algal bloom in the ECS area were obtained. Figure 3 The spectral curves of dinoflagellates and diatoms during algal blooms provided in this application. Figure 3 Figure (a) shows the spectrum curve of dinoflagellates during the bloom period. Figure 3 Figure (b) shows the spectrum curve of diatoms during the algal bloom period. Figure 3 Figure (c) is the spectrum curve of seawater; the horizontal axis of the spectrum curve is the spectrum band of pure seawater, and the vertical axis is the Rrs value of different bands. Figure 3 In the figure, the grey lines indicate the positions of the fluorescence bands at 680 nm and 709 nm.

[0048] It should be noted that the red shift range is the specific interval between the fluorescence peak position in the spectral curve of the algae from the initial short wavelength to the final wavelength position, which can reflect the dynamic changes in the spectral characteristics of the algae. It is understandable that different algae have different red shift ranges, which can reflect the spectral characteristics of different algae. Therefore, by comparing the red shift ranges, the algae types can be effectively distinguished. For example, referring to Figure 3 The fluorescence peak of dinoflagellates appeared at 688 nm from the 1st to the 5th day, and then shifted to between 701 and 707 nm from the 6th to the 11th day; the fluorescence peak of diatoms appeared at 688 nm from the 1st to the 8th day, and then gradually shifted to 701 nm from the 9th to the 15th day.

[0049] Further, based on Figure 3 , determine the first redshift range to be 680 to 710, and determine the second redshift range to be 680 to 710.

[0050] In this step, the first spectral curve of dinoflagellates at different growth stages and the second spectral curve of diatoms at different growth stages are obtained through algae cultivation experiments based on dinoflagellates and diatoms, and the first red shift range of the fluorescence peak of dinoflagellates and the second red shift range of the fluorescence peak of diatoms are determined, which can effectively reflect the dynamic changes of the spectral characteristics of algae, not only can accurately distinguish different types of algae, but also provide a scientific basis for algae classification.

[0051] S1013. Determine a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence according to the candidate wavelength band, the first redshift range, and the second redshift range.

[0052] It should be noted that when determining the target wavelength value, the wavelength value that can distinguish between dinoflagellates and diatoms is preferred to ensure that the target wavelength value can not only reflect the fluorescence characteristics of algae, but also can be used to distinguish different algae. Therefore, it is necessary to first compare the first redshift range and the second redshift range to determine whether there is an overlapping area between the first redshift range and the second redshift range or whether the redshift ranges of the two are independent of each other; for example, when the first redshift range and the second redshift range overlap, the fluorescence characteristic wavelength value within the common overlapping range can be selected as the target wavelength value; when the first redshift range and the second redshift range are independent of each other, different wavelength values ​​can be selected as the target wavelength value, that is, dinoflagellates and diatoms each correspond to a target wavelength value. In this way, while ensuring that the target wavelength value can fully reflect the fluorescence characteristics, by analyzing the differences between different algae and the overlapping area between the first redshift range and the second redshift range, the target wavelength value can be optimized to further meet the classification and monitoring needs of algae.

[0053] Further, the wavelength values ​​in the first red-shift range and the second red-shift range are excluded from the candidate wavelengths, and the wavelengths in the remaining wavelengths that are not affected by fluorescence are selected as the reference wavelength values. It should be noted that when selecting the reference wavelength value, it is necessary to select a wavelength value that is independent of the target wavelength value and has a stable spectral signal as the reference wavelength, so that it can be compared with the target wavelength value to highlight the fluorescence characteristics.

[0054] In this step, it is determined that the target wavelength values ​​include 680 nm and 709 nm, and the reference wavelength value includes 660 nm.

[0055] The method for identifying and classifying algal bloom water bodies provided in this embodiment determines the target wavelength value and the reference wavelength value based on the alternative bands, the first redshift range and the second redshift range, wherein the target wavelength value reflects the fluorescence characteristics of the algae and the reference wavelength value provides a stable background signal; further, by analyzing the overlap or independence of the first redshift range and the second redshift range, the accuracy of algae classification and the monitoring effect can be improved to meet the needs of identifying and classifying algal bloom water bodies.

[0056] S102. Based on the spectral parameters of dinoflagellates and diatoms obtained in the algae culture experiment, determine a target parameter capable of distinguishing dinoflagellates from diatoms, and determine a limit value of the target parameter when distinguishing dinoflagellates from diatoms; wherein the target parameter is fluorescence quantum yield.

[0057] It should be noted that in the algae cultivation experiment, dinoflagellates and diatoms can be cultivated separately, and their spectral characteristics can be measured under the same control conditions. Afterwards, the differences in the spectral characteristics of dinoflagellates and diatoms can be compared to determine the target parameters that can distinguish dinoflagellates and diatoms for classification.

[0058] The spectral parameters in the spectral characteristics include fluorescence intensity, fluorescence quantum yield, fluorescence lifetime, absorption peak position, etc. In this step, firstly, it is necessary to select the target parameter that can distinguish dinoflagellates from diatoms from the spectral parameters, and further, determine the limit value of the target parameter in distinguishing dinoflagellates from diatoms.

[0059] In specific implementation, the spectral characteristics of dinoflagellates and diatoms can be measured separately under the same experimental control conditions to obtain their spectral parameters such as fluorescence intensity, fluorescence quantum yield, fluorescence lifetime, fluorescence flavor and absorption peak position. Furthermore, from the collected spectral parameters, focus on analyzing which parameters have large differences to distinguish between dinoflagellates and diatoms. In specific implementation, the statistical characteristics of each spectral parameter are calculated (for example, descriptive statistics (such as mean, standard deviation, etc.) can be performed on each parameter such as fluorescence quantum yield and fluorescence intensity), and then their distribution differences in dinoflagellates and diatoms are analyzed. For another example, the distribution of different spectral parameters in dinoflagellates and diatoms can be compared through box plots, scatter plots, etc. If the distribution difference of fluorescence quantum yield between the two is significant, it can be selected as the target parameter.

[0060] Figure 4 This is a comparison diagram of the fluorescence quantum yields of dinoflagellates and diatoms shown in an exemplary embodiment of the present application, wherein: Figure 4 Figure (a) shows the relationship between the fluorescence quantum yield of dinoflagellates and the number of days of growth. Figure 4 Figure (b) shows the relationship between the fluorescence quantum yield of diatoms and the number of days of generation. Please refer to Figure 4 ,from Figure 4 It can be seen that the fluorescence quantum yield of diatoms ranges from 0.01 to 0.016 during the growth period, while the fluorescence quantum yield of dinoflagellates ranges from 0.003 to 0.007 during the production period. The difference in fluorescence quantum yield between dinoflagellates and diatoms during algal bloom events is obvious. Therefore, fluorescence quantum yield can be selected as the target parameter for distinguishing dinoflagellates and diatoms for classification.

[0061] It should be noted that the fluorescence quantum yield of algae is the ratio of the unit absorbed light energy converted into fluorescence emission during the photosynthesis of algae. This indicator can reflect the information of light intensity, nutritional status and species composition, that is, this indicator can reflect the fluorescence efficiency of algae chlorophyll, which is closely related to the physiological state, photosynthetic activity and water environment of algae. For different algae, the difference in fluorescence quantum yield is large. In this application, the fluorescence quantum yield is used as the target parameter for distinguishing dinoflagellates and diatoms for classification.

[0062] Furthermore, in this step, after determining that the target parameter that can distinguish dinoflagellates and diatoms for classification is the fluorescence quantum yield, it is also necessary to determine the limit value of the target parameter when distinguishing dinoflagellates and diatoms, so as to accurately classify dinoflagellates and diatoms. In one possible implementation, determining the limit value of the target parameter when distinguishing dinoflagellates and diatoms may include:

[0063] (1) Obtaining data from the geostationary ocean color imager in historical algal bloom events; wherein the historical algal bloom events include dinoflagellate bloom events and diatom bloom events.

[0064] (2) For each historical algal bloom event, the fluorescence quantum yield value under the historical algal bloom event is determined based on the data of the geostationary orbit ocean color imager described in the historical algal bloom event.

[0065] (3) According to the fluorescence quantum yield value of each historical algal bloom event and the algal bloom type corresponding to each historical algal bloom event, the limit value of fluorescence quantum yield in distinguishing dinoflagellates from diatoms is determined.

[0066] In the specific implementation, five dinoflagellate bloom events and two diatom bloom events between 2021 and 2023 are selected to obtain the data of the geostationary ocean color imager during these historical algal bloom events. Furthermore, in step (2), the fluorescence quantum yield value under each historical algal bloom event is determined.

[0067] In specific implementation, the fluorescence quantum yield value can be calculated according to the following formula:

[0068] The fluorescence baseline height value is calculated according to the data of the geostationary ocean color imager, and the specific value of the fluorescence quantum yield is calculated according to the seawater chlorophyll concentration and the fluorescence baseline height value.

[0069] Specifically, when calculating the fluorescence baseline height value according to the data of the geostationary ocean color imager, the fluorescence baseline height value may be calculated according to the second formula; wherein the second formula is:

[0070] ;

[0071] Wherein, FLH is the fluorescence baseline height value; nLw F represents the nLw value of the fluorescence peak band; the nLw R Indicates the nLw value of the right reference band; nLw L Indicates the nLw value of the left reference band; λ F is the central wavelength of the fluorescence band; L is the central wavelength of the right reference band; Ris the central wavelength of the left reference band. The fluorescence peak band refers to the wavelength where the fluorescence intensity of phytoplankton chloroplasts is the highest in the fluorescence band after being excited by sunlight; the right reference band refers to the right area of ​​the fluorescence spectrum where there is no fluorescence emission or very weak emission, and the fluorescence signal is close to the background noise level; the left reference band refers to the left area of ​​the fluorescence spectrum where there is no fluorescence emission or very weak emission, and the fluorescence signal is close to the background noise level.

[0072] Further, when calculating the specific value of the fluorescence quantum yield according to the seawater chlorophyll concentration and the fluorescence baseline height value, the specific value of the fluorescence quantum yield can be calculated according to a third formula; the third formula is:

[0073] ;

[0074] Wherein, the FLH is the fluorescence baseline height value; is the fluorescence quantum yield; and Chla is the chlorophyll concentration in seawater.

[0075] Through the above steps, it is determined that during algal bloom events, the fluorescence quantum yield of diatoms is usually greater than 0.014, while the fluorescence quantum yield of dinoflagellates is usually less than 0.014. Therefore, the cutoff value of fluorescence quantum yield in distinguishing dinoflagellates from diatoms is determined to be 0.014.

[0076] Referring to the previous steps, by obtaining data from the geostationary ocean color imager in historical algal bloom events including dinoflagellate bloom events and diatom bloom events, the fluorescence quantum yield value in each historical algal bloom event is calculated, and by analyzing the fluorescence quantum yield values ​​in dinoflagellate bloom events and diatom bloom events, the distribution characteristics of the fluorescence quantum yield values ​​in dinoflagellate bloom events and diatom bloom events are determined, and then the limit value of the fluorescence quantum yield when distinguishing dinoflagellates from diatoms is determined. In this way, the limit value of the fluorescence quantum yield can be used to accurately determine whether the algal bloom event is a dinoflagellate bloom event or a diatom bloom event, thereby providing a scientific basis for marine ecological monitoring and algal bloom control.

[0077] S103. When using the data of the geostationary ocean color imager to identify and classify algal bloom water bodies, the target remote sensing reflectance value at the target wavelength value, the benchmark remote sensing reflectance value at the benchmark wavelength value and the seawater chlorophyll concentration are obtained from the data of the geostationary ocean color imager.

[0078] In this step, when using the data from the geostationary ocean color imager to identify and classify algal bloom water bodies, the target remote sensing reflectance value at the target wavelength, the baseline remote sensing reflectance value at the baseline wavelength and the seawater chlorophyll concentration are extracted from the data measured by the geostationary ocean color imager. This can provide basic data support for algae classification.

[0079] S104, calculating an algal bloom index according to the target remote sensing reflectance value and the benchmark remote sensing reflectance value, and determining whether an algal bloom exists according to the algal bloom index and the seawater chlorophyll concentration.

[0080] In this step, the algal bloom index is calculated by extracting the target remote sensing reflectance value at the target wavelength and the benchmark remote sensing reflectance value at the benchmark wavelength from the data measured by the geostationary ocean color imager, and the presence of algal bloom is determined by combining the algal bloom index and seawater chlorophyll concentration.

[0081] In a specific implementation, in a possible implementation manner, the algal bloom index may be calculated according to a first formula; wherein the first formula is:

[0082] BIF = M-Rrs660;

[0083] M = max(Rrs680, Rrs709);

[0084] Among them, the BI F is the algal bloom index;

[0085] The Rrs660 is the remote sensing reflectance value at 66nm;

[0086] The Rrs680 is the remote sensing reflectance value at 680nm;

[0087] The Rrs709 is the remote sensing reflectance value at 709 nm.

[0088] It should be noted that the remote sensing reflectance (Rrs) is used to describe the ratio of the light intensity reflected by the water surface at different wavelengths to the incident light intensity.

[0089] Specifically, the maximum value of the remote sensing reflectance values ​​at the target wavelengths of 680nm and 709nm is obtained from the data measured by the geostationary ocean color imager, and then the maximum value is subtracted from the remote sensing reflectance value at the reference wavelength of 660nm to obtain the algal bloom index. In this way, the background interference of non-algae characteristics can be eliminated in the algal bloom index, and the algal bloom phenomenon in the water body can be accurately identified through the algal bloom index.

[0090] Furthermore, after the algal bloom index is calculated, the algal bloom index and the seawater chlorophyll concentration are combined to determine whether an algal bloom exists. Specifically, when the algal bloom index is greater than 0 and the seawater chlorophyll concentration is greater than a first preset threshold, it is determined that an algal bloom exists; when the algal bloom index is not greater than 0, or the seawater chlorophyll concentration is not greater than the first preset threshold, it is determined that an algal bloom does not exist.

[0091] Specifically, the algal bloom index is the result obtained by subtracting the maximum value of the remote sensing reflectance value of the water body surface at the target wavelength values ​​of 680nm and 709nm from the remote sensing reflectance value at the reference wavelength value of 660nm. When the result is greater than 0, that is, the algal bloom index is greater than 0. At this time, the maximum value of the remote sensing reflectance value of the water body surface at the target wavelength values ​​of 680nm and 709nm is greater than the remote sensing reflectance value of the water body surface at the reference wavelength value of 660nm, indicating that the algae concentration in the water surface is too high. At the same time, if the chlorophyll concentration in the seawater is greater than the first preset threshold value, the algae biomass in the seawater exceeds the normal level. In this way, it can be determined that there is an algal bloom in the seawater.

[0092] Furthermore, if the algal bloom index is not greater than 0, or the seawater chlorophyll concentration is not greater than the first preset threshold, that is, the algal bloom index is less than 0 or the seawater chlorophyll concentration is less than the first preset threshold, it can be determined that there is no algal bloom in the seawater.

[0093] It should be noted that when using the algal bloom index to determine whether an algal bloom has occurred, it is necessary to avoid near-infrared band abnormalities caused by high concentrations of suspended particles in the water. Therefore, while using the algal bloom index to determine whether an algal bloom has occurred, the chlorophyll concentration in the seawater is also used to determine whether it exceeds the first preset threshold to assist in identifying the algal bloom, which can improve accuracy.

[0094] Furthermore, the specific value of the first preset threshold value can be set according to the empirical value of the chlorophyll concentration in the seawater during the harmful algal bloom. In the present application, the first preset threshold value is set to 4µg / L.

[0095] S105. When it is determined that an algal bloom exists, a specific value of the fluorescence quantum yield is determined based on the data of the geostationary ocean color imager, and the type of the algal bloom is determined based on the specific value and the boundary value.

[0096] In this step, after determining the presence of algal bloom based on the algal bloom index and the chlorophyll concentration in the seawater, the specific value of the fluorescence quantum yield can be further determined based on the data from the geostationary ocean color imager, and the specific type of algal bloom phenomenon can be determined based on the specific value of the fluorescence quantum yield and the limit value of the fluorescence quantum yield for judging the type of algal bloom.

[0097] Specifically, referring to the above description, the specific value of the fluorescence quantum yield is determined based on the data of the geostationary ocean color imager, including:

[0098] Step 1: Calculate the fluorescence baseline height value according to the data of the geostationary ocean color imager;

[0099] In a specific implementation, the fluorescence baseline height value may be calculated according to a second formula; wherein the second formula is:

[0100] ;

[0101] Wherein, FLH is the fluorescence baseline height value; nLw F represents the nLw value of the fluorescence peak band; the nLw R Indicates the nLw value of the right reference band; nLw L Indicates the nLw value of the left reference band; λ F is the central wavelength of the fluorescence band; L is the central wavelength of the right reference band; R is the center wavelength of the left reference band.

[0102] It should be noted that the fluorescence peak band refers to the wavelength range with the highest fluorescence intensity, which can usually be used to evaluate the fluorescence characteristics of algae or phytoplankton in water bodies; the left reference band refers to a wavelength range located on the left side of the fluorescence band, and the right reference band refers to a wavelength range located on the right side of the fluorescence band. The left reference band and the right reference band are often used to measure background signals that contain no or almost no fluorescence, helping to eliminate spectral interference from other environmental factors.

[0103] Step 2: Calculate the specific value of the fluorescence quantum yield according to the seawater chlorophyll concentration and the fluorescence baseline height value.

[0104] In specific implementation, the specific value of the fluorescence quantum yield can be calculated according to the third formula; the third formula is:

[0105] ;

[0106] Wherein, the FLH is the fluorescence baseline height value; is the fluorescence quantum yield; and Chla is the chlorophyll concentration in seawater.

[0107] Furthermore, after obtaining the fluorescence baseline height value according to the second formula and further calculating the specific value of the fluorescence quantum yield according to the seawater chlorophyll concentration through the third formula, the type of algal bloom can be determined according to the specific value and the boundary value.

[0108] Specifically, when the specific value is greater than the limit value, the type of the algal bloom is determined to be diatom; when the specific value is less than or equal to the limit value, the type of the algal bloom is determined to be dinoflagellate.

[0109] It should be noted that, referring to the previous description, the limit value of the fluorescence quantum yield is set by summarizing the different fluorescence quantum yields of diatoms and dinoflagellates during multiple algal bloom events, and it is not limited in the present application. For example, in one embodiment, the limit value for distinguishing the fluorescence quantum yield is 0.012, that is, when the specific value of the fluorescence quantum yield of the algae is greater than the limit value, the type of the algal bloom is determined to be a diatom; when the specific value of the fluorescence quantum yield of the algae is less than or equal to the limit value, the type of the algal bloom is determined to be a dinoflagellate. Further, different limit values ​​can also be set for the algae that need to be distinguished by the different fluorescence quantum yields of different algae in the algal bloom event. For example, in one embodiment, it is necessary to distinguish diatoms and dinoflagellates by comparing the size of the specific value and the limit value. At this time, the limit value for distinguishing the fluorescence quantum yield can be set to 0.014. In this way, when the specific value of the fluorescence quantum yield of the algae is greater than 0.014, the algae is determined to be a diatom; when the specific value of the fluorescence quantum yield of the algae is less than or equal to 0.014, the algae is determined to be a dinoflagellate.

[0110] The method for identifying and classifying algal bloom water bodies provided in this embodiment determines a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence. In this way, when using the data of the geostationary orbit ocean color imager to identify and classify algal bloom water bodies, the target remote sensing reflectance value at the target wavelength value, the reference remote sensing reflectance value at the reference wavelength value, and the seawater chlorophyll concentration are obtained from the data of the geostationary orbit ocean color imager, and the algal bloom index is calculated according to the target remote sensing reflectance value and the reference remote sensing reflectance value. Then, whether there is an algal bloom is determined according to the algal bloom index and the seawater chlorophyll concentration. Since the algal bloom index is calculated by using the target remote sensing reflectance value and the reference remote sensing reflectance value, it reflects the change in the reflectance of algae in the water body and can sensitively capture the water color changes caused by algae, and the chlorophyll concentration is a direct sign of algal growth and reproduction, which can provide Quantitative data of algae biomass in water bodies, the algal bloom index reflects the population characteristics of algae, pays more attention to the algae's reflection characteristics of light, and can detect the impact of algae on the color of water bodies. The chlorophyll concentration reflects the biomass of algae, which provides quantitative data on the number of algae. When the two are used in combination, they can improve the sensitivity to changes in algal growth, maintain high monitoring sensitivity and stability in different algal growth stages and different environmental conditions, avoid misjudgment that may be caused by a single indicator, and more accurately judge whether algal blooms occur in water bodies. Furthermore, the algal bloom index and chlorophyll concentration can be obtained through remote sensing technology, and have strong spatial resolution. Combining these two indicators, efficient monitoring and classification can be achieved in a large range of waters, and reliable algae growth status data can be provided at different time and spatial scales, facilitating a global assessment of water quality and ecological conditions. In addition, by obtaining the spectral parameters of dinoflagellates and diatoms in the algae cultivation experiment, the target parameter that can distinguish dinoflagellates and diatoms is determined to be the fluorescence quantum yield, and the limit value of the fluorescence quantum yield in distinguishing dinoflagellates and diatoms is determined. In this way, when determining the presence of algae bloom, the specific value of the fluorescence quantum yield is determined based on the data of the geostationary orbit ocean water color imager, and the type of algae bloom is determined according to the specific value and the limit value. Since the fluorescence quantum yield reflects the efficiency of algae photosynthesis, the difference between dinoflagellates and diatoms in this indicator makes it an important feature to distinguish the two. By comparing the spectral parameters, the difference in fluorescence quantum yield between the two types of algae can be accurately captured, which helps to improve the classification accuracy. Furthermore, the setting of the limit value further clarifies the judgment criteria, ensuring that when algae bloom occurs, it is possible to accurately identify which type of algae dominates the changes in the water body; in addition, in this application, the data obtained by the geostationary orbit ocean water color imager can achieve efficient algae monitoring in a large range, with higher sensitivity and accuracy.

[0111] Corresponding to the aforementioned embodiment of a method for constructing an adaptive filtering model, the present application also provides an embodiment of a device for identifying and classifying algal bloom water bodies. Figure 5 This is a schematic diagram of the structure of the first embodiment of the algal bloom water body identification and classification device provided in this application. Figure 5 The device provided in this embodiment includes a determination module 510, a calculation module 520 and an acquisition module 530, wherein: The determination module 510 is used to determine a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence; The calculation module 520 is used to determine the target parameter that can distinguish between dinoflagellates and diatoms based on the spectral parameters of dinoflagellates and diatoms obtained in the algae culture experiment, and determine the limit value of the target parameter when distinguishing between dinoflagellates and diatoms; wherein the target parameter is the fluorescence quantum yield; The acquisition module 530 is used to acquire the target remote sensing reflectance value at the target wavelength value, the reference remote sensing reflectance value at the reference wavelength value, and the seawater chlorophyll concentration from the data of the geostationary orbit ocean color imager when using the data of the geostationary orbit ocean color imager to identify and classify algal bloom water bodies; The determination module 510 is used to calculate an algal bloom index according to the target remote sensing reflectance value and the reference remote sensing reflectance value, and determine whether an algal bloom exists according to the algal bloom index and the seawater chlorophyll concentration; The determination module 510 is used to determine the specific value of the fluorescence quantum yield based on the data of the geostationary ocean color imager when determining the presence of algal bloom, and determine the type of algal bloom based on the specific value and the boundary value.

[0112] The device of this embodiment can be used to perform Figure 1 The steps, specific implementation principles and implementation processes of the method embodiment shown are similar and will not be repeated here.

[0113] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for identifying and classifying algal bloom water bodies, characterized in that: The algal bloom water body identification and classification method is implemented based on data from a geostationary ocean color imager; the method comprises: Determine a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence; Based on the spectral parameters of dinoflagellates and diatoms obtained in the algae culture experiment, a target parameter capable of distinguishing dinoflagellates from diatoms is determined, and a limit value of the target parameter when distinguishing dinoflagellates from diatoms is determined; wherein the target parameter is the fluorescence quantum yield; When using the data of the geostationary ocean color imager to identify and classify algal bloom water bodies, the target remote sensing reflectance value at the target wavelength value, the reference remote sensing reflectance value at the reference wavelength value and the seawater chlorophyll concentration are obtained from the data of the geostationary ocean color imager; Calculating an algal bloom index according to the target remote sensing reflectance value and the reference remote sensing reflectance value, and determining whether an algal bloom exists according to the algal bloom index and the seawater chlorophyll concentration; When the presence of algal bloom is determined, a specific value of the fluorescence quantum yield is determined based on the data of the geostationary ocean color imager, and the type of algal bloom is determined based on the specific value and the boundary value.

2. The method according to claim 1, characterized in that The target wavelength values ​​include 680nm and 709nm, and the reference wavelength value includes 660nm; and calculating the algal bloom index according to the target remote sensing reflectance value and the reference remote sensing reflectance value includes: The algal bloom index is calculated according to the first formula; wherein the first formula is: BIF = M-Rrs660; M = max(Rrs680, Rrs709); Among them, the BI F is the algal bloom index; The Rrs660 is the remote sensing reflectance value at 660nm; The Rrs680 is the remote sensing reflectance value at 680nm; The Rrs709 is the remote sensing reflectance value at 709 nm.

3. The method according to claim 1, characterized in that The step of determining a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by the fluorescence includes: Determine the correlation between the first remote sensing reflectivity data and the second remote sensing reflectivity data at different wavelengths based on the first remote sensing reflectivity data measured by the geostationary ocean color imager and the second remote sensing reflectivity data obtained by actual measurement, and determine the band with the strongest correlation as the candidate band for algal bloom identification; wherein the first remote sensing reflectivity data and the second remote sensing reflectivity data both include remote sensing reflectivity values ​​measured at multiple different locations in the same sea area at multiple different wavelengths; Determine a first red shift range of a fluorescence peak in the first spectral curve and a second red shift range of a fluorescence peak in the second spectral curve according to a first spectral curve of dinoflagellates at different growth stages and a second spectral curve of diatoms at different growth stages; wherein the first spectral curve and the second spectral curve are obtained based on an algae cultivation experiment; According to the candidate wavelength band, the first red shift range and the second red shift range, a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence are determined.

4. The method according to claim 1, characterized in that: Determining the threshold value of the target parameter when distinguishing between dinoflagellates and diatoms comprises: Acquiring data from the geostationary ocean color imager in historical algal bloom events; wherein the historical algal bloom events include dinoflagellate bloom events and diatom bloom events; For each historical algal bloom event, based on the data of the geostationary ocean color imager in the historical algal bloom event, determine the fluorescence quantum yield value under the historical algal bloom event; Based on the fluorescence quantum yield values ​​under each historical algal bloom event and the algal bloom types corresponding to each historical algal bloom event, the boundary value of fluorescence quantum yield in distinguishing dinoflagellates and diatoms is determined.

5. The method according to claim 1 or 4, characterized in that: The specific value of the fluorescence quantum yield is determined based on the data of the geostationary ocean color imager, comprising: Calculating the fluorescence baseline height value according to the data of the geostationary ocean color imager; The specific value of the fluorescence quantum yield is calculated according to the seawater chlorophyll concentration and the fluorescence baseline height value.

6. The method according to claim 5, characterized in that The step of calculating the fluorescence baseline height value according to the data of the geostationary ocean color imager comprises: The fluorescence baseline height value is calculated according to a second formula; wherein the second formula is: ； Wherein, FLH is the fluorescence baseline height value; nLw F represents the nLw value of the fluorescence peak band; R Indicates the nLw value of the right reference band; nLw L Indicates the nLw value of the left reference band; λ F is the central wavelength of the fluorescence band; L is the central wavelength of the right reference band; R is the center wavelength of the left reference band.

7. The method according to claim 5 or 6, characterized in that: The specific value of the fluorescence quantum yield is calculated according to the seawater chlorophyll concentration and the fluorescence baseline height value, including: The specific value of the fluorescence quantum yield is calculated according to the third formula; the third formula is: ； Wherein, the FLH is the fluorescence baseline height value; is the fluorescence quantum yield; and Chla is the chlorophyll concentration in seawater.

8. The method according to claim 1, characterized in that: Determining whether there is an algal bloom according to the algal bloom index and the seawater chlorophyll concentration includes: When the algal bloom index is greater than 0 and the seawater chlorophyll concentration is greater than a first preset threshold, it is determined that an algal bloom exists; When the algal bloom index is not greater than 0, or the seawater chlorophyll concentration is not greater than a first preset threshold, it is determined that there is no algal bloom.

9. The method according to claim 1 or 8, characterized in that: Determining the type of algal bloom according to the specific value and the limit value includes: When the specific value is greater than the limit value, determining that the type of the algal bloom is diatom; When the specific value is less than or equal to the limit value, the type of the algal bloom is determined to be dinoflagellate.

10. A device for identifying and classifying algal bloom water bodies, characterized in that: The algal bloom water body identification and classification method is implemented based on data from a geostationary ocean color imager; the device includes a determination module, a calculation module and an acquisition module, wherein: The determination module is used to determine a target wavelength value that can reflect the fluorescence characteristics of algae and a reference wavelength value that is not affected by fluorescence; The calculation module is used to determine the target parameter that can distinguish between dinoflagellates and diatoms based on the spectral parameters of dinoflagellates and diatoms obtained in the algae cultivation experiment, and determine the limit value of the target parameter when distinguishing between dinoflagellates and diatoms; wherein the target parameter is the fluorescence quantum yield; The acquisition module is used to acquire the target remote sensing reflectance value at the target wavelength value, the reference remote sensing reflectance value at the reference wavelength value, and the seawater chlorophyll concentration from the data of the geostationary orbit ocean water color imager when using the data of the geostationary orbit ocean water color imager to identify and classify algal bloom water bodies; The determination module is used to calculate the algal bloom index according to the target remote sensing reflectance value and the reference remote sensing reflectance value, and determine whether an algal bloom exists according to the algal bloom index and the seawater chlorophyll concentration; The determination module is used to determine the specific value of the fluorescence quantum yield based on the data of the geostationary ocean color imager when determining the presence of algal bloom, and to determine the type of algal bloom based on the specific value and the boundary value.

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