A method and device for identifying and classifying algal bloom water bodies

Abstract

This application provides a method and device for identifying and classifying algal bloom water bodies. The method for identifying and classifying algal bloom water bodies provided by this application includes: determining a target wavelength value reflecting the fluorescence characteristics of algae and a reference wavelength value not affected by fluorescence; based on the spectral parameters of dinoflagellates and diatoms, determining a target parameter capable of distinguishing dinoflagellates and diatoms, and the boundary value when the target parameter distinguishes dinoflagellates and diatoms; wherein, the target parameter is the fluorescence quantum yield; when using the data of a geostationary ocean color imager for identifying and classifying algal bloom water bodies, obtaining the target remote sensing reflectance value, the reference remote sensing reflectance value, and the seawater chlorophyll concentration from the data; calculating the algal bloom index based on the target remote sensing reflectance value and the reference remote sensing reflectance, and determining whether there is an algal bloom according to the algal bloom index and the seawater chlorophyll concentration; when it is determined that there is an algal bloom, determining the type of algal bloom according to the specific value and the boundary value of the fluorescence quantum yield. The method provided by this application can accurately identify algal bloom water bodies.

Description

Technical Field

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

[0002] With the impacts of climate change and human activities, harmful algal bloom (HABs) events in the ocean occur frequently. Among them, harmful algal bloom events refer to the fact that certain algae in the marine environment will multiply rapidly in a short period of time, forming high-density algal populations. The metabolites produced by these algae will pose threats to water quality, ecosystems, and fisheries.

[0003] In the Yangtze River Estuary and the East China Sea regions, dinoflagellate and diatom algal blooms are common marine disasters. In order to respond to the rapidly changing water environment and timely monitor pollution sources, an efficient and real-time water quality monitoring method is needed. However, in traditional water quality monitoring methods, they 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 comprehensively reflect the water quality changes in a large range of waters; moreover, the steps of traditional water quality monitoring methods are cumbersome and require a lot of time to analyze sample data, and they cannot respond to harmful algal bloom events in a timely manner. How to accurately distinguish dinoflagellate and diatom algal blooms and help coastal managers more effectively reduce the harmful impacts brought by 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 to accurately distinguish dinoflagellate and diatom algal blooms and help coastal managers effectively reduce the harmful impacts brought by 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, and the method for identifying and classifying algal bloom water bodies is implemented based on data of a geostationary ocean color imager; the method includes:

[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 the spectral parameters of diatoms obtained in algal culture experiments, determine a target parameter that can distinguish and classify dinoflagellates and diatoms, and determine the boundary value of the target parameter when distinguishing dinoflagellates and diatoms; wherein, the target parameter is the fluorescence quantum yield;

[0009] When identifying and classifying algal bloom water bodies using the data of the geostationary ocean color imager, obtain 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 ocean color imager;

[0010] Calculate the algal bloom index based on the target remote sensing reflectance value and the reference remote sensing reflectance value, and determine whether there is an algal bloom based on the algal bloom index and the seawater chlorophyll concentration;

[0011] When it is determined that there is an algal bloom, determine the specific value of the fluorescence quantum yield based on the data of the geostationary ocean color imager, and determine the type of algal bloom according to the specific value and the threshold value.

[0012] An algal bloom water body identification and classification device, the device includes a determination module, a calculation module and an acquisition module, where;

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

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

[0015] The acquisition module is used to obtain 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 ocean color imager when identifying and classifying algal bloom water bodies using the data of the geostationary ocean color imager;

[0016] The determination module is used to calculate the algal bloom index based on the target remote sensing reflectance value and the reference remote sensing reflectance value, and determine whether there is an algal bloom based on 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 it is determined that there is an algal bloom, and determine the type of algal bloom according to the specific value and the threshold value.

[0018] The algal bloom water body identification and classification method and device provided by this application determine the target wavelength value that can reflect the fluorescence characteristics of algae and the reference wavelength value that is not affected by fluorescence. In this way, when using the data of the geostationary ocean color imager for algal bloom water body identification and classification, 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, it is determined whether there is an algal bloom based on the algal bloom index and the seawater chlorophyll concentration. Since the algal bloom index is calculated from 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, can sensitively capture the water color change caused by algae, while the chlorophyll concentration is a direct indicator of the growth and reproduction of algae and can provide quantitative data on the algal biomass in the water body. The algal bloom index reflects the population characteristics of algae, pays more attention to the light reflection characteristics of algae, can detect the impact of algae on the water color, while the chlorophyll concentration reflects the algal biomass and provides quantitative data on the number of algae. When the two are used in combination, it can improve the sensitivity to the growth change of algae, can maintain a high monitoring sensitivity and stability at different algal growth stages and different environmental conditions, and combines these two indicators to judge whether there is an algal bloom, avoiding misjudgment that may be caused by a single indicator, and can more accurately judge whether an algal bloom has occurred in the water body. Further, both the algal bloom index and the chlorophyll concentration can be obtained through remote sensing technology and have strong spatial resolution ability. Combining these two indicators can achieve efficient monitoring and classification in a large range of waters, can provide reliable data on the algal growth status at different time and space scales, and is convenient for global assessment of water quality and ecological conditions. In addition, through the spectral parameters of dinoflagellates and diatoms obtained in the algal culture experiment, and then based on this, the target parameter that can distinguish dinoflagellates and diatoms is determined to be the fluorescence quantum yield, and the threshold value of the fluorescence quantum yield for distinguishing dinoflagellates and 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 threshold value. Since the fluorescence quantum yield reflects the efficiency of algal 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 differences in the fluorescence quantum yield of these two types of algae can be accurately captured, which helps to improve the classification accuracy. Further, the setting of the threshold value further clarifies the judgment standard to ensure that when an algal bloom occurs, it can accurately identify which type of algae dominates the change of the water body; in addition, in this application, the data obtained by using the geostationary ocean color imager can achieve efficient algal monitoring in a large range, with higher sensitivity and accuracy. Description of the Drawings

[0019] Figure 1 Flow chart of the first embodiment of the algal bloom water body identification and classification method provided by this application;

[0020] Figure 2 Comparison chart between the data of the geostationary ocean color imager shown in an exemplary embodiment of this application and the measured data;

[0021] Figure 3 Spectral curves of dinoflagellates and diatoms during the algal bloom provided by this application;

[0022] Figure 4 Comparison chart of the fluorescence quantum yields of dinoflagellates and diatoms shown in an exemplary embodiment of this application;

[0023] Figure 5 Schematic structural diagram of the first embodiment of the algal bloom water body identification and classification device provided by this application. Detailed implementation manners

[0024] Here, the exemplary embodiments will be described in detail, and the examples are shown in the 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 implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with this application.

[0025] 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 "a", "the", and "said" used in this application are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0026] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such 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 this 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 "when" or "while" or "in response to a determination".

[0027] Specific embodiments are given below to introduce the technical solutions of this application in detail.

[0028] Figure 1 Flow chart of the first embodiment of the algal bloom water body identification and classification method provided by this application. Please refer to Figure 1 , the algal bloom water body identification and classification method provided in this embodiment is implemented based on the data of the geostationary ocean color imager, and the method may include:

[0029] S101. Determine the target wavelength value that can reflect the fluorescence characteristics of algae and the reference wavelength value that is not affected by fluorescence.

[0030] Specifically, the target wavelength value that can reflect the fluorescence characteristics of algae is a specific spectral wavelength for capturing the fluorescence signal of algae. The optical signal at this spectral wavelength can directly reflect the fluorescence characteristics of algae, including reflecting the algal biomass and photosynthetic activity. The reference wavelength value that is not affected by fluorescence includes a spectral wavelength range. The optical signal within this spectral wavelength range is a non-algal fluorescence signal, which is not affected by the fluorescence characteristics of algae and can characterize the water background reflection characteristics where the algae are located.

[0031] 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 the algal fluorescence signal and the effective elimination of non-fluorescence interference can be ensured. Through the combined application of the target wavelength value and the reference wavelength value, the accurate separation and correction of the true algal signal and the non-algal signal in the algal fluorescence signal can be achieved, providing reliable data support for the study of algal biomass and photosynthetic activity.

[0032] Optionally, in a possible implementation manner, the specific implementation process of this step may include:

[0033] S1011. According to the first type of remote sensing reflectance data measured by the geostationary ocean color imager and the second remote sensing reflectance data obtained through on-site measurement, determine the correlation between the first remote sensing reflectance data and the second remote sensing reflectance data at different wavelengths, and determine the band with the strongest correlation as the alternative band for algal bloom identification; wherein, both the first remote sensing reflectance data and the second remote sensing reflectance data include the remote sensing reflectance values measured at multiple different wavelengths for multiple different positions in the same sea area.

[0034] 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 remote sensing reflectance data obtained through on-site measurement, two on-site measurement experiments were carried out. The experimental location was in a certain coastal sea area. The distribution of the cruise sites was set according to actual needs. The experimental time was from November 9th to 10th, 2021 and from April 9th to 18th, 2024. The measurement was carried out under clear weather conditions, and a total of 28 sets of spectral data were obtained. During the on-site measurement, the remote sensing reflectance (Rrs) was measured by a portable spectroradiometer manufactured by ASD Company in the United States (spectral range: 350 - 2500 nm; spectral resolution: 3 nm). The measurement method follows the NASA ocean optics protocol (Mueller et al., 2003).

[0035] The remote sensing reflectance value of a given water body can be calculated by the following formula:

[0036] ;

[0037] Lt is the upward radiation above the water surface; Ls is the downward radiation from the sky; r is the reflectance of the reference panel; Lr is the upward radiation of the reference panel; ρ is the surface reflectance with a value of 0.028.

[0038] Furthermore, the data of the geostationary ocean color imager comes from the National Ocean Satellite Center (https: / / www.nosc.go.kr / eng / main.do).

[0039] In this step, after obtaining the first type of remote sensing reflectance data measured by the geostationary ocean color imager and the second remote sensing reflectance data obtained through on-site measurement, the correlation between the two can be obtained.

[0040] Figure 2 This is a comparison chart between the data of the geostationary ocean color imager and the on-site measurement data shown in an exemplary embodiment of the present application. Among them, (a) to (j) respectively represent the comparison results of the Rrs values of different bands obtained from the GOCI-II data and the Rrs values obtained from in-situ measurement. Further, in (a) to (j), the abscissa represents the remote sensing reflectance results of in-situ measurement, and the ordinate represents the remote sensing reflectance results obtained through the GOCI-II satellite.

[0041] In this step, for different positions in the same sea area, according to the first type of remote sensing reflectance data measured by the geostationary ocean color imager and the second remote sensing reflectance data obtained through on-site measurement, in this way, by comparing the correlation between the first remote sensing reflectance data of different wavelengths and the measured second remote sensing reflectance data at the same position, the alternative bands that can best reflect the characteristics of algal blooms can be screened out, thereby improving the accuracy of algal bloom water body identification.

[0042] Specifically, referring to Figure 2 , the determination coefficients (R²) of 620 nm, 660 nm, 680 nm, and 709 nm are 0.849, 0.878, 0.878, and 0.892 respectively, while the R² values at 412 nm, 443 nm, 490 nm, 510 nm, and 555 nm are 0.374, 0.454, 0.547, 0.441, and 0.537 respectively. In this step, the alternative bands are determined to be 620 nm, 660 nm, 680 nm, and 709 nm.

[0043] S1012. 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 the first spectral curve of dinoflagellates at different growth stages and the second spectral curve of diatoms at the different growth stages; wherein, the first spectral curve and the second spectral curve are obtained based on an algae culture experiment.

[0044] In this application, through an algae culture experiment, spectral curves of dinoflagellates and diatoms during algal blooms in the ECS region were obtained.

[0045] The following is a brief introduction to the algae culture experiment first:

[0046] Specifically, in the algae culture experiment, the algal species were placed in a transparent culture bucket in a thermostatic circulating water bath. The chlorophyll concentration in the algal solution was measured daily by a fluorometer, and the algal cell density was calculated by an optical microscope. The growth stages of phytoplankton were determined through 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:

[0047] I. Cultivate the algal species in a medium containing inactivated seawater, set appropriate conditions of light, temperature, salinity, pH, and light-dark cycle, and shake the flask to prevent algal cells from depositing at the bottom and affecting growth.

[0048] II. In a sterile environment, add an appropriate amount of penicillin during the logarithmic growth phase of the algal mixture, and then add streptomycin sulfate and kanamycin sulfate within 24 hours to remove contaminants. After the algal cells enter the logarithmic growth phase, inoculate them four times into new flasks to activate the cells. The algal cells in the logarithmic growth phase are then inoculated into a transparent PVC culture bucket containing sterilized seawater and medium, and placed in a thermostatic circulating water bath. Each species is cultured in two parallel settings, exposed to natural light under suitable conditions, and shaken daily.

[0049] III. Sample the algal solution daily through a centrifuge tube, measure the algal cell density by an optical microscope, take the average of the results, and determine the growth stage based on the cell density. Measure the fluorescence intensity at the emission peak by a fluorescence spectrophotometer.

[0050] IV. Measure the chlorophyll concentration daily by the filtration method, and measure the spectral curve of the algal mixture by a portable spectroradiometer.

[0051] Specifically, through algae culture, spectral curves of dinoflagellates and diatoms during algal blooms in the ECS region were obtained. Figure 3 These are the spectral curves of dinoflagellates and diatoms during algal blooms provided by this application. Among them,Figure 3 In Figure (a), the spectral curve of dinoflagellates during algal blooms is shown. Figure 3 In Figure (b), the spectral curve of diatoms during algal blooms is shown. Figure 3 In Figure (c), the spectral curve of seawater is shown. Here, the abscissa in the spectral curve represents the spectral bands of pure seawater, and the ordinate represents the Rrs values of different bands. Further, Figure 3 in it, the gray lines indicate the positions of the fluorescence bands at 680 nm and 709 nm.

[0052] It should be noted that the redshift range is the specific interval between the initial short-wavelength position and the final wavelength position of the fluorescence peak in the spectral curve of algae, which can reflect the dynamic changes in the spectral characteristics of algae. It can be understood that the redshift ranges of different algae are different, which can reflect the respective spectral characteristics of different algae. Therefore, by comparing the redshift ranges, different algal types can be effectively distinguished. For example, referring to Figure 3 , the fluorescence peak of dinoflagellates appears at 688 nm from the 1st to the 5th day, and from the 6th to the 11th day, this fluorescence peak shifts to between 701 and 707 nm; the fluorescence peak of diatoms appears at 688 nm from the 1st to the 8th day, and then gradually shifts to 701 nm from the 9th to the 15th day.

[0053] Further, based on Figure 3 , the first redshift range is determined to be from 680 to 710, and the second redshift range is determined to be from 680 to 710.

[0054] In this step, by obtaining the first spectral curve of dinoflagellates at different growth stages and the second spectral curve of diatoms at different growth stages through algal culture experiments on dinoflagellates and diatoms, and determining the first redshift range of the fluorescence peak of dinoflagellates and the second redshift range of the fluorescence peak of diatoms, the dynamic changes in the spectral characteristics of algae can be effectively reflected. It can not only accurately distinguish different algal types but also provide a scientific basis for algal classification.

[0055] S1013. According to the alternative bands, the first redshift range, and the second redshift range, determine the target wavelength values that can reflect the fluorescence characteristics of algae and the reference wavelength values that are not affected by fluorescence.

[0056] It should be noted that when determining the target wavelength value, it is preferred to select the wavelength value that can distinguish dinoflagellates and diatoms, ensuring that the target wavelength value can not only reflect the fluorescence characteristics of algae but also 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 values respectively, that is, each of the dinoflagellates and diatoms corresponds 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 selection of the target wavelength value can be optimized to further meet the requirements for the classification and monitoring of algae.

[0057] Further, exclude the wavelength values within the first redshift range and the second redshift range from the alternative bands, and select the wavelength that is not affected by fluorescence among the remaining wavelengths as the reference wavelength value. It should be noted that when selecting the reference wavelength value, a wavelength value that is independent of the target wavelength value and has a stable spectral signal should be selected as the reference wavelength, so that the fluorescence characteristics can be highlighted by comparing with the target wavelength value.

[0058] In this step, the determined target wavelength values include 680 nm and 709 nm, and the reference wavelength value includes 660 nm.

[0059] The method for identifying and classifying algal bloom water bodies provided in this embodiment determines the target wavelength value and the reference wavelength value according to the alternative bands, the first redshift range, and the second redshift range, where the target wavelength value reflects the fluorescence characteristics of 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 requirements for the identification and classification of algal bloom water bodies.

[0060] S102. Based on the spectral parameters of dinoflagellates and diatoms obtained in the algae culture experiment, determine the target parameter that can distinguish dinoflagellates and diatoms, and determine the boundary value of the target parameter when distinguishing dinoflagellates and diatoms; wherein, the target parameter is the fluorescence quantum yield.

[0061] It should be noted that in the algae culture experiment, dinoflagellates and diatoms can be cultured separately, and their respective spectral characteristics can be measured under the same control conditions. Then, compare the differences in spectral characteristics between dinoflagellates and diatoms to determine the target parameter for classifying and distinguishing dinoflagellates and diatoms.

[0062] Among them, the spectral parameters in the spectral characteristics include fluorescence intensity, fluorescence quantum yield, fluorescence lifetime, absorption peak position, etc. In this step, first, it is necessary to select target parameters from the spectral parameters that can distinguish dinoflagellates and diatoms. Further, determine the boundary values of the target parameters when distinguishing dinoflagellates and diatoms.

[0063] When specifically implemented, under the same experimental control conditions, the spectral characteristics of dinoflagellates and diatoms can be measured respectively to obtain spectral parameters such as their fluorescence intensity, fluorescence quantum yield, fluorescence lifetime, fluorescence flavor, and absorption peak position. Further, among the collected spectral parameters, focus on analyzing which parameters have significant differences to distinguish dinoflagellates and diatoms. When specifically implemented, calculate the statistical characteristics of each spectral parameter (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 analyze their distribution differences in dinoflagellates and diatoms. 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 the fluorescence quantum yield between the two is significant, it can be selected as the target parameter.

[0064] Figure 4 It is a comparison chart of the fluorescence quantum yield of dinoflagellates and diatoms shown in an exemplary embodiment of the present application, where Figure 4 Figure (a) in it is a graph showing the relationship between the fluorescence quantum yield of dinoflagellates and the number of growth days, Figure 4 Figure (b) in it is a graph showing the relationship between the fluorescence quantum yield of diatoms and the number of generation days. Please refer to Figure 4 , from Figure 4 it can be seen that the range of the fluorescence quantum yield of diatoms during the growth period is 0.01 to 0.016, while the range of the fluorescence quantum yield of dinoflagellates during the generation period is 0.003 to 0.007. The difference in the fluorescence quantum yield between dinoflagellates and diatoms during the algal bloom event is obvious. Therefore, the fluorescence quantum yield can be selected as the target parameter for classifying and distinguishing dinoflagellates and diatoms.

[0065] It should be noted that the fluorescence quantum yield of algae is the proportion of the unit absorbed light energy converted into fluorescence emission during the photosynthesis process of algae plants. This index can reflect information on light intensity, nutritional status, and species composition, that is, this index can reflect the fluorescence efficiency of algal chlorophyll, which is closely related to the physiological state, photosynthetic activity of algae, and the water environment status. For different algae, the difference in the fluorescence quantum yield is relatively large. In the present application, the fluorescence quantum yield is used as the target parameter for classifying and distinguishing dinoflagellates and diatoms.

[0066] Further, in this step, after determining that the target parameter for distinguishing dinoflagellates and diatoms for classification is the fluorescence quantum yield, it is also necessary to determine the boundary value of the target parameter when distinguishing dinoflagellates and diatoms for accurately classifying dinoflagellates and diatoms. Among them, in one possible implementation manner, determining the boundary value of the target parameter when distinguishing dinoflagellates and diatoms may include:

[0067] (1) Obtain the data of the geostationary ocean color imager in the historical algal bloom events; among them, the historical algal bloom events include dinoflagellate algal bloom events and diatom algal bloom events.

[0068] (2) 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.

[0069] (3) According to the fluorescence quantum yield values under each historical algal bloom event and the algal bloom types corresponding to each historical algal bloom event, determine the boundary value of the fluorescence quantum yield when distinguishing dinoflagellates and diatoms.

[0070] Specifically, select five dinoflagellate algal bloom events and two diatom algal bloom events between 2021 and 2023, and obtain the data of the geostationary ocean color imager during these historical algal bloom events. Further, in step (2), determine the fluorescence quantum yield values under each historical algal bloom event.

[0071] Specifically, when implementing, the fluorescence quantum yield value can be calculated according to the following formula:

[0072] Calculate the fluorescence baseline height value according to the data of the geostationary ocean color imager, and calculate the specific value of the fluorescence quantum yield according to the seawater chlorophyll concentration and the fluorescence baseline height value.

[0073] Specifically, when calculating the fluorescence baseline height value according to the data of the geostationary ocean color imager, the fluorescence baseline height value can be calculated according to the second formula; among them, the second formula is:

[0074] ;

[0075] Among them, the FLH is the fluorescence baseline height value; the nLw F represents the nLw value of the fluorescence peak band; the nLw R represents the nLw value of the right reference band; nLw L represents the nLw value of the left reference band; λ F is the central wavelength of the fluorescence band; λ L is the central wavelength of the right reference band; λ Ris the central wavelength of the left reference band. The fluorescence peak band refers to the wavelength at which the fluorescence intensity is the highest in the fluorescence band after phytoplankton chloroplasts are excited by sunlight; the right reference band refers to the right region in the fluorescence spectrum where there is no or extremely weak fluorescence emission and the fluorescence signal is close to the background noise level; the left reference band refers to the left region in the fluorescence spectrum where there is no or extremely weak fluorescence emission and the fluorescence signal is close to the background noise level.

[0076] 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 the third formula; the third formula is:

[0077] ;

[0078] where, the FLH is the fluorescence baseline height value; the is the fluorescence quantum yield; the Chla is the seawater chlorophyll concentration.

[0079] Through the above steps, it is determined that during the algal bloom event, 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 boundary value of the fluorescence quantum yield for distinguishing dinoflagellates and diatoms is determined to be 0.014.

[0080] Referring to the previous steps, by obtaining the data of the geostationary ocean color imager in the historical algal bloom events including dinoflagellate algal bloom events and diatom algal bloom events, calculating the fluorescence quantum yield values in each historical algal bloom event, and analyzing the fluorescence quantum yield values in dinoflagellate algal bloom events and diatom algal bloom events, the distribution characteristics of the fluorescence quantum yield values in dinoflagellate algal bloom events and diatom algal bloom events are determined, and then the boundary value of the fluorescence quantum yield for distinguishing dinoflagellates and diatoms is determined. In this way, using this boundary value of the fluorescence quantum yield, it can be accurately judged whether the algal bloom event is a dinoflagellate algal bloom event or a diatom algal bloom event, and thus provide a scientific basis for marine ecological monitoring and algal bloom control.

[0081] S103. When using the data of the geostationary ocean color imager to identify and classify algal bloom water bodies, obtain 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 ocean color imager.

[0082] In this step, when using the data of the geostationary ocean color imager to identify and classify algal bloom water bodies, extract the target remote sensing reflectance value at the target wavelength, the reference remote sensing reflectance value at the reference wavelength, and the seawater chlorophyll concentration from the data measured by the geostationary ocean color imager. In this way, it can provide basic data support for algae classification.

[0083] S104. Calculate the algal bloom index based on the target remote sensing reflectance value and the reference remote sensing reflectance value, and determine whether there is an algal bloom based on the algal bloom index and the seawater chlorophyll concentration.

[0084] In this step, the target remote sensing reflectance value at the target wavelength and the reference remote sensing reflectance value at the reference wavelength are extracted from the data measured by the geostationary ocean color imager to calculate the algal bloom index, and whether there is an algal bloom is determined by integrating the algal bloom index and the seawater chlorophyll concentration.

[0085] Specifically, in a possible implementation, the algal bloom index can be calculated according to the first formula; wherein, the first formula is:

[0086] BIF = M - Rrs660;

[0087] M = max(Rrs680, Rrs709);

[0088] wherein, the BI F is the algal bloom index;

[0089] The Rrs660 is the remote sensing reflectance value at 66nm;

[0090] The Rrs680 is the remote sensing reflectance value at 680nm;

[0091] The Rrs709 is the remote sensing reflectance value at 709nm.

[0092] It should be noted that the remote sensing reflectance value (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.

[0093] Specifically, the maximum value of the remote sensing reflectance values at the target wavelength values of 680nm and 709nm is obtained from the data measured by the geostationary ocean color imager, and then the difference between the maximum value and the remote sensing reflectance value at the reference wavelength value of 660nm is used to obtain the algal bloom index. In this way, the background interference of non-algal 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.

[0094] Furthermore, after calculating the algal bloom index, the algal bloom index and the seawater chlorophyll concentration are combined to determine whether there is an algal bloom. Specifically, when the algal bloom index is greater than 0 and the seawater chlorophyll concentration is greater than the first preset threshold, it is determined that there is an algal bloom; 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 there is no algal bloom.

[0095] Specifically, the algal bloom index is the result obtained by subtracting the remote sensing reflectance value at the reference wavelength of 660 nm from the maximum value among the remote sensing reflectance values at the target wavelengths of 680 nm and 709 nm on the water surface. When the obtained result is greater than 0, that is, the algal bloom index is greater than 0. At this time, the maximum value among the remote sensing reflectance values at the target wavelengths of 680 nm and 709 nm on the water surface is greater than the remote sensing reflectance value at the reference wavelength of 660 nm on the water surface, indicating that the algae concentration in the water surface is too high at this time. At the same time, if the chlorophyll concentration in seawater is greater than the first preset threshold, the algal biomass in seawater exceeds the normal level. In this way, it can be determined that there is an algal bloom phenomenon in seawater.

[0096] Further, 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 phenomenon in seawater.

[0097] It should be noted that when using the algal bloom index to judge whether an algal bloom phenomenon occurs, it is necessary to avoid the abnormal situation of the near-infrared band caused by the high concentration of suspended particles in the water. Therefore, when using the algal bloom index to judge whether an algal bloom phenomenon occurs, the seawater chlorophyll concentration is also used to assist in identifying the algal bloom phenomenon, which can improve the accuracy.

[0098] Further, the specific value of the first preset threshold can be set according to the empirical value of the seawater chlorophyll concentration during harmful algal blooms. In this application, the first preset threshold is set to 4 µg / L.

[0099] S105. When it is determined that there is an algal bloom, determine the specific value of the fluorescence quantum yield based on the data of the geostationary ocean color imager, and determine the type of algal bloom according to the specific value and the boundary value.

[0100] In this step, when it is determined that there is an algal bloom according to the algal bloom index and the seawater chlorophyll concentration, the specific value of the fluorescence quantum yield can be further determined based on the data of the geostationary ocean color imager, and the specific type of the algal bloom phenomenon can be determined according to the specific value of the fluorescence quantum yield and the boundary value of the fluorescence quantum yield for judging the algal bloom type.

[0101] Specifically, referring to the previous description, determining the specific value of the fluorescence quantum yield based on the data of the geostationary ocean color imager includes:

[0102] Step 1: Calculate the fluorescence baseline height value according to the data of the geostationary ocean color imager;

[0103] When specifically implemented, the fluorescence baseline height value can be calculated according to the second formula; where the second formula is:

[0104] ;

[0105] wherein, the FLH is the fluorescence baseline height value; the nLw F represents the nLw value of the fluorescence peak band; the nLw R represents the nLw value of the right reference band; nLw L represents the nLw value of the left reference band; λ F is the central wavelength of the fluorescence band; λ L is the central wavelength of the right reference band; λ R is the central wavelength of the left reference band.

[0106] It should be noted that the fluorescence peak band refers to the wavelength range with the highest fluorescence intensity, and this band can usually be used to evaluate the fluorescence characteristics of algae or phytoplankton in water; the left reference band refers to a wavelength range on the left side of the fluorescence band, and the right reference band refers to the wavelength range on the right side of the fluorescence band. The left reference band and the right reference band are often used to measure the background signal containing little or almost no fluorescence, helping to eliminate spectral interference from other environmental factors.

[0107] Step 2: Calculate the specific value of the fluorescence quantum yield according to the seawater chlorophyll concentration and the fluorescence baseline height value.

[0108] Specifically, the specific value of the fluorescence quantum yield can be calculated according to the third formula; the third formula is:

[0109] ;

[0110] wherein, the FLH is the fluorescence baseline height value; the is the fluorescence quantum yield; the Chla is the seawater chlorophyll concentration.

[0111] Furthermore, after obtaining the fluorescence baseline height value according to the second formula and continuing to calculate the specific value of the fluorescence quantum yield according to the seawater chlorophyll concentration using the third formula, then the type of algal bloom can be determined according to the specific value and the threshold value.

[0112] Specifically, when the specific value is greater than the threshold value, it is determined that the type of algal bloom is diatom; when the specific value is less than or equal to the threshold value, it is determined that the type of algal bloom is dinoflagellate.

[0113] It should be noted that, referring to the previous description, the boundary value of the fluorescence quantum yield is set by summarizing the different fluorescence quantum yields of diatoms and dinoflagellates during multiple algal bloom events. In this application, it is not limited. For example, in one embodiment, the boundary 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 boundary value, the type of algal bloom is determined to be diatoms; when the specific value of the fluorescence quantum yield of the algae is less than or equal to the boundary value, the type of algal bloom is determined to be dinoflagellates. Further, different boundary values can be set for the algae to be distinguished according to the different fluorescence quantum yields of different algae during the algal bloom event. For example, in one embodiment, diatoms and dinoflagellates can be distinguished by comparing the specific value with the boundary value. At this time, the boundary 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 diatoms; 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 dinoflagellates.

[0114] The algal bloom water body identification and classification method provided in this embodiment determines the target wavelength value that can reflect the fluorescence characteristics of algae and the reference wavelength value that is not affected by fluorescence. In this way, when using the data of the geostationary ocean color imager for algal bloom water body identification and classification, 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, it is determined whether there is an algal bloom based on the algal bloom index and the seawater chlorophyll concentration. Since the algal bloom index is calculated from 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 change caused by algae. The chlorophyll concentration is a direct indicator of the growth and reproduction of algae and can provide quantitative data on the algal biomass in the water body. The algal bloom index reflects the population characteristics of algae, pays more attention to the light reflection characteristics of algae, and can detect the impact of algae on the water color. The chlorophyll concentration reflects the algal biomass and provides quantitative data on the number of algae. When the two are used in combination, the sensitivity to the growth change of algae can be improved, and high monitoring sensitivity and stability can be maintained at different algal growth stages and different environmental conditions, avoiding misjudgment that may be caused by a single indicator, and more accurately judging whether an algal bloom has occurred in the water body. Further, both the algal bloom index and the chlorophyll concentration can be obtained through remote sensing technology and have strong spatial resolution ability. Combining these two indicators can achieve efficient monitoring and classification in a large range of waters, and can provide reliable data on the algal growth status at different time and space scales, facilitating the global assessment of water quality and ecological conditions. In addition, the spectral parameters of dinoflagellates and diatoms obtained in the algal culture experiment are used to determine that the target parameter for distinguishing dinoflagellates and diatoms is the fluorescence quantum yield, and the boundary value of the fluorescence quantum yield for distinguishing dinoflagellates and 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 algal 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 the fluorescence quantum yield of these two types of algae can be accurately captured, which helps to improve the classification accuracy. Further, the setting of the boundary value further clarifies the judgment standard to ensure that when an algal bloom occurs, it can be accurately identified which type of algae dominates the change in the water body; in addition, in this application, the data obtained by using the geostationary ocean color imager can achieve efficient algal monitoring in a large range, with higher sensitivity and accuracy.

[0115] Corresponding to the embodiment of the method for constructing the foregoing adaptive filtering model, the present application also provides an embodiment of an algal bloom water body identification and classification device. Figure 5 It is a schematic structural diagram of the first embodiment of the algal bloom water body identification and classification device provided by the present application. Please refer to Figure 5 The device provided in this embodiment includes a determination module 510, a calculation module 520, and an acquisition module 530, where

[0116] 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;

[0117] The calculation module 520 is used to determine a target parameter that can distinguish dinoflagellates and diatoms based on the spectral parameters of dinoflagellates and diatoms obtained in the algal culture experiment, and determine the boundary value of the target parameter when distinguishing dinoflagellates and diatoms; wherein, the target parameter is the fluorescence quantum yield;

[0118] The acquisition module 530 is used to obtain 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 ocean color imager when using the data of the geostationary ocean color imager for algal bloom water body identification and classification;

[0119] The determination module 510 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 there is an algal bloom according to the algal bloom index and the seawater chlorophyll concentration;

[0120] 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 it is determined that there is an algal bloom, and determine the type of the algal bloom according to the specific value and the boundary value.

[0121] The device of this embodiment can be used to execute Figure 1 The steps of the method embodiment shown, and the specific implementation principle and process are similar, and will not be elaborated here.

[0122] The above are only the preferred embodiments of the present application, and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope 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 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.

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: THE F = 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 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: ； Among them, the is the fluorescence baseline height value; represents the nLw value of the fluorescence peak band; Indicates the right reference band value; Indicates the left reference band value; is the central wavelength of the fluorescence band; is the central wavelength of the right reference band; is the center wavelength of the left reference band.

7. The method according to claim 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: ； Among them, the is the fluorescence baseline height value; is the fluorescence quantum yield; is the chlorophyll concentration of the 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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