CN117725345B - Multi-source remote sensing green tide growth rate measuring method based on green tide biomass density - Google Patents
Multi-source remote sensing green tide growth rate measuring method based on green tide biomass density Download PDFInfo
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Abstract
A multi-source remote sensing green tide growth rate measuring method based on green tide biomass density comprises the following steps: s1, calculating a green tide biomass related index by using remote sensing data of a green tide, and converting a calculation result of the green tide biomass related index into a green tide biomass density; s2, according to the relation between the green tide biomass density and the green tide growth rate, which are determined based on biological culture experimental data, a self-shading limiting function between the green tide biomass density and the green tide growth rate, which is calculated based on remote sensing data, is fitted in the step S1; and S3, constructing a green tide growth rate calculation function according to the environmental factor influence function and the self-shading limiting function, so as to determine the green tide growth rate through the green tide growth rate calculation function. The method improves the monitoring and calculating precision of the green tide growth rate based on remote sensing data.
Description
Technical Field
The invention relates to the field of green tide remote sensing monitoring, in particular to a multi-source remote sensing green tide growth rate measuring method based on green tide biomass density.
Background
The principle of the green tide growth rate measuring method is as follows: quantifying the influence of environmental factors on green tide growth and death, wherein the influence comprises nutrient salt concentration, sea surface temperature, illumination intensity, green tide density and other factors; the green tide growth rate calculation method by integrating different data sources comprises the following main processes: ① Acquiring environmental data affecting green tide growth; ② Fitting influence functions of different environmental factors on green tide growth; ③ Constructing a green tide growth rate function; ④ And calculating to obtain the green tide growth rate.
At present, the green tide growth rate measuring method is divided into two cases: 1) A green tide growth rate calculation model based on multi-source remote sensing data; 2) A model was calculated based on the green tide growth rate of the biological culture data.
The green tide growth rate calculation model based on the multi-source remote sensing data comprises the following processing flows: preprocessing remote sensing data of environmental factors required by green tide growth, constructing a function of sea surface temperature, illumination intensity and nutrient salt concentration on the influence of the green tide growth rate, and calculating to obtain the green tide growth rate;
the green tide growth rate calculation model based on the biological culture data comprises the following processing flows: the green tide growth rate is calculated by constructing a function of the influence of sea surface temperature, illumination intensity and nutrient salt concentration on the green tide growth rate, namely adding a self-shading limiting function caused by green tide density, and performing an environment factor control experiment required by green tide growth.
At present, a method for calculating green tide growth based on multi-source remote sensing data is more suitable for monitoring large-scale green tide disasters which occur actually, but the method lacks calculation of a self-shading limiting function caused by high biomass density of green tide, so that the accuracy of an actual calculation result is inaccurate. The green tide growth rate calculated based on the biological culture data is limited by self-shading caused by high green tide biomass density, but lacks a function mapped into remote sensing data, cannot be directly applied to remote sensing image data, and cannot realize large-scale rapid and dynamic green tide growth rate calculation.
It should be noted that the information disclosed in the above background section is only for understanding the background of the application and thus may include information that does not form the prior art that is already known to those of ordinary skill in the art.
Disclosure of Invention
The invention aims to overcome the defects of the background technology and provides a multi-source remote sensing green tide growth rate measuring method based on green tide biomass density.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a multi-source remote sensing green tide growth rate measuring method based on green tide biomass density comprises the following steps:
S1, calculating a green tide biomass related index by using remote sensing data of a green tide, and converting a calculation result of the green tide biomass related index into a green tide biomass density;
S2, according to the relation between the green tide biomass density and the green tide growth rate, which are determined based on biological culture experimental data, a self-shading limiting function between the green tide biomass density and the green tide growth rate, which is calculated based on remote sensing data, is fitted in the step S1;
And S3, constructing a green tide growth rate calculation function according to the environmental factor influence function and the self-shading limiting function, so as to determine the green tide growth rate through the green tide growth rate calculation function.
Further:
The green tide biomass related index comprises a floating algae index or a normalized difference vegetation index.
In the step S1, DN values obtained by preprocessing the remote sensing data are converted into Rayleigh correction reflectivities, the floating algae indexes are calculated according to the Rayleigh correction reflectivities, and the calculation result of the floating algae indexes is converted into the green tide biomass density.
In step S1, the formula for calculating the floating algae index is as follows:
Wherein FAI represents a floating algae index value; 、/> /> Respectively represent the wave bands/>、/>/>Rayleigh corrected reflectance values; /(I)、/>/>Center wavelengths of 645nm, 859nm and 1240nm in the remote sensing image are respectively represented;
The formula for converting the calculation result of the floating algae index into the green tide biomass density is as follows:
where y represents the green tide biomass density per square meter and x represents the value of the floating algal body index.
The preprocessing includes one or more of radiation correction, geometric correction, rayleigh correction, and clipping mosaics.
In step S2, the relationship between the green tide biomass density and the green tide growth rate determined based on the biological culture experimental data is represented by the following formula:
In the method, in the process of the invention, Representing a self-shading restriction function due to green tide biomass density; /(I)Represents green tide biomass density;
the formula of the fitted self-shading limiting function is as follows:
In the method, in the process of the invention, Representing a self-shading limiting function caused by the fitted green tide biomass density suitable for the remote sensing data; /(I)Both y and y represent green tide biomass density.
In step S3, the formula for constructing the green tide growth rate calculation function is as follows:
wherein, Representing green tide growth rate; /(I)、/>、/>The functions of nutrient salt, sea surface temperature and illumination intensity for influencing the growth of green tide are respectively represented, and the values of the functions are respectively calculated values of multi-source remote sensing data.
And using the calculated values of the remote sensing image by the functions corresponding to the nutrient salt, the sea surface temperature and the illumination intensity.
A computer readable storage medium storing a computer program which, when executed by a processor, implements the multi-source remote sensing green tide growth rate measurement method.
The invention has the following beneficial effects:
The invention provides a multisource remote sensing green tide growth rate measuring method based on green tide biomass density, which introduces a processing method for mapping a green tide self-shading function obtained based on biological culture data to a green tide remote sensing index, and the influence of the green tide biomass density on the green tide growth rate is added in the calculation of the green tide growth rate; the method has the advantages that the green tide self-shading function caused by the green tide density is mapped into the remote sensing calculation index, the function curve between the green tide biological density and the growth rate is fitted, the situation that the result precision is low due to the lack of self-shading limitation caused by the green tide density when the green tide growth rate calculation is carried out based on multi-source remote sensing data is made up, the precision of the green tide growth rate calculation based on the multi-source remote sensing data is improved, and better technical support is provided for monitoring and preventing green tide disasters.
Aiming at the defects that the existing method for measuring the growth rate of the green tide based on the multi-source remote sensing data lacks the self-shading limitation caused by the high biomass density of the green tide and is easy to influence the measurement result of the growth rate of the green tide in a large range, the invention provides the method for measuring the growth rate of the green tide based on the biomass density of the green tide, and the defects are effectively avoided. The invention provides a technical idea of mapping a green tide self-shading function to a green tide remote sensing calculation index, wherein the green tide self-shading function obtained based on biological culture data is mapped to the green tide index calculated by the remote sensing data, the influence of green tide biomass density on algae growth is added on the basis of calculating the green tide growth rate by multi-source remote sensing data, the biological significance of green tide monitoring calculation on a large space scale is perfected, and the monitoring calculation precision of measuring the green tide growth rate based on the remote sensing data is improved.
Compared with the traditional method, the method has the advantages that the processing method for measuring the growth rate of the green tide is constructed by mapping the function of the biomass density of the green tide, which is obtained based on biological culture experimental data and influences the growth of the green tide, into the remote sensing data, so that the problem of inaccurate calculation result caused by the lack of a self-shading limiting function in the existing method for calculating the growth rate of the green tide based on the remote sensing data is effectively solved. The self-shading limiting function is mainly caused by the high biomass density of green tide, and the measuring method of the invention adds the function, compensates the explanation of biological mechanism for calculating the growth rate of green tide based on remote sensing data, remarkably improves the monitoring effect of multi-source environmental factors on the biomass influence of green tide, and provides more accurate and reliable technical support for monitoring the disaster of green tide.
Other advantages of embodiments of the present invention are further described below.
Drawings
FIG. 1 is a flow chart of a method for measuring the growth rate of a multi-source remote sensing green tide based on the biomass density of the green tide in an embodiment of the invention.
Fig. 2 is a flowchart of preprocessing multisource remote sensing data according to an embodiment of the present invention.
Detailed Description
The following describes embodiments of the present invention in detail. It should be emphasized that the following description is merely exemplary in nature and is in no way intended to limit the scope of the invention or its applications.
Referring to fig. 1, an embodiment of the present invention provides a method for measuring a growth rate of a green tide by multi-source remote sensing based on a biomass density of the green tide, comprising the steps of:
s1, calculating a green tide biomass related index by using remote sensing data of a green tide, and converting a calculation result of the green tide biomass related index into a green tide biomass density; the green tide biomass related index includes a floating algae index (Floating Algae Index, FAI) or a normalized difference vegetation index (Normalized Difference Vegetation Index, NDVI), preferably a floating algae index, but the invention is not limited thereto;
S2, according to the relation between the green tide biomass density and the green tide growth rate, which are determined based on biological culture experimental data, a self-shading limiting function between the green tide biomass density and the green tide growth rate, which is calculated based on remote sensing data, is fitted in the step S1;
S3, constructing a green tide growth rate calculation function according to an environmental factor influence function (such as a function of influence of nutrient salt, sea surface temperature, illumination intensity and the like on green tide growth) and the self-shading limiting function, so as to determine the green tide growth rate through the green tide growth rate calculation function.
Aiming at the defects that the existing method for measuring the green tide growth rate based on multi-source remote sensing data lacks of self-shading limitation caused by high green tide biomass density and is easy to influence a large-scale green tide growth rate calculation result, the invention provides the method for measuring the green tide growth rate based on multi-source remote sensing biomass density, and the problems are effectively solved. The invention provides a technical idea of mapping a green tide self-shading function to a green tide remote sensing calculation index, wherein the green tide self-shading function obtained based on biological culture data is mapped to the green tide index calculated by the remote sensing data, so that the influence of green tide biomass density on algae growth is added on the basis of calculating the green tide growth rate by multi-source remote sensing data, the biological significance of green tide monitoring calculation on a large space scale is perfected, and the accuracy of measuring the green tide growth rate based on the remote sensing data is improved.
Specific embodiments of the present invention are described further below.
The flow chart of the multi-source remote sensing green tide growth rate measuring method based on green tide biomass density is shown in fig. 1. As an example, the main steps of an embodiment are as follows:
1. searching key factors of mapping green tide self-shading function to remote sensing data
The key point of the influence function of the green tide biomass density is that the self-shading limit generated by the green tide algae with high biomass density can influence the whole growth of the green tide. Mapping the function into the remote sensing image requires the introduction of a key factor of green tide biomass density. When calculating green tide based on remote sensing data, commonly used calculated indices include floating algae index (Floating Algae Index, FAI) and Normalized Difference Vegetation Index (NDVI). But the floating algae index is more suitable for mixed pixel decomposition, and can convert the calculated value into green tide biomass in unit area according to measured data.
(1) MODIS (medium resolution imaging spectrometer) remote sensing data preprocessing: including radiation correction, geometric correction, clipping mosaicing, etc. Fig. 2 is a flow chart of preprocessing multi-source telemetry data according to an embodiment.
(2) Calculating floating algae index: DN values obtained by preprocessing remote sensing data are converted into Rayleigh correction reflectivity through SeaDAS software; then, according to the Rayleigh correction reflectivity, calculating a floating algae index in the MODIS image, wherein the formula is as follows:
Wherein FAI represents a floating algae index value; 、/> /> Respectively represent the wave bands/>、/>/>Rayleigh corrected reflectance values; /(I)、/>/>Center wavelengths of 645nm, 859nm and 1240nm in the MODIS image are shown, respectively.
(3) Conversion of green tide biomass per unit area: the floating algae index calculation was converted to green tide biomass density by the formula shown below:
Wherein y represents the green tide biomass density per square meter (unit: kg/m 2); x represents the value of the calculation index of the floating type algae.
2. Fitting a function between green tide biomass density and green tide growth rate
After the green tide biomass density in the unit area is calculated based on the remote sensing data, the relationship between the green tide biomass density and the growth rate in the biological culture method is combined, and the relationship is fitted, so that the green tide biomass density factor is suitable for the green tide biomass density factor in the unit area obtained by the remote sensing data calculation.
(1) The function between green tide biomass density and green tide growth rate based on biological culture experimental data is as follows:
In the method, in the process of the invention, Representing a self-shading restriction function due to green tide biomass density; /(I)The green tide biomass density is shown in molCm -2 units.
(2) Fitting a function between green tide biomass density and green tide growth rate calculated based on remote sensing data, wherein the fitted formula is as follows:
In the method, in the process of the invention, Representing a self-shading limiting function caused by the fitted green tide biomass density suitable for the remote sensing data; /(I)Both y and y represent green tide biomass density in kg/m 2.
3. Construction of green tide growth Rate calculation function
After fitting the function between green tide biomass density and green tide growth rate, perfecting the method for calculating green tide growth rate based on remote sensing data, wherein the formula is as follows:
wherein, Representing green tide growth rate; /(I)、/>、/>/>The functions of nutrient salt, sea surface temperature, illumination intensity and influence of self-shading limitation on green tide growth are respectively represented, and the values of the functions are respectively calculated values of multi-source remote sensing data.
Compared with the traditional method, the method has the advantages that the processing method for measuring the growth rate of the green tide is constructed by mapping the function of the biomass density of the green tide, which is obtained based on biological culture experimental data and influences the growth of the green tide, into the remote sensing data, so that the problem of inaccurate calculation result caused by the lack of a self-shading limiting function in the existing method for calculating the growth rate of the green tide based on the remote sensing data is effectively solved. The self-shading limiting function is mainly caused by the high biomass density of green tide, and the measuring method of the invention adds the function, compensates the explanation of biological mechanism for calculating the growth rate of green tide based on remote sensing data, remarkably improves the monitoring effect of multi-source environmental factors on the biomass influence of green tide, and provides more accurate and reliable technical support for monitoring the disaster of green tide.
The embodiments of the present invention also provide a storage medium storing a computer program which, when executed, performs at least the method as described above.
The embodiment of the invention also provides a control device, which comprises a processor and a storage medium for storing a computer program; wherein the processor is adapted to perform at least the method as described above when executing said computer program.
The embodiments of the present invention also provide a processor executing a computer program, at least performing the method as described above.
The storage medium may be implemented by any type of non-volatile storage device, or combination thereof. The nonvolatile Memory may be a Read Only Memory (ROM), a programmable Read Only Memory (PROM, programmable Read-Only Memory), an erasable programmable Read Only Memory (EPROM, erasableProgrammable Read-Only Memory), an electrically erasable programmable Read Only Memory (EEPROM, electricallyErasable Programmable Read-Only Memory), a magnetic random Access Memory (FRAM, ferromagneticRandom Access Memory), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a compact disk Read Only Memory (CD-ROM, compact Disc Read-Only Memory); the magnetic surface memory may be a disk memory or a tape memory. The storage media described in embodiments of the present invention are intended to comprise, without being limited to, these and any other suitable types of memory.
In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described as separate units may or may not be physically separate, and units displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, where the foregoing program may be stored in a computer readable storage medium, and when executed, the program performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or optical disk, or the like, which can store program codes.
Or the above-described integrated units of the invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
The methods disclosed in the method embodiments provided by the invention can be arbitrarily combined under the condition of no conflict to obtain a new method embodiment.
The features disclosed in the several product embodiments provided by the invention can be combined arbitrarily under the condition of no conflict to obtain new product embodiments.
The features disclosed in the embodiments of the method or the apparatus provided by the invention can be arbitrarily combined without conflict to obtain new embodiments of the method or the apparatus.
The foregoing is a further detailed description of the invention in connection with the preferred embodiments, and it is not intended that the invention be limited to the specific embodiments described. It will be apparent to those skilled in the art that several equivalent substitutions and obvious modifications can be made without departing from the spirit of the invention, and the same should be considered to be within the scope of the invention.
Claims (7)
1. The multi-source remote sensing green tide growth rate measuring method based on green tide biomass density is characterized by comprising the following steps of:
S1, calculating a green tide biomass related index by using remote sensing data of a green tide, and converting a calculation result of the green tide biomass related index into a green tide biomass density;
S2, according to the relation between the green tide biomass density and the green tide growth rate, which are determined based on biological culture experimental data, a self-shading limiting function between the green tide biomass density and the green tide growth rate, which is calculated based on remote sensing data, is fitted in the step S1;
Wherein, the relationship between the green tide biomass density and the green tide growth rate determined based on the biological culture experimental data is shown by the following formula:
；
In the method, in the process of the invention, Representing a self-shading restriction function due to green tide biomass density; /(I)Represents green tide biomass density;
the formula of the fitted self-shading limiting function is as follows:
；
；
In the method, in the process of the invention, Representing a self-shading limiting function caused by the fitted green tide biomass density suitable for the remote sensing data; y represents green tide biomass density per square meter;
S3, constructing a green tide growth rate calculation function according to an environmental factor influence function and a fitted self-shading limit function, so as to determine the green tide growth rate through the green tide growth rate calculation function, wherein the environmental factor influence function comprises a function of influencing green tide growth by nutrient salt, sea surface temperature and illumination intensity, and the functions corresponding to the nutrient salt, the sea surface temperature and the illumination intensity are calculated values of multi-source remote sensing data respectively.
2. The method for measuring the growth rate of a green tide by multi-source remote sensing based on the green tide biomass density as claimed in claim 1, wherein the green tide biomass related index comprises a floating algae index or a normalized difference vegetation index.
3. The method for measuring the growth rate of the multi-source remote sensing green tide based on the green tide biomass density according to claim 1, wherein the green tide biomass related index is a floating type algae index, in the step S1, DN values obtained by preprocessing the remote sensing data are converted into rayleigh corrected reflectivities, the floating type algae index is calculated according to the rayleigh corrected reflectivities, and the calculation result of the floating type algae index is converted into the green tide biomass density.
4. A method for measuring the growth rate of a green tide by multi-source remote sensing based on the biomass density of the green tide as claimed in claim 3, wherein in the step S1, the formula for calculating the index of the floating algae is as follows:
；
Wherein FAI represents a floating algae index value; 、/> /> Respectively represent the wave bands/>、/>/>Rayleigh corrected reflectance values; /(I)、/>/>Center wavelengths of 645nm, 859nm and 1240nm in the remote sensing image are respectively represented;
The formula for converting the calculation result of the floating algae index into the green tide biomass density is as follows:
；
Wherein x represents the value of the floating algal body index.
5. The green tide biomass density based multi-source remote sensing green tide growth rate measuring method according to claim 3, wherein said pre-processing comprises one or more of radiation correction, geometric correction, rayleigh correction and clipping mosaics.
6. The method for measuring the growth rate of a green tide by multi-source remote sensing based on the biomass density of the green tide according to any one of claims 1 to 5, wherein in the step S3, the formula for constructing the green tide growth rate calculation function is as follows:
；
wherein, Representing green tide growth rate; /(I)、/>、/>The functions of nutrient salt, sea surface temperature and illumination intensity on green tide growth are respectively shown.
7. A computer readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the multi-source remote sensing green tide growth rate measurement method according to any of claims 1 to 6.
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