CN116912672A - Unmanned survey vessel-based biological integrity evaluation method for large benthonic invertebrates - Google Patents
Unmanned survey vessel-based biological integrity evaluation method for large benthonic invertebrates Download PDFInfo
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Abstract
The invention relates to the technical field of ecological environment evaluation and treatment, and discloses a large benthonic invertebrate biological integrity evaluation method based on an unmanned measuring vessel.
Description
Technical Field
The invention relates to the technical field of ecological environment evaluation and treatment, in particular to a large benthonic invertebrate biological integrity evaluation method based on an unmanned survey vessel.
Background
Large benthonic invertebrates are invertebrates that live throughout or most of their life history at the bottom of a body of water, typically over 500 microns in length, and are relatively large in size. They are generally very sensitive to changes in the water environment and have an extremely important role in the health and stability of the water ecosystem. The large benthic invertebrates include crustaceans, gastropods, hirsutides, echinoderms, sponges, coelenterates, and the like. They have unique morphology and function, have important ecological value and biological significance, and are often used as research objects of water ecological environment index species.
In the prior art, with the increasing human activity, the aquatic ecosystem has been increasingly threatened, resulting in serious disruption of the biological integrity of large benthic invertebrates. The existing large benthonic invertebrate biological integrity evaluation method mainly depends on traditional manual sampling and field investigation, but the method has the defects of low sampling efficiency, high cost, long time consumption and the like, and is difficult to meet the biological integrity evaluation requirement of large-scale and high space-time resolution. Therefore, an efficient, quantitative assessment method is needed. Sample data are acquired by adopting an unmanned measuring ship and a remote sensing technology, the time and space limitations are avoided, the biological integrity assessment with large scale and high resolution can be realized, the biological integrity of a large benthic invertebrate can be accurately assessed, and a scientific basis is provided for ecological protection and resource management; in view of this, we propose a method for evaluating the biological integrity of large benthic invertebrates based on unmanned survey vessels.
Disclosure of Invention
The invention aims to provide a large benthonic invertebrate biological integrity evaluation method based on an unmanned survey vessel, so as to solve the problems in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions: a method for evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel, the method comprising the steps of:
s1, acquiring a position coordinate of a monitored water area, a survey route and a monitoring sample point;
s2, planning unmanned survey ship routes and tasks, and preparing related monitoring equipment;
s3, collecting sample data through an unmanned measuring ship carrying high-resolution remote sensing equipment;
s4, image processing analysis and extraction of information of the large benthonic invertebrate;
s5, species identification and quantity calculation of the large benthonic invertebrates;
s6, establishing a system dynamics integral model;
s7, constructing an evaluation index and an evaluation method;
s8, assessing the health condition of the large benthic invertebrate;
s9, calculating the biological integrity score of the large benthic invertebrate;
s10, scoring the biological integrity of the large benthic invertebrate;
s11, outputting an evaluation result, and verifying and optimizing.
Optionally, in the step S1, the water area position coordinate is obtained through a technical approach, where the technical approach includes:
geographic information system software; the geographic information system software marks the water area position on the map and acquires corresponding longitude and latitude coordinates;
satellite remote sensing technology; the satellite remote sensing technology acquires a high-resolution image of a water area, extracts water area position information from the image, designs a survey route according to a monitoring purpose and monitoring parameters, and can use sampling methods such as random sampling, system sampling, hierarchical sampling and the like to ensure that samples are representative. And selecting a proper investigation route to cover different areas and water depths of the water area by considering the geographical characteristics of the water area, the water flow dynamics, the water depth change and other factors. Survey routes can be planned and calibrated using auxiliary tools such as maps, satellite images, and the like. Selecting a proper monitoring sample point. The positions of the sampling points, such as the positions close to the outlet, the inlet, the estuary and the like of the water body, and the sampling points with different water depths and vegetation coverage degrees, can be considered. The number and distribution of the sampling points are required to be reasonably arranged according to the monitoring purpose and the resource limitation, and a plurality of sampling points are usually required to be arranged on a survey route so as to obtain more comprehensive monitoring data;
designing the route and task area of the survey ship according to the monitoring targets and parameters: and (3) selecting proper airlines and mission areas by considering factors such as geographical features of the water area, water flow dynamics, water depth change and the like, and ensuring that a monitoring range covers a key area of the target water area. And selecting a proper unmanned measuring ship model, and configuring corresponding monitoring equipment and sensors, such as a water quality sensor, a water temperature sensor, a water level sensor and the like. The equipment is ensured to have high precision, high stability and high reliability, and can meet the monitoring requirement. Meanwhile, equipment is installed and debugged, and normal operation of the equipment is ensured. Before formal monitoring, unmanned survey vessels are tested and validated, including ship performance testing, sensor calibration and validation, and line and mission area validation, etc. Through testing and verification, it is ensured that the survey vessel can accurately and reliably perform predetermined airlines and tasks.
Optionally, the step S3 further includes: the submarine substrates with different depths can be identified by using a multispectral or hyperspectral imaging technology, and whether the submarine invertebrates exist under the submarine substrates can be judged by the reflectivity of the spectrum; so as to understand the distribution range and the density distribution condition of the materials; the acoustic profile of the benthic invertebrate can be obtained using sonar techniques. Such as the size, morphology and number of invertebrates. The laser scanning technology can acquire three-dimensional morphological data of the benthonic invertebrate, and the size, morphology, structure, distribution and the like of the benthonic invertebrate can be known by accurately measuring the three-dimensional morphological data.
Optionally, the S4 includes: denoising, correcting, enhancing and the like are carried out on the acquired image data so as to improve the accuracy and reliability of subsequent processing and analysis; and extracting outline and key characteristic points of benthonic animals according to morphological characteristics, texture characteristics, color characteristics and the like of the large benthonic invertebrates for subsequent species identification and quantity calculation.
Optionally, the step S5 includes: through the study and analysis of a large number of benthonic invertebrate data, a computer automatically learns the rules and modes in the data, so that species identification and counting are carried out on benthonic invertebrates;
extracting local features of the processed image by using a SIFT, SURF, ORB feature point extraction algorithm, and then performing image matching by using a feature matching algorithm, so that species identification of benthonic animals is realized;
and calculating the number of all the detected benthonic animals through feature point matching, so as to realize the counting of benthonic animals. Meanwhile, manual labeling and verification are needed to ensure the accuracy of identification and counting.
Optionally, the step S6 includes: for health evaluation of large benthonic invertebrates, a mathematical model can be established by adopting an integral model of system dynamics, and analysis and evaluation can be carried out;
the integral model can comprehensively analyze the relation of the accumulated change of a plurality of variables in time, and is very suitable for describing the life cycle of benthonic invertebrate and the dynamic change of the number, distribution, growth and the like of the benthonic invertebrate. Based on the integral model, a model between the ecological variable and the environmental variable associated with the health of the benthonic invertebrate can be established and a trend in the health of the benthonic invertebrate can be predicted.
Optionally, the step S8 includes: calculating the biological integrity index score may be accomplished by:
s81, determining an evaluation index: establishing an evaluation index system comprising a species richness index, a biomass or density index, a community structure index, a pollution index and the like according to the ecological characteristics and the habitat requirements of the large benthonic invertebrate;
s82, calculating a species richness index S: calculating a species richness index S by using Shannon-Wiener index or Simpson dominance index;
s83, calculating benthic invertebrate biomass or density index: the density index of the large benthic invertebrate is measured or estimated, and the density index can be measured by methods such as manual sampling, oxygen electrode sampling and the like;
s84, calculating benthonic invertebrate community structure index: calculating the composition ratio of different groups of benthic invertebrates;
s85, calculating a pollution index: estimating the productivity of the bottom water area by using an oxygen electrode method or other actual measurement means to evaluate the nutrition status of the surface water body;
s86, calculating a biological integrity index: combining the evaluation results of the four indexes, adopting a weighted average method to formulate a certain weight coefficient for each index, and combining a comprehensive deduction method to give a corresponding evaluation result;
s87, formulating an evaluation standard: and establishing a corresponding evaluation standard by using the scoring result and the index standard to determine the evaluation grade of the biological integrity of the large benthonic invertebrate.
Optionally, the S9 includes: assigning a score to the benthonic invertebrate based on the calculated biological integrity score for the large benthonic invertebrate, the calculation formula being:
BIBIS is a score for evaluating biological integrity index of river and lake large benthic invertebrates; BIBIO is a monitoring value for evaluating the biological integrity index of the large benthic invertebrate in the river and lake; BIBIE is the best expected value of the biological integrity index of the large benthic invertebrate in the water ecological partition of the river and lake.
Optionally, the step S10 includes: the biological integrity evaluation result of the large benthonic animal can be output into a report form, which comprises quantitative description, data chart display and interpretation analysis of the evaluation result, and the evaluation result is displayed in a visual tool form such as a map and a chart, so that visual understanding and analysis are facilitated.
Optionally, the step S11 includes: and verifying and optimizing the evaluation result, wherein the verification comprises comparison verification with actual field investigation data and comparison analysis of different parameter combinations, so that the accuracy and reliability of an evaluation model are improved, the optimization and improvement of the model are carried out, and the evaluation precision and the application range of the method are continuously improved.
Compared with the prior art, the invention provides a large benthonic invertebrate biological integrity evaluation method based on an unmanned survey vessel, which has the following beneficial effects:
according to the method for evaluating the biological integrity of the large benthonic invertebrate based on the unmanned measuring vessel, the unmanned measuring vessel is carried with high-resolution remote sensing equipment to obtain images of the large benthonic invertebrate, an image processing algorithm is utilized to identify and count the large benthonic invertebrate, then a system dynamics integral model is established, and the health condition and the biological integrity of the large benthonic invertebrate are evaluated through indexes such as species diversity, quantity distribution, ecological habit and the like.
Drawings
FIG. 1 is a schematic flow chart of the present invention.
FIG. 2 is a schematic representation of scoring criteria for the biological integrity index of a large benthic invertebrate in accordance with the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1-2, the present invention provides a technical solution: a method for evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel, the method comprising the steps of:
s1, acquiring a position coordinate of a monitored water area, a survey route and a monitoring sample point;
s2, planning unmanned survey ship routes and tasks, and preparing related monitoring equipment;
the water area position coordinates are obtained through a technical approach, which comprises the following steps:
geographic information system software; the geographic information system software marks the water area position on the map and acquires corresponding longitude and latitude coordinates;
satellite remote sensing technology; the satellite remote sensing technology obtains the high-resolution image of the water area, extracts the water area position information from the image, designs a survey route according to the monitoring purpose and the monitoring parameters, and can use sampling methods such as random sampling, system sampling, hierarchical sampling and the like to ensure that the sample is representative. And selecting a proper investigation route to cover different areas and water depths of the water area by considering the geographical characteristics of the water area, the water flow dynamics, the water depth change and other factors. Survey routes can be planned and calibrated using auxiliary tools such as maps, satellite images, and the like. Selecting a proper monitoring sample point. The positions of the sampling points, such as the positions close to the outlet, the inlet, the estuary and the like of the water body, and the sampling points with different water depths and vegetation coverage degrees, can be considered. The number and distribution of the sampling points are required to be reasonably arranged according to the monitoring purpose and the resource limitation, and a plurality of sampling points are usually required to be arranged on a survey route so as to obtain more comprehensive monitoring data;
designing the route and task area of the survey ship according to the monitoring targets and parameters: and (3) selecting proper airlines and mission areas by considering factors such as geographical features of the water area, water flow dynamics, water depth change and the like, and ensuring that a monitoring range covers a key area of the target water area. And selecting a proper unmanned measuring ship model, and configuring corresponding monitoring equipment and sensors, such as a water quality sensor, a water temperature sensor, a water level sensor and the like. The equipment is ensured to have high precision, high stability and high reliability, and can meet the monitoring requirement. Meanwhile, equipment is installed and debugged, and normal operation of the equipment is ensured. Before formal monitoring, unmanned survey vessels are tested and validated, including ship performance testing, sensor calibration and validation, and line and mission area validation, etc. Through testing and verification, it is ensured that the survey vessel can accurately and reliably perform predetermined airlines and tasks.
S3, collecting sample data through an unmanned measuring ship carrying high-resolution remote sensing equipment;
the scheme can identify the submarine substrates with different depths by using a multispectral or hyperspectral imaging technology, and can judge whether the submarine invertebrates exist under the submarine substrates or not by using the reflectivity of the spectrum; so as to understand the distribution range and the density distribution condition of the materials;
the acoustic profile of the benthic invertebrate can be obtained using sonar techniques. Such as the size, morphology and number of invertebrates. The laser scanning technology can acquire three-dimensional morphological data of the benthonic invertebrate, and the size, morphology, structure, distribution and the like of the benthonic invertebrate can be known by accurately measuring the three-dimensional morphological data.
S4, image processing analysis and extraction of information of the large benthonic invertebrate;
the method comprises the steps of denoising, correcting, enhancing and the like on acquired image data to improve the accuracy and reliability of subsequent processing and analysis;
and extracting outline and key characteristic points of benthonic animals according to morphological characteristics, texture characteristics, color characteristics and the like of the large benthonic invertebrates for subsequent species identification and quantity calculation.
S5, species identification and quantity calculation of the large benthonic invertebrates;
through the study and analysis of a large number of benthonic invertebrate data, a computer automatically learns the rules and modes in the data, so that species identification and counting are carried out on benthonic invertebrates;
extracting local features of the processed image by using a SIFT, SURF, ORB feature point extraction algorithm, and then performing image matching by using a feature matching algorithm to realize species identification of benthonic animals, wherein the feature matching algorithm is one or more of FLANN and KNN;
and calculating the number of all the detected benthonic animals through feature point matching, so as to realize the counting of benthonic animals. Meanwhile, manual labeling and verification are needed to ensure the accuracy of identification and counting.
S6, establishing a system dynamics integral model;
for health evaluation of large benthonic invertebrates, a mathematical model can be established by adopting an integral model of system dynamics, and analysis and evaluation can be carried out;
the integral model can comprehensively analyze the relation of the accumulated change of a plurality of variables in time, and is very suitable for describing the life cycle of benthonic invertebrate and the dynamic change of the number, distribution, growth and the like of the benthonic invertebrate. Based on the integral model, a model between the ecological variable and the environmental variable associated with the health of the benthonic invertebrate can be established and a trend in the health of the benthonic invertebrate can be predicted.
S7, constructing an evaluation index and an evaluation method;
s8, assessing the health condition of the large benthic invertebrate;
notably, calculating the biological integrity index score may be accomplished by:
s81, determining an evaluation index: establishing an evaluation index system comprising a species richness index, a biomass or density index, a community structure index, a pollution index and the like according to the ecological characteristics and the habitat requirements of the large benthonic invertebrate;
s82, calculating a species richness index S: calculating a species richness index S by using Shannon-Wiener index or Simpson dominance index;
s83, calculating benthic invertebrate biomass or density index: determination or estimation of the Density index of a large benthic invertebrate, which can be determined by manual sampling, oxygen electrode sampling, and the like, in g/m 2 Or kg/m 2 ；
S84, calculating benthonic invertebrate community structure index: calculating the composition ratio of different groups of benthic invertebrates;
s85, calculating a pollution index: estimating the productivity of the bottom water area by using an oxygen electrode method or other actual measurement means to evaluate the nutrition status of the surface water body;
s86, calculating a biological integrity index: combining the evaluation results of the four indexes, adopting a weighted average method to formulate a certain weight coefficient for each index, and combining a comprehensive deduction method to give a corresponding evaluation result;
s87, formulating an evaluation standard: and establishing a corresponding evaluation standard by using the scoring result and the index standard to determine the evaluation grade of the biological integrity of the large benthonic invertebrate.
S9, calculating the biological integrity score of the large benthic invertebrate;
assigning a score to the benthonic invertebrate based on the calculated biological integrity score for the large benthonic invertebrate, the calculation formula being:
BIBIS is a score for evaluating biological integrity index of river and lake large benthic invertebrates; BIBIO is a monitoring value for evaluating the biological integrity index of the large benthic invertebrate in the river and lake; BIBIE is the best expected value of the biological integrity index of the large benthic invertebrate in the water ecological partition of the river and lake.
S10, scoring the biological integrity of the large benthic invertebrate;
the biological integrity evaluation result of the large benthonic animal can be output into a report form, which comprises quantitative description, data chart display and interpretation analysis of the evaluation result, and the evaluation result is displayed in a visual tool form such as a map and a chart, so that visual understanding and analysis are facilitated.
S11, outputting an evaluation result, and verifying and optimizing.
And verifying and optimizing the evaluation result, wherein the verification comprises comparison verification with actual field investigation data and comparison analysis of different parameter combinations, so that the accuracy and reliability of an evaluation model are improved, the optimization and improvement of the model are carried out, and the evaluation precision and the application range of the method are continuously improved.
The foregoing invention has been generally described in great detail, but it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, it is intended to cover modifications or improvements within the spirit of the inventive concepts.
Claims (10)
1. A method for evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel, which is characterized by comprising the following steps: the method comprises the following steps:
s1, acquiring a position coordinate of a monitored water area, a survey route and a monitoring sample point;
s2, planning unmanned survey ship routes and tasks, and preparing related monitoring equipment;
s3, collecting sample data through an unmanned measuring ship carrying high-resolution remote sensing equipment;
s4, image processing analysis and extraction of information of the large benthonic invertebrate;
s5, species identification and quantity calculation of the large benthonic invertebrates;
s6, establishing a system dynamics integral model;
s7, constructing an evaluation index and an evaluation method;
s8, assessing the health condition of the large benthic invertebrate;
s9, calculating the biological integrity score of the large benthic invertebrate;
s10, scoring the biological integrity of the large benthic invertebrate;
s11, outputting an evaluation result, and verifying and optimizing.
2. A method of evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel as claimed in claim 1, wherein: in the step S1, the water area position coordinates are obtained through a technical approach, wherein the technical approach comprises the following steps:
geographic information system software; the geographic information system software marks the water area position on the map and acquires corresponding longitude and latitude coordinates;
satellite remote sensing technology; the satellite remote sensing technology acquires a high-resolution image of a water area, extracts water area position information from the high-resolution image, and designs a survey route according to a monitoring purpose and monitoring parameters.
3. A method of evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel as claimed in claim 1, wherein: the step S3 further includes:
the submarine substrates with different depths can be identified by using a multispectral or hyperspectral imaging technology, and whether the submarine invertebrates exist under the submarine substrates can be judged by the reflectivity of the spectrum;
the acoustic profile of the benthic invertebrate can be obtained using sonar techniques.
4. A method of evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel as claimed in claim 1, wherein: the step S4 comprises the following steps:
denoising, correcting and enhancing the acquired image data;
and extracting outline and key feature points of the benthonic animal according to morphological features, texture features and color features of the large benthonic invertebrate.
5. A method of evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel as claimed in claim 1, wherein: the step S5 comprises the following steps: species identification and enumeration of benthonic invertebrates by learning and analyzing a plurality of benthonic invertebrate data, the computer automatically learning rules and patterns therein;
extracting local features of the processed image by using a SIFT, SURF, ORB feature point extraction algorithm, and then performing image matching by using a feature matching algorithm to realize species identification of benthonic animals;
the number of all benthonic animals detected is calculated by the feature point matching.
6. A method of evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel as claimed in claim 1, wherein: the step S6 comprises the following steps: and (3) evaluating the health of the large benthic invertebrate, and establishing a mathematical model by adopting an integral model of system dynamics, and analyzing and evaluating.
7. A method of evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel as claimed in claim 1, wherein: the step S8 comprises the following steps: calculating the biological integrity index score may be accomplished by:
s81, determining an evaluation index: establishing an evaluation index system according to ecological characteristics and habitat requirements of the large benthonic invertebrate, wherein the evaluation index system comprises a species richness index, a biomass or density index, a community structure index and a pollution index;
s82, calculating a species richness index S: calculating a species richness index S by using Shannon-Wiener index or Simpson dominance index;
s83, calculating benthic invertebrate biomass or density index: determining or estimating a density index of the large benthic invertebrate;
s84, calculating benthonic invertebrate community structure index: calculating the composition ratio of different groups of benthic invertebrates;
s85, calculating a pollution index: estimating the productivity of the bottom water area by using an oxygen electrode method, and evaluating the nutrition status of the surface water body by other actual measurement means;
s86, calculating a biological integrity index: combining the evaluation results of the four indexes, adopting a weighted average method to formulate a certain weight coefficient for each index, and combining a comprehensive deduction method to give a corresponding evaluation result;
s87, formulating an evaluation standard: and establishing a corresponding evaluation standard by using the scoring result and the index standard to determine the evaluation grade of the biological integrity of the large benthonic invertebrate.
8. A method of evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel as claimed in claim 1, wherein: the step S9 includes: assigning a score to the benthonic invertebrate based on the calculated biological integrity score for the large benthonic invertebrate, the calculation formula being:
BIBIS is a score for evaluating biological integrity index of river and lake large benthic invertebrates; BIBIO is a monitoring value for evaluating the biological integrity index of the large benthic invertebrate in the river and lake; BIBIE is the best expected value of the biological integrity index of the large benthic invertebrate in the water ecological partition of the river and lake.
9. A method of evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel as claimed in claim 1, wherein: the S10 comprises the step of outputting the biological integrity evaluation result of the large benthonic animal into a report form, wherein the report form comprises quantitative description, data chart display and interpretation analysis of the evaluation result.
10. A method of evaluating the biological integrity of a large benthonic invertebrate based on an unmanned survey vessel as claimed in claim 1, wherein: the step S11 includes: and verifying and optimizing the evaluation result, wherein the verification and optimization comprises comparison and analysis of comparison and verification with actual field investigation data and different parameter combinations.
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