CN117114453A - Marine carbon sink state evaluation system based on aquatic organism observation - Google Patents
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Abstract
The invention relates to the technical field of ocean carbon sink, and because the carbon fixing capability of ocean plants is higher than that of all other types of ocean ecological systems, and aquatic organisms comprise aquatic plants, the invention provides an ocean carbon sink state evaluation system based on aquatic organism observation, which evaluates the ocean carbon sink state of the aquatic plants, and discloses an ocean carbon sink state evaluation system based on the aquatic organism observation, which comprises the following components: a grid detection group; a plurality of monitoring piles; the sampling module is used for collecting a current plant sample at a current sampling time point in the grid detection group and periodically obtaining a plant actual measurement sample before the current sampling time point; the processing module is used for obtaining a sample distance between the two samples according to the plant prediction sample and the current plant sample; an analysis module; and the evaluation module is used for acquiring all current plant sample data of which the sample distance is smaller than the preset sample distance threshold value, and evaluating the ocean carbon sink state of the target monitoring area according to the current plant sample data.
Description
Technical Field
The invention relates to the technical field of ocean carbon sink, in particular to an ocean carbon sink state evaluation system based on aquatic organism observation.
Background
Ocean carbon sequestration refers to a process and mechanism of absorbing and solidifying carbon dioxide in the atmosphere with the ocean as a specific carrier, refers to the ability or capacity of ocean carbon storage for a period of time, also known as blue carbon, and it is investigated that more than half of the circulation and fixation of carbon dioxide on earth is accomplished by the ocean, which can not only store carbon for a long period of time, but also redistribute carbon dioxide, which is the most efficient carbon sequestration.
The coastal 'blue carbon' ecosystem such as mangrove, seaweed beds and salt marsh is the most dense carbon sink area in biosphere, and has the advantages of high productivity, strong suspension capturing capability, low decomposition rate of organic carbon in seaweed bed sediment and relative stability, so that the coastal 'blue carbon' ecosystem has high sediment carbon burying rate and extremely high carbon fixing capability, wherein the carbon fixing capability of marine living plants is higher than that of all other types of marine ecosystems, and quantitative research on the carbon fixing capability of living plants in the marine 'blue carbon' ecosystem is necessary.
Aquatic organisms are a collective term for organisms living in various types of water bodies. Including aquatic higher plants. To evaluate the state of ocean carbon sink, quantitative research on aquatic higher plants in the ocean is necessary, so that an ocean carbon sink state evaluation system based on aquatic organism observation is provided for evaluating the state of ocean carbon sink for plants.
Disclosure of Invention
The invention aims to provide an ocean carbon sink state evaluation system based on aquatic organism observation, which solves the following technical problems:
how to provide an assessment system capable of assessing the state of a marine carbon sink for plants.
The aim of the invention can be achieved by the following technical scheme:
an aquatic organism observation based marine carbon sink state assessment system comprising:
the grid detection group is divided according to the distribution area of the target monitoring area;
the monitoring piles are arranged in the grid detection group and are used for monitoring environmental indexes and plant distribution areas in the grid detection group;
the sampling module is used for collecting a current plant sample at a current sampling time point in the grid detection group and periodically obtaining a plant actual measurement sample before the current sampling time point;
the processing module predicts a plant prediction sample at a current sampling time point according to the obtained plant actual measurement sample, obtains a sample distance between the two samples according to the plant prediction sample and the current plant sample, and corrects the next sampling time according to the sample distance;
the analysis module is used for judging and comparing the sample distance with a preset sample distance threshold, and if the sample distance is not smaller than the preset sample distance threshold, eliminating all sample data in the corresponding grid detection group;
and the evaluation module is used for acquiring all current plant sample data of which the sample distance is smaller than the preset sample distance threshold value, and evaluating the ocean carbon sink state of the target monitoring area according to the current plant sample data.
Preferably, the monitoring pile comprises an environmental index monitoring unit and a shooting unit, wherein the environmental index monitoring unit is used for acquiring environmental indexes, and the shooting unit is used for acquiring plant distribution areas.
Preferably, the process of predicting the plant prediction sample at the current sampling time point according to the obtained plant actual measurement sample comprises the following steps:
establishing a measured data set of the plant measured sample according to the plant measured sample obtained periodically;
analyzing and fitting according to the actual measurement data set to obtain a rule function of each sample parameter changing along with time;
and obtaining a prediction data set of the plant prediction sample at the current sampling time point according to a regular function of each sample parameter changing along with time.
Preferably, the process of obtaining a sample distance between two samples from the plant prediction sample and the current plant sample comprises:
by the formula:
calculating a sample distance between the plant prediction sample and the current plant sample；
Wherein,for the number of items of the sample parameter, +.>，/>Is->Weight coefficient of term sample parameter, +.>Is->Application coefficients of the term sample parameters, +.>Is->Predicted value of item sample parameter +.>Is->The current value of the item sample parameter.
Preferably, the process of correcting the next sampling time according to the sample distance includes:
by the formula:
calculate the next sampling time interval；
Wherein,for the initial sampling time interval, +.>Is a time distance correction function.
Preferably, the process of comparing the sample distance with a preset sample distance threshold comprises:
sample distance between the plant prediction sample and the current plant sampleAnd corresponding threshold condition->And (3) performing comparison:
if it isJudging that the current plant sample is abnormal;
otherwise, judging that the current plant sample is normal, and according to the corrected sampling time intervalThe next sampling is performed.
Preferably, the process of obtaining all current plant sample data with the sample distance smaller than the preset sample distance threshold value and evaluating the ocean carbon sink state of the target monitoring area according to the current plant sample data comprises the following steps:
after preprocessing the current plant sample, measuring the carbon reserves of the current plant sample by adopting an elemental analyzer;
by the formula:
calculating total carbon reserves of plants in target monitoring areas；
Wherein,is->Plant distribution area in the monitoring range of individual monitoring posts, +.>Is->Plant area in sampling range of each monitoring pile, < >>For the initial number of monitoring piles, < > for the initial number of monitoring piles, > for the monitoring of>Predicting a sample distance for the plant from a current plant sample/>The number of monitoring piles greater than the corresponding threshold condition,/->Is->The carbon reserves of the plants in the sampling range of the piles are monitored.
Preferably, the firstThe carbon reserve calculation process of the plants in the sampling range of the monitoring piles comprises the following steps:
by the formula:
calculate the firstMonitoring carbon reserves of plants in the sampling range of the piles;
wherein,as a function of ambient carbon reserves; />Is an environmental index.
The invention has the beneficial effects that: according to the marine carbon sink state evaluation system based on aquatic organism observation, grid detection groups are divided according to the distribution area of a target monitoring area, then a plurality of monitoring piles are arranged in each grid detection group, environmental indexes and plant distribution areas of the monitoring pile areas are monitored through the monitoring piles, so that the carbon reserves of plants in a single monitoring pile sampling range are calculated, and then the total carbon reserves of plants in the target monitoring area are calculated through the carbon reserves of the plants in the single monitoring pile sampling range, so that the plants in the target monitoring area are sampled to obtain the carbon sink state of the target monitoring area;
meanwhile, a plant actual measurement sample is periodically obtained before a current sampling time point, a current plant sample is collected at the current sampling time point, a plant prediction sample at the current sampling time point is obtained according to the obtained plant actual measurement sample, a sample distance between two samples is obtained according to the plant prediction sample and the current plant sample, whether the current plant sample is qualified or not can be judged through the sample distance between the two samples, when the sample distance is smaller than a preset sample distance threshold value, the current plant sample is qualified, the current plant sample can be used as a sample for carbon sink state evaluation, otherwise, the environment or the plant and the like in a current plant sample area can be damaged or polluted, all sample data in a corresponding grid detection group are removed, and the carbon sink state evaluation data of the target monitoring area are not made, so that the accuracy of the carbon sink state evaluation is improved.
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The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic diagram of a system module connection according to 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.
Referring to fig. 1, the present invention is a marine carbon sink state evaluation system based on aquatic organism observation, comprising:
the grid detection group is divided according to the distribution area of the target monitoring area;
the monitoring piles are arranged in the grid detection group and are used for monitoring environmental indexes and plant distribution areas in the grid detection group;
the sampling module is used for collecting a current plant sample at a current sampling time point in the grid detection group and periodically obtaining a plant actual measurement sample before the current sampling time point;
the processing module predicts a plant prediction sample at a current sampling time point according to the obtained plant actual measurement sample, obtains a sample distance between the two samples according to the plant prediction sample and the current plant sample, and corrects the next sampling time according to the sample distance;
the analysis module is used for judging and comparing the sample distance with a preset sample distance threshold value, and eliminating all sample data in the corresponding grid detection group if the sample distance is not smaller than the preset sample distance threshold value;
the evaluation module is used for acquiring all current plant sample data with the sample distance smaller than a preset sample distance threshold value, and evaluating the ocean carbon sink state of the target monitoring area according to the current plant sample data.
According to the technical scheme, the grid detection groups are divided according to the distribution area of the target monitoring area, the dividing method is mainly used for acquiring image data of the target monitoring area through remote sensing monitoring, acquiring the image data of the target monitoring area after pretreatment through radiation correction, geometric correction, atmosphere correction, cloud removal and image standardization, dividing the grid detection groups according to the plant distribution area in the image data, arranging a plurality of monitoring piles in each grid detection group, monitoring the environmental index and the plant distribution area of the monitoring pile area through the monitoring piles, calculating the carbon reserves of plants in the sampling range of the single monitoring pile, and calculating the total carbon reserves of the plants in the target monitoring area through the carbon reserves of the plants in the sampling range of the single monitoring pile, so as to sample the plants in the target monitoring area to acquire the carbon sink state of the target monitoring area; meanwhile, a plant actual measurement sample is periodically obtained before a current sampling time point, a current plant sample collected at the current sampling time point is predicted to obtain a plant prediction sample at the current sampling time point according to the obtained plant actual measurement sample, a sample distance between two samples is obtained according to the plant prediction sample and the current plant sample, whether the current plant sample is qualified or not can be judged through the sample distance between the two samples, when the sample distance is smaller than a preset sample distance threshold value, the current plant sample is qualified, the current plant sample can be used as a sample for carrying out carbon sink state evaluation, otherwise, the environment or plants and the like in a current plant sample area can be damaged or polluted, all sample data in a corresponding grid detection group are removed, and the carbon sink state evaluation data of the target monitoring area are not carried out, so that the accuracy of carbon sink state evaluation is improved, the distribution area of plants can be changed along with the change of growth conditions, the carbon reserves of the plants can be calculated according to the plant distribution area through remote sensing monitoring and monitoring piles in real time, the carbon reserves of the plants can be calculated at different time points, and the carbon sink state evaluation efficiency of the plants can be carried out at different time points.
The monitoring stake includes environmental index monitoring unit and camera shooting unit, and environmental index monitoring unit is used for obtaining environmental index, and camera shooting unit is used for obtaining plant distribution area.
Through the technical scheme, the environment index is obtained through the environment index monitoring unit, the environment index comprises but is not limited to water temperature, salinity, PH value and the like, and the plant distribution area of the monitoring pile area is obtained through the camera unit.
The process for predicting and obtaining the plant prediction sample at the current sampling time point according to the obtained plant actual measurement sample comprises the following steps:
establishing an actual measurement data set of the plant actual measurement sample according to the plant actual measurement sample obtained periodically;
analyzing and fitting according to the actual measurement data set to obtain a rule function of each sample parameter changing along with time;
and obtaining a prediction data set of the plant prediction sample at the current sampling time point according to a regular function of each sample parameter changing along with time.
Through the above technical scheme, the present embodiment provides a method for predicting a plant prediction sample at a current sampling time point according to an obtained plant actual measurement sample, specifically, an actual measurement data set of the plant actual measurement sample is established according to a plant actual measurement sample obtained periodically; analyzing and fitting according to the actual measurement data set to obtain a rule function of each sample parameter changing along with time; according to the regular function of each sample parameter changing along with time, a prediction data set of a plant prediction sample at the current sampling time point is obtained, the plant prediction sample can be obtained through the prediction data set, and the regular function of each sample parameter changing along with time is obtained through the prior art without requirement.
The process of obtaining a sample distance between two samples from a plant prediction sample and a current plant sample includes:
by the formula:
calculating a sample distance between a plant prediction sample and a current plant sample ；
Wherein,for the number of items of the sample parameter, +.>，/>Is->Weight coefficient of term sample parameter, +.>Is the firstApplication coefficients of the term sample parameters, +.>Is->Predicted value of item sample parameter +.>Is->The current value of the item sample parameter.
Through the above technical solution, the present embodiment provides a method for obtaining a sample distance between two samples according to a plant prediction sample and a current plant sample, specifically, by a formulaObtained by the method, wherein，/>For the number of items of the sample parameter, +.>，/>Is->The weighting coefficients of the term sample parameters,is->Application coefficients of the term sample parameters, +.>Is->Predicted value of item sample parameter +.>Is->Current value of the sample parameter, weighting coefficient of the sample parameter +.>Fitting according to experimental data.
The process of correcting the next sampling time according to the sample distance comprises the following steps:
by the formula:
calculate the next sampling time interval；
Wherein,for the initial sampling time interval, +.>Is a time distance correction function.
Through the above technical solution, this embodiment provides a method for correcting the next sampling time according to the sample distance, specifically by a formulaCalculate the next sampling time interval +.>；
Wherein,for the initial sampling time interval, +.>The method is a time distance correction function, so that the next sampling time is corrected according to the sample distance, the accuracy of the collected sample is improved, the sampling precision is improved, and the carbon sink of the ocean is periodically evaluated in the modeAnd the state improves the evaluation efficiency of the carbon sink state.
It should be noted that the initial sampling time intervalFitting according to the rule function and experimental data to obtain +.>Fitting according to experimental data.
The process of judging and comparing the sample distance with a preset sample distance threshold comprises the following steps:
sample distance between plant prediction sample and current plant sampleAnd corresponding threshold condition->And (3) performing comparison:
if it isJudging that the current plant sample is abnormal;
otherwise, judging that the current plant sample is normal, and according to the corrected sampling time intervalThe next sampling is performed.
Through the above technical solution, the present embodiment provides a method for comparing a sample distance with a preset sample distance threshold, specifically, comparing a sample distance between a plant prediction sample and a current plant sampleAnd corresponding threshold condition->And (3) performing comparison: if->Description of the Environment or plant within the current plant sample areaIf the current plant sample is possibly damaged or polluted, judging that the current plant sample is abnormal; otherwise, judging that the current plant sample is normal, and according to the corrected sampling time interval +.>And the next sampling is carried out, so that the sampling period is accurately sampled according to the sample distance, the sampling time can be accurately adjusted according to the growth condition or seasonal variation of plants, and the accuracy of carbon sink evaluation is improved.
The process for acquiring all current plant sample data with the sample distance smaller than the preset sample distance threshold value and evaluating the ocean carbon sink state of the target monitoring area according to the current plant sample data comprises the following steps:
after preprocessing the current plant sample, measuring the carbon reserves of the current plant sample by adopting an elemental analyzer;
by the formula:
calculating total carbon reserves of plants in target monitoring areas；
Wherein,is->Plant distribution area in the monitoring range of individual monitoring posts, +.>Is->Plant area in sampling range of each monitoring pile, < >>To monitor the initial number of piles +.>Predicting sample distance for a plant from a current plant sampleThe number of monitoring piles greater than the corresponding threshold condition,/->Is->The carbon reserves of the plants in the sampling range of the piles are monitored.
Through the above technical scheme, the embodiment provides a method for evaluating the ocean carbon sink state of a target monitoring area according to the current plant sample data, specifically, after preprocessing the current plant sample, measuring the carbon reserves of the current plant sample by adopting an element analyzer; the pretreatment comprises the following steps: dividing a plant sample into four parts of roots, rhizomes, upright stems and leaves, respectively filling the four parts into aluminum foil bags, drying the plant sample at a constant temperature of 50-60 ℃ to constant weight, weighing the dried sample, crushing and grinding the dried sample, measuring the organic carbon content of the dried sample by using an elemental analyzer to obtain the carbon reserves of the plant in the sampling range of a single monitoring pile, and then, carrying out the following steps:calculating the total carbon reserve of the plants in the target monitoring area +.>Wherein->Is->Plant distribution area in the monitoring range of individual monitoring posts, +.>Is->Plant area in sampling range of each monitoring pile, < >>To monitor the initial number of piles +.>Sample distance for plant prediction sample and current plant sample +.>The number of monitoring piles greater than the corresponding threshold condition,/->Is->The carbon reserves of the plants in the sampling range of the monitoring piles can be calculated according to the plant distribution area, and then the carbon sink state of the target monitoring area can be estimated according to the carbon reserves.
It should be noted that the initial number of piles is monitoredAccording to the plant distribution area of remote sensing monitoring, the monitoring stake can monitor the plants in the area without omission.
First, theThe carbon reserve calculation process of the plants in the sampling range of the monitoring piles comprises the following steps:
by the formula:
calculate the firstMonitoring carbon reserves of plants in the sampling range of the piles;
wherein,as a function of ambient carbon reserves; />Is an environmental index.
Through the above technical solution, this embodiment provides a first embodimentThe carbon reserve calculation method of the plants in the sampling range of the monitoring piles comprises the following steps of: />Calculate->Monitoring carbon reserves of plants in the sampling range of the piles; wherein (1)>As a function of ambient carbon reserves; />And calculating the total carbon reserves of the plants in the target monitoring area by using the carbon reserves of the plants in the sampling range of the single monitoring pile as an environmental index, so as to evaluate the carbon sink state of the target monitoring area.
The environmental index data is obtained according to each sensor on the pile, and the environmental carbon reserve functionFitting according to experimental data.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (8)
1. An aquatic organism observation based marine carbon sink state assessment system, comprising:
the grid detection group is divided according to the distribution area of the target monitoring area;
the monitoring piles are arranged in the grid detection group and are used for monitoring environmental indexes and plant distribution areas in the grid detection group;
the sampling module is used for collecting a current plant sample at a current sampling time point in the grid detection group and periodically obtaining a plant actual measurement sample before the current sampling time point;
the processing module predicts a plant prediction sample at a current sampling time point according to the obtained plant actual measurement sample, obtains a sample distance between the two samples according to the plant prediction sample and the current plant sample, and corrects the next sampling time according to the sample distance;
the analysis module is used for judging and comparing the sample distance with a preset sample distance threshold, and if the sample distance is not smaller than the preset sample distance threshold, eliminating all sample data in the corresponding grid detection group;
and the evaluation module is used for acquiring all current plant sample data of which the sample distance is smaller than the preset sample distance threshold value, and evaluating the ocean carbon sink state of the target monitoring area according to the current plant sample data.
2. The marine carbon sink state evaluation system based on aquatic organism observation according to claim 1, wherein the monitoring pile comprises an environmental index monitoring unit for acquiring an environmental index and a camera unit for acquiring a plant distribution area.
3. The marine carbon sink state evaluation system based on aquatic organism observation according to claim 1, wherein the process of predicting a plant prediction sample at a current sampling time point from the obtained plant actual measurement sample comprises:
establishing a measured data set of the plant measured sample according to the plant measured sample obtained periodically;
analyzing and fitting according to the actual measurement data set to obtain a rule function of each sample parameter changing along with time;
and obtaining a prediction data set of the plant prediction sample at the current sampling time point according to a regular function of each sample parameter changing along with time.
4. The marine carbon sink state assessment system based on aquatic organism observations of claim 1, wherein the process of obtaining a sample distance between the two samples from the plant prediction sample and a current plant sample comprises:
by the formula:
calculating a sample distance between the plant prediction sample and the current plant sample；
Wherein,for the number of items of the sample parameter, +.>，/>Is->Weight coefficient of term sample parameter, +.>Is->Application coefficients of the term sample parameters, +.>Is->Predicted value of item sample parameter +.>Is->The current value of the item sample parameter.
5. An aquatic speciation based marine carbon sink state estimation system according to claim 1 wherein correcting a next sampling time based on the sample distance comprises:
by the formula:
calculate the next sampling time interval；
Wherein,for the initial sampling time interval, +.>Is a time distance correction function.
6. The marine carbon sink state assessment system based on aquatic specie observation of claim 1, wherein the process of determining and comparing the sample distance to a preset sample distance threshold comprises:
sample distance between the plant prediction sample and the current plant sampleAnd corresponding threshold condition->And (3) performing comparison:
if it isJudging that the current plant sample is abnormal;
otherwise, judging that the current plant sample is normal, and according to the corrected sampling time intervalThe next sampling is performed.
7. The marine carbon sink state estimation system based on aquatic organism observation of claim 1, wherein the process of acquiring all current plant sample data for which the sample distance is less than the preset sample distance threshold and estimating the marine carbon sink state of the target monitoring area from the current plant sample data comprises:
after preprocessing the current plant sample, measuring the carbon reserves of the current plant sample by adopting an elemental analyzer;
by the formula:
calculating total carbon reserves of plants in target monitoring areas；
Wherein,is->Monitoring range of individual monitoring pilesArea of distribution of plants in->Is->Plant area in sampling range of each monitoring pile, < >>For the initial number of monitoring piles, < > for the initial number of monitoring piles, > for the monitoring of>Sample distance for the plant prediction sample and the current plant sample +.>The number of monitoring piles greater than the corresponding threshold condition,/->Is->The carbon reserves of the plants in the sampling range of the piles are monitored.
8. An aquatic speciation based marine carbon sink state assessment system according to claim 7, wherein the firstThe carbon reserve calculation process of the plants in the sampling range of the monitoring piles comprises the following steps:
by the formula:
calculate the firstMonitoring carbon reserves of plants in the sampling range of the piles;
wherein,as a function of ambient carbon reserves; />Is an environmental index.
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| CN117314020A (en) * | 2023-11-28 | 2023-12-29 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Wetland carbon sink data monitoring system of plankton |
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| CN105677770A (en) * | 2015-12-30 | 2016-06-15 | 浙江海洋学院 | Inshore oceanic environment data monitoring adaptive sampling method |
| CN116485263A (en) * | 2023-04-25 | 2023-07-25 | 中国林业科学研究院亚热带林业研究所 | River wetland carbon sink monitoring and evaluating method |
| CN116773516A (en) * | 2023-04-26 | 2023-09-19 | 中国科学院空天信息创新研究院 | Soil carbon content analysis system based on remote sensing data |
| CN116429988A (en) * | 2023-06-09 | 2023-07-14 | 海南中南标质量科学研究院有限公司 | Dynamic remote sensing monitoring device for ocean plant carbon sink |
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| CN117314020A (en) * | 2023-11-28 | 2023-12-29 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Wetland carbon sink data monitoring system of plankton |
| CN117314020B (en) * | 2023-11-28 | 2024-02-27 | 生态环境部华南环境科学研究所(生态环境部生态环境应急研究所) | Wetland carbon sink data monitoring system of plankton |
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