CN113570265A - Offshore eutrophication evaluation system - Google Patents

Offshore eutrophication evaluation system Download PDF

Info

Publication number
CN113570265A
CN113570265A CN202110879217.4A CN202110879217A CN113570265A CN 113570265 A CN113570265 A CN 113570265A CN 202110879217 A CN202110879217 A CN 202110879217A CN 113570265 A CN113570265 A CN 113570265A
Authority
CN
China
Prior art keywords
offshore
module
water body
chlorophyll
eutrophication
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202110879217.4A
Other languages
Chinese (zh)
Inventor
鲁栋梁
杨斌
黄鹄
王希龙
亢振军
周姣娣
黄海方
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beibu Gulf University
Original Assignee
Beibu Gulf University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beibu Gulf University filed Critical Beibu Gulf University
Priority to CN202110879217.4A priority Critical patent/CN113570265A/en
Publication of CN113570265A publication Critical patent/CN113570265A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0639Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/18Water
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/21Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/241Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2411Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • General Physics & Mathematics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Chemical & Material Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Development Economics (AREA)
  • Educational Administration (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Economics (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Strategic Management (AREA)
  • Health & Medical Sciences (AREA)
  • Food Science & Technology (AREA)
  • Operations Research (AREA)
  • Tourism & Hospitality (AREA)
  • General Business, Economics & Management (AREA)
  • Marketing (AREA)
  • Game Theory and Decision Science (AREA)
  • Quality & Reliability (AREA)
  • Medicinal Chemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Biochemistry (AREA)
  • Analytical Chemistry (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)

Abstract

The invention discloses an offshore eutrophication evaluation system, which comprises: the acquisition module is used for acquiring offshore water body data and transmitting the offshore water body data to the preprocessing module and the storage module; the storage module is used for storing the offshore water body data acquired by the acquisition module; the pretreatment module is used for pretreating offshore water body data; the processing module is used for processing the preprocessed offshore water body data to obtain a threshold value; and the early warning module is used for giving an alarm when the detection value exceeds the threshold value. The method adopts a fluorescence method to measure the concentration of chlorophyll a, carries out multi-parameter evaluation, improves the accuracy rate of evaluating whether the water body is in an eutrophication state, and leads the processing module to be capable of calculating the threshold value of whether any offshore water body is in the eutrophication state through the training of the support vector machine model on the processing module, thereby reducing the influence of the diversity of variables in the water body on the evaluation accuracy.

Description

Offshore eutrophication evaluation system
Technical Field
The invention relates to the field of water eutrophication, in particular to an offshore eutrophication evaluation system.
Background
Eutrophication is a phenomenon of water enrichment due to the increase of nutrient substances, including nutrient salts such as nitrogen and phosphorus, and causes rapid growth of advanced plants such as algae, which affects the ecological balance of the water. With the increase of human activities and the acceleration of industrialization process, a large amount of domestic sewage and industrial wastewater are directly or indirectly discharged into the ocean, so that the problem of offshore eutrophication becomes more and more serious, the problem becomes an ecological problem which is generally concerned by coastal cities of various countries all over the world, the ecological environment is influenced, the production and the life of people are also influenced, and the offshore eutrophication becomes one of important factors which seriously threaten the ecological health of the ocean.
At present, the method comprises a single-factor method and a comprehensive index evaluation method, wherein the single-factor evaluation method mainly comprises a physical method, a chemical method, a biological method and a TSI method, and the single-factor evaluation method is a method for evaluating the eutrophication state of the water body through single physical, chemical and biological parameters which can directly or indirectly react with the eutrophication state of the water body. The single-factor evaluation method has the advantages of convenience and rapidness in testing, and relatively accurate evaluation on eutrophication of a freshwater system, but for a more complex seawater system, the single-factor evaluation method is difficult to ensure accuracy. The comprehensive index evaluation method using physical, chemical and biological factors as indexes mainly comprises an eutrophication index method (E value method), a nutritional state quality index method (NQI method) and a TRIX index method. The E value method is an empirical method, and has the advantages that the method is simple, but the method cannot comprehensively reflect the offshore eutrophication condition, the evaluation result is relatively comprehensive, and the accuracy needs to be considered; NQI the method comprises detecting nitrogen and phosphorus content, comparing the real-time detection value with a threshold value determined according to the water quality of seawater; the TRIX index method sets the upper limit and the lower limit of evaluation parameters, and takes the saturation of nitrogen, phosphorus and dissolved oxygen and the chlorophyll concentration as the evaluation parameters, so that the method has the advantages that the evaluation result is more comprehensive and accurate, but the threshold values of the evaluation parameters in different sea areas generally have larger difference, and therefore, the method cannot be applied to the comparison of the eutrophication levels of different water bodies. In summary, compared with a single factor evaluation method, the comprehensive index evaluation method comprehensively considers the comprehensive influence of multiple factors such as biology, chemistry and physics, but due to the complexity of a marine ecosystem and the interaction of multiple factors of an ecological environment, the characteristics of offshore eutrophication are also considered, a more accurate method is adopted, and the research on a method for automatically monitoring whether a water body is eutrophication is less, so that an evaluation system which sufficiently solves the problems in the prior art is urgently needed in society.
Disclosure of Invention
The invention aims to provide an offshore eutrophication evaluation system, which solves the problems in the prior art.
In order to achieve the purpose, the invention provides the following scheme:
the invention provides an offshore eutrophication evaluation system, which comprises:
the acquisition module is used for acquiring offshore water body data and transmitting the offshore water body data to the preprocessing module and the storage module;
the storage module is used for storing the offshore water body data acquired by the acquisition module;
the preprocessing module is used for preprocessing the offshore water body data;
the processing module is used for processing the preprocessed offshore water body data to obtain a threshold value;
the early warning module is used for alarming when the detection value exceeds the threshold value;
the acquisition module is respectively connected with the storage module and the preprocessing module, and the preprocessing module is connected with the early warning module through the processing module.
Further, the acquisition module comprises a positioning unit, a total nitrogen sensor, a total phosphorus sensor and a chlorophyll a sensor, wherein the positioning unit is used for positioning the acquisition site, the total nitrogen sensor is used for measuring the total nitrogen content in the offshore water body, the total phosphorus sensor is used for measuring the total phosphorus content in the offshore water body, and the chlorophyll a sensor is used for measuring the chlorophyll a concentration in the offshore water body.
Further, the chlorophyll-a sensor includes an underwater fluorometer for making fluorescence measurements of the offshore body of water and a filter module for filtering the offshore body of water.
Further, the specific method for measuring the chlorophyll a concentration is as follows: filtering the offshore water body based on the filtering module, and measuring a fluorescence value once by using the underwater fluorometer after filtering is finished, wherein the fluorescence value is used as a first fluorescence value and is recorded; and after the measurement, extracting the offshore water body filtered by acetone, measuring a fluorescence value once by using a fluorimeter after the extraction is finished, taking the fluorescence value as a second fluorescence value and recording the second fluorescence value, and calculating based on the first fluorescence value and the second fluorescence value to obtain the chlorophyll a concentration.
Further, the specific method for processing the preprocessed offshore water data by the processing module is as follows: dividing the preprocessed offshore water body data into a training set and a testing set, training on the basis of a support vector machine, optimizing parameters of the processing module on the basis of a training result, finishing the training after the recognition accuracy is greater than a preset value, obtaining thresholds of the total nitrogen content, the total phosphorus content and the chlorophyll a concentration, and judging whether the state of the offshore water body is eutrophication or not by the processing module on the basis of the thresholds.
Further, the processing module is further configured to count the total nitrogen content, the total phosphorus content, and the chlorophyll-a concentration to form a bar graph, a line graph, and a pie graph.
Further, the offshore eutrophication evaluation system further comprises a display module for displaying the total nitrogen content, the total phosphorus content, the chlorophyll a concentration of the offshore water body, and the bar graph, the line graph and the pie graph in real time.
Furthermore, the alarm mode of the early warning module is audible and visual alarm, and specific alarm information is displayed on the display module.
The invention discloses the following technical effects:
the invention provides an offshore eutrophication evaluation system, which adopts various sensors to collect key parameters underwater and position the collected places, so that the positions of the parameters are convenient to confirm at the later stage, the accuracy of the system is improved, the concentration of chlorophyll a is measured by adopting a fluorescence method, multi-parameter evaluation is carried out, the accuracy of evaluating whether a water body is in an eutrophication state is improved, a processing module can calculate the threshold value of whether any offshore water body is in the eutrophication state by training the processing module through a support vector machine model, the influence of the diversity of variables in the water body on the evaluation accuracy is reduced, an alarm module timely alarms to help workers report and solve the eutrophication situation at the first time, and the efficiency of solving the offshore eutrophication problem is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a system according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to various exemplary embodiments of the invention, the detailed description should not be construed as limiting the invention but as a more detailed description of certain aspects, features and embodiments of the invention.
It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Further, for numerical ranges in this disclosure, it is understood that each intervening value, between the upper and lower limit of that range, is also specifically disclosed. Every smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in a stated range is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included or excluded in the range.
It will be apparent to those skilled in the art that various modifications and variations can be made in the specific embodiments of the present disclosure without departing from the scope or spirit of the disclosure. Other embodiments will be apparent to those skilled in the art from consideration of the specification. The specification and examples are exemplary only.
As used herein, the terms "comprising," "including," "having," "containing," and the like are open-ended terms that mean including, but not limited to.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The invention provides an offshore eutrophication evaluation system, as shown in fig. 1, comprising:
the acquisition module is used for acquiring offshore water body data and transmitting the offshore water body data to the preprocessing module and the storage module;
the storage module is used for storing the offshore water body data acquired by the acquisition module;
the preprocessing module is used for preprocessing the offshore water body data;
the processing module is used for processing the preprocessed offshore water body data to obtain a threshold value;
the early warning module is used for alarming when the detection value exceeds the threshold value;
the acquisition module is respectively connected with the storage module and the preprocessing module, and the preprocessing module is connected with the early warning module through the processing module.
Further, the acquisition module comprises a positioning unit, a total nitrogen sensor, a total phosphorus sensor and a chlorophyll a sensor, wherein the positioning unit is used for positioning the acquisition site, the total nitrogen sensor is used for measuring the total nitrogen content in the offshore water body, the total phosphorus sensor is used for measuring the total phosphorus content in the offshore water body, and the chlorophyll a sensor is used for measuring the chlorophyll a concentration in the offshore water body.
Further, the chlorophyll-a sensor includes an underwater fluorometer for making fluorescence measurements of the offshore body of water and a filter module for filtering the offshore body of water.
Further, the specific method for measuring the chlorophyll a concentration is as follows: filtering the offshore water body based on the filtering module, and measuring a fluorescence value once by using the underwater fluorometer after filtering is finished, wherein the fluorescence value is used as a first fluorescence value and is recorded; and after the measurement, extracting the offshore water body filtered by acetone, measuring a fluorescence value once by using a fluorimeter after the extraction is finished, taking the fluorescence value as a second fluorescence value and recording the second fluorescence value, and calculating based on the first fluorescence value and the second fluorescence value to obtain the chlorophyll a concentration.
Further, the specific method for processing the preprocessed offshore water data by the processing module is as follows: dividing the preprocessed offshore water body data into a training set and a testing set, training on the basis of a support vector machine, optimizing parameters of the processing module on the basis of a training result, finishing the training after the recognition accuracy is greater than a preset value, obtaining thresholds of the total nitrogen content, the total phosphorus content and the chlorophyll a concentration, and judging whether the state of the offshore water body is eutrophication or not by the processing module on the basis of the thresholds.
Further, the processing module is further configured to count the total nitrogen content, the total phosphorus content, and the chlorophyll-a concentration to form a bar graph, a line graph, and a pie graph.
Further, the offshore eutrophication evaluation system further comprises a display module for displaying the total nitrogen content, the total phosphorus content, the chlorophyll a concentration of the offshore water body, and the bar graph, the line graph and the pie graph in real time.
Furthermore, the alarm mode of the early warning module is audible and visual alarm, and specific alarm information is displayed on the display module.
The acquisition module also comprises a water level sensor, a water temperature sensor, a turbidity sensor, a temperature and humidity sensor, a water flow sensor, a PH sensor, a dissolved oxygen sensor and a conductivity sensor;
the positioning unit is a Beidou positioning module or a GPS positioning module
The total phosphorus sensor adopts a PhosphaxSigma total phosphorus on-line monitor, the total nitrogen sensor adopts an NHN-202 ammonia nitrogen digital sensor, and the chlorophyll a sensor adopts a Cyclops-7 underwater fluorometer;
the system also comprises a communication module used for alarming or communicating the mobile terminal, wherein the communication module comprises a cable and an optical cable in wired communication, 2G/3G/4G/LTE connection and WIFI/wireless local area network connection in wireless communication, and the mobile terminal comprises a mobile phone, a tablet computer or a notebook computer;
the processing module adopts a desktop computer or a notebook computer;
the display module 4 adopts a liquid crystal display screen;
chlorophyll a concentration measuring method: 1000ml of water sample is collected at each station, and the collected water sample is filtered by a GF/F glass fiber membrane with the aperture of 0.47 mu m. After filtration, extraction was carried out using 90% acetone for about 23-24 hours. And (3) measuring fluorescence values before acidification and after acidification by using a fluorometer, and finally calculating to obtain a chlorophyll a concentration value.
The working process of the preprocessing module comprises the following steps:
1. normalization
The method comprises the steps of normalizing all data by using a normalization function scaleFORSVM, storing the original data into a storage module in order to prevent the loss of original data information, normalizing according to each parameter during normalization, and normalizing the data to [ -1, 1] by default during normalization.
2. Dimensionality reduction pretreatment
The dimension reduction preprocessing process is a process of selecting parameter principal components, and the principal components are selected to achieve maximum explanation of the original variables, and the default is 90%.
The processing module works:
the kernel function adopted by the processing module is an RBF kernel function, so that a gamma factor (g) in the RBF kernel function is set, C and g are selected in a certain value range, the C and g are brought into a support vector machine model, and the C and g with the highest classification accuracy are selected as the optimal C and g. And if the minimum C corresponds to a plurality of groups of g, selecting the first group as the optimal parameter, and selecting the minimum C as the optimal parameter combination from all C and g which can achieve the highest classification accuracy, wherein the larger the C is, the more the learning phenomenon of the support vector machine model is caused, so that the classification accuracy of the classifier is reduced. In addition, a heuristic algorithm can be adopted to carry out parameter optimization of the support vector machine, the heuristic algorithm optimization method can realize parameter optimization in a larger range without traversing all parameter points in a grid, and the heuristic algorithm parameter optimization mainly comprises genetic algorithm parameter optimization (GA) and particle swarm optimization parameter optimization.
Selecting different training set sample numbers to respectively obtain three classification accuracy rates of the model, specifically comparing with a fuzzy comprehensive evaluation level, an NQI classification level, an E value classification level and a TRIX classification level, wherein the verification training set classification accuracy rate is the accuracy rate of classifying the training set of the model, the judgment prediction set classification accuracy rate is the classification accuracy rate obtained by judging the prediction set by the model, the cross verification average classification accuracy rate is the average accuracy rate under the cross verification thought and is also an important index for processing the effect of the module, the cross verification method obtains the average value of the classification accuracy rates by taking a plurality of groups of training sets and testing sets alternately, judges whether the average value exceeds a preset value, and finishes training if the average value exceeds the preset value.
In the description of the present invention, it is to be understood that the terms "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, are merely for convenience of description of the present invention, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
The above-described embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solutions of the present invention can be made by those skilled in the art without departing from the spirit of the present invention, and the technical solutions of the present invention are within the scope of the present invention defined by the claims.

Claims (8)

1. An offshore eutrophication evaluation system is characterized in that: the method comprises the following steps:
the acquisition module is used for acquiring offshore water body data and transmitting the offshore water body data to the preprocessing module and the storage module;
the storage module is used for storing the offshore water body data acquired by the acquisition module;
the preprocessing module is used for preprocessing the offshore water body data;
the processing module is used for processing the preprocessed offshore water body data to obtain a threshold value;
the early warning module is used for alarming when the detection value exceeds the threshold value;
the acquisition module is respectively connected with the storage module and the preprocessing module, and the preprocessing module is connected with the early warning module through the processing module.
2. The offshore eutrophication evaluation system of claim 1, wherein: the acquisition module comprises a positioning unit, a total nitrogen sensor, a total phosphorus sensor and a chlorophyll a sensor, wherein the positioning unit is used for positioning an acquisition site, the total nitrogen sensor is used for measuring the total nitrogen content in the offshore water body, the total phosphorus sensor is used for measuring the total phosphorus content in the offshore water body, and the chlorophyll a sensor is used for measuring the chlorophyll a concentration in the offshore water body.
3. The offshore eutrophication evaluation system of claim 2, wherein: the chlorophyll a sensor comprises an underwater fluorometer and a filtering module, wherein the underwater fluorometer is used for measuring the fluorescence value of the offshore water body, and the filtering module is used for filtering the offshore water body.
4. The offshore eutrophication evaluation system of claim 3, wherein: the specific method for measuring the chlorophyll a concentration is as follows: filtering the offshore water body based on the filtering module, and measuring a fluorescence value once by using the underwater fluorometer after filtering is finished, wherein the fluorescence value is used as a first fluorescence value and is recorded; and after the measurement, extracting the offshore water body filtered by acetone, measuring a fluorescence value once by using a fluorimeter after the extraction is finished, taking the fluorescence value as a second fluorescence value and recording the second fluorescence value, and calculating based on the first fluorescence value and the second fluorescence value to obtain the chlorophyll a concentration.
5. The offshore eutrophication evaluation system of claim 2, wherein: the specific method for processing the preprocessed offshore water body data by the processing module is as follows: dividing the preprocessed offshore water body data into a training set and a testing set, training on the basis of a support vector machine, optimizing parameters of the processing module on the basis of a training result, finishing the training after the recognition accuracy is greater than a preset value, obtaining thresholds of the total nitrogen content, the total phosphorus content and the chlorophyll a concentration, and judging whether the state of the offshore water body is eutrophication or not by the processing module on the basis of the thresholds.
6. The offshore eutrophication evaluation system of claim 5, wherein: the processing module is further used for counting the total nitrogen content, the total phosphorus content and the chlorophyll a concentration to form a column diagram, a line diagram and a pie diagram.
7. The offshore eutrophication evaluation system of claim 6, wherein: the offshore eutrophication evaluation system further comprises a display module for displaying the total nitrogen content, the total phosphorus content, the chlorophyll a concentration of the offshore water body, the bar chart, the line chart and the pie chart in real time.
8. The offshore eutrophication evaluation system of claim 7, wherein: the alarm mode of the early warning module is acousto-optic alarm, and meanwhile, specific alarm information is displayed on the display module.
CN202110879217.4A 2021-08-02 2021-08-02 Offshore eutrophication evaluation system Pending CN113570265A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110879217.4A CN113570265A (en) 2021-08-02 2021-08-02 Offshore eutrophication evaluation system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110879217.4A CN113570265A (en) 2021-08-02 2021-08-02 Offshore eutrophication evaluation system

Publications (1)

Publication Number Publication Date
CN113570265A true CN113570265A (en) 2021-10-29

Family

ID=78169888

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110879217.4A Pending CN113570265A (en) 2021-08-02 2021-08-02 Offshore eutrophication evaluation system

Country Status (1)

Country Link
CN (1) CN113570265A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117992801A (en) * 2024-04-03 2024-05-07 南京信息工程大学 Sea area monitoring method and system through satellite remote sensing technology

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
UA37626U (en) * 2008-04-24 2008-12-10 Харьковский Научно-Исследовательский Отдел Экологически Безопасного Природопользования Совета По Изучению Продуктивных Сил Украины Национальной Академии Наук Украины Method for evaluation of risk of water use from surface water objects
KR20110067964A (en) * 2009-12-15 2011-06-22 연세대학교 산학협력단 Method and apparatus for water quality monitoring using remote sensing technique
CN102411732A (en) * 2010-09-19 2012-04-11 中国科学院海洋研究所 China coastal eutrophication evaluation model and operation system construction method thereof
CN206960461U (en) * 2017-07-03 2018-02-02 三峡大学 The intelligent high-precision real-time evaluation system of Reservoir Eutrophication
CN109784752A (en) * 2019-01-28 2019-05-21 中国科学院重庆绿色智能技术研究院 A kind of reservoir area of Three Gorges water eutrophication risk assessment early warning system and its analysis method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
UA37626U (en) * 2008-04-24 2008-12-10 Харьковский Научно-Исследовательский Отдел Экологически Безопасного Природопользования Совета По Изучению Продуктивных Сил Украины Национальной Академии Наук Украины Method for evaluation of risk of water use from surface water objects
KR20110067964A (en) * 2009-12-15 2011-06-22 연세대학교 산학협력단 Method and apparatus for water quality monitoring using remote sensing technique
CN102411732A (en) * 2010-09-19 2012-04-11 中国科学院海洋研究所 China coastal eutrophication evaluation model and operation system construction method thereof
CN206960461U (en) * 2017-07-03 2018-02-02 三峡大学 The intelligent high-precision real-time evaluation system of Reservoir Eutrophication
CN109784752A (en) * 2019-01-28 2019-05-21 中国科学院重庆绿色智能技术研究院 A kind of reservoir area of Three Gorges water eutrophication risk assessment early warning system and its analysis method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
李建等: "《近岸/内陆水环境定量遥感时空谱研究及应用》", 31 January 2018, 武汉大学出版社, pages: 23 *
杨士瑛等编著: "《三门湾自然环境特征与资源可持续利用》", 30 September 2018, 中国海洋大学出版社, pages: 469 - 470 *
王红军等: "《基于知识的机电系统故障诊断与预测技术》", 31 January 2014, 中国财富出版社, pages: 169 - 173 *
裴中平等: "《入河排污口设置论证技术与实例》", 31 March 2017, 长江出版社, pages: 99 - 100 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117992801A (en) * 2024-04-03 2024-05-07 南京信息工程大学 Sea area monitoring method and system through satellite remote sensing technology

Similar Documents

Publication Publication Date Title
CN108830425A (en) Prediction of Reservoir Water Quality system and method
CN106940363B (en) A kind of marine pollution method for early warning based on marine organisms behavior reaction
Krause et al. Production, dissolution, accumulation, and potential export of biogenic silica in a Sargasso Sea mode‐water eddy
CN105261027A (en) Method and system for detecting sludge settlement ratio based on image processing
CN116233370A (en) Intelligent video monitoring method based on water quality monitoring
CN114218864A (en) Net cage netting damage detection method and device based on mathematics twinning and storage medium
CN113570265A (en) Offshore eutrophication evaluation system
CN114839343B (en) Portable water quality monitoring and inspecting instrument device and using method
CN113610381A (en) Water quality remote real-time monitoring system based on 5G network
CN114858221A (en) Intelligent water bloom early warning system and method based on water area nutrition state prediction
CN108801361A (en) A kind of water monitoring device of physics and chemistry bioconjugation
CN109115270B (en) A kind of data collection process method of multi-parameter water quality data parallel acquisition system
CN115508528A (en) River and lake water quality-hydrodynamics online intelligent monitoring system and method
CN214122000U (en) Floating algae detection equipment
CN106932550A (en) Offshore water quality remote sensing early warning system
US20230341370A1 (en) Detection of change in physicochemical composition of a liquid
CN106503449A (en) A kind of urban ecology health monitoring and managing system
CN112147294A (en) Sewage treatment detection analysis and assessment system and assessment method thereof
CN111443053A (en) Water quality on-line monitoring and early warning system based on biological behavior and multispectral
CN106441445A (en) Split aquaculture water quality detection method
CN111024913A (en) Control method and device of urban inland river surge miniature water quality detection equipment system
CN117668472B (en) Island reef environment multi-parameter monitoring method and system
CN110658316A (en) Water quality online monitoring method and system
CN205404403U (en) Total nitrogen water quality monitoring system
CN116698794B (en) Device and method for detecting transparency of water body by utilizing multi-parameter water quality sensor

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20211029

RJ01 Rejection of invention patent application after publication