CN111311081A - Ocean ecological abnormity danger identification method and device based on multi-source heterogeneous data - Google Patents

Ocean ecological abnormity danger identification method and device based on multi-source heterogeneous data Download PDF

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CN111311081A
CN111311081A CN202010074214.9A CN202010074214A CN111311081A CN 111311081 A CN111311081 A CN 111311081A CN 202010074214 A CN202010074214 A CN 202010074214A CN 111311081 A CN111311081 A CN 111311081A
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杨超宇
许炜铭
江丽芳
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South China Sea Prediction Center Of State Oceanic Administration Guangzhou Ocean Prediction Station Of State Oceanic Administration
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Abstract

The invention discloses a marine ecological abnormity risk identification method based on multi-source heterogeneous data, which comprises the following steps: acquiring a multi-source heterogeneous data file of a target sea area; generating a quality control report according to the multi-source heterogeneous data file; establishing a marine information database according to multi-source heterogeneous data meeting a data quality standard; establishing an ocean numerical model on a cloud platform, and updating an ocean information database to obtain an updated ocean information database; acquiring a primary marine ecological anomaly index data product according to the updated marine information database; carrying out weighted average on each marine ecological anomaly index data product to obtain a secondary marine ecological anomaly index data product of a target sea area; and detecting a threshold value of the secondary marine ecological abnormal index data product, and if an abnormal index greater than a first preset threshold value exists, sending early warning information. The marine ecological abnormal danger identification method based on the multi-source heterogeneous data can effectively improve the accuracy of marine ecological abnormal danger identification.

Description

Ocean ecological abnormity danger identification method and device based on multi-source heterogeneous data
Technical Field
The invention relates to the technical field of ecological monitoring, in particular to a marine ecological abnormity danger identification method and device based on multi-source heterogeneous data.
Background
In recent years, coastal ecological disasters frequently occur in China, and researches on the ecological disasters become a hot problem concerned by academia. The concept of marine ecological disasters is originally introduced by the definition of land ecological disasters, and the coastal zones and offshore ecological environment deterioration caused by accidents such as red tide, sea area pollution, oil spill and the like are all classified into the marine ecological disasters. Green tide disasters of enteromorpha in 2008 and 2012 cause serious threats to major international events such as Ojasai in Qingdao city and Suiyang city sub-Sha Congress; jellyfish disasters encountered by a Qingdao power plant in 7 months in 2009 are the most serious, the safe operation of the power plant is influenced, and the jellyfish quantity removed by a water intake of the power plant is more than 10 ten thousand kilos at the maximum day. At present, marine ecological disasters in China are getting more serious, so that early warning needs to be carried out on the marine ecological disasters, and losses caused by the marine disasters are reduced to the maximum extent. Research shows that the method of utilizing remote sensing images, numerical simulation and the like is an effective means for marine ecological disaster early warning and disaster emergency decision. The marine ecological disaster is an event influenced by multiple factors, and the biological, chemical and physical mechanisms of the development and extinction process are complex, so that the problem of complexity and changeability of the marine ecological water body abnormity is solved based on big data high-intelligence parallel computation, and the main development direction for further improving the sea area resource management is provided.
How to acquire big data and extract potential value from the massive marine observation and environmental numerical forecast data is the core of marine big data supported by current information technology. As a high-value resource, the ocean big data has wide application prospect and development potential, is a hot problem in the current ocean information field research, and is an important basis for implementing ocean strengthening strategy, developing ocean resources, pulling ocean economy and maintaining national ocean interests. The existing marine ecological abnormal danger identification method mainly realizes identification of marine ecological abnormal dangers through chlorophyll concentration abnormity identification or water color identification.
The existing marine ecological abnormal danger identification method has the following technical problems:
the method considers that the induction factor of the marine ecological disaster is single, and the complex characteristic of the marine ecological disaster is not fully considered; the applied data source is single, and the multi-element marine environment information is not fully utilized; the analysis method is single, and the marine physics-biology coupling process is not fully considered, so that the marine ecological danger level cannot be accurately identified.
Disclosure of Invention
The embodiment of the invention provides a method and a device for identifying marine ecological abnormal danger based on multi-source heterogeneous data, which can effectively improve the accuracy of identifying the marine ecological abnormal danger.
In order to achieve the above object, in one aspect, an embodiment of the present invention provides a marine ecological anomaly risk identification method based on multi-source heterogeneous data, including:
acquiring a multi-source heterogeneous data file of a target sea area in an automatic capture mode;
automatically detecting the multi-source heterogeneous data file according to a data quality standard and generating a quality control report;
establishing a marine information database according to the multi-source heterogeneous data meeting the data quality standard in the quality control report;
establishing an ocean numerical model on a cloud platform, setting a parameter mode model according to the environment configuration of the cloud platform and the water body characteristics of a target sea area, calculating and outputting a three-dimensional flow field in parallel, performing quality control management, and updating the ocean information database to obtain an updated ocean information database;
acquiring a primary marine ecological anomaly index data product according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method;
carrying out weighted average on each marine ecological anomaly index data product to obtain a secondary marine ecological anomaly index data product of the target sea area;
and carrying out threshold detection on the secondary marine ecological anomaly index data product according to an automatic threshold detection technology, and if an anomaly index larger than a first preset threshold exists, sending early warning information of the target sea area secondary marine ecological anomaly index data product to a preset address.
Further, the obtaining of the multi-source heterogeneous data file of the target sea area in an automatic capture manner specifically includes:
updating and downloading the multi-source heterogeneous data file of the target sea area regularly or in real time in a downloading interface or webpage data intelligent extraction mode, wherein the multi-source heterogeneous data file comprises: remote sensing data, meteorological data, fixed point on-line monitoring data and reanalysis data.
Further, establishing a marine information database according to the meta-information and the data entity corresponding to the meta-information, specifically:
according to the parameter physical characteristics corresponding to the data entities in the multi-source heterogeneous data meeting the data quality standard, performing quality control management on the data entities, collecting the data attributes of the multi-source heterogeneous data meeting the data quality standard, and constructing and storing meta information describing the characteristics of the data entities; and establishing a marine information database according to the meta information and the data entity corresponding to the meta information.
Further, an ocean numerical model is established on a cloud platform, a parameter mode model is set according to the environment configuration of the cloud platform and the water body characteristics of a target sea area, a three-dimensional flow field is calculated and output in parallel, quality control management is carried out, the ocean information database is updated, and an updated ocean information database is obtained, specifically:
generating boundary condition data of a model open boundary according to climate state data in the ocean information database, selecting parameters according to cloud platform environment configuration and the water body characteristics of the target sea area, adjusting the resolving capability of the ocean numerical model in the complex terrain of the target sea area, optimizing the parameters according to historical measured ocean survey data in the ocean information database, correcting regional errors of the model, performing parallel calculation on the ocean numerical model through multiple threads to obtain three-dimensional flow field information, and performing quality control management on the data through outputting the physical significance of the parameters; and constructing meta-information according to the data attributes of the ocean numerical model simulation flow field, cataloguing and warehousing the meta-information in combination with the data entities corresponding to the meta-information, and updating the ocean information database to obtain an updated ocean information database.
Further, the primary marine ecological abnormality index data product comprises: identifying indexes of chlorophyll a concentration abnormal ecological disasters, phytoplankton fluorescence height FLH abnormal ecological disasters and effective photosynthetic radiation PAR ecological disasters; the step of obtaining a primary marine ecological anomaly index data product according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method comprises the following specific steps:
obtaining the radiance of a water color remote sensing satellite L1b, the remote sensing reflectivity Rrs and the geometric positioning information GLT according to the updated ocean information database, carrying out atmospheric correction based on short wave infrared band extrapolation and a multi-source data fusion technology to obtain the L2 remote sensing reflectivity Rrs, and obtaining the chlorophyll a concentration by applying a water color parameter inversion algorithm of the fluorescence characteristic of phytoplankton; obtaining the fluorescence height FLH and the effective photosynthetic radiation PAR of the phytoplankton based on an L2 remote sensing reflectivity inversion algorithm;
subtracting the climate state average chlorophyll a concentration of the historical remote sensing data in the cloud platform database from the chlorophyll a concentration to obtain time-space distribution data with abnormal chlorophyll a concentration, marking the sea area with the abnormal chlorophyll a concentration as marine ecological positive abnormity, assigning a value of 2, and assigning values of other sea areas as 0 to obtain an ecological disaster identification index with abnormal chlorophyll a concentration;
subtracting the climate-state average phytoplankton fluorescence height FLH of historical remote sensing data in the cloud platform database from the phytoplankton fluorescence height FLH to obtain abnormal space-time distribution data of the phytoplankton fluorescence height FLH, marking the sea area with the abnormal phytoplankton fluorescence height FLH as the marine ecology positive abnormity, assigning the sea area with the abnormal phytoplankton fluorescence height FLH as 2, and assigning the other sea areas as 0 to obtain the abnormal ecological disaster identification index of the phytoplankton fluorescence height FLH;
and calculating the average value of the effective photosynthetic radiation PAR for 3 days, marking the sea area with the average effective photosynthetic radiation PAR larger than a second preset value threshold as marine ecological positive abnormity, assigning a value of 1, and assigning values of other sea areas as 0 to obtain an effective photosynthetic radiation PAR ecological disaster identification index.
Further, the primary ocean ecological anomaly index data product further includes a precipitation ecological disaster identification index, a sea surface temperature ecological disaster identification index, a sea surface wind field wind speed ecological disaster identification index and a surface layer ocean current ecological disaster identification index, and the primary ocean ecological anomaly index data product is obtained according to the time-space distribution characteristics of the environmental parameters in the updated ocean information database and a threshold judgment method, and specifically includes:
acquiring GPM L3 meshed precipitation parameters prepititionalCal published by NASA according to the updated ocean information database, and acquiring GPM L3 precipitation data of the target sea area; acquiring AVHRR gridding sea surface temperature inversion parameters sst published by NOAA according to the updated sea information database, and extracting AVHRR sea surface temperature data of the target sea area; acquiring Ascat gridding 10m wind field data issued by NOAA according to the updated ocean information database, and extracting 10m sea surface wind field wind speed data of the target water body; acquiring ocean current data output in a numerical mode according to the updated ocean information database;
threshold judgment is carried out on the GPM L3 precipitation data, the sea area of which the GPM L3 real-time precipitation data are larger than a third preset threshold value on the same day is marked as a negative ocean ecology abnormity, the assignment is-1, and the assignment of other sea areas is 0; the sea area with the historical precipitation data of the GPM L314 day ahead larger than a fourth preset threshold is marked as the positive ocean ecological abnormality, the value is assigned to 0.5, and the values of other sea areas are assigned to 0, so that the precipitation ecological disaster identification index is obtained;
threshold judgment is carried out on the AVHRR sea surface temperature data, the sea area where the AVHRR real-time sea surface temperature data on the same day is larger than a fifth preset threshold or smaller than a sixth preset threshold is marked as a negative abnormality of marine ecology, the assignment is-1, and the assignment of other sea areas is 0; the sea area with the difference value between the real-time sea surface temperature data of the AVHRR on the same day and the sea surface temperature data of the AVHRR within seven days larger than a seventh preset threshold is marked as a marine ecological positive exception, the sea area is assigned with 1, and the other sea areas are assigned with 0, so that a sea surface temperature ecological disaster identification index is obtained;
threshold judgment is carried out on the ASCAT real-time 10m sea surface wind field wind speed data, sea areas with 10m sea surface wind field wind speed data larger than an eighth preset threshold on the same day of the ASCAT are marked as marine ecological negative anomalies, the assignment is-1, and the assignment of other sea areas is 0, so that a sea surface wind field wind speed ecological disaster identification index is obtained;
threshold judgment is carried out on the ocean current data, the ocean area where the ocean current data of the current day is larger than a ninth preset threshold is marked as an ocean ecological negative abnormity, the value is assigned to be-1, the value assigned to other ocean areas is assigned to be 0, and an ocean current ecological disaster identification index is obtained;
further, the primary marine ecological anomaly index data product further comprises a water quality buoy ecological disaster identification index, and the primary marine ecological anomaly index data product is obtained according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method, and specifically comprises the following steps:
and (3) carrying out threshold judgment on the real-time online monitoring data of the target sea area, marking the real-time numerical value of the chlorophyll a concentration as the fixed-point marine ecology positive abnormity if the chlorophyll a concentration is higher than the online monitoring data for 3 days, marking the floating plant fluorescence as the fixed-point marine ecology positive abnormity if the floating plant fluorescence is higher than the online monitoring data for 3 days, marking the dissolved oxygen saturation as the fixed-point marine ecology positive abnormity if the dissolved oxygen saturation is higher than a tenth preset threshold, marking the pH value as the fixed-point marine ecology positive abnormity if the pH value is higher than an eleventh preset threshold, and assigning the abnormal index of the online monitoring data as the sum of abnormal parameters, wherein the abnormal parameters comprise the leaf chlorophyll a concentration abnormity, the floating plant fluorescence abnormity and the dissolved oxygen saturation, and accumulating and summing the abnormal parameters to obtain the water buoy ecological disaster identification index.
On the other hand, another embodiment of the invention provides a marine ecological anomaly risk identification device based on multi-source heterogeneous data, which comprises a first data acquisition module, a report generation report, a database establishment module, a database updating module, a second data acquisition module, a third data acquisition module and an early warning sending module;
the first data acquisition module is used for acquiring a multi-source heterogeneous data file of a target sea area in an automatic capture mode;
the report generation report is used for automatically detecting the multi-source heterogeneous data file according to a data quality standard and generating a quality control report;
the database establishing module is used for establishing a marine information database according to the multi-source heterogeneous data meeting the data quality standard in the quality control report;
the database updating module is used for establishing an ocean numerical model on a cloud platform, setting a parameter mode model according to the environment configuration of the cloud platform and the water body characteristics of a target sea area, calculating and outputting a three-dimensional flow field in parallel, performing quality control management, and updating the ocean information database to obtain an updated ocean information database;
the second data acquisition module is used for acquiring a primary marine ecological anomaly index data product according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method;
the third data acquisition module carries out weighted average on each marine ecological anomaly index data product to obtain a secondary marine ecological anomaly index data product of the target sea area;
the early warning sending module is used for carrying out threshold detection on the secondary marine ecological abnormity index data product according to an automatic threshold detection technology, and sending early warning information of the target sea area secondary marine ecological abnormity index data product to a preset address if an abnormity index larger than a first preset threshold exists.
The embodiment of the invention provides a method and a device for identifying ocean ecological abnormity danger based on multi-source heterogeneous data. Acquiring chlorophyll a concentration, phytoplankton fluorescence height FLH, effective photosynthetic radiation PAR, GPM L3 precipitation data, AVHRR sea surface temperature data, ASCAT10m sea surface wind field wind speed data, surface layer sea current flow field data and water quality buoy parameters according to an ocean information database, and generating a chlorophyll a concentration abnormal ecological disaster identification index, a phytoplankton fluorescence height FLH abnormal ecological disaster identification index, an effective photosynthetic radiation PAR ecological disaster identification index, a precipitation ecological disaster identification index, a sea surface temperature data ecological disaster identification index, a sea surface wind field wind speed ecological disaster identification index and a water quality buoy ecological disaster identification index. The target sea area secondary marine ecological anomaly index data product is obtained according to the target sea area primary marine ecological anomaly index weighted average, so that marine ecological hazard identification of the target sea area is realized, the complexity of marine ecological disaster outbreak factors is fully considered, the accuracy of marine ecological anomaly hazard identification can be effectively improved, and the discovery rate of marine ecological disasters can be effectively improved.
Drawings
Fig. 1 is a schematic flow chart of a marine ecological anomaly risk identification method based on multi-source heterogeneous data according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of ROMS surface flow velocity prediction products of a marine ecological anomaly risk identification method based on multi-source heterogeneous data according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a water anomaly index distribution data product of a marine ecological anomaly risk identification method based on multi-source heterogeneous data according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a marine ecological anomaly risk identification device based on multi-source heterogeneous data according to an embodiment of the present invention.
Detailed Description
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.
Please refer to fig. 1:
a first embodiment of the invention.
The embodiment of the invention provides a marine ecological abnormity risk identification method based on multi-source heterogeneous data, which comprises the following steps:
acquiring a multi-source heterogeneous data file of a target sea area in an automatic capture mode;
automatically detecting the multi-source heterogeneous data file according to a data quality standard and generating a quality control report;
establishing a marine information database according to the multi-source heterogeneous data meeting the data quality standard in the quality control report;
establishing an ocean numerical model on a cloud platform, setting a parameter mode model according to the environment configuration of the cloud platform and the water body characteristics of a target sea area, calculating and outputting a three-dimensional flow field in parallel, performing quality control management, and updating the ocean information database to obtain an updated ocean information database;
acquiring a primary marine ecological anomaly index data product according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method;
carrying out weighted average on each marine ecological anomaly index data product to obtain a secondary marine ecological anomaly index data product of the target sea area;
and carrying out threshold detection on the secondary marine ecological anomaly index data product according to an automatic threshold detection technology, and if an anomaly index larger than a first preset threshold exists, sending early warning information of the target sea area secondary marine ecological anomaly index data product to a preset address.
In the embodiment of the invention, the anomaly index of the secondary marine ecological anomaly index data product in the target sea area is obtained by carrying out weighted average on each marine ecological anomaly index, the anomaly index is in a numerical range of-3 to 11.5, when the anomaly index of the secondary marine ecological anomaly index data product is greater than 1, the possibility of marine water body ecological anomaly is not eliminated, and the higher the danger level of the water body ecological anomaly is along with the increase of the numerical value, when the anomaly index greater than 1 is judged to exist, the early warning mail of the secondary marine ecological anomaly index data product is automatically and intelligently sent to the address of the address list by adopting a sendmail command of matlab, so that full-automatic and intelligent prejudgment is realized, the early warning information is issued, and the early warning product is issued through Web Service.
In the embodiment of the invention, a marine information database is established according to data entities and meta-information in multi-source heterogeneous data meeting a data quality standard by automatically capturing a multi-source heterogeneous data file, ocean current data of a target sea area is obtained by calculating a marine numerical model, a simulation result is cataloged and recorded into the marine information database, chlorophyll a concentration, phytoplankton fluorescence height FLH (fluorescence Line height) and effective photosynthetic Radiation PAR (Photo-synthetic Active Radiation), GPM (global prediction measurement) L3 Precipitation data, AVHRR (advanced vertical Resolution radiometer) sea temperature data, ASCAT (advanced scientific radiometer) 10m sea surface wind field wind speed data, sea current data and buoy data are obtained according to the marine information database, and a chlorophyll a concentration abnormal ecological identification index, a phytoplankton fluorescence height FLH abnormal ecological Radiation disaster identification index and effective ecological Radiation disaster index identification index are generated, The method comprises the steps of identifying rainfall ecological disaster identification indexes, sea surface temperature ecological disaster identification indexes, sea surface wind field wind speed ecological disaster identification indexes, surface layer ocean current ecological disaster identification indexes and water buoy ecological disaster identification indexes, obtaining target sea area secondary ocean ecological abnormity index data products according to primary ocean ecological abnormity index data products, identifying ocean ecological hazards in a target sea area, fully considering the complexity of ocean ecological disaster outbreak factors, effectively improving accuracy of identifying ocean ecological abnormity hazards, and effectively improving the discovery rate of ocean ecological disasters.
As a specific implementation manner of the embodiment of the present invention, the multi-source heterogeneous data file of the target sea area is obtained in an automatic capture manner, which specifically includes:
regularly or in real time, updating and downloading the multi-source heterogeneous data file of the target sea area in an intelligent extraction mode of a downloading interface or webpage data, wherein the multi-source heterogeneous data file comprises: remote sensing data, meteorological data, fixed point on-line monitoring data and reanalysis data.
In the embodiment of the invention, through a downloading interface, the method adopts crontab to download regularly and automatically obtain the multi-protocol (FTP, FTPS, HTTP, HTTPS, SCP and TELNET) remote sensing data, meteorological data, fixed point on-line monitoring data and the multi-source heterogeneous data file of reanalysis data of a target sea area, and uses a developed interface aiming at a standard format aiming at the format standardized in automatically captured data, such as NetCDF, GRIB, HDF, XML and the like; the self-developed conversion files are seamlessly integrated for other non-standard formats, and the sorting, classification and storage of the multi-source heterogeneous data files are realized on the Alice cloud big data platform; capturing corresponding webpage key information by utilizing curl and data resource URL of a libcur library, analyzing file keywords by utilizing grep commands, obtaining a data updating list, generating a multisource heterogeneous data file obtained by sensing the updating change of issued data, putting the URL corresponding to the updated multisource heterogeneous data into a URL queue to be captured, capturing the latest relevant parameter file by adopting a message-driven multithreading parallel downloading mode, combining a wget breakpoint downloading mode to realize intelligent downloading, sorting and classifying of non-standardized interface files and storing in an Aliyun big data platform.
As a specific implementation manner of the embodiment of the present invention, establishing a marine information database according to the meta information and the data entity corresponding to the meta information specifically includes:
according to the parameter physical characteristics corresponding to the data entities in the multi-source heterogeneous data meeting the data quality standard, performing quality control management on the data entities, collecting the data attributes of the multi-source heterogeneous data meeting the data quality standard, and constructing and storing meta information describing the characteristics of the data entities; and establishing a marine information database according to the meta information and the data entity corresponding to the meta information.
As a specific implementation manner of the embodiment of the present invention, an ocean numerical model is established on a cloud platform, a parameter tuning model is set according to environment configuration of the cloud platform and characteristics of a target sea area water body, a three-dimensional flow field is calculated and output in parallel, quality control management is performed, and an ocean information database is updated to obtain an updated ocean information database, which specifically comprises:
generating boundary condition data of a model open boundary according to climate state data in the ocean information database, selecting parameters according to cloud platform environment configuration and the water body characteristics of the target sea area, adjusting the resolving capability of the ocean numerical model in the complex terrain of the target sea area, optimizing the parameters according to historical measured ocean survey data in the ocean information database, correcting regional errors of the model, performing parallel calculation on the ocean numerical model through multiple threads to obtain three-dimensional flow field information, and performing quality control management on the data through outputting the physical significance of the parameters; and constructing meta-information according to the data attributes of the ocean numerical model simulation flow field, cataloguing and warehousing the meta-information in combination with the data entities corresponding to the meta-information, and updating the ocean information database to obtain an updated ocean information database.
It is understood that the Ocean numerical model in the embodiment of the present invention includes an roms (local Ocean modeling system) model, an fvom (complete Volume coast Ocean model) model, and a hycom (hybrid coordination Ocean model) model.
As a specific implementation manner of the embodiment of the present invention, the primary marine ecological anomaly index data product includes: identifying indexes of chlorophyll a concentration abnormal ecological disasters, phytoplankton fluorescence height FLH abnormal ecological disasters and effective photosynthetic radiation PAR ecological disasters; the step of obtaining a primary marine ecological anomaly index data product according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method comprises the following specific steps:
obtaining the radiance of a water color remote sensing satellite L1b, the remote sensing reflectivity Rrs and the geometric positioning information GLT according to the updated ocean information database, carrying out atmospheric correction based on short wave infrared band extrapolation and a multi-source data fusion technology to obtain the L2 remote sensing reflectivity Rrs, and obtaining the chlorophyll a concentration by applying a water color parameter inversion algorithm of the fluorescence characteristic of phytoplankton; obtaining the fluorescence height FLH and the effective photosynthetic radiation PAR of the phytoplankton based on an L2 remote sensing reflectivity inversion algorithm;
subtracting the climate state average chlorophyll a concentration of the historical remote sensing data in the cloud platform database from the chlorophyll a concentration to obtain time-space distribution data with abnormal chlorophyll a concentration, marking the sea area with the abnormal chlorophyll a concentration as marine ecological positive abnormity, assigning a value of 2, and assigning values of other sea areas as 0 to obtain an ecological disaster identification index with abnormal chlorophyll a concentration;
subtracting the climate-state average phytoplankton fluorescence height FLH of historical remote sensing data in the cloud platform database from the phytoplankton fluorescence height FLH to obtain abnormal space-time distribution data of the phytoplankton fluorescence height FLH, marking the sea area with the abnormal phytoplankton fluorescence height FLH as the marine ecology positive abnormity, assigning the sea area with the abnormal phytoplankton fluorescence height FLH as 2, and assigning the other sea areas as 0 to obtain the abnormal ecological disaster identification index of the phytoplankton fluorescence height FLH;
and calculating the average value of the effective photosynthetic radiation PAR for 3 days, marking the sea area with the average effective photosynthetic radiation PAR larger than a second preset value threshold as marine ecological positive abnormity, assigning a value of 1, and assigning values of other sea areas as 0 to obtain an effective photosynthetic radiation PAR ecological disaster identification index.
In the embodiment of the invention, the average effective photosynthetic radiation PAR is more than 50 (W.m) by calculating the 3-day average value of the effective photosynthetic radiation PAR-2.μm-1.sr-1) The sea area is marked as the positive and abnormal marine ecology, the value is 1, the value of other sea areas is 0, and the effective photosynthetic radiation PAR ecological disaster identification index is obtained.
As a specific implementation manner of the embodiment of the present invention, the primary marine ecological anomaly index data product further includes a precipitation ecological disaster identification index, a sea surface temperature ecological disaster identification index, a sea surface wind field wind speed ecological disaster identification index, and a surface layer sea current ecological disaster identification index, and the primary marine ecological anomaly index data product is obtained according to the time-space distribution characteristic of the environmental parameters in the updated marine information database and the threshold judgment method, and specifically includes:
acquiring GPM L3 meshed precipitation parameters prepititionalCal published by NASA according to the updated ocean information database, and acquiring GPM L3 precipitation data of the target sea area; acquiring AVHRR gridding sea surface temperature inversion parameters sst published by NOAA according to the updated sea information database, and extracting AVHRR sea surface temperature data of the target sea area; acquiring Ascat gridding 10m wind field data issued by NOAA according to the updated ocean information database, and extracting 10m sea surface wind field wind speed data of the target water body; acquiring ocean current data output in a numerical mode according to the updated ocean information database;
threshold judgment is carried out on the GPM L3 precipitation data, the sea area of which the GPM L3 real-time precipitation data are larger than a third preset threshold value on the same day is marked as a negative ocean ecology abnormity, the assignment is-1, and the assignment of other sea areas is 0; the sea area with the historical precipitation data of the GPM L314 day ahead larger than a fourth preset threshold is marked as the positive ocean ecological abnormality, the value is assigned to 0.5, and the values of other sea areas are assigned to 0, so that the precipitation ecological disaster identification index is obtained;
threshold judgment is carried out on the AVHRR sea surface temperature data, the sea area where the AVHRR real-time sea surface temperature data on the same day is larger than a fifth preset threshold or smaller than a sixth preset threshold is marked as a negative abnormality of marine ecology, the assignment is-1, and the assignment of other sea areas is 0; the sea area with the difference value between the real-time sea surface temperature data of the AVHRR on the same day and the sea surface temperature data of the AVHRR within seven days larger than a seventh preset threshold is marked as a marine ecological positive exception, the sea area is assigned with 1, and the other sea areas are assigned with 0, so that a sea surface temperature ecological disaster identification index is obtained;
threshold judgment is carried out on the ASCAT real-time 10m sea surface wind field wind speed data, sea areas with 10m sea surface wind field wind speed data larger than an eighth preset threshold on the same day of the ASCAT are marked as marine ecological negative anomalies, the assignment is-1, and the assignment of other sea areas is 0, so that a sea surface wind field wind speed ecological disaster identification index is obtained;
and judging a threshold value of the ocean current data, wherein the ocean area of the current day, which is larger than the ninth preset threshold value, is marked as an ocean ecological negative abnormity, the value is-1, and the values of other ocean areas are 0, so that an ocean current ecological disaster identification index is obtained.
In the embodiment of the invention, threshold judgment is carried out on the GPM L3 precipitation data, the sea area of which the daily real-time precipitation data is more than 0.05(mm/hr) of the GPM L3 is marked as negative ocean ecology anomaly and is assigned as-1, and the other sea areas are assigned as 0; marking the sea area with historical rainfall data more than 0.5(mm/hr) before the GPM L314 day as marine ecological positive abnormity, and assigning a value of 0.5, and assigning values of other sea areas of 0 to obtain a rainfall ecological disaster identification index;
threshold judgment is carried out on the AVHRR sea surface temperature data, the sea area of which the AVHRR real-time sea surface temperature data is greater than 32 (DEG C) or less than 20 (DEG C) on the current day is marked as negative abnormality of marine ecology, the assignment is-1, and the assignment of other sea areas is 0; the sea area with the difference value between the real-time sea surface temperature data of the AVHRR on the same day and the sea surface temperature data within the seven days of the AVHRR being more than 2 (DEG C) is marked as the sea ecology positive abnormity, the assignment is 1, the assignment of other sea areas is 0, and the sea surface temperature ecological disaster identification index is obtained;
threshold judgment is carried out on the ASCAT real-time 10m sea surface wind field wind speed data, sea areas with the 10m sea surface wind field wind speed data being more than 5(m/s) on the same day of the ASCAT are marked as negative marine ecological anomalies, the assignment is-1, the assignment of other sea areas is 0, and a sea surface wind field wind speed ecological disaster identification index is obtained;
and judging a threshold value of the ocean current data, wherein the ocean area with the current day ocean current data larger than 0.5(m/s) is marked as ocean ecological negative abnormity, the value is-1, and the values of other ocean areas are 0, so that the ocean current ecological disaster identification index is obtained.
As a specific implementation manner of the embodiment of the present invention, the primary marine ecological anomaly index data product further includes a water quality buoy ecological disaster identification index, and the primary marine ecological anomaly index data product is obtained according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method, and specifically includes:
and (3) carrying out threshold judgment on the real-time online monitoring data of the target sea area, marking the real-time numerical value of the chlorophyll a concentration as the fixed-point marine ecology positive abnormity if the chlorophyll a concentration is higher than the online monitoring data for 3 days, marking the floating plant fluorescence as the fixed-point marine ecology positive abnormity if the floating plant fluorescence is higher than the online monitoring data for 3 days, marking the dissolved oxygen saturation as the fixed-point marine ecology positive abnormity if the dissolved oxygen saturation is higher than a tenth preset threshold, marking the pH value as the fixed-point marine ecology positive abnormity if the pH value is higher than an eleventh preset threshold, and assigning the abnormal index of the online monitoring data as the sum of abnormal parameters, wherein the abnormal parameters comprise the leaf chlorophyll a concentration abnormity, the floating plant fluorescence abnormity and the dissolved oxygen saturation, and accumulating and summing the abnormal parameters to obtain the water buoy ecological disaster identification index.
In the embodiment of the invention, threshold judgment is carried out on the real-time online monitoring data of the target sea area, if the real-time value of the chlorophyll a concentration is higher than the online monitoring data by 3 days, the real-time value is marked as fixed-point marine ecological positive abnormity, if the phytoplankton fluorescence is higher than the online monitoring data by 3 days, the balance phytoplankton fluorescence is marked as fixed-point marine ecological positive abnormity, if the dissolved oxygen saturation is higher than 100%, the fixed-point marine ecological positive abnormity is marked, if the pH value is higher than 8.3, the fixed-point marine ecological positive abnormity is marked, and the abnormity index of the online monitoring data is assigned as the sum of abnormity parameters, wherein the abnormity parameters comprise the chlorophyll a concentration abnormity, the phytoplankton fluorescence abnormity and the dissolved oxygen saturation, and the abnormity parameters are accumulated and summed to obtain the water.
The embodiment of the invention has the following beneficial effects:
in the embodiment of the invention, a multi-source heterogeneous data file is automatically captured, an ocean information database is established according to data entities and meta-information in the multi-source heterogeneous data which accord with a data quality standard, ocean current data of a target sea area are calculated through an ocean numerical model, a simulation result is cataloged and recorded into the ocean information database, chlorophyll a concentration, phytoplankton fluorescence height FLH, effective photosynthetic radiation PAR, GPM L3 precipitation data, AVHRR sea surface temperature data, ASCAT10m sea surface wind field wind speed data, ocean current data and water quality buoy data are obtained according to the ocean information database, and a chlorophyll a concentration abnormal ecological disaster identification index, a phytoplankton fluorescence height FLH abnormal ecological disaster identification index, effective photosynthetic radiation PAR ecological disaster identification index, sea surface temperature ecological disaster identification index, sea surface wind field wind speed ecological disaster identification index, The identification index of the surface ocean current ecological disasters and the identification index of the water quality buoy ecological disasters are obtained, and a target sea area secondary ocean ecological abnormity index data product is obtained according to the primary ocean ecological abnormity index data product, so that the identification of the ocean ecological dangers of the target sea area is realized, the complexity of ocean ecological disaster outbreak factors is fully considered, the accuracy of the identification of the ocean ecological abnormity dangers can be effectively improved, and the discovery rate of the ocean ecological disasters can be effectively improved.
Please refer to fig. 2-3:
a second embodiment of the present invention is provided.
The embodiment of the invention provides a marine ecological abnormity risk identification method based on multi-source heterogeneous data, which is used for analyzing offshore coastal sea area ecological abnormity monitoring. The method is applied to marine ecological anomaly monitoring of offshore sea areas of Guangdong city in 03 and 27 days of 2016, the marine ecological anomaly identification method provided by the embodiment finds ecological anomalies in a target sea area, and a marine monitoring department detects water bodies in the area and finds that the anomalies are ecological anomalies caused by red-tide algae serving as dominant algae species. Fig. 2 is a schematic diagram of a product predicted by the ROMS surface flow rate of the marine ecological abnormal risk identification method based on multi-source heterogeneous data according to an embodiment of the present invention, and fig. 3 is a schematic diagram of a product of water body abnormal index distribution data of the marine ecological abnormal risk identification method based on multi-source heterogeneous data according to an embodiment of the present invention. Therefore, the method for identifying the marine ecological anomaly danger provided by the embodiment has better capability of judging the level of the marine ecological anomaly in the coastal region, and can provide decision support for judging the ecological anomaly event.
Please refer to fig. 4:
a third embodiment of the present invention.
The embodiment of the invention provides a marine ecological abnormity risk identification device based on multi-source heterogeneous data, which comprises a first data acquisition module, a report generation report, a database establishment module, a database updating module, a second data acquisition module, a third data acquisition module and an early warning sending module, wherein the report generation report is generated by a report generation module;
the first data acquisition module is used for acquiring a multi-source heterogeneous data file of a target sea area in an automatic capture mode;
the report generation report is used for automatically detecting the multi-source heterogeneous data file according to a data quality standard and generating a quality control report;
the database establishing module is used for establishing a marine information database according to the multi-source heterogeneous data meeting the data quality standard in the quality control report;
the database updating module is used for establishing an ocean numerical model on a cloud platform, setting a parameter mode model according to the environment configuration of the cloud platform and the water body characteristics of a target sea area, calculating and outputting a three-dimensional flow field in parallel, performing quality control management, and updating the ocean information database to obtain an updated ocean information database;
the second data acquisition module is used for acquiring a primary marine ecological anomaly index data product according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method;
the third data acquisition module carries out weighted average on each marine ecological anomaly index data product to obtain a secondary marine ecological anomaly index data product of the target sea area;
the early warning sending module is used for carrying out threshold detection on the secondary marine ecological abnormity index data product according to an automatic threshold detection technology, and sending early warning information of the target sea area secondary marine ecological abnormity index data product to a preset address if an abnormity index larger than a first preset threshold exists.
In the embodiment of the invention, a multi-source heterogeneous data file is automatically captured, an ocean information database is established according to data entities and meta-information in the multi-source heterogeneous data which accord with a data quality standard, ocean current data of a target sea area are calculated through an ocean numerical model, a simulation result is cataloged and recorded into the ocean information database, chlorophyll a concentration, phytoplankton fluorescence height FLH, effective photosynthetic radiation PAR, GPM L3 precipitation data, AVHRR sea surface temperature data, ASCAT10m sea surface wind field wind speed data, ocean current data and water quality buoy data are obtained according to the ocean information database, and a chlorophyll a concentration abnormal ecological disaster identification index, a phytoplankton fluorescence height FLH abnormal ecological disaster identification index, effective photosynthetic radiation PAR ecological disaster identification index, sea surface temperature ecological disaster identification index, sea surface wind field wind speed ecological disaster identification index, The identification index of the surface ocean current ecological disasters and the identification index of the water quality buoy ecological disasters are obtained, and a target sea area secondary ocean ecological abnormity index data product is obtained according to the primary ocean ecological abnormity index data product, so that the identification of the ocean ecological dangers of the target sea area is realized, the complexity of ocean ecological disaster outbreak factors is fully considered, the accuracy of the identification of the ocean ecological abnormity dangers can be effectively improved, and the discovery rate of the ocean ecological disasters can be effectively improved.
It should be noted that the above-described device embodiments are merely illustrative, and units illustrated as separate components may or may not be physically separate, and components illustrated as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
The foregoing is a preferred embodiment of the present invention, and it should be noted that it would be apparent to those skilled in the art that various modifications and enhancements can be made without departing from the principles of the invention, and such modifications and enhancements are also considered to be within the scope of the invention.

Claims (8)

1. A marine ecological abnormal danger identification method based on multi-source heterogeneous data is characterized by comprising the following steps:
acquiring a multi-source heterogeneous data file of a target sea area in an automatic capture mode;
automatically detecting the multi-source heterogeneous data file according to a data quality standard and generating a quality control report;
establishing a marine information database according to the multi-source heterogeneous data meeting the data quality standard in the quality control report;
establishing an ocean numerical model on a cloud platform, setting a parameter mode model according to the environment configuration of the cloud platform and the water body characteristics of a target sea area, calculating and outputting a three-dimensional flow field in parallel, performing quality control management, and updating the ocean information database to obtain an updated ocean information database;
acquiring a primary marine ecological anomaly index data product according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method;
carrying out weighted average on each marine ecological anomaly index data product to obtain a secondary marine ecological anomaly index data product of the target sea area;
and carrying out threshold detection on the secondary marine ecological anomaly index data product according to an automatic threshold detection technology, and if an anomaly index larger than a first preset threshold exists, sending early warning information of the target sea area secondary marine ecological anomaly index data product to a preset address.
2. The method for identifying marine ecological anomaly risks based on multi-source heterogeneous data according to claim 1, wherein the multi-source heterogeneous data file of the target sea area is obtained in an automatic capture mode, and specifically comprises the following steps:
updating and downloading the multi-source heterogeneous data file of the target sea area regularly or in real time in a downloading interface or webpage data intelligent extraction mode, wherein the multi-source heterogeneous data file comprises: remote sensing data, meteorological data, fixed point on-line monitoring data and reanalysis data.
3. The method for identifying marine ecological anomaly risks based on multi-source heterogeneous data according to claim 1, wherein a marine information database is established according to the meta-information and data entities corresponding to the meta-information, and specifically comprises:
according to the parameter physical characteristics corresponding to the data entities in the multi-source heterogeneous data meeting the data quality standard, performing quality control management on the data entities, collecting the data attributes of the multi-source heterogeneous data meeting the data quality standard, and constructing and storing meta information describing the characteristics of the data entities; and establishing a marine information database according to the meta information and the data entity corresponding to the meta information.
4. The method for identifying the marine ecological abnormal danger based on the multi-source heterogeneous data as claimed in claim 1, wherein an ocean numerical model is established on a cloud platform, a parameter tuning model is set according to the environmental configuration of the cloud platform and the characteristics of the water body in the target sea area, a three-dimensional flow field is calculated and output in parallel, quality control management is performed, the marine information database is updated, and an updated marine information database is obtained, specifically:
generating boundary condition data of a model open boundary according to climate state data in the ocean information database, selecting parameters according to cloud platform environment configuration and the water body characteristics of the target sea area, adjusting the resolving capability of the ocean numerical model in the complex terrain of the target sea area, optimizing the parameters according to historical measured ocean survey data in the ocean information database, correcting regional errors of the model, performing parallel calculation on the ocean numerical model through multiple threads to obtain three-dimensional flow field information, and performing quality control management on the data through outputting the physical significance of the parameters; and constructing meta-information according to the data attributes of the ocean numerical model simulation flow field, cataloguing and warehousing the meta-information in combination with the data entities corresponding to the meta-information, and updating the ocean information database to obtain an updated ocean information database.
5. The marine ecological anomaly risk identification method based on multi-source heterogeneous data according to claim 1, wherein the primary marine ecological anomaly index data product comprises: identifying indexes of chlorophyll a concentration abnormal ecological disasters, phytoplankton fluorescence height FLH abnormal ecological disasters and effective photosynthetic radiation PAR ecological disasters; the step of obtaining a primary marine ecological anomaly index data product according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method comprises the following specific steps:
obtaining the radiance of a water color remote sensing satellite L1b, the remote sensing reflectivity Rrs and the geometric positioning information GLT according to the updated ocean information database, carrying out atmospheric correction based on short wave infrared band extrapolation and a multi-source data fusion technology to obtain the L2 remote sensing reflectivity Rrs, and obtaining the chlorophyll a concentration by applying a water color parameter inversion algorithm of the fluorescence characteristic of phytoplankton; obtaining the fluorescence height FLH and the effective photosynthetic radiation PAR of the phytoplankton based on an L2 remote sensing reflectivity inversion algorithm;
subtracting the climate state average chlorophyll a concentration of the historical remote sensing data in the cloud platform database from the chlorophyll a concentration to obtain time-space distribution data with abnormal chlorophyll a concentration, marking the sea area with the abnormal chlorophyll a concentration as marine ecological positive abnormity, assigning a value of 2, and assigning values of other sea areas as 0 to obtain an ecological disaster identification index with abnormal chlorophyll a concentration;
subtracting the climate-state average phytoplankton fluorescence height FLH of historical remote sensing data in the cloud platform database from the phytoplankton fluorescence height FLH to obtain abnormal space-time distribution data of the phytoplankton fluorescence height FLH, marking the sea area with the abnormal phytoplankton fluorescence height FLH as the marine ecology positive abnormity, assigning the sea area with the abnormal phytoplankton fluorescence height FLH as 2, and assigning the other sea areas as 0 to obtain the abnormal ecological disaster identification index of the phytoplankton fluorescence height FLH;
and calculating the average value of the effective photosynthetic radiation PAR for 3 days, marking the sea area with the average effective photosynthetic radiation PAR larger than a second preset value threshold as marine ecological positive abnormity, assigning a value of 1, and assigning values of other sea areas as 0 to obtain an effective photosynthetic radiation PAR ecological disaster identification index.
6. The method for identifying marine ecological abnormal risks based on multi-source heterogeneous data according to claim 5, wherein the primary marine ecological abnormal index data product further comprises a precipitation ecological disaster identification index, a sea surface temperature ecological disaster identification index, a sea surface wind field wind speed ecological disaster identification index and a surface sea current ecological disaster identification index, and the primary marine ecological abnormal index data product is obtained according to the space-time distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method, and specifically comprises:
acquiring GPM L3 meshed precipitation parameters prepititionalCal published by NASA according to the updated ocean information database, and acquiring GPM L3 precipitation data of the target sea area; acquiring AVHRR gridding sea surface temperature inversion parameters sst published by NOAA according to the updated sea information database, and extracting AVHRR sea surface temperature data of the target sea area; acquiring Ascat gridding 10m wind field data issued by NOAA according to the updated ocean information database, and extracting 10m sea surface wind field wind speed data of the target water body; acquiring ocean current data output in a numerical mode according to the updated ocean information database;
threshold judgment is carried out on the GPM L3 precipitation data, the sea area of which the GPM L3 real-time precipitation data are larger than a third preset threshold value on the same day is marked as a negative ocean ecology abnormity, the assignment is-1, and the assignment of other sea areas is 0; the sea area with the historical precipitation data of the GPM L314 day ahead larger than a fourth preset threshold is marked as the positive ocean ecological abnormality, the value is assigned to 0.5, and the values of other sea areas are assigned to 0, so that the precipitation ecological disaster identification index is obtained;
threshold judgment is carried out on the AVHRR sea surface temperature data, the sea area where the AVHRR real-time sea surface temperature data on the same day is larger than a fifth preset threshold or smaller than a sixth preset threshold is marked as a negative abnormality of marine ecology, the assignment is-1, and the assignment of other sea areas is 0; the sea area with the difference value between the real-time sea surface temperature data of the AVHRR on the same day and the sea surface temperature data of the AVHRR within seven days larger than a seventh preset threshold is marked as a marine ecological positive exception, the sea area is assigned with 1, and the other sea areas are assigned with 0, so that a sea surface temperature ecological disaster identification index is obtained;
threshold judgment is carried out on the ASCAT real-time 10m sea surface wind field wind speed data, sea areas with 10m sea surface wind field wind speed data larger than an eighth preset threshold on the same day of the ASCAT are marked as marine ecological negative anomalies, the assignment is-1, and the assignment of other sea areas is 0, so that a sea surface wind field wind speed ecological disaster identification index is obtained;
and judging a threshold value of the ocean current data, wherein the ocean area of the current day, which is larger than the ninth preset threshold value, is marked as an ocean ecological negative abnormity, the value is-1, and the values of other ocean areas are 0, so that an ocean current ecological disaster identification index is obtained.
7. The method for identifying marine ecological abnormal risks based on multi-source heterogeneous data according to claim 5, wherein the primary marine ecological abnormal index data product further comprises a water quality buoy ecological disaster identification index, and the primary marine ecological abnormal index data product is obtained according to the updated spatial-temporal distribution characteristics of the environmental parameters in the marine information database and a threshold judgment method, and specifically comprises:
and (3) carrying out threshold judgment on the real-time online monitoring data of the target sea area, marking the real-time numerical value of the chlorophyll a concentration as the fixed-point marine ecology positive abnormity if the chlorophyll a concentration is higher than the online monitoring data for 3 days, marking the floating plant fluorescence as the fixed-point marine ecology positive abnormity if the floating plant fluorescence is higher than the online monitoring data for 3 days, marking the dissolved oxygen saturation as the fixed-point marine ecology positive abnormity if the dissolved oxygen saturation is higher than a tenth preset threshold, marking the pH value as the fixed-point marine ecology positive abnormity if the pH value is higher than an eleventh preset threshold, and assigning the abnormal index of the online monitoring data as the sum of abnormal parameters, wherein the abnormal parameters comprise the leaf chlorophyll a concentration abnormity, the floating plant fluorescence abnormity and the dissolved oxygen saturation, and accumulating and summing the abnormal parameters to obtain the water buoy ecological disaster identification index.
8. A marine ecological abnormity danger identification device based on multi-source heterogeneous data is characterized by comprising a first data acquisition module, a report generation report, a database establishment module, a database updating module, a second data acquisition module, a third data acquisition module and an early warning sending module;
the first data acquisition module is used for acquiring a multi-source heterogeneous data file of a target sea area in an automatic capture mode;
the report generation report is used for automatically detecting the multi-source heterogeneous data file according to a data quality standard and generating a quality control report;
the database establishing module is used for establishing a marine information database according to the multi-source heterogeneous data meeting the data quality standard in the quality control report;
the database updating module is used for establishing an ocean numerical model on a cloud platform, setting a parameter mode model according to the environment configuration of the cloud platform and the water body characteristics of a target sea area, calculating and outputting a three-dimensional flow field in parallel, performing quality control management, and updating the ocean information database to obtain an updated ocean information database;
the second data acquisition module is used for acquiring a primary marine ecological anomaly index data product according to the time-space distribution characteristics of the environmental parameters in the updated marine information database and a threshold judgment method;
the third data acquisition module carries out weighted average on each marine ecological anomaly index data product to obtain a secondary marine ecological anomaly index data product of the target sea area;
the early warning sending module is used for carrying out threshold detection on the secondary marine ecological abnormity index data product according to an automatic threshold detection technology, and sending early warning information of the target sea area secondary marine ecological abnormity index data product to a preset address if an abnormity index larger than a first preset threshold exists.
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