CN111782689A - Multi-task parallel processing method based on satellite data - Google Patents
Multi-task parallel processing method based on satellite data Download PDFInfo
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Abstract
The disclosure provides a multi-task parallel processing method based on satellite data, and relates to the technical field of data processing. The multitask parallel processing method based on satellite data comprises the following steps: receiving broadcast data transmitted by a meteorological satellite; acquiring original resolution true data of a meteorological satellite and related multi-source satellite auxiliary data; determining the coordinate of the attention area, splicing and correcting the original resolution data and the multi-source satellite auxiliary data according to the coordinate of the attention area, and generating first-stage meteorological data with the same format as the original resolution data; the multi-source satellite auxiliary data comprises at least one of remote sensing data, geographic data and auxiliary meteorological data acquired by a multi-source satellite. By the technical scheme, the integrated meteorological data is generated aiming at the concerned area, timeliness, reliability and integrity of services such as meteorological early warning, earthquake prevention and disaster reduction are improved, real-time extraction, automatic processing and automatic monitoring of satellite data are realized, and reliable technical support is provided for meteorological monitoring.
Description
Technical Field
The present disclosure relates to the field of data processing technologies, and in particular, to a method and an apparatus for multitask parallel processing based on satellite data, an electronic device, and a readable storage medium.
Background
Because the influence of environmental meteorological factors is great in the production, construction and equipment operation processes, the application of meteorological data and satellite remote sensing data is more and more extensive at present, and the quality requirement of people on meteorological service is continuously improved.
In the existing meteorological monitoring process, the detection strength of natural disasters is low due to poor image quality and single data type of a meteorological cloud picture. How to improve the image quality, the multi-source and the data information amount of the meteorological data becomes a problem to be solved urgently.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The present disclosure is directed to a method, an apparatus, an electronic device, and a readable storage medium for multitasking parallel processing based on satellite data, which overcome, at least to some extent, the problems of singular image data and low information volume in the related art.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to one aspect of the present disclosure, there is provided a method for multitasking parallel processing based on satellite data, comprising: receiving broadcast data transmitted by a meteorological satellite; acquiring original resolution true data of a meteorological satellite and related multi-source satellite auxiliary data; determining the coordinate of the attention area, splicing and correcting the original resolution data and the multi-source satellite auxiliary data according to the coordinate of the attention area, and generating first-stage meteorological data with the same format as the original resolution data; the multi-source satellite auxiliary data comprises at least one of remote sensing data, geographic data and auxiliary meteorological data acquired by a multi-source satellite.
In a disclosed embodiment, the multi-source satellite assistance data includes at least one of polar satellite data, geostationary satellite data and infrared imaging satellite data.
In one disclosed embodiment, polar orbit satellite data comprises wind cloud series one satellite data and/or wind cloud series three satellite data, static satellite data comprises wind cloud series two satellite data and/or wind cloud series four satellite data, and infrared imaging satellite data comprises thermal imaging data of the earth environment.
In one disclosed embodiment, generating first-stage meteorological data in the same format as the raw resolution real data comprises: and carrying out standardization processing on the spliced meteorological data to generate first-stage meteorological data, wherein the standardization processing comprises at least one of amplification, filtering, frequency conversion, demodulation, error correction decoding and display.
In one disclosed embodiment, obtaining raw resolution true data for a meteorological satellite and associated multi-source satellite aiding data comprises: determining a configuration file of a service platform associated with a meteorological satellite; and acquiring original resolution true data fed back by the service platform according to the configuration file, and receiving related multi-source satellite auxiliary data and high-resolution satellite data processing system data.
In one disclosed embodiment, determining the coordinates of the region of interest, and performing splicing correction on the original resolution true data and the multi-source satellite auxiliary data to generate first-stage meteorological data with the same format as that of the original resolution true data comprises: unpacking the received original resolution true data and the multi-source satellite auxiliary data according to the received broadcast data; determining longitude and latitude information of the coordinates of the attention area; performing equal longitude and latitude projection processing on the unpacked original resolution true data and the multisource satellite auxiliary data according to the longitude and latitude information to obtain strip-shaped meteorological data; and splicing and correcting the strip-shaped meteorological data according to the coordinates of the attention area to generate first-stage meteorological data with the same format as the original resolution real data.
In one disclosed embodiment, the method for multitasking and parallel processing based on satellite data further comprises: performing quality control and format conversion on the output first-stage meteorological data; determining second-level meteorological data associated with the first-level meteorological data, and/or determining third-level meteorological data associated with the first-level meteorological data; and archiving the second-level meteorological data and/or the third-level meteorological data, wherein the second-level meteorological data is physical parameter data with the same resolution and position as the first-level meteorological data, and the third-level meteorological data is data projected on the same space-time coordinate as the first-level meteorological data.
In one disclosed embodiment, the method for multitasking and parallel processing based on satellite data further comprises: responding to the received user access request, and slicing the spliced meteorological data according to the user access request; sorting according to the resolution and the picture size of the sliced meteorological data, and storing by adopting a response pyramid; and feeding back corresponding meteorological data according to the user access request, wherein the meteorological data comprises static meteorological pictures and/or dynamic meteorological pictures.
In one disclosed embodiment, the dynamic weather picture includes at least one of a visible cloud, an infrared cloud, and a color cloud.
In one disclosed embodiment, the feeding back of the corresponding weather data according to the user access request includes: determining satellite orbit information and/or playing parameter information according to the user access request; and generating a playing control instruction according to the satellite orbit information and/or the playing parameter information, and sending the playing control instruction, wherein the playing control instruction is used for carrying out operation control on the playing process of the meteorological data, and the operation control comprises at least one of starting, stopping, pausing and fast forwarding.
In one disclosed embodiment, the method for multitasking and parallel processing based on satellite data further comprises: determining a data channel of original resolution real data; determining strong convection clouds and non-convection clouds in the meteorological image according to the data channel; and tracking the strong convection cloud cluster by adopting a convolutional neural network and/or an optical flow valve algorithm.
According to still another aspect of the present disclosure, there is provided a satellite data-based multitask parallel processing apparatus including: the acquisition module is used for receiving broadcast data sent by a meteorological satellite; the acquisition module is also used for acquiring original resolution true data of the meteorological satellite and related multi-source satellite auxiliary data; the determining module is used for determining the coordinates of the attention area, splicing and correcting the original resolution real data and the multi-source satellite auxiliary data according to the coordinates of the attention area, and generating first-stage meteorological data with the same format as the original resolution real data; the multi-source satellite auxiliary data comprises at least one of remote sensing data, geographic data and auxiliary meteorological data acquired by a multi-source satellite.
According to still another aspect of the present disclosure, there is provided an electronic device including: a processor; and a memory for storing executable instructions for the processor; wherein the processor is configured to perform any of the satellite data based multitasking parallel processing methods described above via execution of executable instructions.
According to yet another aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the satellite data based multitask parallel processing method of any one of the above.
According to the satellite data processing scheme provided by the embodiment of the disclosure, the original resolution true data and the multi-source satellite auxiliary data are spliced and corrected to generate high-quality first-level meteorological data (namely fusion meteorological data in a specified format), namely, multi-source, multi-scale and multi-form meteorological monitoring data is provided, and the timeliness and reliability of natural disaster prevention and earthquake prevention and disaster reduction are improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
FIG. 1A shows an architectural schematic of an autonomous driving satellite data processing system in an embodiment of the disclosure;
FIG. 1B shows a data flow diagram of an autonomous driving satellite data processing system in an embodiment of the disclosure;
FIG. 2 is a schematic flow chart diagram illustrating a method for satellite data-based multitasking parallel processing in an embodiment of the present disclosure;
FIG. 3 illustrates a flow diagram of another satellite data-based multitasking parallel processing method in an embodiment of the present disclosure;
FIG. 4 illustrates a flow diagram of another satellite data-based multitasking parallel processing method in an embodiment of the present disclosure;
FIG. 5 illustrates a flow diagram of another satellite data-based multitasking parallel processing method in an embodiment of the present disclosure;
FIG. 6 illustrates a flow diagram of another satellite data-based multitasking parallel processing method in an embodiment of the present disclosure;
FIG. 7 illustrates a flow diagram of another satellite data-based multitasking parallel processing method in an embodiment of the present disclosure;
FIG. 8 illustrates a flow diagram of another satellite data-based multitasking parallel processing method in an embodiment of the present disclosure;
FIG. 9 illustrates a flow diagram of another satellite data-based multitasking parallel processing method in an embodiment of the present disclosure;
FIG. 10 is a schematic block diagram of a satellite data based multitasking parallel processing unit according to an embodiment of the present disclosure;
FIG. 11 shows a schematic block diagram of one of the electronic devices of an embodiment of the present disclosure; and
FIG. 12 shows a schematic diagram of one of the computer-readable storage media of the embodiments of the disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
According to the scheme provided by the application, the original resolution true data and the multi-source satellite auxiliary data are spliced and corrected to generate high-quality fusion meteorological data, and a multi-source, multi-scale and multi-form satellite data processing scheme is also provided.
The scheme provided by the embodiment of the application relates to the technology, and is specifically explained by the following embodiment.
As shown in fig. 1A, the satellite data processing system includes communication components such as a channel 200 and a receiver 300, such as an antenna, low noise amplifier, high frequency signal divider, signal modulator, wires and accessories, satellite data processor, and the like.
The satellite data processing system further includes a data distribution module 700 for data reception, data distribution, hardware monitoring, and the like.
The data receiving and inputting program is responsible for receiving satellite data of the satellite data database 100, storing the received sub-packet data, sending the sub-packet data to the data preprocessing module 400 for processing by the data distribution program, and continuing to generate various image products by the product generating module 500.
The product generation module 500 determines the range of the region of interest through the configuration file in combination with auxiliary information such as conventional weather data, numerical weather forecast, ground high-altitude observation data, national satellite products and the like, generates projected weather data and partial auxiliary data through equal longitude and latitude projection, and generates cloud detection, cloud classification, cloud phase state, convection birth and multi-channel synthetic image products through advanced algorithm calculation.
On the basis, corresponding release products and climate data set products are calculated and generated, and quality control is carried out on various output products, and format standardization and image output are carried out on output data.
The products output by the product generation module 500 include, but are not limited to, cloud classification products, sea surface temperature products, cloud ceiling height, air pressure products, snow accumulation detection products, clear air detection products, fog detection products, sand and dust detection products, cloud optical thickness products, convection products, fire detection, and the like.
In addition, the data distribution program can also send the meteorological data to the product display module 600, and the format conversion program in the product display module 600 can complete decompression, data splicing and format conversion of the original data sub-packets. In one aspect, a thematic map of the HDF5 standard is generated and stored locally, and product viewing functionality is provided for the user. In another aspect, data is provided for a cloud animation program.
In summary, the satellite data processing System of the present disclosure obtains auxiliary data such as required data forecast data and partial live data from a national Integrated meteorological information Sharing System (CIMISS) database. The data receiving and processing functions are mainly to complete the functions of receiving, amplifying, filtering, frequency conversion, data demodulation, error correction decoding, data instant display and recording and the like of remote sensing satellite signals. The method comprises the steps of continuously and stably collecting satellite remote sensing information through an antenna, amplifying and frequency converting satellite signals, demodulating the frequency-converted signals according to a new generation digital satellite broadcasting standard, and performing quick viewing and data transmission on demodulated original data. The service maintainer 800 can configure, repair and maintain the satellite data processing system through human-computer interaction, and the data user 900 can perform human-computer interaction with the product display module 600 to obtain a dynamically displayed or statically displayed cloud picture.
As shown in fig. 1B, taking a himwari-8 (sunflower series No. 8, abbreviated as H8 or sunflower-8) satellite as an example, the satellite data processing system can be divided into a data layer 1002, a service layer 1004 and an application layer 1006, and the data processing process can be, for example:
(1) the satellite data processing system starts to automatically run for 7 x 24 hours after being started.
(2) The satellite data processing system receives broadcast data of H8, and the data receiving subsystem acquires standard data (original resolution real data of H8) of a cloud platform, multi-source satellite data and shared auxiliary data. And after the received multiple types of data are managed by the data interface, pyramid data generation is continuously carried out.
(3) The satellite data processing system provides a product configuration service, a data management service, a data service (an image data service and a vector data service), a cloud picture processing service, a spatial analysis service, a data acquisition service, an image processing service, a satellite map service, and the like. And the satellite data processing system downloads the observation data and the auxiliary data of the required satellite from the cloud platform, the provincial weather network data sharing platform and the CIMISS according to the data receiving configuration information. The user can acquire the satellite map through a browser.
(4) And receiving corresponding original resolution true data of H8 aiming at H8 broadcast data, transmitting block data required by high-aging product processing to a product processing server by a receiving satellite data processing system according to a configuration file, and carrying out preprocessing such as splicing, clipping, projecting and calibrating.
(5) The satellite data processing system makes an operation plan of the whole satellite data processing system according to the broadcasting schedule, wherein the operation plan comprises a data receiving plan, a data transmission plan and the like. As a monitoring and statistical basis for the operation of the full satellite data processing system. The data receiving sub-satellite data processing system carries out quick-look monitoring on H8 received data in real time in the data receiving process, and monitors the data receiving condition.
(6) And the satellite data processing system acquires numerical forecast data from the outside according to the product processing requirement and transmits the numerical forecast data to the product processing server.
(7) The product processing software can respectively set data receiving and processing areas according to user requirements, and can configure different data projection modes and data image palettes.
A satellite data-based multitask parallel processing method according to this embodiment of the present disclosure is described below with reference to fig. 2. The method of multitasking and parallel processing based on satellite data shown in fig. 2 is only an example, and should not bring any limitation to the function and the scope of the application of the embodiments of the present disclosure.
As shown in fig. 2, the method for multitasking and parallel processing based on satellite data includes:
step S202, receiving broadcast data sent by a meteorological satellite.
The broadcast data of the present disclosure may include, for example, satellite regular data, custom format data, weather radar data, and the like, but is not limited thereto.
And step S204, acquiring original resolution true data of the meteorological satellite and related multi-source satellite auxiliary data.
The original resolution true data is applied to the local service system, namely the format of the original resolution true data meets the format requirement of the local service system. Additionally, the multi-source satellite assistance data may be, for example, but not limited to, wind cloud three-satellite data, wind cloud four-satellite data, infrared satellite data, and sunflower series satellite data.
And S206, determining the coordinates of the area of interest, splicing and correcting the original resolution data and the multi-source satellite auxiliary data according to the coordinates of the area of interest, and generating first-stage meteorological data with the same format as the original resolution data.
According to the satellite data processing scheme defined by the disclosure, satellite signals of a certain waveband are continuously and stably received through an antenna, the signals are amplified and frequency-converted through an amplifier, and data are displayed and recorded in real time. And then, carrying out data demodulation on the frequency-converted signals according to a new generation digital satellite broadcasting standard, and carrying out quick viewing and data transmission on the demodulated original data.
Meanwhile, the network cloud platform is utilized to configure the area information and the cloud platform information of the data to be downloaded according to the user requirements, and the true data of the original resolution of the satellite is acquired in a real-time pushing or timing downloading mode.
The multi-source satellite auxiliary data may include, but is not limited to, conventional weather data, numerical weather forecast, ground high-altitude observation number, and foreign satellite products.
In summary, the range of the attention area is determined through the configuration file, the original resolution true data and the multi-source satellite auxiliary data are spliced and corrected according to the attention area, the projected first-stage meteorological data and part of the projected auxiliary data are generated through equal longitude and latitude projection, cloud pictures and convection nascent products are calculated and generated by adopting an advanced algorithm, quality control is conducted on various output products, format standardization and image output are conducted on the output data, and the first-stage meteorological data, the second-stage meteorological data and the third-stage meteorological data are archived.
The division of the multi-source satellite assistance data by data type may include, but is not limited to, remote sensing data, geographic data, and auxiliary meteorological data, for example.
In one disclosed embodiment, the division of the multi-source satellite assistance data by satellite type may include, for example, at least one of polar satellite data, geostationary satellite data, and infrared imaging satellite data.
In one disclosed embodiment, polar orbit satellite data comprises wind cloud series one satellite data and/or wind cloud series three satellite data, static satellite data comprises wind cloud series two satellite data and/or wind cloud series four satellite data, and infrared imaging satellite data comprises thermal imaging data of the earth environment.
In one disclosed embodiment, the original resolution real data is sunflower eight-series satellite data, and the multi-source satellite auxiliary data comprises wind cloud three-series satellites, wind cloud four-series satellites, infrared imaging satellite data and the like. Basic products and regional convection cloud quasi-real-time dynamic tracking monitoring early warning products based on a sunflower-8 satellite are developed based on the application requirements, and early warning products capable of monitoring severe weather such as strong convection, rainstorm and the like are generated.
The satellite data channels and associated channel parameters that may be received by the service system for H8 are shown in table 1-1 below:
TABLE 1-1H8 Observation channel definitions
For H8 data, only the HRIT (High-rate information transmission) data is received and processed, and the data document list of the HRIT data is shown in the following tables 1-2:
TABLE 1-2HRIT data List
As shown in fig. 3, in one disclosed embodiment, generating first-level meteorological data in the same format as the raw resolution real data comprises:
step S2062, the spliced meteorological data is subjected to standardization processing to generate first-stage meteorological data, and the standardization processing comprises at least one of amplification, filtering, frequency conversion, demodulation, error correction decoding and display.
In the above embodiment, by performing standardized processing on the spliced weather data, the format of the generated first-level weather data can meet the format requirement of the local business system, so as to perform operations such as data processing, distribution, access provision and the like inside the system. The spliced meteorological data products are displayed in each service scene, and the method has the advantages of multiple product types, long data time sequence, strong product spatiality and relevance and the like.
As shown in fig. 4, in one disclosed embodiment, acquiring raw resolution true data of a meteorological satellite and associated multi-source satellite aiding data comprises:
step S2042, determining a configuration file of a service platform associated with the meteorological satellite.
For different databases in different languages, the databases are used for configuring corresponding data products, including precision, longitude and latitude, range, solar radiation angle, gradient and the like. The configuration file is mainly used for configuring corresponding data environments by utilizing a plurality of databases, is mainly in a TXT (Text file) format, is added with environments according to product requirements, and is mainly configured by background developers according to requirements.
Step S2044, obtaining the original resolution true data fed back by the service platform according to the configuration file, and receiving related multisource satellite auxiliary data and high-resolution satellite data processing system data.
TABLE 1-3 satellite data processing System Equipment List
| Serial number | Content providing method and apparatus | Number of |
| 1 | C wave band parabolic antenna (including feed source) | 1 set of |
| 2 | Integrated high-frequency extension set | 1 is provided with |
| 3 | Receiver with a plurality of receivers | 1 table |
| 4 | Radio frequency cable | 1 strip (length within 100 meters) |
| 5 | Satellite small station data receiving processor | 1 table |
| 6 | Network data receiving processor | 1 table |
| 7 | Satellite antenna matching infrastructure | 1 set of |
| 8 | Data receiving client software | 1 set of |
| 9 | Data processing application software | 1 set of |
In the above embodiments, the satellite data processing system hardware composition and function are as shown in tables 1-3 and tables 1-4. After the configuration file is generated, the satellite data processing system can passively receive the multisource satellite auxiliary data and the high-resolution satellite data processing system data according to the configuration file, or actively request the multisource satellite auxiliary data and the high-resolution satellite data processing system data from the server according to the configuration file, so that the efficiency and the reliability of satellite data fusion are improved.
TABLE 1-4 satellite data processing System technical parameters
As shown in fig. 5, in one embodiment of the disclosure, determining coordinates of a region of interest, and performing stitching correction on the original resolution true data and the multi-source satellite auxiliary data, and generating first-stage meteorological data in the same format as the original resolution true data includes:
step S2062, unpacking the received original resolution true data and the multi-source satellite auxiliary data according to the received broadcast data.
Step S2064, determining latitude and longitude information of the coordinates of the region of interest.
And S2066, performing equal longitude and latitude projection processing on the unpacked original resolution true data and the multisource satellite auxiliary data according to the longitude and latitude information to obtain strip-shaped meteorological data.
Step S2068, splicing and correcting the strip-shaped meteorological data according to the attention area coordinates, and generating first-stage meteorological data with the same format as the original resolution real data.
In the above embodiment, after determining the longitude and latitude information of the coordinates of the region of interest, performing equal longitude and latitude projection processing on the unpacked original resolution true data and the multisource satellite auxiliary data according to the longitude and latitude information to splice the strip-shaped meteorological data, and particularly performing pixel correction on a spliced edge by combining the longitude and latitude information to improve the resolution and quality of the fused meteorological data.
As shown in fig. 6, in one embodiment of the disclosure, the method for multitasking and parallel processing based on satellite data further comprises:
and step S208, performing quality control and format conversion on the output first-stage meteorological data.
In step S210, second-level meteorological data associated with the first-level meteorological data is determined, and/or third-level meteorological data associated with the first-level meteorological data is determined.
Step S212, archiving the second-level meteorological data and/or the third-level meteorological data, wherein the second-level meteorological data is physical parameter data with the same resolution and position as the first-level meteorological data, and the third-level meteorological data is data projected on the same space-time coordinate as the first-level meteorological data.
In the above embodiment, after the original resolution real data is spliced with auxiliary information such as weather data, numerical weather forecast, ground high-altitude observation data, foreign satellite products, and the like, the multi-source fusion meteorological data is generated. Furthermore, the quality control and the format conversion are carried out on the output first-stage meteorological data, so that the image quality and the resolution of the fused meteorological data are improved.
As shown in fig. 7, in one embodiment of the disclosure, the method for multitasking and parallel processing based on satellite data further comprises:
and step S214, responding to the received user access request, and slicing the spliced meteorological data according to the user access request.
And S216, sorting according to the resolution and the picture size of the sliced meteorological data, and storing by adopting a response pyramid.
Step S218, corresponding meteorological data is fed back according to the user access request, and the meteorological data comprises static meteorological pictures and/or dynamic meteorological pictures.
In the above embodiment, because the data characteristics of the satellite data processing system defined by the present disclosure are various and the representation forms are different (spatial distribution data, forecast field data, etc.), the characteristics of each type of data need to be fully embodied on the display. Therefore, the data processing in the pyramid mode provides quick and stable support for the visual loading of large data volume, and the two-dimensional and three-dimensional integrated information display technology is used for providing various display forms for various multi-characteristic data.
In addition, a satellite diagram framework is used as a solution of a remote sensing data publishing platform, and a unified interaction platform which is based, standard and feasible for project monitoring, data configuration, data display, data publishing and data downloading is provided.
And finally, providing a secondary development solution through a satellite map system, providing a multi-language multi-platform secondary development component interface for the whole display scheme, and providing support for multi-terminal application display of a desktop terminal, a webpage terminal, a mobile terminal and the like.
In one disclosed embodiment, the dynamic weather picture includes at least one of a visible cloud, an infrared cloud, and a color cloud.
As shown in fig. 8, in one embodiment of the disclosure, the feeding back the corresponding weather data according to the user access request, where the weather data includes the static weather picture and/or the dynamic weather picture specifically includes:
step S2182, determining satellite orbit information and/or playing parameter information according to the user access request.
And S2184, generating a playing control instruction according to the satellite orbit information and/or the playing parameter information and sending the playing control instruction, wherein the playing control instruction is used for carrying out operation control on the playing process of the meteorological data, and the operation control comprises at least one of starting, stopping, pausing and fast forwarding.
In the above embodiment, the user mainly needs to search for satellite animation images at different times, and channel settings may also be performed, including, but not limited to, infrared 1, infrared 2, infrared 3, infrared 4, and visible light channels. In addition, the user can also set playing parameters, such as animation parameter paths and video settings.
In the satellite data access process of the present disclosure, the data interaction process between the front end and the background is mainly involved from shooting to generating the final result, which may be, for example, the extraction of data by the background data interface, and the front end searches the data information in the corresponding database according to the user setting, and then presents these interaction processes in an animation manner.
As shown in fig. 9, in one embodiment of the disclosure, the method for multitasking and parallel processing based on satellite data further comprises:
step S220, determine the data channel of the original resolution real data.
And step S222, determining strong convection clouds and non-convection clouds in the meteorological image according to the data channel.
And S224, tracking the strong convection cloud cluster by adopting a convolutional neural network and/or an optical flow valve algorithm.
In the above embodiment, the cloud images may be first image-identified and classified using a convolutional neural network, for example, to generate a cloud detection product. Secondly, performing cloud phase recognition on the cloud pixel by adopting a light valve algorithm based on first-stage meteorological data and cloud detection products of radiometric calibration and geographic positioning, combining surface type data, spectrum and texture characteristics of visible light, infrared and near-infrared channels and different thermodynamic phase states of cloud top particles, and obtaining a cloud phase product with original resolution.
And continuing downscaling processing based on the cloud picture processing result, combining the obtained thin roll cloud and broken cloud identification results, and performing high, medium and low cloud identification on the cloud pixels by adopting a threshold method to obtain a cloud classification product with the resolution of 1 km.
For example, the first-stage meteorological data output by the satellite data processing system disclosed by the disclosure is a fire monitoring product, and fire point real-time detection, fire point classification, fire spot ground calculation, fire power influence enhancement processing and the like are mainly performed according to multi-source satellite remote sensing L1 data, meteorological data and other auxiliary data. And calculating the fire risk grade at the future time based on the meteorological data, and uniformly storing, managing and accessing the generated meteorological data products by adopting a file system and a relational database. The B/S framework is adopted to display other auxiliary data in the satellite data processing system, and fire risk grade early warning analysis and risk occurrence statistics can effectively monitor fire points and carry out early warning.
The satellite data-based multitasking parallel processing device 1100 according to this embodiment of the present disclosure is described below with reference to fig. 10. The satellite data-based multitasking parallel processing device 1100 shown in fig. 10 is only an example, and should not bring any limitation to the function and the scope of use of the embodiments of the present disclosure.
As shown in fig. 10, the satellite data-based multitasking parallel processing device 1100 includes an acquisition module 1102 and a determination module 1104.
The obtaining module 1102 is configured to receive broadcast data transmitted by a weather satellite. The acquisition module 1102 is further configured to acquire raw resolution true data of the meteorological satellite and related multi-source satellite assistance data. The determining module 1104 is configured to determine a coordinate of an attention area, and perform splicing correction on the original resolution data and the multi-source satellite auxiliary data according to the coordinate of the attention area to generate first-stage meteorological data in the same format as the original resolution data.
The multi-source satellite auxiliary data comprises at least one of remote sensing data, geographic data and auxiliary meteorological data acquired by a multi-source satellite.
An electronic device 1200 according to this embodiment of the disclosure is described below with reference to fig. 11. The electronic device 1200 shown in fig. 11 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 11, electronic device 1200 is embodied in the form of a general purpose computing device. The components of the electronic device 1200 may include, but are not limited to: the processing unit 1210, the memory unit 1220, and a bus 1230 connecting the components of the different satellite data processing systems, including the memory unit 1220 and the processing unit 1210.
Where the memory unit stores program code, the program code may be executed by the processing unit 1210 such that the processing unit 1210 performs the steps according to various exemplary embodiments of the present disclosure described in the above-mentioned "exemplary methods" section of this specification. For example, the processing unit 1210 may perform all the steps as shown in fig. 2 to 9, and other steps defined in the satellite data-based multitask parallel processing method of the present disclosure.
The storage unit 1220 may include a readable medium in the form of a volatile memory unit, such as a random access memory unit (RAM)12201 and/or a cache memory unit 12202, and may further include a read only memory unit (ROM) 12203.
The electronic device 1200 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 1200 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 1250.
Also, the electronic device 1200 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 1260. As shown, the network adapter 1260 communicates with the other modules of the electronic device 1200 via the bus 1230. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID satellite data processing systems, tape drives, and data backup storage satellite data processing systems, and the like.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the disclosure described in the above-mentioned "exemplary methods" section of this specification, when the program product is run on the terminal device.
Referring to fig. 12, a program product 1300 for implementing the above method according to an embodiment of the present disclosure is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not so limited, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution satellite data processing system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution satellite data processing system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps be performed in this particular order, or that all of the illustrated steps be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (10)
1. A multitask parallel processing method based on satellite data is characterized by comprising the following steps:
receiving broadcast data transmitted by a meteorological satellite;
acquiring original resolution true data of the meteorological satellite and related multi-source satellite auxiliary data;
determining the coordinate of an attention area, splicing and correcting the original resolution data and the multi-source satellite auxiliary data according to the coordinate of the attention area, and generating first-stage meteorological data with the same format as the original resolution data;
the multi-source satellite auxiliary data comprises at least one of remote sensing data, geographic data and auxiliary meteorological data acquired by a multi-source satellite.
2. The satellite data-based multitasking parallel processing method according to claim 1,
the multi-source satellite assistance data comprises at least one of polar orbit satellite data, geostationary satellite data and infrared imaging satellite data.
3. The satellite data-based multitask parallel processing method according to claim 2, wherein the polar orbit satellite data comprises first wind cloud series satellite data and/or third wind cloud series satellite data, the still satellite data comprises second wind cloud series satellite data and/or fourth wind cloud series satellite data, and the infrared imaging satellite data comprises thermal imaging data of the earth environment.
4. The satellite data-based multitasking parallel processing method according to claim 1, wherein generating first-stage meteorological data having the same format as said raw resolution real data comprises:
and carrying out standardization processing on the spliced meteorological data to generate the first-stage meteorological data, wherein the standardization processing comprises at least one of amplification, filtering, frequency conversion, demodulation, error correction decoding and display.
5. The satellite data-based multitask parallel processing method according to claim 1, wherein obtaining raw resolution true data of said meteorological satellite and related multisource satellite auxiliary data comprises:
determining a configuration file of a service platform associated with the meteorological satellite;
and acquiring original resolution true data fed back by the service platform according to the configuration file, and receiving related multi-source satellite auxiliary data and high-resolution satellite data processing system data.
6. The satellite data-based multitask parallel processing method according to claim 1, wherein the step of determining the coordinates of the region of interest, performing splicing correction on the original resolution true data and the multi-source satellite auxiliary data, and generating first-stage meteorological data with the same format as that of the original resolution true data comprises the steps of:
unpacking the received original resolution true data and the multi-source satellite auxiliary data according to the received broadcast data;
determining longitude and latitude information of the coordinates of the attention area;
performing equal longitude and latitude projection processing on the unpacked original resolution true data and the multisource satellite auxiliary data according to the longitude and latitude information to obtain strip-shaped meteorological data;
and splicing and correcting the strip-shaped meteorological data according to the attention area coordinates to generate first-stage meteorological data with the same format as the original resolution real data.
7. The satellite data-based multitasking parallel processing method according to claim 1, further comprising:
performing quality control and format conversion on the output first-stage meteorological data;
determining second-level meteorological data associated with the first-level meteorological data, and/or determining third-level meteorological data associated with the first-level meteorological data;
and archiving the second-level meteorological data and/or the third-level meteorological data, wherein the second-level meteorological data is physical parameter data with the same resolution and position as the first-level meteorological data, and the third-level meteorological data is data projected on the same space-time coordinate as the first-level meteorological data.
8. The satellite data-based multitask parallel processing method according to any one of claims 1-7, further comprising:
responding to a received user access request, and slicing the spliced meteorological data according to the user access request;
sorting according to the resolution and the picture size of the sliced meteorological data, and storing by adopting a response pyramid;
and feeding back corresponding meteorological data according to the user access request, wherein the meteorological data comprises static meteorological pictures and/or dynamic meteorological pictures.
9. The satellite data-based multitask parallel processing method according to claim 8, wherein the step of feeding back the corresponding meteorological data according to the user access request, wherein the meteorological data including a static meteorological picture and/or a dynamic meteorological picture specifically comprises the following steps:
determining satellite orbit information and/or playing parameter information according to the user access request;
and generating a playing control instruction according to the satellite orbit information and/or the playing parameter information, and sending the playing control instruction, wherein the playing control instruction is used for carrying out operation control on the playing process of the meteorological data, and the operation control comprises at least one of starting, stopping, pausing and fast forwarding.
10. The satellite data-based multitask parallel processing method according to any one of claims 1-7, further comprising:
determining a data channel of the original true-resolution data;
determining strong convection clouds and non-convection clouds in the meteorological image according to the data channel;
and tracking the strong convection cloud cluster by adopting a convolutional neural network and/or an optical flow valve algorithm.
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