Marine site selection intelligent auxiliary method based on four-dimensional spacetime digital twinning

Abstract

This application discloses an intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins, relating to the field of marine planning technology. The method includes: determining a site selection index library based on the marine use scenario type corresponding to the marine use demand; filtering out a first candidate marine area matching the site selection index library based on the four-dimensional spatiotemporal data corresponding to the candidate marine areas in the four-dimensional spatiotemporal digital base; generating sensitive area avoidance information corresponding to the first candidate marine area based on preset ecological sensitive areas; selecting a second candidate marine area from the first candidate marine area based on the sensitive area avoidance information; determining the comprehensive evaluation result of the second candidate marine area based on a multi-dimensional evaluation model; selecting a third candidate marine area from the second candidate marine area based on the comprehensive evaluation result; displaying the target evolution trend of the third candidate marine area in the digital twin model corresponding to the third candidate marine area; and generating a target site selection scheme based on the target evolution trend and the third candidate marine area. This method solves the problems of low efficiency and low accuracy of manual site selection.

Description

Technical Field

[0001] This application relates to the field of marine planning technology, and in particular to an intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins. Background Technology

[0002] With the deepening development of marine resources, human demand for marine space utilization is becoming increasingly diversified, encompassing various types such as offshore wind power, modern ports, marine ranching (aquaculture), land reclamation, coastal industry, and island tourism. While bringing economic benefits, these various marine activities inevitably cause complex impacts on marine hydrological conditions, the ecological environment, and the interaction between land and sea. Therefore, scientific and accurate site selection for marine use and environmental impact prediction have become crucial links in balancing economic development and ecological protection.

[0003] However, the relevant technologies for marine site selection remain in a human-dominated stage. This requires the manual collection of multi-source heterogeneous data on all oceans, the manual marking of ecologically sensitive areas, and the proactive avoidance of sensitive areas. Then, based on the remaining ocean data, a manual comparison is made with the actual marine use needs, and seemingly suitable sea areas are selected based on subjective experience. This human-dominated site selection method has low intelligence, low efficiency, and low site selection accuracy.

[0004] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this application is to provide an intelligent auxiliary method, device, and storage medium for marine site selection based on four-dimensional spatiotemporal digital twins, aiming to solve the technical problems of low intelligence level in human-led marine site selection, resulting in low efficiency and low site selection accuracy.

[0006] To achieve the above objectives, this application proposes an intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins. The steps of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins include: Based on the type of sea use scenario corresponding to sea use demand, a site selection index library is determined, and the first candidate sea that matches the site selection index library is selected according to the four-dimensional spatiotemporal data corresponding to the candidate sea in the four-dimensional spatiotemporal digital base. Based on the preset ecologically sensitive areas, sensitive area avoidance information corresponding to the first candidate ocean is generated, and a second candidate ocean is selected from the first candidate ocean based on the sensitive area avoidance information; The comprehensive evaluation result of the second candidate ocean is determined based on the multi-dimensional evaluation model, and the third candidate ocean is selected from the second candidate ocean based on the comprehensive evaluation result; The digital twin model corresponding to the third candidate ocean demonstrates the target evolution trend of the third candidate ocean; Based on the target evolution trend and the third alternative marine generation target site selection scheme.

[0007] For example, before the step of determining the site selection index library based on the type of marine use scenario corresponding to marine use demand, and filtering out the first candidate marine ocean matching the site selection index library based on the four-dimensional spatiotemporal data corresponding to the candidate marine ocean in the four-dimensional spatiotemporal digital base, the method further includes: Acquire four-dimensional spatiotemporal data corresponding to each candidate ocean, wherein the four-dimensional spatiotemporal data includes spatial data, temporal data, attribute data, and evolutionary data; The four-dimensional spatiotemporal data is standardized, including unifying the coordinate system corresponding to the spatial data, unifying the time format corresponding to the time data, unifying the data encoding corresponding to the attribute data, and generating historical evolution trends based on the temporal change characteristics of the evolution data. Establish the correlation between the standardized four-dimensional spatiotemporal data, and based on the correlation, fuse and store the standardized four-dimensional spatiotemporal data to construct the four-dimensional spatiotemporal digital base corresponding to the candidate ocean.

[0008] For example, the step of determining the site selection index library based on the type of marine use scenario corresponding to marine use demand, and filtering out the first candidate marine ocean matching the site selection index library based on the four-dimensional spatiotemporal data corresponding to the candidate marine ocean in the four-dimensional spatiotemporal digital base includes: Obtain the preset relationship between preset sea use scenario types and preset site selection index library, and use the preset site selection index library corresponding to the sea use scenario type as the site selection index library according to the preset relationship; Obtain each location selection index in the location selection index library and the location selection index range corresponding to each location selection index; Based on the aforementioned correlation, obtain the first indicator data in the four-dimensional spatiotemporal data that matches the location indicator; The ocean corresponding to the first indicator data falling within the location indicator range is selected as the first candidate ocean.

[0009] For example, before the step of generating sensitive area avoidance information corresponding to the first candidate ocean based on preset ecological sensitive areas, and selecting a second candidate ocean from the first candidate ocean based on the sensitive area avoidance information, the method further includes: Acquire sensitive area sample data, extract sensitive features based on the sensitive area sample data, and generate a sensitive area sample library; The preset model is trained based on the sensitive area sample library to generate a sensitive area recognition model; Based on the aforementioned correlation, the corresponding four-dimensional spatiotemporal data is input into the sensitive area identification model to obtain the preset ecological sensitive area identified by the sensitive area identification model. A sensitive area vector map layer is generated based on the regional boundary corresponding to the preset ecological sensitive area, and the sensitive area vector map layer is associated and stored in the four-dimensional spatiotemporal digital base.

[0010] For example, the step of generating sensitive area avoidance information corresponding to the first candidate ocean based on preset ecological sensitive areas, and selecting a second candidate ocean from the first candidate ocean based on the sensitive area avoidance information includes: Based on the four-dimensional spatiotemporal digital base, obtain the ocean vector map layer corresponding to the first candidate ocean; Perform spatial overlay analysis on the ocean vector map layer corresponding to each of the first candidate oceans and the sensitive area vector map layer to determine the overlapping area between the ocean vector map layer and the sensitive area vector map layer; When the percentage of overlapping area corresponding to the overlapping region is greater than or equal to a preset ratio, the sensitive area avoidance information is generated based on the overlapping region. The first site selection range corresponding to the first candidate ocean is adjusted based on the sensitive area avoidance information, and the second candidate ocean is determined based on the adjusted first site selection range.

[0011] For example, the step of adjusting the first site selection range corresponding to the first candidate ocean based on the sensitive area avoidance information, and determining the second candidate ocean based on the adjusted first site selection range includes: Based on the adjusted first location range, return to the step of obtaining the first indicator data that matches the location indicator in the four-dimensional spatiotemporal data according to the association relationship; If the first candidate ocean corresponding to the adjusted first site selection range is within the site selection index range corresponding to the site selection index, and the overlapping area ratio of the first candidate ocean is less than the preset ratio, then the first candidate ocean will be used as the second candidate ocean.

[0012] For example, the step of determining the comprehensive evaluation result of the second candidate ocean based on the multi-dimensional evaluation model, and selecting the third candidate ocean from the second candidate ocean based on the comprehensive evaluation result, includes: Obtain evaluation indicators and corresponding quantitative scoring ranges for the evaluation indicators. The evaluation indicators include at least one of the following: natural conditions indicators, ecological and environmental protection indicators, policy compliance indicators, economic feasibility indicators, and safety and control indicators. Based on the aforementioned correlation, obtain second indicator data that matches the evaluation indicator; The evaluation score corresponding to the second indicator data is determined based on the quantitative scoring range. The comprehensive evaluation result corresponding to each of the second candidate oceans is determined based on the evaluation score; The second candidate ocean whose comprehensive evaluation result exceeds the preset evaluation result will be used as the third candidate ocean.

[0013] For example, the step of displaying the target evolution trend of the third candidate ocean in the digital twin model corresponding to the third candidate ocean includes: The four-dimensional spatiotemporal data of the third candidate ocean are obtained from the four-dimensional spatiotemporal digital base, a digital twin model of the third candidate ocean is generated based on the four-dimensional spatiotemporal data, and the digital twin model is output. Obtain the historical evolution trend corresponding to the third candidate ocean, and determine the future evolution trend of the third candidate ocean under at least one preset working condition based on the historical evolution trend; The target evolution trend of the third candidate ocean is generated based on the historical evolution trend and the future evolution trend, and the target evolution trend is displayed in the digital twin model.

[0014] For example, the step of selecting a location for a target based on the target evolution trend and the third alternative ocean generation target includes: The environmental change parameters corresponding to the third candidate ocean are determined based on the target evolution trend. The environmental change parameters include at least one of ecological environment change parameters, topographic and geomorphological change parameters, and hydrological condition change parameters. The environmental change parameters are compared with a preset safety threshold range, and the target risk point and the target risk level corresponding to the target risk point are determined based on the environmental change parameters that exceed the preset safety threshold range. The second site selection range corresponding to the third alternative ocean is adjusted according to the target risk point and the target risk level to generate the fourth alternative ocean; The target site selection scheme is generated based on the fourth alternative ocean.

[0015] For example, the step of generating the target site selection scheme based on the fourth candidate ocean includes: The four-dimensional spatiotemporal data corresponding to the fourth candidate ocean are compared with the preset compliance verification rules to determine the compliance verification result corresponding to the fourth candidate ocean. The compliance verification result includes compliant items and non-compliant items. Based on the compliance verification results and the marine sea use site selection report template, a marine sea use site selection report corresponding to the sea use demand is generated. The marine sea use site selection report includes at least one of the following: sea use demand, various alternative marine areas, sensitive area avoidance information, comprehensive evaluation results, and target evolution trend. The target site selection scheme is generated based on the marine site selection report.

[0016] Furthermore, to achieve the above objectives, this application also proposes an intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins. The intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer program is configured to implement the steps of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins as described above.

[0017] Furthermore, to achieve the above objectives, this application also proposes an intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins. The intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer program is configured to implement the steps of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins as described above.

[0018] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins as described above.

[0019] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins as described above.

[0020] One or more technical solutions proposed in this application have at least the following technical effects: After establishing a four-dimensional spatiotemporal digital base based on the four-dimensional spatiotemporal data of each candidate ocean, this application integrates the four-dimensional spatiotemporal data of each candidate ocean, solving the problem of data fragmentation caused by the inability of manual data collection, thereby providing comprehensive and real-time data support for ocean site selection; This application also pre-sets a site selection index library for each ocean use scenario type, adapting to different ocean use scenario types. After receiving an ocean use request, it filters out the site selection index library adapted to the ocean use scenario type corresponding to the ocean use request, and then calls the four-dimensional spatiotemporal data in the four-dimensional spatiotemporal digital base based on the site selection index library to filter out the first candidate ocean that meets the site selection index library, solving the problem of low site selection accuracy caused by the inability of manual selection of suitable areas to adapt to different scenarios; In addition, this application pre-sets a preset generation After generating the first candidate ocean, sensitive area avoidance information is generated based on the preset ecological sensitive areas to screen out the second candidate ocean that does not have geographical conflicts with the preset ecological sensitive areas. Based on the automatic labeling of the preset ecological sensitive areas and the automatic generation of sensitive area avoidance information based on the preset ecological sensitive areas, the avoidance of ecological sensitive areas is intelligent and precise. Then, the second candidate ocean is evaluated from multiple dimensions using a multi-dimensional evaluation model to further optimize the site selection scheme and screen out the third candidate ocean. Then, a digital twin model corresponding to the third candidate ocean is generated to achieve synchronization with the real ocean. The target evolution trend of the third candidate ocean is then visualized in the digital twin model to provide users with site selection reference and intelligently assist users in determining the optimal ocean from the third candidate ocean. After visually displaying the target evolution trend of the third candidate ocean, a target site selection scheme is generated based on the target evolution trend. This application automatically responds to marine use needs through a full-chain design that "constructs a four-dimensional spatiotemporal digital base, then uses the four-dimensional spatiotemporal digital base to complete multi-level screening, and finally generates a target site selection scheme". It also automatically outputs site selection schemes to users. This not only improves site selection efficiency through the intelligence and automation of the entire site selection process, but also improves site selection accuracy. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1This is a schematic diagram of the modular structure of the four-dimensional spatiotemporal digital twin intelligent auxiliary device for marine site selection in this application; Figure 2 This is a schematic diagram of the four-dimensional spacetime digital base of this application; Figure 3 A schematic diagram illustrating the intelligent auxiliary process for marine site selection based on four-dimensional spatiotemporal digital twins for the marine site selection based on four-dimensional spatiotemporal digital twins of this application; Figure 4 This is a flowchart illustrating the second embodiment of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in this application. Figure 5 This is a detailed flowchart of step S10 of the second embodiment of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in this application; Figure 6 This is a detailed flowchart of step S20 of the second embodiment of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in this application; Figure 7 This is a detailed flowchart of step S30 of the second embodiment of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in this application; Figure 8 This is a detailed flowchart of step S40 of the second embodiment of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in this application; Figure 9 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in the embodiments of this application.

[0024] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0025] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0026] In related technologies, marine site selection remains largely manual, requiring the manual collection of multi-source heterogeneous data from all ocean sources, manual marking of ecologically sensitive areas, and proactive avoidance of these areas. Then, based on the remaining ocean data, a manual comparison is made with the actual marine use needs, relying on subjective experience to select seemingly suitable sea areas. This manual-driven site selection method suffers from low intelligence, low efficiency, and low accuracy.

[0027] This application establishes a four-dimensional spatiotemporal digital base based on the four-dimensional spatiotemporal data of various candidate oceans. This base integrates the four-dimensional spatiotemporal data of each candidate ocean, solving the problems of incomplete data collection due to manual data collection and data fragmentation, thus providing comprehensive and real-time data support for ocean site selection. Furthermore, this application pre-sets a site selection index library for each ocean use scenario type, adapting to different scenario types. Upon receiving an ocean use request, it filters out a site selection index library suitable for that scenario type, and then calls upon the four-dimensional spatiotemporal data in the four-dimensional spatiotemporal digital base to select the first candidate ocean that meets the index. This solves the problem of low site selection accuracy caused by manual selection of suitable areas failing to adapt to different scenarios. Additionally, this application pre-sets a preset ecologically sensitive area, which is used when generating the first candidate ocean. After selecting an ocean, sensitive area avoidance information is generated based on preset ecological sensitive areas to screen out a second alternative ocean that does not have geographical conflicts with the preset ecological sensitive areas. By automatically marking preset ecological sensitive areas and automatically generating sensitive area avoidance information based on preset ecological sensitive areas, intelligent and precise ecological sensitive area avoidance is achieved. Then, a multi-dimensional evaluation model is used to evaluate the second alternative ocean from multiple dimensions to further optimize the site selection scheme and screen out a third alternative ocean. Then, a digital twin model corresponding to the third alternative ocean is generated to achieve synchronization with the real ocean. The target evolution trend of the third alternative ocean is then visualized in the digital twin model to provide users with site selection reference and intelligently assist users in determining the optimal ocean from the third alternative ocean. After visually displaying the target evolution trend of the third alternative ocean, a target site selection scheme is generated based on the target evolution trend. This application automatically responds to marine use needs through a full-chain design that "constructs a four-dimensional spatiotemporal digital base, then uses the four-dimensional spatiotemporal digital base to complete multi-level screening, and finally generates a target site selection scheme". It also automatically outputs site selection schemes to users. This not only improves site selection efficiency through the intelligence and automation of the entire site selection process, but also improves site selection accuracy.

[0028] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0029] This invention provides a method, apparatus, and computer-readable storage medium for intelligent marine site selection based on four-dimensional spatiotemporal digital twins.

[0030] The intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twin provided in this invention embodiment can be an independent electronic device. The electronic device can be a mobile terminal and a fixed terminal, including but not limited to integrated devices such as smartphones, smartwatches, tablets, laptops, and smart vehicle terminals. The fixed terminal includes but is not limited to desktop computers and smart TVs.

[0031] Optionally, the electronic device may also be a server or other device. The server may be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms, but is not limited to these.

[0032] It should be noted that the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in this application embodiment can be implemented by the server alone, by the terminal alone, or by both the terminal and the server.

[0033] The following description uses the example of a smart auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins, implemented independently by a terminal, to illustrate the method.

[0034] First Embodiment like Figure 1 As shown, the intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twin provided in this embodiment of the invention includes: The four-dimensional spatiotemporal digital base module 10 is used to construct a four-dimensional spatiotemporal digital base based on the four-dimensional spatiotemporal data corresponding to the ocean to be selected. The multi-scenario differentiated index adaptation module 20 is used to determine the site selection index library based on the type of sea use scenario corresponding to the sea use demand, and to filter out the first candidate sea that matches the site selection index library according to the four-dimensional spatiotemporal data corresponding to the candidate sea in the four-dimensional spatiotemporal digital base. The ecologically sensitive area automatic identification and avoidance module 30 is used to generate sensitive area avoidance information corresponding to the first candidate ocean based on the preset ecologically sensitive area, and to select a second candidate ocean from the first candidate ocean based on the sensitive area avoidance information. The five-dimensional integrated intelligent demonstration module 40 is used to determine the comprehensive evaluation result of the second candidate ocean based on the multi-dimensional evaluation model, and to select the third candidate ocean from the second candidate ocean based on the comprehensive evaluation result; The digital twin dynamic simulation and deduction module 50 is used to display the target evolution trend of the third candidate ocean in the digital twin model corresponding to the third candidate ocean, and generate a target site selection scheme based on the target evolution trend and the third candidate ocean, wherein the target site selection scheme includes a fourth candidate ocean; The compliance verification and report generation module 60 is used to compare the four-dimensional spatiotemporal data corresponding to the fourth candidate ocean with preset compliance verification rules to determine the compliance verification result corresponding to the fourth candidate ocean. The compliance verification result includes compliant items and non-compliant items. Based on the compliance verification result and the ocean use site selection report template, the module generates an ocean use site selection report corresponding to the ocean use demand. The ocean use site selection report includes at least one of the following: ocean use demand, various candidate oceans, sensitive area avoidance information, comprehensive evaluation results, and target evolution trend.

[0035] In this embodiment, the intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins further includes a data acquisition unit. The data acquisition unit is used to collect four-dimensional spatiotemporal data corresponding to each candidate ocean through multiple sources. The four-dimensional spatiotemporal data includes spatial data, temporal data, attribute data, and evolution data. The spatial data is used to describe the marine spatial characteristics of each candidate ocean. The spatial data includes, but is not limited to, the marine boundary, water depth, topography, and seabed topography corresponding to each candidate ocean. The spatial data can be collected through GPS devices, remote sensing images of the candidate ocean, or seabed exploration equipment, without limitation. For example, the positioning coordinates of the marine boundary corresponding to each candidate ocean are obtained through GPS devices, the topography and seabed topography of each candidate ocean are obtained through remote sensing images, and high-precision water depth data is obtained through seabed exploration equipment (such as a multibeam echo sounder), finally obtaining spatial data including marine boundary, water depth, topography, and seabed topography. The time data records the time-related information of each candidate ocean, including but not limited to data collection time, marine environmental change time series, and marine use approval time nodes. The attribute data describes the non-spatial characteristics of each candidate ocean, including but not limited to marine use, marine ownership, marine water quality, marine sediment, and marine life distribution. The evolutionary data reflects the patterns of change of each candidate ocean over time, including but not limited to marine environmental change trends, evolution patterns of ecologically sensitive areas, and changes in marine use demand.

[0036] Optionally, the data acquisition unit sends the acquired four-dimensional spatiotemporal data to the four-dimensional spatiotemporal digital base module 10, so that the four-dimensional spatiotemporal digital base module 10 can construct a four-dimensional spatiotemporal digital base corresponding to the selected ocean.

[0037] It is understandable that the collected four-dimensional spatiotemporal data is multi-source heterogeneous data, with inherent differences in format, accuracy, reference, and semantics. Without standardization, the data cannot be fused, leading to low location accuracy. Therefore, after collecting the four-dimensional spatiotemporal data, it is standardized to eliminate differences such as format and spatial coordinate system deviations. This application employs different standardization methods for different four-dimensional spatiotemporal data. The standardization methods for the four-dimensional spatiotemporal data include: A unified coordinate system for spatial data; Standardize the time format corresponding to the time data; Unify the data encoding corresponding to the attribute data; Historical evolution trends are generated based on the temporal variation characteristics of the evolution data.

[0038] In one embodiment, when spatial data is collected, spatial data from different sources (such as GPS measured points, remote sensing imagery, and nautical chart scans) often use different geographic coordinate systems. Without a coordinate system conversion, the coordinates of the same spatial location will be misaligned in different geographic coordinate systems, leading to deviations in subsequent ecologically sensitive area overlay analysis and site selection boundary calculations. Therefore, this application converts the original coordinate system of the spatial data into a preset coordinate system, ensuring that all spatial data are in a unified preset coordinate system, thus unifying the coordinate system corresponding to the spatial data. The preset coordinate system can be the WGS84 coordinate system. After the coordinate system conversion, the spatial data in the preset coordinate system is uniformly encapsulated into a preset vector format. Subsequently, an intelligent auxiliary method for marine site selection can be executed based on the spatial data in the preset vector format, avoiding discrepancies in the same spatial data due to different coordinate systems, data formats, and data precision, which could prevent matching with candidate marine areas.

[0039] In one embodiment, after collecting time data, the time data is uniformly converted into time data in a preset time format, which may be UTC time format to eliminate time zone differences; optionally, after unifying the time format of the time data, a timestamp index is established with the time data in the unified time format, and the standardized four-dimensional spatiotemporal data corresponding to each candidate ocean is stored in the timestamp index, and then the four-dimensional spatiotemporal data corresponding to the timestamp index can be found according to the timestamp index.

[0040] In one embodiment, after the attribute data is collected, it is uniformly converted into attribute data with a preset data code. The preset data code includes the data type and the data value range. For example, the attribute data includes the sea area use. The description information corresponding to the sea area use obtained from different channels is different; for example, channel A shows the sea area use as industrial, while channel B shows the sea area use as industrial sea area. To enable the computer to accurately identify the sea area use, the attribute data is uniformly converted into attribute data under the preset data code (e.g., the data code corresponding to industrial sea area is G-01). Optionally, the preset data code also includes the data type and the data value range. The preset data code is used to remove duplicate data, outlier coordinates, severely missing attribute data, and logically contradictory data from the attribute data. Key missing attribute data is supplemented and improved, and invalid data that cannot be supplemented is removed, thus eliminating data redundancy.

[0041] In one embodiment, after collecting evolutionary data, a preset time-series analysis method is used to extract the temporal change features in the evolutionary data to generate the historical evolution trend of each candidate ocean. Specifically, the evolutionary data is sorted according to the timestamp index to generate an evolutionary data time series. Based on the evolutionary data time series, the temporal change features that have changed (such as changes in water depth, changes in erosion and deposition rates, changes in shoreline displacement, and changes in the area of ​​sensitive areas) are determined. Based on the time series, the historical evolution trend corresponding to each of the temporal change features is generated (such as the shoreline displacement rate to the sea being 0.12 m / year).

[0042] Optionally, after standardizing the four-dimensional spatiotemporal data, a correlation relationship is established between the standardized four-dimensional spatiotemporal data. Based on the correlation relationship, the standardized four-dimensional spatiotemporal data is fused and stored to construct a four-dimensional spatiotemporal digital base corresponding to the candidate ocean. In one embodiment, the correlation relationship can be a relationship established by using the spatial location of the candidate ocean as a spatial index, and using the spatial index to associate other spatial data, temporal data, attribute data, and evolutionary data corresponding to the candidate ocean. This enables the classified storage of four-dimensional spatiotemporal data of candidate oceans at different spatial locations and the fused storage of four-dimensional spatiotemporal data of the same candidate ocean, so as to realize the retrieval of four-dimensional spatiotemporal data of the candidate ocean corresponding to the spatial location based on the spatial location. Optionally, the correlation relationship includes the correlation relationship between temporal data and evolutionary data, using temporal data as a timestamp index, and mapping the evolutionary data to the timestamp index. The evolutionary data is indexed by timestamps, allowing for categorized storage of the data. Subsequently, the evolutionary data of different candidate oceans corresponding to a given timestamp index can be retrieved. The association also includes the relationship between spatial location and attribute data. Using spatial location as a spatial index, the spatial location is associated with the attribute data of the candidate ocean corresponding to that location, enabling categorized storage of attribute data for different candidate oceans and fused storage of attribute data for the same candidate ocean. The association may also include the relationship between spatial location and temporal data, and the relationship between spatial location and evolutionary data, etc., which will not be elaborated here. It should be noted that this application embodiment uses the relationship between spatial location and four-dimensional spatiotemporal data as an example for analysis.

[0043] Furthermore, after establishing the aforementioned association, the four-dimensional spatiotemporal data is fused and stored based on the association. This embodiment employs a distributed database (such as Hadoop) to construct a storage system, distributing the associated four-dimensional spatiotemporal data. Then, based on the association and the four-dimensional spatiotemporal data, the construction of the four-dimensional spatiotemporal digital base corresponding to the candidate ocean is completed. It should be noted that the four-dimensional spatiotemporal digital base module 10 includes a data interface to enable unified access to the four-dimensional spatiotemporal data by other modules, supporting subsequent data reading and interaction among various modules. For example, refer to... Figure 2 , Figure 2 Example diagram of a four-dimensional spacetime digital base.

[0044] Optionally, the four-dimensional spacetime digital base module 10 supports real-time updates, acquires four-dimensional spacetime data in real time, and updates the four-dimensional spacetime digital base based on the latest four-dimensional spacetime data to ensure the real-time performance and accuracy of the data.

[0045] In one optional implementation, the multi-scenario differentiated index adaptation module 20 pre-sets a preset relationship between preset marine use scenario types and preset site selection index libraries. Different preset marine use scenario types correspond to different preset site selection index libraries. This preset site selection index library is used to filter out the first candidate ocean corresponding to the preset marine use scenario type from the candidate oceans. The preset site selection index library includes at least one site selection index, each site selection index corresponds to a different site selection index range, and different site selection indices correspond to different site selection weights. Specifically, the preset marine use scenario types include, but are not limited to, land reclamation, port use, aquaculture use, offshore wind power use, industrial use, and cultural tourism use. For example, the site selection index library corresponding to land reclamation includes: {water depth index, [water depth less than or equal to 10m]; topography index, [topography index less than or equal to 5 degrees]; sensitive area distance index, [sensitive area distance greater than or equal to 1km]; geological stability level index, [geological stability level greater than or equal to good level]; ...}.

[0046] Optionally, upon receiving a marine use demand that includes a marine use scenario type, a site selection index library corresponding to the marine use scenario type is determined according to a preset relationship. The site selection index intervals in the library, along with the ocean to be selected, are then used to filter the ocean to obtain a first candidate ocean. The four-dimensional spatiotemporal data corresponding to the first candidate ocean satisfies the site selection indexes and intervals required by the site selection index library. Specifically, after determining the site selection index library corresponding to the marine use demand, the data interface of the four-dimensional spatiotemporal digital base module 10 is called. Based on the association established in the four-dimensional spatiotemporal digital base, the first index data matching the site selection index is searched. For example, for the water depth index in the site selection index library, the water depth data of 3m corresponding to ocean A with spatial location ID_001 in the four-dimensional spatiotemporal digital base is selected. Then, the found first index data is compared with its corresponding site selection index interval. When all the first index data are within the site selection index interval, the ocean to be selected is taken as the first candidate ocean. Furthermore, after determining the first candidate ocean, the data is transmitted to the ecologically sensitive area automatic identification and avoidance module 30, so that the ecologically sensitive area automatic identification and avoidance module 30 can determine whether the first candidate ocean overlaps with the preset ecologically sensitive area. If there is an overlap, the first candidate ocean is adjusted and a second candidate ocean is determined. The second candidate ocean does not overlap with the preset ecologically sensitive area.

[0047] In one optional implementation, the ecologically sensitive area automatic identification and avoidance module 30 pre-selects various preset ecologically sensitive areas; optionally, the method for selecting various preset ecologically sensitive areas is as follows: acquiring sensitive area sample data, extracting sensitive features based on the sensitive area sample data, and generating a sensitive area sample library; training a preset model based on the sensitive area sample library to generate a sensitive area identification model; inputting the corresponding four-dimensional spatiotemporal data into the sensitive area identification model according to the correlation relationship to obtain the preset ecologically sensitive areas identified by the sensitive area identification model; generating a sensitive area vector layer based on the regional boundary corresponding to the preset ecologically sensitive area, and storing the sensitive area vector layer in association with the four-dimensional spatiotemporal digital base.

[0048] Optionally, the sensitive area sample data includes positively sensitive area sample data, which includes ecologically sensitive areas with confirmed rights. The sensitive area sample data also includes non-sensitive area sample data, which includes non-sensitive areas. For example, remote sensing image samples and field survey samples of mangroves, coral reefs, and seagrass beds in a certain sea area are collected. Sensitive features for characterizing sensitive areas are extracted from the sensitive area sample data. These sensitive features include, but are not limited to, remote sensing image features, topographic features, geomorphic features, hydrological features, and biological features; for example, the sensitive features corresponding to mangroves are [water depth -2m to 0m, topographic slope <2°, salinity: 25-30ppt]. Optionally, after obtaining the sensitive features, a sensitive area sample library is generated based on the sensitive features and the sensitive area sample data. Further, a preset model is trained based on the sensitive area sample library to generate a sensitive area identification model. The preset model includes, but is not limited to, deep learning models such as CNN convolutional neural networks. The preset model can also be a random forest model, a support vector machine model, etc., which are not limited here. After generating the sensitive area identification model, four-dimensional spatiotemporal data corresponding to each candidate ocean are retrieved from the four-dimensional spatiotemporal digital base according to the aforementioned correlation. Sensitive features are extracted from the four-dimensional spatiotemporal data, and these sensitive features are input into the sensitive area identification model so that the model can determine the preset ecologically sensitive areas in the candidate oceans based on the four-dimensional spatiotemporal data. After determining the preset ecologically sensitive areas, boundary identification is performed on the preset ecologically sensitive areas to obtain the corresponding regional boundaries. A sensitive area vector layer is generated based on the regional boundaries to determine the spatial location of the preset ecologically sensitive areas. A spatial index is generated based on the spatial location, and the sensitive area vector layer corresponding to the preset ecologically sensitive areas is stored in the four-dimensional spatiotemporal digital base based on the spatial index. Optionally, it can also involve determining the candidate ocean where the preset ecological sensitive area is located, associating and storing the sensitive area data corresponding to the preset ecological sensitive area with the four-dimensional spatiotemporal data of the candidate ocean, and then directly determining the preset ecological sensitive area in the candidate ocean when the candidate ocean is found later; or it can involve determining the range of the digital sensitive area of ​​the preset ecological sensitive area in the four-dimensional spatiotemporal digital base, and superimposing the sensitive area vector layer on the range of the digital sensitive area corresponding to the four-dimensional spatiotemporal digital base, whereby the range of the digital sensitive area is used to characterize the spatial mapping area of ​​the sensitive area vector layer in the four-dimensional spatiotemporal digital base. In one optional implementation, the preset ecologically sensitive area generated by the sensitive area identification model is used to compare with the first candidate ocean corresponding to the marine use demand. It is determined whether the percentage of the overlapping area between the first candidate ocean and the preset ecologically sensitive area is greater than or equal to a preset ratio. If so, the first candidate ocean needs to be adjusted until the percentage of the overlapping area between the adjusted first candidate ocean and the preset ecologically sensitive area is less than the preset ratio, so as to prevent damage to the preset ecologically sensitive area.

[0049] In one embodiment, after obtaining a first candidate ocean, a marine vector layer of the first candidate ocean in a four-dimensional spatiotemporal digital base is obtained. The marine vector layer is used to define the digital sea area range corresponding to the first candidate ocean in the four-dimensional spatiotemporal digital base. The digital sea area range represents the spatial mapping area of ​​the marine vector layer in the four-dimensional spatiotemporal digital base. A preset ecologically sensitive area's digital sensitive area range in the four-dimensional spatiotemporal digital base is also obtained. The method for performing spatial overlay analysis between the marine vector layer and the sensitive area vector layer is as follows: a spatial topology algorithm is used to calculate whether there is an overlapping area between the digital sensitive area range and the digital sea area range. If so, the overlapping area is taken as the overlapping area between the marine vector layer and the sensitive area vector layer, and then the area of ​​the overlapping area is obtained. The area of ​​the overlapping area can be the area of ​​the overlapping area in the four-dimensional spatiotemporal digital base, or it can be the actual area of ​​the overlapping area.

[0050] Furthermore, the overlapping area ratio corresponding to the overlapping area of ​​the overlapping region is obtained. This overlapping area ratio can be the ratio between the overlapping area of ​​the overlapping region and the ocean area of ​​the first candidate ocean, or it can be the ratio between the overlapping area of ​​the overlapping region and the sensitive area area of ​​the preset ecologically sensitive zone. When the overlapping area ratio is greater than or equal to the preset ratio, it is determined that the first candidate ocean contains a large area of ​​the preset ecologically sensitive zone. In this case, the first site selection range corresponding to the first candidate ocean needs to be adjusted to prevent conflicts with the preset ecologically sensitive zone. It should be noted that different preset ecologically sensitive zones correspond to different preset ratios. The higher the sensitivity level of the preset ecologically sensitive zone, the lower the corresponding preset ratio, and vice versa, to balance the importance of the preset ecologically sensitive zone and the flexibility of site selection.

[0051] Specifically, when the percentage of overlapping area is greater than or equal to a preset ratio, sensitive area avoidance information is generated based on the overlapping area. This sensitive area avoidance information includes conflict type, conflict level, avoidance direction, and avoidance distance. The sensitive area avoidance information is used to guide the adjustment of the first site selection range corresponding to the first candidate ocean. For example, the sensitive area avoidance information is "This area overlaps with the mangrove sensitive area, the conflict level is level one, and it is recommended to adjust it 500 meters to the northeast."

[0052] In one embodiment, the conflict type is determined based on the sensitive area type of the preset ecologically sensitive zone corresponding to the overlap. The sensitive area types include, but are not limited to, mangroves, coral reefs, and seagrass beds. The conflict type includes, but is not limited to, mangrove conflict, coral reef conflict, and seagrass bed conflict. The conflict level is determined based on the sensitive area level of the preset ecologically sensitive zone corresponding to the overlap. Different preset ecologically sensitive zones correspond to different sensitive area levels; for example, the sensitive area level corresponding to mangroves exceeds the sensitive area level corresponding to seagrass beds. The avoidance direction is determined based on the location of the overlapping area within the preset ecologically sensitive zone. A direction pointing outwards from the preset ecologically sensitive zone is determined based on the location of the overlapping area, and this direction is used as the avoidance direction. For example, if the overlapping area is located northwest of the mangroves, the direction pointing outwards from the preset ecologically sensitive zone is southeast, and the avoidance direction is southeast, allowing the candidate ocean to avoid the mangroves. The avoidance distance is determined based on the overlapping area of ​​the overlapping areas; the larger the overlapping area, the larger the corresponding avoidance distance. It should be noted that different preset ecologically sensitive areas correspond to different sensitivity levels. When calculating the avoidance distance, the avoidance distance is determined by combining the sensitivity level and the overlapping area. The higher the sensitivity level, the larger the corresponding avoidance distance. After calculating the initial avoidance distance based on the overlapping area, a correction coefficient is determined based on the sensitivity level. The higher the sensitivity level, the larger the corresponding correction coefficient. The product of the initial avoidance distance and the correction coefficient is then used as the avoidance distance. For example, if the initial avoidance distance is 500m, and the preset ecologically sensitive area corresponding to the overlap is mangrove forest, the corresponding correction coefficient is 1.5, then the generated avoidance distance is 500*1.5=750m; if the preset ecologically sensitive area corresponding to the overlap is seagrass bed, the corresponding correction coefficient is 1.1, then the generated avoidance distance is 500*1.1=550m.

[0053] In another embodiment, the sensitive area avoidance information can also be used to guide the cutting of overlapping areas from the first site selection range corresponding to the first candidate ocean, so that the remaining sea area range can be used as the second candidate ocean. In this case, the sensitive area avoidance information includes the overlapping area, so that the overlapping area can be removed from the first site selection range corresponding to the first candidate ocean based on the spatial location, and the second candidate ocean can be determined based on the removed first site selection range.

[0054] In this embodiment, to prevent the selected ocean from conflicting with a pre-defined ecologically sensitive area during subsequent construction, after generating sensitive area avoidance information, this embodiment acquires the evolution data corresponding to the pre-defined ecologically sensitive area, generates a historical evolution trend, determines the future evolution trend of the pre-defined ecologically sensitive area based on the historical evolution trend, determines the future regional boundary of the pre-defined ecologically sensitive area in a future time period based on the future regional boundary, determines the overlapping area and the percentage of overlapping area based on the future regional boundary, and adjusts the avoidance direction and avoidance distance in the sensitive area avoidance information based on the overlapping area and the percentage of overlapping area; for example, if the percentage of overlapping area in the future time period shows an upward trend, the avoidance distance is increased. Thus, based on the fact that the pre-defined ecologically sensitive area changes over time, this application introduces the future evolution trend of the pre-defined ecologically sensitive area to adjust the site selection range, improving the accuracy of site selection.

[0055] In another embodiment, the future evolution trend of the first candidate ocean can be predicted based on the four-dimensional spatiotemporal data of the first candidate ocean. The overlapping area and the area ratio of the overlapping area can be predicted based on the future evolution trend of the first candidate ocean. The sensitive area avoidance information can be adjusted based on the predicted overlapping area and the area ratio of the overlapping area, so as to adjust the site selection range by incorporating the future evolution trend of the candidate ocean.

[0056] In another embodiment, the current overlapping area and the area ratio of the current overlapping area can be obtained, and the first future evolution trend of the preset ecologically sensitive area and the second future evolution trend corresponding to the first candidate ocean can be obtained. The future overlapping area and the future overlapping area ratio are determined based on the first future evolution trend and the second future evolution trend. Finally, sensitive area avoidance information is generated based on the current overlapping area, the area ratio of the current overlapping area, the future overlapping area and the future overlapping area ratio.

[0057] In this embodiment, after generating sensitive area avoidance information, the ecologically sensitive area automatic identification and avoidance module 30 obtains the first site selection range corresponding to the first candidate ocean, adjusts the first site selection range based on the sensitive area avoidance information, and uses the sea area corresponding to the adjusted first site selection range as the second candidate ocean. The number of oceans corresponding to the first candidate ocean is greater than the number of oceans corresponding to the second candidate ocean, the sea area corresponding to the first candidate ocean is greater than the sea area corresponding to the second candidate ocean, and the overlap area ratio between the second candidate ocean and the preset ecologically sensitive area is less than a preset ratio.

[0058] It should be noted that the four-dimensional spatiotemporal data of the second candidate ocean corresponding to the adjusted first site selection range differs from that of the first candidate ocean. Therefore, the four-dimensional spatiotemporal data of the second candidate ocean may not meet the site selection index library. Based on this, after adjusting the first site selection range, the adjusted first site selection range is returned to the multi-scenario differentiated index adaptation module 20. The multi-scenario differentiated index adaptation module 20 determines the first candidate ocean of the adjusted first site selection range based on the adjusted first site selection range. According to the correlation, it retrieves the first index data corresponding to the adjusted first candidate ocean from the four-dimensional spatiotemporal digital base module 10. Then, it compares the retrieved first index data with the site selection index library corresponding to the sea use demand. When the first index data is within the site selection index range corresponding to the site selection index library, it is determined that the first candidate ocean corresponding to the adjusted first site selection range meets the site selection index library. Then, the first candidate ocean corresponding to the adjusted first site selection range is used as the second candidate ocean. When the first indicator data is not within the location indicator range, discard the first candidate ocean that does not meet the location indicator range and use the other first candidate oceans as the second candidate oceans.

[0059] In one optional implementation, after determining the second candidate ocean, the selected second candidate ocean is input into the five-dimensional integrated intelligent evaluation module 40, so that the five-dimensional integrated intelligent evaluation module 40 can perform a multi-dimensional comprehensive evaluation of the second candidate ocean and determine the comprehensive evaluation corresponding to each second candidate ocean. The five-dimensional integrated intelligent evaluation module 40 includes a multi-dimensional evaluation model, which is used to comprehensively evaluate the second candidate ocean from multiple evaluation dimensions. The evaluation dimensions include, but are not limited to, natural conditions, ecological and environmental protection, policy compliance, economic feasibility, and safety and prevention dimensions. The corresponding evaluation indicators include at least one of the following: natural conditions, ecological and environmental protection, policy compliance, economic feasibility, and safety and prevention indicators.

[0060] In one optional implementation, the comprehensive evaluation of the second candidate ocean from multiple evaluation dimensions involves obtaining the evaluation indicators corresponding to each evaluation dimension and the quantitative scoring range corresponding to each evaluation indicator. This quantitative scoring range includes a predefined score range (e.g., 0-100 points) to standardize the scoring criteria for the second indicator data. Then, the data interface of the four-dimensional spatiotemporal digital base module 10 is invoked to retrieve the second indicator data corresponding to the evaluation indicator. Based on the quantitative scoring range and the second indicator data, the evaluation score of the second candidate ocean under each evaluation indicator is determined. Then, a weighted fusion is performed based on the evaluation scores and weights corresponding to each evaluation indicator, and the calculation result is used as the comprehensive evaluation result of the second candidate ocean. Specifically, the natural condition indicators are used to quantify the evaluation scores corresponding to natural conditions such as water depth, topography, and climate; the ecological and environmental protection indicators are used to quantify the evaluation scores corresponding to ecological and environmental protection conditions such as distance to sensitive areas and ecological and environmental impact; the policy compliance indicators are used to quantify the evaluation scores corresponding to sea use approval requirements and planning legality; the economic feasibility indicators are used to quantify the evaluation scores corresponding to construction costs and expected benefits; and the safety and control indicators are used to quantify the assessment scores corresponding to geological safety and disaster risks. For example, the evaluation indicators, corresponding evaluation weights, and quantitative scoring ranges for the five evaluation dimensions are as follows: Natural conditions indicator [weight 0.25; quantitative scoring range for water depth indicator includes {h is the water depth value, 10m≦h≦20m, 90-100 points; h≥20m or 5m≦h≦10m, 60-90 points; other water depth values, 0-60 points}]; Ecological and environmental protection indicator [weight 0.25; quantitative scoring range for sensitive area distance indicator includes {t is the sensitive area distance, 500m≦t, 90-100 points; 200m≦h<500m, 60-90 points; t<200m, 0-60 points}]. When the second indicator data for the second candidate ocean includes a water depth of 20m, the evaluation score corresponding to this second indicator data is 100 points.

[0061] Furthermore, the comprehensive evaluation results corresponding to the second candidate oceans are obtained. Second candidate oceans whose comprehensive evaluation results exceed the preset evaluation results are selected as third candidate oceans, while second candidate oceans whose comprehensive evaluation results are lower than the preset evaluation results are excluded. For example, the preset evaluation result is set to 80 points, and second candidate oceans with a total score ≥ 80 points are selected. Alternatively, the second candidate oceans can be sorted from highest to lowest based on their comprehensive evaluation results, and a preset number of second candidate oceans are selected as third candidate oceans based on the sorting results, such as the top three second candidate oceans.

[0062] It should be noted that, in order to better assist users in selecting suitable oceans, after determining the comprehensive evaluation results for each second alternative ocean, the advantages and disadvantages of each second alternative ocean are determined based on the evaluation scores obtained by the second alternative ocean on each evaluation indicator. Evaluation indicators with scores higher than the preset scores are identified as the advantages of the second alternative ocean, while evaluation indicators with scores lower than the preset scores are identified as the disadvantages of the second alternative ocean. For example, if Ocean A has a comprehensive evaluation result of 92 points and an ecological and environmental protection indicator score of 100 points, its corresponding advantage is a high ecological and environmental protection score, and its disadvantage is a low economic feasibility indicator score. In one embodiment, after determining the comprehensive evaluation results of each second candidate ocean, each second candidate ocean is output in descending order of the comprehensive evaluation results, along with its corresponding advantages and disadvantages, for the user to evaluate and select a suitable sea area. Alternatively, after determining the comprehensive evaluation results of each second candidate ocean and selecting a third candidate ocean, each third candidate ocean is output in descending order of the comprehensive evaluation results of the third candidate ocean, along with its corresponding advantages and disadvantages, for the user to evaluate and select a suitable sea area from the third candidate ocean.

[0063] Optionally, after determining each third candidate ocean, the digital twin dynamic simulation and deduction module 50 generates a digital twin model corresponding to each third candidate ocean and outputs the digital twin model; in the process of displaying the digital twin model, the comprehensive evaluation results, advantages and disadvantages of each third candidate ocean can also be displayed to assist users in selecting a suitable sea area.

[0064] In one embodiment, the method for generating digital twin models corresponding to each third candidate ocean is as follows: Based on a four-dimensional spatiotemporal digital base, four types of ocean data are integrated and stored: spatial data, temporal data, attribute data, and evolutionary data. First, a three-dimensional model of the third candidate ocean is constructed according to a preset ratio based on the spatial data. Then, remote sensing imagery and survey data are used to refine the model, including real-world elements such as seabed topography, coastline, marine facilities, and ecological zones. Next, the attribute data is linked and bound to the three-dimensional model. Finally, based on the temporal and evolutionary data, the dynamic changes of the third candidate ocean at different time points are determined. The digital twin model is then built based on the dynamic changes and the three-dimensional model. It should be noted that the digital twin model recreates the real-world scene information of the third candidate ocean, including topography, water depth, ecological environment, and surrounding facilities, achieving real-time synchronization with the actual third candidate ocean. After the four-dimensional spatiotemporal data is updated, the constructed digital twin model also changes with the updated four-dimensional spatiotemporal data, achieving data synchronization.

[0065] Optionally, after the digital twin model is output, the user can click on the digital twin model to view the comprehensive evaluation results, advantages and disadvantages of the third alternative ocean, so that the user can select a suitable sea area based on the displayed digital twin model and comprehensive evaluation results.

[0066] Furthermore, after generating the digital twin model, the digital twin dynamic simulation and deduction module 50 can also determine the target evolution trend of the third candidate ocean and display the corresponding target evolution trend in each digital twin model. The method for determining the target evolution trend of each third candidate ocean can be to obtain the historical evolution trend of each third candidate ocean, determine the future evolution trend of the third candidate ocean under at least one preset operating condition based on the historical evolution trend, and generate the target evolution trend by combining the historical evolution trend and the future evolution trend.

[0067] In one embodiment, the preset operating conditions include, but are not limited to, climate change operating conditions, marine environment change operating conditions, and marine engineering construction operating conditions. The climate change operating conditions are used to predict changes in the ecological environment, topography, and hydrological conditions of the third candidate marine environment after climate conditions change. Examples include hydrological changes caused by extreme weather events such as temperature fluctuations, monsoon transitions, rainfall increases / decreases, and typhoons / cold waves; shoreline and seabed topographic evolution caused by strong wind and wave erosion and precipitation runoff impacts; and ecological changes such as changes in biological growth status, shifts in ecological community distribution, and changes in the living environment of sensitive areas caused by changes in sunlight and temperature. The marine environment change operating conditions are used to predict changes in the ecological environment, topography, and hydrological conditions of the third candidate marine environment after changes in the marine environment. Examples include changes in tidal currents, water temperature and salinity, and water content. Changes in hydrological conditions, such as sediment load; topographic and geomorphological changes, such as seabed topography and coastline evolution caused by seawater erosion and siltation; ecological and environmental changes, such as fluctuations in water quality indicators, migration of biological communities, and alterations in the state of ecologically sensitive areas; and changes in the ecological environment, topography, and hydrological conditions of a third candidate marine area after the commencement of marine engineering construction projects such as land reclamation, port construction, offshore wind power, and aquaculture. For example, hydrological changes caused by construction disturbances, such as changes in water flow, turbulent water flow, and sediment suspension and diffusion; topographic and geomorphological changes caused by filling operations, earth and rock stockpiling, and engineering pile foundation construction, such as changes in seabed elevation, local landform reshaping, and coastline morphology; and ecological changes caused by construction pollution, habitat destruction, and water disturbances, such as water quality decline, biological escape, and damage to the function of ecologically sensitive areas.

[0068] It should be noted that the preset operating conditions may also include routine marine operation and maintenance conditions. These conditions are used to predict changes in the ecological environment, topography, and hydrological conditions of the third candidate marine environment after the long-term operation of marine supporting facilities. Examples include changes in hydrological conditions such as waterway navigation, equipment maintenance, and water flow disturbances, water turbulence, and local water level fluctuations caused by ship traffic; topographic changes such as local seabed erosion and shoreline wear caused by ship anchoring and wave scouring; and ecological changes such as minor fluctuations in water quality, alterations in biological habitat patterns, and changes in local ecological activity caused by ship sewage discharge and navigation disturbances. The preset operating conditions may also include other conditions, such as human activity conditions and marine motion conditions, which are not limited here.

[0069] Optionally, after generating the target evolution trend, the target evolution trend is displayed in a digital twin model. The target evolution trend includes environmental parameters of the third candidate ocean at different time points, such as ecological environment parameters, topographic parameters, and hydrological condition parameters.

[0070] In another embodiment, after visualizing the evolution trend of the target, environmental change parameters are obtained. These environmental change parameters are used to characterize the amount and / or rate of change between the environmental parameters of the third candidate ocean at various future time points in the future time period and the environmental parameters at the current time point.

[0071] Optionally, the environmental change parameters include ecological environment change parameters, topographic and geomorphological change parameters, and hydrological condition change parameters. These environmental change parameters are compared with a preset safety threshold range, which is a reasonable range corresponding to the environmental parameters pre-set in accordance with marine regulations, ecological protection standards, and engineering safety specifications, and serves as the basis for risk assessment. This application embodiment pre-defines the relationship between environmental parameters and preset risk points. Different environmental change parameters correspond to different preset risk points. For example, ecological environment change parameters include dissolved oxygen changes, and the corresponding preset risk point is water quality deterioration; when dissolved oxygen content continues to decrease, a risk point of water quality deterioration is determined.

[0072] In one embodiment, environmental change parameters are compared with a preset safety threshold range. When the environmental change parameters exceed the preset safety threshold range, a preset risk point corresponding to the environmental change parameters is used as the target risk point. The environmental change parameters are compared with the interval values ​​in the preset safety threshold range, where the interval values ​​are the maximum and minimum interval values. The difference between the environmental change parameters and the interval values ​​is used to determine the target risk level. The larger the difference, the higher the target risk level; the smaller the difference, the lower the target risk level. Alternatively, the target risk level can be determined based on the duration of the exceedance of the preset safety threshold range. The shorter the duration, the lower the target risk level; the longer the duration, the higher the target risk level.

[0073] Optionally, after determining the target risk points and target risk levels, the second site selection range corresponding to the third candidate ocean is adjusted according to the target risk points and target risk levels. The adjusted second site selection range is used to determine the fourth candidate ocean. A target site selection scheme is generated based on the fourth candidate ocean. The target site selection scheme includes, but is not limited to, the four-dimensional spatiotemporal data of each fourth candidate ocean, the site selection range, the comprehensive evaluation results, the overlapping area with the preset ecologically sensitive area, the distance between the fourth candidate ocean and the preset ecologically sensitive area, the stored target risk points, and the target risk levels. Additionally, engineering design parameters can be adjusted to eliminate the environmental impact of engineering operations. It should be noted that after adjusting the second site selection range and / or adjusting the engineering design parameters, the target evolution trend is regenerated based on the adjusted second site selection range and / or engineering design parameters to reassess environmental change parameters and target risk points until no target risk points exist and / or the target risk level corresponding to the target risk points is lower than the preset risk level.

[0074] Optionally, after determining the fourth candidate marine area, the compliance verification and report generation module 60 is invoked. This module performs compliance verification based on preset compliance verification rules and generates a marine area site selection report based on the verification results. Specifically, national and local marine area laws, regulations, and industry standards are obtained. Core verification points, such as the scope of use, intended purpose, and safe distance from ecologically sensitive areas, are extracted. Preset compliance verification rules are generated based on these core verification points. Then, the four-dimensional spatiotemporal data corresponding to the fourth candidate marine area is retrieved using these rules to determine whether the fourth candidate marine area meets all the preset compliance verification rules. A compliance verification result is generated, including compliant and non-compliant items. If non-compliant items exist, the third site selection scope and / or engineering design parameters corresponding to the fourth candidate marine area are adjusted until the final site selection scheme meets all the preset compliance verification rules.

[0075] Optionally, after the fourth alternative ocean meets the preset compliance verification rules, the output results of each module and the compliance verification results are obtained respectively; based on the output results and the compliance verification results, fill data is generated in the ocean use site selection report template, and the fill data is used to fill the ocean use site selection report template to generate an ocean use site selection report. The ocean user site selection report includes at least one of the following: ocean use demand, alternative oceans output by each module (first alternative ocean, second alternative ocean, third alternative ocean, and fourth alternative ocean), sensitive area avoidance information, comprehensive evaluation results, and target evolution trend. Further, after generating the ocean use site selection report, the ocean use site selection report is used as the target site selection scheme, and the target site selection scheme is output.

[0076] In one specific implementation, refer to Figure 3 , Figure 3 This document illustrates a flowchart illustrating the execution of a four-dimensional spatiotemporal digital twin-based intelligent auxiliary device for marine site selection, demonstrating how it implements a four-dimensional spatiotemporal digital twin-based intelligent auxiliary method for marine site selection. The method by which the four-dimensional spatiotemporal digital twin-based intelligent auxiliary device for marine site selection executes the four-dimensional spatiotemporal digital twin-based intelligent auxiliary method for marine site selection in this embodiment is as follows: Step 1: Collect four-dimensional spatiotemporal data for each candidate ocean. The four-dimensional spatiotemporal data includes four-dimensional ocean data composed of spatial data, temporal data, attribute data, and evolutionary data. Step 2: The four-dimensional spatiotemporal digital base module 10 constructs a four-dimensional spatiotemporal digital base based on four-dimensional spatiotemporal data to integrate, standardize, store, and update the four-dimensional spatiotemporal data in real time. Step 3: Responding to the user's input of sea use demand including sea use scenario types, the multi-scenario differentiated indicator adaptation module 20 automatically matches the site selection indicator library corresponding to the sea use scenario type and filters out the first candidate ocean that meets the requirements of the site selection indicator library. Step 4: After the ecologically sensitive area automatic identification and avoidance module 30 extracts the preset ecologically sensitive area, it overlays and analyzes the preset ecologically sensitive area with the first candidate ocean. When a conflict is determined, it outputs sensitive area avoidance information and filters out the second candidate ocean without conflict. Step 5: The five-dimensional integrated intelligent demonstration module 40 performs quantitative scoring and comprehensive evaluation on the second candidate ocean, and selects the third candidate ocean whose comprehensive evaluation results exceed the preset evaluation results; Step 6: The digital twin dynamic simulation and deduction module 50 performs dynamic simulation and risk prediction on the third candidate ocean to iteratively optimize the third candidate ocean, and uses the iteratively optimized third candidate ocean as the fourth candidate ocean. Step 7: The compliance verification and report generation module 60 performs compliance verification on the fourth alternative marine area, determines the compliance of the fourth alternative marine area, automatically generates a marine area site selection report, outputs the target site selection plan, and completes the entire intelligent auxiliary process for marine area site selection.

[0077] This application proposes an intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins. It adopts a modular collaborative architecture, comprising a four-dimensional spatiotemporal digital base module 10, a multi-scenario differentiated indicator adaptation module 20, an ecologically sensitive area automatic identification and avoidance module 30, a five-dimensional integrated intelligent demonstration module 40, a digital twin dynamic simulation and deduction module 50, and a compliance verification and report generation module 60. The four-dimensional spatiotemporal digital base module 10 integrates four types of multi-source heterogeneous marine data—spatial data, temporal data, attribute data, and evolutionary data—from various candidate marine areas to construct a four-dimensional spatiotemporal digital base. After acquiring marine use requirements including different marine use scenarios, the multi-scenario differentiated indicator adaptation module 20 matches the corresponding site selection indicator library to filter the selected sites. The first candidate ocean is then identified. The ecologically sensitive area automatic identification and avoidance module 30 overlays and analyzes the preset ecologically sensitive area and the first candidate ocean. If there is an overlap, it outputs sensitive area avoidance information to obtain the second candidate ocean. The five-dimensional integrated intelligent demonstration module 40 conducts quantitative scoring and comprehensive evaluation of the second candidate ocean, and selects the third candidate ocean that meets the comprehensive evaluation results. The digital twin dynamic simulation and deduction module 50 conducts multi-condition dynamic simulation, risk prediction and iterative optimization for the third candidate ocean, and the optimized fourth candidate ocean is formed. Finally, the compliance verification and report generation module 60 performs compliance verification on the fourth candidate ocean, generates compliance verification results, and automatically generates a standardized marine use site selection report to output the target site selection plan, realizing a fully intelligent site selection process. This application embodiment relies on a unified four-dimensional spatiotemporal digital base to achieve unified management of multi-source marine data, and then gradually optimizes the site selection range through multi-level screening. It also uses simulation to identify potential risks in advance and automatically optimize the site selection range. Finally, it completes the compliance verification process and automatically generates a marine use site selection report, thereby reducing subjective bias and omissions caused by manual operation and simultaneously improving the screening efficiency and site selection accuracy of marine use sites.

[0078] Second Embodiment Based on the first embodiment, referring to Figure 4 , Figure 4 A flowchart illustrating an intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins is presented. The steps of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins include steps S10 to S50: Step S10: Determine the site selection index library based on the type of sea use scenario corresponding to the sea use demand, and filter out the first candidate sea that matches the site selection index library according to the four-dimensional spatiotemporal data corresponding to the candidate sea in the four-dimensional spatiotemporal digital base. Step S20: Generate sensitive area avoidance information corresponding to the first candidate ocean according to the preset ecological sensitive area, and select a second candidate ocean from the first candidate ocean based on the sensitive area avoidance information; Step S30: Determine the comprehensive evaluation result of the second candidate ocean based on the multi-dimensional evaluation model, and select a third candidate ocean from the second candidate ocean based on the comprehensive evaluation result; Step S40: Display the target evolution trend of the third candidate ocean in the digital twin model corresponding to the third candidate ocean; Step S50: Based on the target evolution trend and the third alternative marine generation target location scheme.

[0079] In this embodiment of the application, a four-dimensional spatiotemporal digital foundation is constructed based on the four-dimensional spatiotemporal data of each candidate ocean to achieve the integration, standardization, and unified access of the four-dimensional data (spatial data, temporal data, attribute data, and evolutionary data) of the candidate oceans; wherein, the method of constructing the four-dimensional spatiotemporal digital foundation includes: Acquire four-dimensional spatiotemporal data corresponding to each candidate ocean, wherein the four-dimensional spatiotemporal data includes spatial data, temporal data, attribute data, and evolutionary data; The four-dimensional spatiotemporal data is standardized, including unifying the coordinate system corresponding to the spatial data, unifying the time format corresponding to the time data, unifying the data encoding corresponding to the attribute data, and generating historical evolution trends based on the temporal change characteristics of the evolution data. Establish the correlation between the standardized four-dimensional spatiotemporal data, and based on the correlation, fuse and store the standardized four-dimensional spatiotemporal data to construct the four-dimensional spatiotemporal digital base corresponding to the candidate ocean.

[0080] In one optional implementation, the four-dimensional spatiotemporal data includes spatial data, temporal data, attribute data, and evolutionary data. The spatial data describes the spatial characteristics of each candidate ocean area, including but not limited to the ocean boundaries, water depth, topography, and seabed topography corresponding to each candidate ocean. The spatial data can be acquired using GPS devices, remote sensing images of the candidate ocean areas, or seabed exploration equipment; no specific method is used here. For example, the positioning coordinates of the ocean boundaries corresponding to each candidate ocean area are obtained using GPS devices, the topography and seabed topography of each candidate ocean area are obtained using remote sensing images, and high-precision water depth data is obtained using seabed exploration equipment (such as a multibeam echo sounder), ultimately yielding spatial data containing ocean boundaries, water depth, topography, and seabed topography. The temporal data records the time and time-related information of each candidate ocean area, including but not limited to data acquisition time, marine environmental change time series, and sea area use approval time nodes. The attribute data is used to describe the non-spatial characteristics of each candidate ocean, including but not limited to sea area use, sea area ownership, sea water quality, seabed sediment, and marine organism distribution. The evolution data is used to reflect the changing patterns of each candidate ocean over time, including but not limited to marine environmental change trends, evolution patterns of ecologically sensitive areas, and data on changes in sea area use demand.

[0081] After acquiring four-dimensional spatiotemporal data, the data is standardized to eliminate differences such as format and spatial coordinate system deviations. This application employs different standardization methods for different four-dimensional spatiotemporal data. The standardization methods for the four-dimensional spatiotemporal data include: A unified coordinate system for spatial data; Standardize the time format corresponding to the time data; Unify the data encoding corresponding to the attribute data; Historical evolution trends are generated based on the temporal variation characteristics of the evolution data.

[0082] In one embodiment, when spatial data is collected, different geographic coordinate systems are often used based on spatial data from different sources (such as GPS measured points, remote sensing imagery, and nautical chart scans). Without a coordinate system conversion, the coordinates of the same spatial location will be misaligned in different geographic coordinate systems, leading to deviations in subsequent analysis of ecologically sensitive areas and calculation of site selection boundaries. Therefore, this application converts the original coordinate system of the spatial data into a preset coordinate system, ensuring that all spatial data are in a unified preset coordinate system, thus unifying the coordinate system corresponding to the spatial data. The preset coordinate system can be the WGS84 coordinate system. After the coordinate system conversion, the spatial data in the preset coordinate system is uniformly encapsulated into a preset vector format. This allows for subsequent execution of intelligent auxiliary steps for marine site selection based on the spatial data in the preset vector format, avoiding discrepancies in the same spatial data due to different coordinate systems, data formats, or data precision, which could prevent matching with candidate marine areas.

[0083] In one embodiment, after collecting time data, the time data is uniformly converted into time data in a preset time format. The preset time format can be UTC time format to eliminate time zone differences. Optionally, after unifying the time format of the time data, a timestamp index is established with the time data in the unified time format. The standardized four-dimensional spatiotemporal data corresponding to each candidate ocean is stored in the timestamp index. Subsequently, the four-dimensional spatiotemporal data corresponding to the timestamp index can be found according to the timestamp index.

[0084] In one embodiment, after the attribute data is collected, it is uniformly converted into attribute data with a preset data code. The preset data code includes the data type and the data value range. For example, the attribute data includes the sea area use. The description information corresponding to the sea area use obtained from different channels is different. For example, channel A shows the sea area use as industrial; channel B shows the sea area use as industrial sea use. In order for the computer to identify the accurate sea area use, the attribute data is uniformly converted into attribute data under the preset data code (e.g., the data code corresponding to industrial sea use is G-01). Optionally, the preset data code also includes the data type and the data value range. By using the preset data code, duplicate data, outlier coordinates, data with severe attribute missingness, and logically contradictory data in the attribute data are removed. Key data with missing attributes are supplemented and improved, and invalid data that cannot be supplemented is removed to eliminate data redundancy.

[0085] In one embodiment, after collecting evolutionary data, a preset time-series analysis method is used to extract the temporal change features in the evolutionary data to generate the historical evolution trend of each candidate ocean. Specifically, the evolutionary data is sorted according to the timestamp index to generate an evolutionary data time series. Based on the evolutionary data time series, the temporal change features that have changed (such as changes in water depth, changes in erosion and deposition rates, changes in shoreline displacement, and changes in the area of ​​sensitive areas) are determined. Based on the time series, the historical evolution trend corresponding to each of the temporal change features is generated (such as the shoreline displacement rate to the sea being 0.12 m / year).

[0086] Optionally, after standardizing the four-dimensional spatiotemporal data, a correlation relationship is established between the standardized four-dimensional spatiotemporal data. Based on the correlation relationship, the standardized four-dimensional spatiotemporal data is fused and stored to construct a four-dimensional spatiotemporal digital base corresponding to the candidate ocean. In one embodiment, the correlation relationship can be a relationship established by using the spatial location of the candidate ocean as a spatial index, and using the spatial index to associate other spatial data, temporal data, attribute data, and evolutionary data corresponding to the candidate ocean. This enables the classified storage of four-dimensional spatiotemporal data of candidate oceans at different spatial locations and the fused storage of four-dimensional spatiotemporal data of the same candidate ocean, so as to realize the retrieval of four-dimensional spatiotemporal data of the candidate ocean corresponding to the spatial location based on the spatial location. Optionally, the correlation relationship includes the correlation relationship between temporal data and evolutionary data, using temporal data as a timestamp index, and mapping the evolutionary data to the timestamp index. The evolutionary data is indexed by timestamps, allowing for categorized storage of the data. This enables subsequent retrieval of evolutionary data for different candidate oceans based on the timestamp index. The association also includes the relationship between spatial location and attribute data. Using spatial location as a spatial index, the spatial location is associated with the attribute data of the candidate ocean corresponding to that location, enabling categorized storage of attribute data for different candidate oceans and fused storage of attribute data for the same candidate ocean. The association may also include relationships between spatial location and temporal data, and relationships between spatial location and evolutionary data, etc., which will not be elaborated here. It should be noted that this application embodiment uses the relationship between spatial location and four-dimensional spatiotemporal data as an example for analysis.

[0087] Furthermore, after establishing the aforementioned association, the four-dimensional spatiotemporal data is fused and stored based on the association. This embodiment employs a distributed database (such as Hadoop) to construct a storage system, distributing the associated four-dimensional spatiotemporal data, and then constructing the four-dimensional spatiotemporal digital base corresponding to the candidate ocean based on the association and the four-dimensional spatiotemporal data. It should be noted that when the four-dimensional spatiotemporal data is updated in real time, the four-dimensional spatiotemporal digital base is updated based on the real-time updated four-dimensional spatiotemporal data.

[0088] Furthermore, after the user inputs their marine use requirements, the marine use scenario type is determined based on the marine use requirements, and a site selection index library is determined based on the marine use scenario type. This application embodiment pre-sets a preset relationship between preset marine use scenario types and preset site selection index libraries. Different preset marine use scenario types correspond to different preset site selection index libraries. This preset site selection index library is used to filter out the first candidate ocean corresponding to the preset marine use scenario type from the candidate oceans. The preset site selection index library includes at least one site selection index, each site selection index corresponds to a different site selection index range, and different site selection indicators correspond to different site selection weights. Specifically, the preset marine use scenario types include, but are not limited to, land reclamation, port use, aquaculture use, offshore wind power use, industrial use, and cultural tourism use, etc. For example, the site selection index library for land reclamation includes: {water depth index, [water depth less than or equal to 10m]; topography index, [topography index less than or equal to 5 degrees]; sensitive area distance index, [sensitive area distance greater than or equal to 1km]; geological stability level index, [geological stability level greater than or equal to good level]; ...}

[0089] Optionally, refer to Figure 5 Step S10 includes: Step S11: Obtain the preset relationship between the preset sea use scenario type and the preset site selection index library, and use the preset site selection index library corresponding to the sea use scenario type as the site selection index library according to the preset relationship. Step S12: Obtain each location index in the location index library and the location index range corresponding to the location index. Step S13: Obtain the first indicator data that matches the location index in the four-dimensional spatiotemporal data according to the correlation relationship; Step S14: Select the ocean corresponding to the location index range of the first index data as the first candidate ocean.

[0090] Optionally, upon receiving a marine use demand that includes a marine use scenario type, a site selection index library corresponding to the marine use scenario type is determined according to a preset relationship. The site selection index intervals in the library, along with the candidate marine area within each interval, are used to filter for a first candidate marine area. The four-dimensional spatiotemporal data corresponding to this first candidate marine area satisfies the site selection indexes and intervals required by the site selection index library. Specifically, after determining the site selection index library corresponding to the marine use demand, a four-dimensional spatiotemporal digital base is invoked. Based on the established relationships within the four-dimensional spatiotemporal digital base, first index data matching the site selection index is searched. For example, for the water depth index in the site selection index library, the water depth data of 3m corresponding to marine area A at spatial location ID_001 in the four-dimensional spatiotemporal digital base is selected. The found first index data is then compared with its corresponding site selection index interval. When all first index data fall within the site selection index interval, the candidate marine area is selected as the first candidate marine area.

[0091] Furthermore, after determining the first candidate ocean, it is determined whether the first candidate ocean overlaps with the preset ecologically sensitive area. If there is an overlap, the first candidate ocean is adjusted, and a second candidate ocean is determined, which does not overlap with the preset ecologically sensitive area.

[0092] In one embodiment, the method of generating a preset ecologically sensitive area and associating and storing the preset ecologically sensitive area with a four-dimensional spatiotemporal digital base includes: Acquire sensitive area sample data, extract sensitive features based on the sensitive area sample data, and generate a sensitive area sample library; The preset model is trained based on the sensitive area sample library to generate a sensitive area recognition model; Based on the aforementioned correlation, the corresponding four-dimensional spatiotemporal data is input into the sensitive area identification model to obtain the preset ecological sensitive area identified by the sensitive area identification model. A sensitive area vector map layer is generated based on the regional boundary corresponding to the preset ecological sensitive area, and the sensitive area vector map layer is associated and stored in the four-dimensional spatiotemporal digital base.

[0093] In one optional implementation, the sensitive area sample data includes positive sensitive area sample data, which includes ecologically sensitive areas with confirmed rights. The sensitive area sample data also includes non-sensitive area sample data, which includes non-sensitive areas. For example, remote sensing image samples and field survey samples of mangroves, coral reefs, and seagrass beds in a certain sea area are collected. Sensitive features for characterizing the sensitive areas are extracted from the sensitive area sample data. These sensitive features include, but are not limited to, remote sensing image features, topographic features, geomorphic features, hydrological features, and biological features; for example, the sensitive features corresponding to mangroves are [water depth -2m to 0m, topographic slope <2°, salinity: 25-30ppt]. Optionally, after obtaining the sensitive features, a sensitive area sample library is generated based on the sensitive features and the sensitive area sample data. Further, a preset model is trained based on the sensitive area sample library to generate a sensitive area identification model. The preset model includes, but is not limited to, deep learning models such as CNN convolutional neural networks. The preset model can also be a random forest model, a support vector machine model, etc., which are not limited here.

[0094] Furthermore, after generating the sensitive area identification model, four-dimensional spatiotemporal data corresponding to each candidate ocean is retrieved from the four-dimensional spatiotemporal digital base according to the aforementioned correlation. Sensitive features corresponding to each candidate ocean are extracted based on the four-dimensional spatiotemporal data, and these sensitive features are input into the sensitive area identification model. This allows the sensitive area identification model to determine preset ecologically sensitive areas within the candidate oceans based on the four-dimensional spatiotemporal data. After determining the preset ecologically sensitive areas, boundary identification is performed on these areas to obtain their corresponding regional boundaries. A sensitive area vector layer is generated based on these regional boundaries, and then imported into the four-dimensional spatiotemporal digital base to achieve associated storage between the preset ecologically sensitive areas and the four-dimensional spatiotemporal digital base.

[0095] In one optional implementation, the spatial location corresponding to the preset ecologically sensitive area is determined, a spatial index corresponding to the preset ecologically sensitive area is generated based on the spatial location, and the sensitive area vector layer corresponding to the preset ecologically sensitive area is stored in a four-dimensional spatiotemporal digital base based on the spatial index. Optionally, it can also be that a candidate ocean where the preset ecologically sensitive area is located is determined, and the sensitive area data corresponding to the preset ecologically sensitive area is associated and stored with the four-dimensional spatiotemporal data of the candidate ocean. When the candidate ocean is found later, the preset ecologically sensitive area in the candidate ocean can be directly determined. Alternatively, it can be that the digital sensitive area range of the preset ecologically sensitive area in the four-dimensional spatiotemporal digital base is determined, and the sensitive area vector layer is superimposed on the digital sensitive area range corresponding to the four-dimensional spatiotemporal digital base. This digital sensitive area range is used to characterize the spatial mapping area of ​​the sensitive area vector layer in the four-dimensional spatiotemporal digital base. Optionally, after determining the preset ecologically sensitive areas and storing them in a four-dimensional spatiotemporal digital base, ecologically sensitive area avoidance can be achieved subsequently based on the preset ecologically sensitive areas stored in the four-dimensional spatiotemporal digital base. In this embodiment, after determining the first candidate ocean, a second candidate ocean is selected based on the first candidate ocean and the preset ecologically sensitive areas. The second candidate ocean has no conflict with or has a small overlap with the preset ecologically sensitive areas; refer to Figure 6 Step S20 includes: Step S21: Obtain the ocean vector map layer corresponding to the first candidate ocean based on the four-dimensional spatiotemporal digital base; Step S22: Perform spatial overlay analysis on the ocean vector map layer corresponding to each of the first candidate oceans and the sensitive area vector map layer to determine the overlapping area between the ocean vector map layer and the sensitive area vector map layer; Step S23: When the percentage of overlapping area corresponding to the overlapping region is greater than or equal to a preset ratio, generate the sensitive area avoidance information based on the overlapping region; Step S24: Adjust the first site selection range corresponding to the first candidate ocean based on the sensitive area avoidance information, and determine the second candidate ocean based on the adjusted first site selection range.

[0096] A first candidate ocean is obtained as a marine vector layer in a four-dimensional spatiotemporal digital base. This marine vector layer is used to define the digital sea area range corresponding to the first candidate ocean in the four-dimensional spatiotemporal digital base. The digital sea area range represents the spatial mapping area of ​​the marine vector layer in the four-dimensional spatiotemporal digital base. A preset ecologically sensitive area is also obtained as a digitally sensitive area range in the four-dimensional spatiotemporal digital base. The method for performing spatial overlay analysis between the marine vector layer and the sensitive area vector layer is as follows: a spatial topology algorithm is used to calculate whether there is an overlapping area between the digitally sensitive area range and the digital sea area range. If so, this overlapping area is taken as the overlapping area between the marine vector layer and the sensitive area vector layer, and then the area of ​​the overlapping area is obtained. This overlapping area area can be the area of ​​the overlapping area in the four-dimensional spatiotemporal digital base, or it can be the actual area of ​​the overlapping area.

[0097] Furthermore, the overlapping area ratio corresponding to the overlapping area of ​​the overlapping region is obtained. This overlapping area ratio can be the ratio between the overlapping area of ​​the overlapping region and the ocean area of ​​the first candidate ocean, or it can be the ratio between the overlapping area of ​​the overlapping region and the sensitive area area of ​​the preset ecologically sensitive zone. When the overlapping area ratio is greater than or equal to the preset ratio, it is determined that the first candidate ocean contains a large area of ​​the preset ecologically sensitive zone. In this case, the first site selection range corresponding to the first candidate ocean needs to be adjusted to prevent conflicts with the preset ecologically sensitive zone. It should be noted that different preset ecologically sensitive zones correspond to different preset ratios. The higher the sensitivity level of the preset ecologically sensitive zone, the lower the corresponding preset ratio, and vice versa, to balance the importance of the preset ecologically sensitive zone and the flexibility of site selection.

[0098] Specifically, when the percentage of overlapping area is greater than or equal to a preset ratio, sensitive area avoidance information is generated based on the overlapping area. This sensitive area avoidance information includes conflict type, conflict level, avoidance direction, and avoidance distance. This information guides the adjustment of the first site selection range corresponding to the first candidate ocean. For example, the sensitive area avoidance information might be: "This area overlaps with a mangrove sensitive area, the conflict level is Level 1, and it is recommended to adjust it 500 meters northeast." Then, the first site selection range corresponding to the first candidate ocean is obtained. Based on the sensitive area avoidance information, the first site selection range is adjusted, and the sea area corresponding to the adjusted first site selection range is designated as the second candidate ocean. The number of oceans corresponding to the first candidate ocean is greater than the number of oceans corresponding to the second candidate ocean, the sea area corresponding to the first candidate ocean is greater than the sea area corresponding to the second candidate ocean, and the percentage of overlapping area between the second candidate ocean and the preset ecological sensitive area is less than a preset ratio.

[0099] It should be noted that the four-dimensional spatiotemporal data of the second candidate ocean corresponding to the adjusted first site selection range differs from that of the first candidate ocean. Therefore, the four-dimensional spatiotemporal data of the second candidate ocean may not meet the site selection index library. Based on this, after adjusting the first site selection range, the following steps are performed: Based on the adjusted first location range, return to the step of obtaining the index data that matches the location index in the four-dimensional spatiotemporal data according to the association relationship; If the first candidate ocean corresponding to the adjusted first site selection range is within the site selection index range corresponding to the site selection index, and the overlapping area ratio of the first candidate ocean is less than the preset ratio, then the first candidate ocean will be used as the second candidate ocean.

[0100] Based on the adjusted first site selection range, a first candidate ocean is determined. According to the correlation, the first indicator data corresponding to the adjusted first candidate ocean is retrieved from the four-dimensional spatiotemporal digital base. This retrieved first indicator data is then compared with the site selection indicator database corresponding to the sea use demand. If the first indicator data falls within the corresponding site selection indicator range in the database, the first candidate ocean corresponding to the adjusted first site selection range is determined to meet the site selection indicator database, and this first candidate ocean is then designated as the second candidate ocean. If the first indicator data does not fall within the site selection indicator range, the first candidate ocean that does not meet the site selection indicator range is discarded, and other first candidate oceans are designated as the second candidate ocean.

[0101] Furthermore, after determining the second candidate ocean, different second candidate oceans have different advantages and disadvantages. To help users select a suitable ocean more quickly, this application embodiment also proposes to comprehensively evaluate each second candidate ocean, rank each second candidate ocean according to the comprehensive evaluation results, and output the ranked second candidate oceans. Users can determine a better second candidate ocean based on the ranking results; alternatively, second candidate oceans that meet preset evaluation results can be selected based on the comprehensive evaluation results, while second candidate oceans with lower comprehensive evaluation results can be excluded. Optionally, refer to Figure 7 Step S30 includes: Step S31: Obtain the evaluation indicators and the corresponding quantitative scoring ranges for the evaluation indicators. The evaluation indicators include at least one of the following: natural condition indicators, ecological and environmental protection indicators, policy compliance indicators, economic feasibility indicators, and safety and control indicators. Step S32: Obtain second indicator data that matches the evaluation indicator based on the correlation relationship; Step S33: Determine the evaluation score corresponding to the second indicator data based on the quantitative scoring range; Step S34: Determine the comprehensive evaluation result corresponding to each of the second candidate oceans based on the evaluation scores; Step S35: The second candidate ocean corresponding to the comprehensive evaluation result exceeding the preset evaluation result is selected as the third candidate ocean.

[0102] In one optional implementation, the scores of the second candidate ocean are determined under different evaluation dimensions using multiple evaluation dimensions. The scores are then combined to obtain a comprehensive evaluation result for the second candidate ocean. These evaluation dimensions include, but are not limited to, natural conditions, ecological and environmental protection, policy compliance, economic feasibility, and safety and security. Optionally, the scores of the second candidate ocean under different evaluation dimensions are determined by identifying the evaluation indicators corresponding to different evaluation dimensions and the corresponding quantitative scoring ranges. The corresponding evaluation indicators include at least one of the following: natural conditions, ecological and environmental protection, policy compliance, economic feasibility, and safety and security. The quantitative scoring range includes a predefined score range (e.g., 0-100 points) to standardize the scoring criteria for the second indicator data corresponding to the evaluation indicator. This second indicator data is the indicator data in four-dimensional spatiotemporal data that matches the evaluation indicator. For example, if the evaluation indicator is water depth, then the second indicator data is the actual water depth value corresponding to Ocean A. The natural conditions index is used to quantify the evaluation scores corresponding to natural conditions such as water depth, topography, and climate; the ecological and environmental protection index is used to quantify the evaluation scores corresponding to ecological and environmental protection conditions such as distance from sensitive areas and ecological and environmental impact; the policy compliance index is used to quantify the evaluation scores corresponding to sea use approval requirements and planning legality; the economic feasibility index is used to quantify the evaluation scores corresponding to construction costs and expected benefits; and the safety and control index is used to quantify the assessment scores corresponding to geological safety and disaster risks.

[0103] In one embodiment, after determining the evaluation indicators and the quantitative scoring range, a four-dimensional spatiotemporal digital base is retrieved to obtain second indicator data that matches the evaluation indicators for the second candidate ocean. Then, the evaluation score of the second candidate ocean under each evaluation indicator is determined based on the quantitative scoring range and the second indicator data. Finally, a weighted fusion is performed based on the evaluation scores and evaluation weights corresponding to each evaluation indicator, and the calculation result is used as the comprehensive evaluation result of the second candidate ocean.

[0104] Optionally, after determining the comprehensive evaluation result corresponding to the second candidate ocean, the second candidate ocean whose comprehensive evaluation result exceeds the preset evaluation result is selected as the third candidate ocean, and the second candidate ocean whose comprehensive evaluation result is lower than the preset evaluation result is excluded. For example, the preset evaluation result is set to 80 points, and the second candidate oceans corresponding to a total score ≥ 80 points are selected. Alternatively, the second candidate oceans can be sorted from high to low according to the comprehensive evaluation results corresponding to each second candidate ocean, and a preset number of second candidate oceans are selected as the third candidate oceans based on the sorting results, such as the top three second candidate oceans.

[0105] It should be noted that, in order to better assist users in selecting a suitable ocean, after determining the comprehensive evaluation results for each second alternative ocean, the advantages and disadvantages of each second alternative ocean are determined based on the evaluation scores obtained by the second alternative ocean on each evaluation indicator. Evaluation indicators with scores higher than the preset scores are identified as advantages of the second alternative ocean, while evaluation indicators with scores lower than the preset scores are identified as disadvantages of the second alternative ocean. For example, if Ocean A has a comprehensive evaluation result of 92 points, an evaluation score of 100 points for the ecological and environmental protection indicator, and an evaluation score of 40 points for the economic feasibility indicator, its advantage is a high score for ecological and environmental protection, and its disadvantage is a low score for the economic feasibility indicator.

[0106] In one embodiment, after determining the comprehensive evaluation results of each second candidate ocean, each second candidate ocean is output in descending order of the comprehensive evaluation results, along with its corresponding advantages and disadvantages, for the user to evaluate and select a suitable sea area. Alternatively, after determining the comprehensive evaluation results of each second candidate ocean and selecting a third candidate ocean, each third candidate ocean is output in descending order of the comprehensive evaluation results of the third candidate ocean, along with its corresponding advantages and disadvantages, for the user to evaluate and select a suitable sea area from the third candidate ocean.

[0107] Furthermore, after identifying the third candidate ocean, to better assist users in selecting suitable sea areas from it, a target evolution trend for the third candidate ocean is generated. This trend is then visualized in a digital twin model of the third candidate ocean, allowing users to select suitable sea areas based on this trend. (Refer to...) Figure 8 Step S40 includes: Step S41: Obtain four-dimensional spatiotemporal data of the third candidate ocean from the four-dimensional spatiotemporal digital base, generate a digital twin model of the third candidate ocean based on the four-dimensional spatiotemporal data, and output the digital twin model. Step S42: Obtain the historical evolution trend corresponding to the third candidate ocean, and determine the future evolution trend of the third candidate ocean under at least one preset working condition based on the historical evolution trend. Step S43: Generate the target evolution trend of the third candidate ocean based on the historical evolution trend and the future evolution trend, and display the target evolution trend in the digital twin model.

[0108] In one optional implementation, based on the four-dimensional runaway data of the four-dimensional spatiotemporal digital base, a 1:1 digital twin model of the third candidate ocean is constructed to recreate the real-world scenario of the third candidate ocean, including its topography, water depth, ecological environment, and surrounding facilities, achieving real-time synchronization with the real sea area. Then, based on the historical evolution trends of each third candidate ocean, the future evolution trend of the third candidate ocean under at least one preset operating condition is determined. A target evolution trend is generated by combining the historical evolution trend and the future evolution trend. The preset operating conditions include, but are not limited to, climate change operating conditions, marine environmental change operating conditions, and marine engineering construction operating conditions.

[0109] Optionally, after generating the target evolution trend, the target evolution trend is displayed in a digital twin model. The target evolution trend includes environmental parameters of the third candidate ocean at different time points, such as ecological environment parameters, topographic parameters, and hydrological condition parameters.

[0110] Understandably, when showcasing the evolution trend of the target, users can select a better third alternative ocean based on experience, such as choosing the third alternative ocean whose ecology does not degrade as the target site selection scheme corresponding to this ocean use demand.

[0111] In an optional implementation, this embodiment of the application further automatically predicts potential target risk points (such as ecological degradation, geological disasters, compliance changes, etc.) in the third candidate marine area based on the target evolution trend, and labels each target risk point with a risk level (high, medium, low). The third candidate marine area is then adjusted based on the target risk points and risk levels to obtain a better site selection scheme. In one embodiment, step S50 includes: The environmental change parameters corresponding to the third candidate ocean are determined based on the target evolution trend. The environmental change parameters include at least one of ecological environment change parameters, topographic and geomorphological change parameters, and hydrological condition change parameters. The environmental change parameters are compared with a preset safety threshold range, and the target risk point and the target risk level corresponding to the target risk point are determined based on the environmental change parameters that exceed the preset safety threshold range. The second site selection range corresponding to the third alternative ocean is adjusted according to the target risk point and the target risk level to generate the fourth alternative ocean; The target site selection scheme is generated based on the fourth alternative ocean.

[0112] Optionally, the environmental change parameters are used to characterize the amount and / or rate of change of environmental parameters at various future time points in the third candidate ocean compared to the environmental parameters at the current time point. This application embodiment pre-sets preset safety threshold ranges for each environmental change parameter. These preset safety threshold ranges are reasonable ranges corresponding to environmental parameters pre-defined in conjunction with marine regulations, ecological protection standards, and engineering safety specifications, and serve as the basis for risk assessment. Different environmental parameters correspond to different preset risk points. For example, ecological environment change parameters include dissolved oxygen changes, and the corresponding preset risk point is water quality deterioration; when dissolved oxygen content continues to decline, a risk point of water quality deterioration is determined.

[0113] In one embodiment, environmental change parameters are compared with a preset safety threshold range. When the environmental change parameters exceed the preset safety threshold range, a preset risk point corresponding to the environmental change parameters is used as the target risk point. The environmental change parameters are compared with the interval values ​​in the preset safety threshold range, where the interval values ​​are the maximum and minimum interval values. The difference between the environmental change parameters and the interval values ​​is used to determine the target risk level. The larger the difference, the higher the target risk level; the smaller the difference, the lower the target risk level. Alternatively, the target risk level can be determined based on the duration of the exceedance of the preset safety threshold range. The shorter the duration, the lower the target risk level; the longer the duration, the higher the target risk level.

[0114] Optionally, after determining the target risk points and target risk levels, the second site selection range corresponding to the third candidate ocean is adjusted according to the target risk points and target risk levels. The adjusted second site selection range is used to determine the fourth candidate ocean. A target site selection scheme is generated based on the fourth candidate ocean. The target site selection scheme includes, but is not limited to, the four-dimensional spatiotemporal data of each fourth candidate ocean, the site selection range, the comprehensive evaluation results, the overlapping area with the preset ecologically sensitive area, the distance between the fourth candidate ocean and the preset ecologically sensitive area, the stored target risk points, and the target risk levels. Additionally, engineering design parameters can be adjusted to eliminate the environmental impact of engineering operations. It should be noted that after adjusting the second site selection range and / or adjusting the engineering design parameters, the target evolution trend is regenerated based on the adjusted second site selection range and / or engineering design parameters to reassess environmental change parameters and target risk points until no target risk points exist and / or the target risk level corresponding to the target risk points is lower than the preset risk level.

[0115] Furthermore, after completing the risk assessment, a marine site selection report is generated and output as the target site selection plan to the user for viewing. Specifically: The four-dimensional spatiotemporal data corresponding to the fourth candidate ocean are compared with the preset compliance verification rules to determine the compliance verification result corresponding to the fourth candidate ocean. The compliance verification result includes compliant items and non-compliant items. Based on the compliance verification results and the marine sea use site selection report template, a marine sea use site selection report corresponding to the sea use demand is generated. The marine sea use site selection report includes at least one of the following: sea use demand, various alternative marine areas, sensitive area avoidance information, comprehensive evaluation results, and target evolution trend. The target site selection scheme is generated based on the marine site selection report.

[0116] In one optional implementation, after determining the fourth candidate marine area, a compliance verification is performed on the fourth candidate marine area based on preset compliance verification rules, and a marine area site selection report is generated based on the compliance verification results. Specifically, national and local marine area laws, regulations, and industry standards are obtained, and core verification points such as the scope of use, intended use, and safe distance from ecologically sensitive areas are extracted. Preset compliance verification rules are generated based on these core verification points, and then the four-dimensional spatiotemporal data corresponding to the fourth candidate marine area is retrieved using the preset compliance verification rules to determine whether the fourth candidate marine area meets each of the preset compliance verification rules, generating a compliance verification result. This compliance verification result includes compliant items and non-compliant items. If non-compliant items exist, the third site selection scope and / or engineering design parameters corresponding to the fourth candidate marine area are adjusted until the final site selection scheme meets all preset compliance verification rules.

[0117] Optionally, after the fourth candidate ocean meets all preset compliance verification rules, a compliance verification result is obtained; based on the ocean-related data generated by this intelligent auxiliary process for ocean use site selection based on four-dimensional spatiotemporal digital twin and the compliance verification result, fill data is generated in the ocean use site selection report template, and the fill data is used to fill the ocean use site selection report template to generate an ocean use site selection report; wherein, the ocean-related data includes, but is not limited to, user-input ocean use demand, ocean use scenario type, site selection indicator library, first indicator data, first candidate ocean, sensitive area avoidance information, overlapping areas, and overlapping areas. The marine user site selection report includes at least one of the following: overlapping area ratio, first site selection range, second alternative marine area, comprehensive evaluation results, evaluation indicators, quantitative evaluation interval, second indicator data, evaluation score, third alternative marine area, target evolution trend, environmental change parameters, target risk points, target risk wind turbines, second site selection range, fourth alternative marine area, target site selection scheme, preset compliance verification rules, and compliance verification results. Furthermore, after generating the marine site selection report, the marine site selection report is used as the target site selection scheme, and the target site selection scheme is output.

[0118] This application proposes an intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins. It integrates four types of multi-source heterogeneous marine data—spatial, temporal, attribute, and evolutionary data—from various candidate marine areas using a four-dimensional spatiotemporal digital base module to construct a four-dimensional spatiotemporal digital base. After acquiring marine use demands including different marine use scenario types, it matches corresponding site selection index libraries based on the scenario type to select a first candidate marine area. Then, it overlays and analyzes a pre-defined ecologically sensitive area with the first candidate marine area, outputting sensitive area avoidance information in overlapping areas to obtain a second candidate marine area. Next, it performs quantitative scoring and comprehensive evaluation on the second candidate marine area, selecting a third candidate marine area that meets the comprehensive evaluation criteria. Then, it conducts dynamic simulations of multiple pre-defined operating conditions, risk prediction, and iterative optimization on the third candidate marine area, resulting in a fourth candidate marine area. Finally, it performs compliance verification on the fourth candidate marine area, generates compliance verification results, and automatically generates a standardized marine site selection report to output the target site selection scheme, realizing a fully intelligent site selection process. This application's embodiments rely on a unified four-dimensional spatiotemporal digital platform to achieve unified management of multi-source marine data. It then optimizes the site selection range through multi-level screening, and uses simulation to identify potential risks in advance and automatically optimize the site selection range. Finally, it completes the compliance verification process and automatically generates a marine site selection report, thereby reducing subjective bias and oversight caused by manual operation and simultaneously improving the screening efficiency and accuracy of marine site selection. It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins. Many simple modifications based on this technical concept are within the scope of protection of this application.

[0119] This application provides an intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins. The intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins includes: at least one processor; and a memory communicatively connected to at least one processor; wherein the memory stores instructions executable by at least one processor, and the instructions are executed by at least one processor to enable at least one processor to execute the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in the above embodiment 1.

[0120] The following is for reference. Figure 9This document illustrates a structural schematic diagram of a marine site selection intelligent auxiliary device based on four-dimensional spatiotemporal digital twin, suitable for implementing embodiments of this application. The marine site selection intelligent auxiliary device based on four-dimensional spatiotemporal digital twin in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 9 The intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twin shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0121] like Figure 9 As shown, the intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in read-only memory (ROM) 1002 or the program loaded from storage device 1003 into random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the marine site selection intelligent auxiliary equipment based on four-dimensional spatiotemporal digital twins to exchange data with other devices wirelessly or via wired communication. Although the figure shows a marine site selection intelligent auxiliary equipment based on four-dimensional spatiotemporal digital twins with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0122] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0123] The intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins provided in this application, employing the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in the above embodiments, can solve the technical problems of low intelligence level in manually-led marine site selection, resulting in low efficiency and low site selection accuracy. Compared with the prior art, the beneficial effects of the intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins provided in this application are the same as those of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins provided in the above embodiments, and other technical features in the intelligent auxiliary device for marine site selection based on four-dimensional spatiotemporal digital twins are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0124] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0125] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0126] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins in the above embodiments.

[0127] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0128] The aforementioned computer-readable storage medium may be included in a marine site selection intelligent auxiliary device based on four-dimensional spatiotemporal digital twin; or it may exist independently and not be assembled into a marine site selection intelligent auxiliary device based on four-dimensional spatiotemporal digital twin.

[0129] The aforementioned computer-readable storage medium carries one or more programs that, when executed by a four-dimensional spatiotemporal digital twin-based intelligent auxiliary device for marine site selection, enable the device to write computer program code for performing the operations of this application in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0130] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0131] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0132] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins. This solves the technical problem of low efficiency and low site selection accuracy caused by the low level of intelligence in manually-led marine site selection. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins provided in the above embodiments, and will not be repeated here.

[0133] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins.

[0134] The computer program product provided in this application can solve the technical problem of low efficiency and low accuracy in marine site selection caused by low level of intelligence in manual-led marine site selection. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins provided in the above embodiments, and will not be repeated here.

[0135] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A smart auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins, characterized in that, The steps of the intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twins include: Acquire four-dimensional spatiotemporal data corresponding to each candidate ocean, wherein the four-dimensional spatiotemporal data includes spatial data, temporal data, attribute data, and evolutionary data; The four-dimensional spatiotemporal data is standardized, including unifying the coordinate system corresponding to the spatial data, unifying the time format corresponding to the time data, unifying the data encoding corresponding to the attribute data, and generating historical evolution trends based on the temporal change characteristics of the evolution data. Establish the correlation between the standardized four-dimensional spatiotemporal data, and based on the correlation, fuse and store the standardized four-dimensional spatiotemporal data to construct the four-dimensional spatiotemporal digital base corresponding to the candidate ocean. Based on the type of sea use scenario corresponding to sea use demand, a site selection index library is determined, and the first candidate sea that matches the site selection index library is selected according to the four-dimensional spatiotemporal data corresponding to the candidate sea in the four-dimensional spatiotemporal digital base. Based on the preset ecologically sensitive areas, sensitive area avoidance information corresponding to the first candidate ocean is generated, and a second candidate ocean is selected from the first candidate ocean based on the sensitive area avoidance information; The comprehensive evaluation result of the second candidate ocean is determined based on the multi-dimensional evaluation model, and the third candidate ocean is selected from the second candidate ocean based on the comprehensive evaluation result; The digital twin model corresponding to the third candidate ocean demonstrates the target evolution trend of the third candidate ocean; Based on the target evolution trend and the third alternative marine generation target site selection scheme.

2. The intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twin as described in claim 1, characterized in that, The step of determining the site selection index library based on the marine use scenario type corresponding to marine use demand, and filtering out the first candidate ocean that matches the site selection index library based on the four-dimensional spatiotemporal data corresponding to the candidate ocean in the four-dimensional spatiotemporal digital base includes: Obtain the preset relationship between preset sea use scenario types and preset site selection index library, and use the preset site selection index library corresponding to the sea use scenario type as the site selection index library according to the preset relationship; Obtain each location selection index in the location selection index library and the location selection index range corresponding to each location selection index; Based on the aforementioned correlation, obtain the first indicator data in the four-dimensional spatiotemporal data that matches the location indicator; The ocean corresponding to the first indicator data falling within the location indicator range is selected as the first candidate ocean.

3. The intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twin as described in claim 1, characterized in that, Before the step of generating sensitive area avoidance information corresponding to the first candidate ocean based on the preset ecological sensitive areas, and selecting a second candidate ocean from the first candidate ocean based on the sensitive area avoidance information, the method further includes: Acquire sensitive area sample data, extract sensitive features based on the sensitive area sample data, and generate a sensitive area sample library; The preset model is trained based on the sensitive area sample library to generate a sensitive area recognition model; Based on the aforementioned correlation, the corresponding four-dimensional spatiotemporal data is input into the sensitive area identification model to obtain the preset ecological sensitive area identified by the sensitive area identification model. A sensitive area vector map layer is generated based on the regional boundary corresponding to the preset ecological sensitive area, and the sensitive area vector map layer is associated and stored in the four-dimensional spatiotemporal digital base.

4. The intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twin as described in claim 3, characterized in that, The step of generating sensitive area avoidance information corresponding to the first candidate ocean based on preset ecological sensitive areas, and selecting a second candidate ocean from the first candidate ocean based on the sensitive area avoidance information includes: Based on the four-dimensional spatiotemporal digital base, obtain the ocean vector map layer corresponding to the first candidate ocean; Perform spatial overlay analysis on the ocean vector map layer corresponding to each of the first candidate oceans and the sensitive area vector map layer to determine the overlapping area between the ocean vector map layer and the sensitive area vector map layer; When the percentage of overlapping area corresponding to the overlapping region is greater than or equal to a preset ratio, the sensitive area avoidance information is generated based on the overlapping region. The first site selection range corresponding to the first candidate ocean is adjusted based on the sensitive area avoidance information, and the second candidate ocean is determined based on the adjusted first site selection range.

5. The intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twin as described in claim 2, characterized in that, The step of adjusting the first site selection range corresponding to the first candidate ocean based on the sensitive area avoidance information, and determining the second candidate ocean based on the adjusted first site selection range includes: Based on the adjusted first location range, return to the step of obtaining the first indicator data that matches the location indicator in the four-dimensional spatiotemporal data according to the association relationship; If the first candidate ocean corresponding to the adjusted first site selection range is within the site selection index range corresponding to the site selection index, and the overlapping area ratio of the first candidate ocean is less than the preset ratio, then the first candidate ocean will be used as the second candidate ocean.

6. The intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twin as described in claim 1, characterized in that, The step of determining the comprehensive evaluation result of the second candidate ocean based on the multi-dimensional evaluation model, and selecting the third candidate ocean from the second candidate ocean based on the comprehensive evaluation result, includes: Obtain evaluation indicators and corresponding quantitative scoring ranges for the evaluation indicators. The evaluation indicators include at least one of the following: natural conditions indicators, ecological and environmental protection indicators, policy compliance indicators, economic feasibility indicators, and safety and control indicators. Based on the aforementioned correlation, obtain second indicator data that matches the evaluation indicator; The evaluation score corresponding to the second indicator data is determined based on the quantitative scoring range. The comprehensive evaluation result corresponding to each of the second candidate oceans is determined based on the evaluation score; The second candidate ocean whose comprehensive evaluation result exceeds the preset evaluation result will be used as the third candidate ocean.

7. The intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twin as described in claim 1, characterized in that, The steps for demonstrating the target evolution trend of the third candidate ocean using a digital twin model corresponding to the third candidate ocean include: The four-dimensional spatiotemporal data of the third candidate ocean are obtained from the four-dimensional spatiotemporal digital base, a digital twin model of the third candidate ocean is generated based on the four-dimensional spatiotemporal data, and the digital twin model is output. Obtain the historical evolution trend corresponding to the third candidate ocean, and determine the future evolution trend of the third candidate ocean under at least one preset working condition based on the historical evolution trend; The target evolution trend of the third candidate ocean is generated based on the historical evolution trend and the future evolution trend, and the target evolution trend is displayed in the digital twin model.

8. The intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twin as described in claim 7, characterized in that, The step of selecting a location for a target based on the target evolution trend and the third alternative marine generation target site selection scheme includes: The environmental change parameters corresponding to the third candidate ocean are determined based on the target evolution trend. The environmental change parameters include at least one of ecological environment change parameters, topographic and geomorphological change parameters, and hydrological condition change parameters. The environmental change parameters are compared with a preset safety threshold range, and the target risk point and the target risk level corresponding to the target risk point are determined based on the environmental change parameters that exceed the preset safety threshold range. The second site selection range corresponding to the third alternative ocean is adjusted according to the target risk point and the target risk level to generate the fourth alternative ocean; The target site selection scheme is generated based on the fourth alternative ocean.

9. The intelligent auxiliary method for marine site selection based on four-dimensional spatiotemporal digital twin as described in any one of claims 1-8, characterized in that, The step of generating the target site selection scheme based on the fourth candidate ocean includes: The four-dimensional spatiotemporal data corresponding to the fourth candidate ocean are compared with the preset compliance verification rules to determine the compliance verification result corresponding to the fourth candidate ocean. The compliance verification result includes compliant items and non-compliant items. Based on the compliance verification results and the marine sea use site selection report template, a marine sea use site selection report corresponding to the sea use demand is generated. The marine sea use site selection report includes at least one of the following: sea use demand, various alternative marine areas, sensitive area avoidance information, comprehensive evaluation results, and target evolution trend. The target site selection scheme is generated based on the marine site selection report.

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