Marine archaeological survey result data visualization-based method and system

Abstract

The invention discloses a data visualization method and system based on marine archaeological survey results, belongs to the technical field of computer data processing and visualization, and aims to solve the technical problems of difficulty in integration of multi-source heterogeneous data, single visualization form and insufficient interactivity in existing marine archaeological data visualization. According to the method, multi-source marine archaeological survey data is acquired, standardized preprocessing and space-time registration are completed, a'ruin-detection area-cultural relic point-literature 'four-layer associated data model under a unified space-time reference system is constructed, and seabed three-dimensional scene construction, multi-source data fusion and multi-dimensional visual mapping rendering are realized. And meanwhile, an interactive analysis interface is provided to support result exploration and query, and multi-end output is realized through an output module. The system for realizing the method comprises a data access module, a data governance module, a visual processing engine module, an interaction analysis module and an output module. Integrated management and fusion display of multi-source data are achieved, the scientific research value and the science popularization effect of marine archaeological achievements are improved, and the method can be widely applied to the fields of marine archaeological research, cultural relic protection and science popularization.

Description

Technical Field

[0001] The present invention relates to the technical field of computer data processing and visualization, and specifically relates to a method and system for visualizing the data of marine archaeological survey results, which is applicable to the integrated management, processing analysis and visual display of multi-source survey results data of marine archaeology, and can be widely applied to related fields such as marine archaeological research, cultural relics protection and popular science. Background Art

[0002] Marine archaeology is an important means to explore the marine historical culture and protect underwater cultural relics. Its survey work will generate a large amount of multi-type and heterogeneous result data, mainly including acoustic detection data (such as multi-beam and side-scan sonar data), optical image data (such as underwater photography and video data), geophysical data (such as magnetic anomalies and shallow profile data), cultural relic positioning data, cultural relic attribute data and relevant historical literature materials, etc. These data are the core basis for studying the distribution law of underwater sites, the evolution process of cultural relics and the marine historical culture, and their utilization efficiency directly affects the scientific research progress and the effect of achievement transformation of marine archaeological work.

[0003] At present, there is no systematic solution in the existing visualization technology that can realize the integration of multi-source heterogeneous data of marine archaeological data, multi-dimensional fusion visualization, full-process interactive analysis and multi-terminal output, and it is difficult to meet the actual needs of scientific research and popular science.

[0004] Therefore, a method and system for visualizing the data of marine archaeological survey results are proposed, which can realize the integration of multi-source heterogeneous data, flexible interactive analysis and multi-terminal popular science output through a four-layer associated data model, lightweight WebGL rendering, multi-dimensional fusion visualization and full-process interactive analysis. Summary of the Invention

[0005] The present invention discloses a method and system for visualizing the data of marine archaeological survey results.

[0006] A method for visualizing the data of marine archaeological survey results includes the following steps:

[0007] Step S1, data access and preprocessing:

[0008] Obtain multi-source marine archaeological survey data through data collection means. The multi-source data includes at least two of acoustic detection data (multi-beam data, side-scan sonar data), optical image data (underwater photography images, underwater video frame images), geophysical data (magnetic anomaly data, submarine shallow profile data), positioning data (coordinates of unearthed cultural relics, boundary coordinates of detection areas), cultural relic attribute data (types of cultural relics, ages, materials, sizes, etc.) and literature materials (historical records, archaeological reports, etc.).

[0009] First, the acquired multi-source data undergoes standardized preprocessing. Each step works in synergy to improve data quality, providing support for subsequent data modeling and visualization. Specifically, the standardized preprocessing encompasses three core stages: data format conversion, data cleaning, and data mosaicking. It further includes feature extraction to extract core features from various data types, improving the accuracy of subsequent visualization. Furthermore, it includes data verification to check the completeness and accuracy of the preprocessed data, ensuring that the data meets the requirements for subsequent modeling.

[0010] Furthermore, the raw data in different formats undergoes a unified conversion process to form a universally compatible format. Specifically, multibeam sonar data and side-scan sonar data are converted into a universal raster, underwater video is converted into frame images, and the format of cultural relic attribute data is standardized to ensure that all types of data can be stably identified and efficiently processed by subsequent modules.

[0011] Furthermore, techniques such as regular expressions and outlier detection algorithms were used to clean the data, removing noisy, redundant, and invalid data. Invalid data included artifact attribute data lacking key information and data with excessively large positioning deviations. Missing data was also appropriately supplemented using nearest neighbor interpolation to fill in a small number of missing positioning data.

[0012] Furthermore, fragmented acoustic and optical image data are stitched together and integrated. Specifically, multiple side-scan sonar images can be stitched together into a complete image of the detection area, and multiple underwater photographic images can be stitched together into a panoramic image of the site, realizing the integrated presentation of multi-source data and providing a complete data foundation for subsequent 3D scene construction.

[0013] Specifically, corresponding algorithms are used to extract the core features of various data types, providing precise support for subsequent visualization mapping and rendering. The feature extraction results will be directly used for 3D scene texture optimization, data layer marking, and accurate rendering of visualization elements, improving the accuracy and detail of the visualization display. Among these methods, image recognition algorithms are used to extract the outline and texture features of cultural relics, terrain analysis algorithms are used to extract the undulation features of the seabed topography, and anomaly detection algorithms are used to extract anomalous area features from acoustic and geophysical data.

[0014] Furthermore, spatiotemporal registration of all data was completed, unifying all types of data under the same spatiotemporal reference system. The spatial reference system adopted was the Chinese Geodetic Coordinate System 2000 (CGCS2000), ensuring precise spatial alignment of all data. The time reference adopted was UTC time, and data collected at different times were time-calibrated to ensure consistency of data in the time dimension, laying the foundation for the subsequent construction of a data model under a unified spatiotemporal reference system.

[0015] Step S2, Building the Related Data Model: Based on the multi-source data after spatiotemporal registration in step S1, a marine archaeological correlation data model under a unified spatiotemporal reference system is constructed. The model adopts a four-layer correlation structure of "site-exploration area-artifact point-document", breaking the traditional decentralized data management mode and realizing spatiotemporal and attribute correlation of various types of data.

[0016] Using "archaeological site" as the core node of the entire data model, basic information about the site is entered, including the site name, spatial range, formation period, and archaeological discovery time.

[0017] Furthermore, the site is linked to the corresponding archaeological exploration area, and basic information of the exploration area is entered, including the boundary coordinates of the exploration area, the exploration time, the exploration equipment, the exploration parameters, etc., so as to realize the association between the site and the exploration process data.

[0018] Furthermore, the detection area is linked with all the cultural relics excavation sites within that area, and information such as the location coordinates, excavation time, and stratum of the cultural relics sites is entered to realize the connection between the detection area and the spatial distribution of cultural relics.

[0019] Furthermore, each cultural relic site is associated with its corresponding cultural relic attribute data, including information such as the type, age, material, size, preservation status, and inspection report of the cultural relic, thus linking the cultural relic site with detailed cultural relic information.

[0020] Furthermore, the sites, exploration areas, and artifact sites are linked with corresponding historical documents and archaeological reports, and information such as the name, author, publication date, and core content of the documents are entered to achieve a full-link association between data and documents, providing support for data tracing and archaeological research.

[0021] After the model is built, all data in the model are stored in a spatiotemporal database and an attribute database, respectively. The spatiotemporal database is used to store spatial data, temporal data, and relationships, while the attribute database is used to store non-spatial data such as cultural relic attributes and documentary materials. The spatiotemporal database is built using a PostgreSQL database and a PostGIS spatial extension component. PostGIS can efficiently support the associated storage of spatial data and attribute data and is compatible with the Chinese Geodetic Coordinate System 2000 (CGCS2000), adapting to the data storage requirements under the unified spatiotemporal reference system of this invention, and realizing efficient data storage, querying, and management.

[0022] Step S3: 3D Scene Fusion and Construction

[0023] Based on the marine archaeological associated data model constructed in step S2, we carried out the construction of three-dimensional seabed scenes and the fusion processing of multi-source data to achieve integrated display of multiple types of data.

[0024] Specifically, the visualization processing engine generates a digital elevation model (DEM) of the seabed based on preprocessed multibeam data through interpolation algorithms, which can accurately restore the topographic features of the seabed (such as undulations, gullies, shoals, etc.). Furthermore, it uses side-scan sonar images as texture maps and overlays them onto the surface of the seabed DEM through texture mapping technology, which significantly enhances the realism and detail recognition of the seabed scene. It further optimizes the texture maps by noise reduction to remove image noise interference, making it easier for users to intuitively understand the actual appearance of the seabed.

[0025] Furthermore, for typical architectural remains and unearthed artifacts within the site, 3D laser scanning technology was used to acquire their 3D point cloud data. Subsequent processing, including manual correction and texture mapping, was then used to optimize the details of the 3D model, ensuring consistency between the model and the physical objects. Simultaneously, the corresponding artifact attribute information and basic site information from the associated data model were bound to the 3D model, enabling one-click "model-data" association and providing convenient support for subsequent interactive analysis and data traceability.

[0026] Furthermore, the preprocessed acoustic anomaly data, magnetic anomaly data, artifact excavation site markers, and positioning data are layered and overlaid onto the 3D underwater scene according to spatiotemporally registered coordinates, allowing users to intuitively observe the spatial relationships between various data types. To achieve clear differentiation and correlation of data, acoustic and magnetic anomaly areas are marked with different colored blocks, and artifact excavation sites are marked with personalized icons. Different types of data correspond to independent layers, achieving spatial alignment and fusion display of multi-source data.

[0027] Step S4: Visual Mapping and Interactive Rendering

[0028] It offers multiple visualization dimensions for users to choose from, performs visualization mapping and rendering processing on the multi-source data fused in the S3 step, and transforms abstract data into intuitive visualization elements.

[0029] The multi-dimensional visualization mapping and rendering are as follows:

[0030] The timeline control visualizes the spatiotemporal sequence of marine archaeological data, dynamically displaying the data along a time dimension. Specifically, it covers the complete timeline from the formation and evolution of a site to its discovery, the exploration process of archaeological surveys (including exploration areas and results at different time periods), and the burial, evolution, and excavation processes of artifacts. Users can drag the timeline to switch between different time points and view the data distribution and scene status, intuitively perceiving the temporal evolution patterns of marine archaeological findings.

[0031] Furthermore, various visualization charts are used to visualize the multi-dimensional attributes of cultural relics and exploration data. Specifically, heatmaps can be used to display the distribution density of cultural relics, with darker colors indicating denser distribution; scatter plots can be used to present the spatial distribution differences of different types of cultural relics, with different types of relics marked with different colors and shapes; correlation network diagrams can be used to show the relationship between cultural relic attributes (age, material), excavation location, and site, where nodes represent data objects and lines represent relationships; and bar charts and line charts can be used to compare exploration data from different exploration areas and statistically analyze the number of cultural relic types, helping users quickly uncover the distribution patterns and correlation characteristics behind the data.

[0032] Furthermore, based on the constructed 3D underwater scene, scene fusion visualization is achieved by layering and overlaying acoustic data layers, optical image layers, geophysical data layers, and artifact marker layers. Users can freely control the display and hiding of each layer, enabling the combined display of different types of data. For example, users can simultaneously display seabed topography, artifact excavation sites, and magnetic anomaly areas, intuitively analyzing the correlation between artifact distribution and the geophysical environment; they can also fuse underwater photographic images with the 3D scene to achieve a comparative display of "real scene - model," enhancing the intuitiveness and practicality of data presentation.

[0033] Furthermore, the simulation and visualization feature is an optional visualization dimension. Based on archaeological speculation, historical data, and exploration data, animation rendering technology is used to dynamically simulate and display the original form of the site, the trajectory of human activities within the site, the burial process of artifacts, and their evolution. For example, for underwater ancient city sites, this visualization dimension can simulate and display the original architectural layout of the ancient city, human living scenes, and the complete process of the ancient city being submerged by seawater and evolving to the present day. This provides both intuitive reference for archaeological research and vivid content support for popular science displays.

[0034] Furthermore, the visualization rendering is performed in a browser environment based on WebGL technology, using the Three.js graphics library to complete lightweight rendering of the 3D scene and picking of visualization elements, effectively avoiding hardware performance limitations and ensuring smooth operation of the visualization scene. Shaders are used to adjust parameters such as lighting and color to further enhance the intuitiveness and aesthetics of the visualization display. Raycasting technology is used to enable users to accurately select visualization elements in the 3D scene. Once selected, it can trigger a data tracing function, thereby achieving full-link data query. The logical processing of interactive events is handled by the interaction analysis module.

[0035] Specifically, during the rendering process, the system receives user-initiated operation commands through the interactive interface and updates the visual display content in real time. These operation commands include layer control commands, spatiotemporal or attribute-based query and filtering commands, scene perspective transformation commands, or data tracing commands, implemented as follows:

[0036] Furthermore, the layer control panel in the interface settings enables multi-layer control. Users can freely select the data source layers to be displayed (such as terrain layers, cultural relic layers, acoustic data layers, etc.), and adjust the transparency and display order of the layers to achieve visualization of different data combinations and meet the diverse viewing needs of users.

[0037] Furthermore, spatiotemporal queries are achieved through query input boxes and conditional filtering controls. Users can combine and filter the data they need by time range (such as exploration results from a specific year), spatial region (such as cultural relics within a specific exploration area), cultural relic attributes (such as cultural relics from a specific era or made of a specific material), and data type (such as acoustic anomaly data). The query results will be highlighted in the visualization scene, and detailed information about the corresponding data will be displayed simultaneously, improving the accuracy and efficiency of data queries.

[0038] Furthermore, it supports first-person and third-person perspective underwater scene roaming to achieve scene perspective changes. Users can control the movement, rotation, and zoom of the viewpoint using the mouse and keyboard to achieve a comprehensive view from macroscopic seabed topography to microscopic individual artifacts. This function also supports custom profile cutting analysis. Users can set the position and angle of the cutting plane to view the internal structure of the site and seabed strata, gain a deeper understanding of the burial state of the site, and provide more comprehensive perspective support for archaeological research.

[0039] Furthermore, by clicking on any element in the visualized scene (such as cultural relic markers, abnormal areas, or site boundaries) to trigger data tracing, the user can view the original data (such as original detection data, photos of unearthed cultural relics), processing procedures, and related literature with one click, thus achieving full-chain data tracing and providing convenient and efficient support for scientific research and analysis.

[0040] Simultaneously, it supports multi-terminal and multi-format output of visualization results, specifically implemented as follows:

[0041] It supports multi-terminal output adaptation, including web browsers, mobile applications, and large immersive display devices. The web version adopts a responsive design to adapt to computer browsers of different sizes, allowing researchers to view and analyze data online. The mobile version generates lightweight display pages that can be viewed on mobile devices such as phones and tablets. The large-screen display is adapted to the display screens of museums and research institutions to achieve immersive display. The visualization processing engine can adapt and output rendered data to different types of user interaction terminals to ensure consistent display effects across all terminals.

[0042] Furthermore, it can generate three types of visualization deliverables: static, dynamic, and interactive, enabling multi-format output. Static deliverables include visualized images and data reports; dynamic deliverables include visualized videos and animations; and interactive deliverables include visualized reports and interactive demo programs. Visualized reports can automatically integrate statistical results, visual charts, and analytical conclusions, and support exporting to PDF, Word, and other formats to meet users' needs for saving and sharing their results.

[0043] Corresponding to the above method, the present invention also provides a marine archaeological data visualization system for implementing the above method. This system is an implementation combining hardware architecture and software modules, and its specific structure is as follows:

[0044] The system includes data acquisition and processing equipment, a data processing server, and a user interaction terminal. All hardware devices work collaboratively, and the software modules are deployed within the data processing server. The hardware devices and software modules correspond one-to-one and work in tandem, as follows: the data acquisition and processing equipment corresponds to the data access module, responsible for data acquisition and initial transmission; the data processing server carries five major software modules, responsible for data processing, modeling, rendering, and interactive logic processing; the user interaction terminal corresponds to the interactive analysis module and the output module, responsible for sending instructions and displaying results.

[0045] 1. Data acquisition and processing equipment is used to acquire raw data from multi-source heterogeneous marine archaeological surveys. Specifically, it can interface with marine archaeological survey equipment (such as multibeam sonar, side-scan sonar, and underwater cameras), existing databases, and document management systems to achieve batch import and real-time acquisition of data. It further includes a data caching unit for temporary storage of the acquired raw data to prevent data loss during transmission. The acquired data is transmitted to a data processing server for subsequent processing by software modules.

[0046] 2. The data processing server is communicatively connected to the data acquisition and processing equipment, serving as the core hardware carrier of the system. Internally, it runs five major software modules: a data access module, a data governance module, a visualization processing engine, an interactive analysis module, and an output module. Each software module operates independently yet collaboratively, with the following specific functions:

[0047] The data access module is mainly used to receive multi-source marine archaeological survey data transmitted by data acquisition and processing equipment, perform standardized preprocessing operations, support data access in multiple formats such as GeoTiff, SHP, JPG, and MP4, and output standardized data that meets the requirements of subsequent modules, providing data support for the data governance module.

[0048] The data governance module can receive standardized data output from the data access module, construct a four-layer association data model of "site-exploration area-cultural relic site-document" through data association algorithms, verify the integrity and accuracy of the data, and remove invalid association data; based on the constructed four-layer association data model, the associated data is stored in a spatiotemporal database; the spatiotemporal database is built using PostgreSQL+PostGIS to achieve efficient storage and management of spatial data, attribute data and association relationships, and support fast data query, update and deletion.

[0049] The visualization processing engine generates and outputs visualization rendering data; it achieves lightweight rendering of 3D scenes based on WebGL technology, and uses the Three.js framework to build underwater terrain models and 3D models of cultural relics. It enhances scene realism through techniques such as texture mapping and lighting rendering; it has a built-in multi-source data fusion algorithm to achieve spatial alignment and fusion of different types of data; it provides a variety of visualization rendering algorithms, supports rendering of multiple visualization dimensions such as spatiotemporal sequences, multi-dimensional attributes, scene fusion, and simulation reproduction, and outputs intuitive and smooth visualization scene data, which is then transmitted to the interactive analysis module.

[0050] The interactive analysis module provides the relevant logic processing for the human-computer interaction analysis interface. It receives operation commands sent by the user's interactive terminal and transmits the commands to the visualization processing engine. At the same time, it receives the updated visualization data returned by the visualization processing engine and feeds it back to the user's interactive terminal for display. It achieves accurate picking of visualization elements through ray detection technology and supports interactive functions such as multi-layer control, spatiotemporal query, scene perspective change, and data tracing to meet users' needs for in-depth data exploration.

[0051] The output module is used to execute the visualization output steps according to the instructions sent by the user's interactive terminal, exporting the current visualization scene as a static image, dynamic video, or an interactive report document containing visualization icons, realizing multi-form output; at the same time, it provides an API interface based on the RESTful specification to support third-party systems to call data or visualization results in the spatiotemporal database.

[0052] 3. The user interaction terminal is communicatively connected to the data processing server and is used to send relevant user instructions to the visualization processing engine and receive and display the visualization rendering data. The user interaction terminal includes at least one graphics display device, which may be one or more of a web browser, mobile terminal application, or large immersive display device, to adapt to the usage scenario needs of different users. Attached Figure Description

[0053] Figure 1 This is a flowchart of the core steps of the marine archaeological survey data visualization method of the present invention.

[0054] Figure 2 This is a diagram illustrating the overall architecture of the data visualization system based on marine archaeological survey results of this invention. Detailed Implementation

[0055] Example 1: Marine Archaeological Data Visualization Process Based on the Method of the Invention

[0056] In one embodiment, this embodiment takes the archaeological survey data of an underwater ancient city site in a certain sea area as the research object, and uses the method of the present invention to realize data visualization. The specific process corresponds to steps S1 to S4 of the method of the present invention, as detailed below:

[0057] Step S1: Data Access and Preprocessing

[0058] Multi-source archaeological survey data of the underwater ancient city site were collected using data acquisition and processing equipment, including multibeam acoustic data, side-scan sonar data, underwater photographic images, underwater video data, artifact excavation location data, artifact attribute data (including information such as artifact type, age, and material), and related historical documents. After the data collection was completed, all raw data was transmitted to the data processing server, where the data access module performed subsequent processing.

[0059] The standardized preprocessing is as follows:

[0060] Format conversion is achieved through the GDAL library built into the data access module. This library supports the parsing and conversion of various commonly used marine archaeology data formats such as GeoTiff and SHP. It can convert multibeam and side-scan sonar data into the GeoTiff universal raster format, extract frame images from underwater videos according to adaptation requirements, and convert positioning data into JSON format, thereby ensuring that various types of data can be stably recognized by subsequent modules. The frame extraction frequency and format conversion type can be adjusted according to actual data processing needs.

[0061] The core features of various data types are extracted using corresponding algorithms and parameters, providing precise support for subsequent visualization rendering. This step also utilizes the OpenCV library to assist in image feature extraction and image enhancement, effectively improving the clarity of underwater photographic images and facilitating the accurate extraction of artifact outlines and texture features, further optimizing the detail and realism of subsequent 3D scene rendering. Specifically, the outline and texture features of unearthed porcelain and pottery artifacts are extracted using the YOLOv5 image recognition algorithm. The training parameters can be set to adapt to actual needs and can be flexibly adjusted according to the actual artifact type and recognition accuracy requirements, enabling effective feature recognition. The undulation features of the seabed topography are extracted using the SIFT algorithm, with an extraction threshold set to adapt to the terrain complexity, which can be adjusted according to the terrain complexity, effectively identifying abnormal terrain areas such as city walls and roads in ancient city ruins. Abnormal area features in acoustic and magnetic data are extracted using the isolated forest algorithm, with an identification threshold set to adapt to the density of abnormal areas, which can be adjusted according to the density of abnormal areas, initially identifying areas where artifacts are buried, thus achieving effective feature recognition.

[0062] Fragmented side-scan sonar images are stitched together to form a complete underwater image of the ancient city ruins exploration area; underwater photographic images are stitched together to form a panoramic image of the ancient city ruins, achieving integrated data presentation.

[0063] The data governance module receives standardized data output from the data access module, unifies all types of data to the National Geodetic Coordinate System 2000 (CGCS2000), performs coordinate calibration on positioning data and terrain data to ensure accurate spatial alignment, and calibrates the detection data collected at different time periods to UTC time according to adaptation requirements to ensure consistency in the time dimension, laying the foundation for the subsequent construction of the S2 correlation data model.

[0064] Step S2, Building the Related Data Model:

[0065] The data governance module in the data processing server uses the underwater ancient city site as the core node to construct a four-layer interconnected data model: "Site - Exploration Area - Artifact Sites - Documents". The specific process is as follows:

[0066] Enter the basic information of the underwater ancient city site, including the site name, spatial range, formation period, and archaeological discovery time, and complete the entry of core node information.

[0067] The site was associated with the corresponding exploration area, and the boundary coordinates, exploration time, exploration equipment (multibeam sonar, side-scan sonar) and exploration parameters (exploration depth, resolution) of each exploration area were recorded.

[0068] The detection area is linked to the sites where cultural relics were unearthed within that area, and the location coordinates, excavation time, and stratum of each cultural relic site are recorded.

[0069] Each cultural relic site is associated with its corresponding cultural relic attribute data, and the type of cultural relic (porcelain, pottery, bronze, etc.), era (early, middle, and late Han Dynasty), material, size, preservation status, and test report are entered.

[0070] The site, exploration area, and cultural relic site are associated with the corresponding historical documents, and the name, author, and core content of the documents are entered to achieve a full-link association between data and documents.

[0071] After the associated data model is constructed, all data is stored in the PostgreSQL+PostGIS spatiotemporal database and attribute database respectively to achieve efficient data storage and query. This database combination can efficiently support the associated storage of spatial data and attribute data, and is compatible with the National Geodetic Coordinate System 2000 (CGCS2000), thus perfectly adapting to the data storage requirements of this embodiment and ensuring the efficiency of data query, update and deletion.

[0072] Step S3: 3D Scene Fusion and Construction

[0073] The visualization engine in the data processing server, based on the associated data model built in step S2, performs 3D seabed scene construction and multi-source data fusion processing. The specific process is as follows:

[0074] Based on the preprocessed multibeam sonar data, a digital elevation model (DEM) of the underwater ancient city ruins was generated using the Kriging interpolation algorithm. The algorithm's variogram model was a Gaussian model, and the interpolation resolution was set to adapt to the actual needs, allowing for flexible adjustment based on detection accuracy and scene requirements. This method can reproduce the topographic undulations of the seabed and clearly present the outlines of the city walls and roads of the ancient city ruins. Subsequently, the stitched side-scan sonar images were used as texture maps and superimposed on the surface of the DEM model to enhance the realism of the seabed scene. This step used the Three.js framework to construct the seabed topography model and implemented lightweight rendering based on WebGL technology to ensure smooth scene operation.

[0075] Representative site structures and several typical unearthed artifacts (including common types such as porcelain, pottery, and bronze) from the ancient city ruins were selected. 3D laser scanning technology was used to automatically model the artifacts and obtain 3D point cloud data. The model details were then manually corrected and optimized, and texture maps were added to ensure that the model was consistent with the real objects. At the same time, the artifact attribute information and unearthed information in the associated data model were bound to the corresponding 3D model to achieve one-click association between "model and data".

[0076] Acoustic anomaly data, magnetic anomaly data, and various artifact excavation site markers are layered and overlaid onto the seabed 3D scene according to their spatiotemporally registered coordinates, achieving clear differentiation and fusion of the data. To ensure clear data differentiation, acoustic anomaly areas are marked with red blocks, magnetic anomaly areas with yellow blocks, and artifact excavation sites with blue icons. Different types of data are displayed using different layers, achieving fusion of multi-source data. This step uses the Turf.js library to implement spatial fusion and overlay analysis of multi-source data, which is suitable for the multi-source data fusion requirements of this embodiment. The marker colors and icon styles can be adjusted according to actual display needs.

[0077] Step S4: Visual Mapping and Interactive Rendering

[0078] Based on the needs of scientific research analysis and popular science display, the visualization engine in the data processing server selects four dimensions for visualization mapping and rendering: spatiotemporal sequence visualization, multi-dimensional attribute visualization, scene fusion visualization, and simulation reproduction visualization. Simultaneously, it receives operation commands from user terminals to achieve interactive analysis and output of results. The specific process is as follows:

[0079] The multi-dimensional visualization rendering is as follows:

[0080] A timeline control developed using the ECharts library enables visualization of spatiotemporal sequences. This library provides smooth chart rendering, supports free selection and dragging of time ranges, and dynamically displays the complete timeline of the underwater ancient city site, from its formation, prosperity, and decline during the Han Dynasty, to its submersion by seawater, and finally to its archaeological discovery and exploration. Specifically, users can drag the timeline to view the site's status at different time points (such as the original appearance of the ancient city, the submersion process, and the current seabed state) and exploration results (such as the exploration areas and unearthed artifacts at different time periods). This section also utilizes the GSAP library to implement dynamic animation effects for the spatiotemporal sequence, accurately presenting the timeline of the site's evolution and the changes in the distribution of artifacts. The time accuracy of the timeline and the animation playback speed can be adjusted according to actual needs.

[0081] A heat map of cultural relic distribution density was generated to visualize multi-dimensional attributes and clearly show the distribution of cultural relic points; a scatter plot was used to present the spatial distribution differences of different types of cultural relics; and a correlation network diagram was used to show the relationship between the age of cultural relics and their excavation location, revealing that cultural relics from the mid-Han Dynasty were mainly distributed in the central area of ​​the ancient city.

[0082] The system enables scene fusion visualization in a 3D underwater scene, simultaneously displaying terrain layers, artifact layers, acoustic anomaly zones, and magnetic anomaly zones. By adjusting the transparency of each layer, the system allows for a direct view of the relationship between artifact distribution and anomaly areas. It reveals that artifacts are mainly concentrated in acoustic and magnetic anomaly zones, providing a reference for subsequent archaeological exploration.

[0083] Based on historical data, archaeological speculation, and exploration data, animation rendering technology is used to simulate and visualize the underwater ancient city, showcasing its original architectural layout, human living scenes, and the complete process of its submersion and evolution to the present day. This provides an intuitive reference for archaeological research and vivid content for popular science exhibitions.

[0084] Rendering is performed in a browser environment based on WebGL technology. The Three.js graphics library is used for lightweight rendering of 3D scenes to ensure smooth scene operation. Shaders are used to adjust lighting and shadow effects to improve the intuitiveness and aesthetics of visualization. Ray detection technology is used to accurately pick up visualized elements to support subsequent interactive operations.

[0085] The spatiotemporal query responds to user queries sent via a web browser. Users input search criteria such as "mid-Han Dynasty, porcelain" into the query input box and send the command. The interactive analysis module receives the command and transmits it to the visualization processing engine, which then performs filtering operations through Elasticsearch. This search tool boasts fast retrieval speed, supports multi-condition queries, and achieves efficient query response. It can filter out mid-Han Dynasty porcelain artifacts that meet the criteria, highlighting the search results in a 3D scene. Simultaneously, it feeds back the attribute information, excavation location, and relevant literature of each artifact to the web browser for user viewing and analysis.

[0086] With multi-layer control, users can send commands to hide the magnetic anomaly area layer through the layer control panel of a web browser (user interaction terminal). The interactive analysis module receives the commands and transmits them to the visualization processing engine. The engine updates the scene in real time. When the magnetic anomaly area layer is hidden, users can view the relationship between the distribution of cultural relics and the acoustic anomaly area separately. Users can also adjust the transparency of the terrain layer, and the engine updates the scene synchronously, making it easier for users to view the relationship between the seabed topography and the distribution of cultural relics.

[0087] With the scene perspective changing, users can send first-person perspective roaming commands through the mouse and keyboard of a web browser. The interactive analysis module receives the commands and transmits them to the visualization processing engine. The engine controls the movement of the viewpoint, allowing users to view the city wall ruins and artifact models up close. Users can also send cutting commands to set the position and angle of the cutting plane. The engine generates the cut scene to show the internal structure of the ancient city wall and help users understand the construction techniques of the city wall.

[0088] Data traceability allows users to send a data traceability command by clicking on a marker of a Han Dynasty porcelain artifact through a web browser. The interactive analysis module receives the command and transmits it to the visualization processing engine. The engine then calls relevant data from the spatiotemporal database and feeds back the artifact's original excavation photos, original location data, test reports, and relevant Han Dynasty documents to the web browser, thus achieving end-to-end data traceability.

[0089] The output results, in response to the output commands from the user interaction terminal, are as follows:

[0090] Multi-terminal output: Users send multi-terminal output commands through a web browser. The output module in the data processing server responds to the commands, generating an online display page for researchers to view and analyze data online; generating a lightweight mobile page that supports viewing on mobile phones (user interaction terminals); adapting to museum large screens (user interaction terminals) to achieve immersive display; and the visualization processing engine adapts the rendered data to the display requirements of different terminals to ensure consistent display effects.

[0091] Multiple output formats: Responding to user-sent export commands, the output module supports multiple resolution options and offers high video export efficiency, capable of exporting visualized images and videos; it also generates PDF format visualized reports, automatically integrating data statistics, visualized charts, and analysis conclusions to meet users' needs for saving and sharing their results.

[0092] This method and system are also applicable to other types of marine archaeological scenarios, such as shipwreck sites and scattered cultural relics sites.

[0093] It should also be noted that the terms “comprising,” “including,” and any variations thereof in this application are intended to cover non-exclusive inclusion, that is, a process, method, apparatus, or system that comprises a series of elements includes not only the elements expressly listed, but also inherent elements or conventional additional elements that are not expressly listed but are known to those skilled in the art.

[0094] Those skilled in the art will understand that embodiments of the present invention can be embodied as methods, systems, or computer program products. Therefore, without departing from the core ideas of the present invention, it can be implemented in pure hardware, pure software, or a combination of hardware and software. All equivalent modifications, substitutions, or combinations based on the technical solutions of the present invention should be considered to fall within the protection scope defined by the claims.

Claims

1. A method for visualizing data based on marine archaeological survey results, characterized in that, Includes the following steps: Step S1: Data access and preprocessing. Obtain multi-source heterogeneous marine archaeological survey data. After standardizing and preprocessing the data, register all preprocessed data to the same spatiotemporal reference system. Step S2: Construction of the associated data model. Based on the spatiotemporally registered data, a four-layer associated data model under a unified spatiotemporal reference system is constructed. The model takes the site as the core node and sequentially associates the exploration area, cultural relics points and documentary materials to establish the spatiotemporal and attribute association relationships between each data object. The associated data is then stored in the spatiotemporal database. Step S3: 3D scene fusion and construction. Based on the associated data model, a digital elevation model of the seabed is generated using multibeam data, and side-scan sonar images are mapped onto the surface of the model as textures to construct a basic seabed 3D scene. The spatial location information of acoustic anomaly areas, magnetic anomaly areas, and the sites where cultural relics were unearthed, as well as the 3D models of typical cultural relics or site structures, are fused and superimposed onto the basic seabed 3D scene according to their spatiotemporal coordinates to form an enhanced 3D scene that integrates multi-source data. Step S4, Visualization Mapping and Interactive Rendering: Based on the enhanced 3D scene, at least one visualization dimension is selected for rendering and display according to user instructions, and operation instructions initiated by the user through the interactive interface are received, and the visualization display content is updated in real time.

2. The method according to claim 1, characterized in that, The multi-source heterogeneous marine archaeological survey data includes at least acoustic detection data, optical image data, and artifact attribute data; the standardized preprocessing includes data format conversion, data cleaning, and data mosaicking. Data format conversion converts raw data of different formats into a common format that the system can recognize. Data cleaning removes noise and invalid data and fills in missing data. Data mosaicking stitches together and integrates fragmented image data.

3. The method according to claim 2, characterized in that, The standardized preprocessing also includes feature extraction and data verification. Image recognition algorithms are used to extract the outline features of cultural relics from optical image data, and terrain analysis algorithms are used to extract the seabed topography features from acoustic detection data. Data verification is used to check the integrity and accuracy of the preprocessed data to ensure that the data meets the requirements for subsequent modeling.

4. The method according to claim 1, characterized in that, The three-dimensional model of the typical cultural relic or site structure is bound to the corresponding cultural relic attribute information in the associated data model.

5. The method according to claim 1, characterized in that, The S4 visualization dimensions include spatiotemporal sequence visualization, multi-dimensional attribute visualization, scene fusion visualization, and simulation reproduction visualization. The operation commands include layer control commands, spatiotemporal or attribute query and filtering commands, scene perspective transformation commands, and data tracing commands.

6. A marine archaeological data visualization system for implementing the method of any one of claims 1 to 5, characterized in that, The system includes data acquisition and processing equipment, a data processing server, and a user interaction terminal. The data acquisition and processing equipment is used to acquire raw data from multi-source, heterogeneous marine archaeological surveys. The data processing server is communicatively connected to the data acquisition and processing equipment and internally operates a data access module, a data governance module, a visualization processing engine, an interactive analysis module, and an output module. These modules work collaboratively with a clear data flow: the data access module receives raw data and performs standardized preprocessing, providing standardized data support for the data governance module; the data governance module constructs a correlated data model based on the standardized data and stores it in a spatiotemporal database, while also providing data support for the visualization processing engine; the visualization processing engine relies on the correlated data model to complete the construction and rendering of a 3D scene, providing rendering data support for the interactive analysis module. The interactive analysis module receives operation commands from the user's interactive terminal and, in conjunction with the visualization processing engine, feeds back the updated rendering data to the user's interactive terminal. The output module relies on the rendering data from the visualization processing engine and the associated data from the spatiotemporal database to perform the output operation; the user interaction terminal is connected to the data processing server to send user commands and display the visualization rendering data.

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