Construction method and system of sponge city model based on BIM technology

Abstract

The present invention relates to a construction method and system of a sponge city model based on BIM technology, comprising the following steps: classifying an urban underlying surface based on the fused geographic information data to obtain underlying surface types and underlying surface type topological relationship diagrams corresponding to the underlying surface types; simulating and analyzing the rainwater runoff path of the target sponge city based on the underlying surface type topological relationship diagram to obtain a rainwater runoff path network; designing the layout of urban rainwater storage facilities in the target sponge city based on the underlying surface type and the rainwater runoff path network to obtain a rainwater storage facility layout plan; constructing a virtual sponge city model based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan, thereby solving the technical problem that it is difficult for traditional methods to fully consider the complex and changeable urban topography and landforms, resulting in difficulty in reflecting the influence of different types of ground covers on the rainwater runoff path.

Description

Technical Field

[0001] The present invention relates to the technical field of sponge cities, and in particular to a method and system for constructing a sponge city model based on BIM technology. Background Art

[0002] With the acceleration of urbanization, the urban hydrological environment has suffered unprecedented challenges. The traditional urban construction model often ignores the importance of natural water cycle, leading to a series of problems such as urban waterlogging, water shortage and water pollution. Especially in the case of heavy rainfall or long duration, the carrying capacity of the urban drainage system is particularly insufficient, which aggravates these problems. In order to meet these challenges, the concept of sponge city came into being, aiming to achieve effective collection, purification and utilization of rainwater by imitating the natural water cycle process. However, in the planning and construction process of sponge city, how to accurately evaluate the impact of urban underlying surface on rainwater management, and how to scientifically and rationally layout rainwater storage facilities have become key issues that need to be solved.

[0003] Most existing sponge city models rely on traditional GIS (geographic information system) technology and limited data sources, which to some extent limits the accuracy and practicality of the models. For example, traditional methods are difficult to fully consider factors such as complex and changeable urban topography and land use. The classification of urban underlying surfaces is not detailed enough and cannot accurately reflect the impact of different types of ground covers on rainwater runoff paths. In addition, existing technologies have difficulty in fusing large amounts of heterogeneous geographic information data, which directly affects the accuracy of subsequent rainwater runoff path simulations. Therefore, it is particularly important to develop a new sponge city modeling method that can effectively integrate multiple data sources and improve model accuracy and practicality.

[0004] In this context, a method for constructing a sponge city model based on BIM (Building Information Modeling) technology is proposed to overcome the limitations of existing technologies. This method first ensures the comprehensiveness and accuracy of the data by deeply mining and integrating the geographic information data of the target sponge city; then, the urban underlying surface is divided in detail using advanced classification algorithms, providing a reliable basis for subsequent simulation of rainwater runoff paths; finally, combined with the optimized layout of rainwater storage facilities, a highly realistic virtual sponge city model is constructed through BIM technology. This method can not only provide strong technical support for the planning and design of sponge cities, but also provide more intuitive and accurate decision-making basis for urban management decision makers, which is conducive to promoting the sustainable development of sponge cities. Summary of the invention

[0005] The main purpose of the present invention is to provide a method and system for constructing a sponge city model based on BIM technology, which solves the technical problems that traditional methods are difficult to comprehensively consider factors such as complex and changeable urban topography and land use, and the classification of urban underlying surfaces is not detailed enough to reflect the impact of different types of ground covers on rainwater runoff paths.

[0006] To achieve the above object, the present invention provides a method for constructing a sponge city model based on BIM technology, comprising the following steps:

[0007] Acquire geographic information data of the target sponge city, and perform data fusion on the geographic information data to obtain fused geographic information data;

[0008] Based on the fused geographic information data, urban underlying surfaces are classified to obtain underlying surface types and underlying surface type topological relationship diagrams corresponding to the underlying surface types;

[0009] Based on the topological relationship diagram of the underlying surface types, a rainwater runoff path simulation analysis is performed on the target sponge city to obtain a rainwater runoff path network; wherein the rainwater runoff path network is the relationship between the water flow direction and flow rate between different underlying surface types;

[0010] Based on the underlying surface type and the rainwater runoff path network, design the layout of urban rainwater storage facilities in the target sponge city to obtain a layout plan of rainwater storage facilities;

[0011] Through the preset BIM technology, a virtual sponge city model is constructed based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan.

[0012] Furthermore, the acquiring of geographic information data of the target sponge city and data fusion of the geographic information data to obtain fused geographic information data includes:

[0013] The topography of the target sponge city is collected by using a preset drone aerial photography technology to obtain an original geographic information image;

[0014] Preprocessing the original geographic information image to obtain a clean geographic information image;

[0015] Performing pixel-level segmentation on the clean geographic information image using a preset U-Net architecture to extract boundary information of different types of land features in the target sponge city from the clean geographic information image to obtain a land feature classification map;

[0016] Performing spatial interpolation processing on the land feature classification map to obtain an interpolated land feature classification map;

[0017] The interpolated feature classification map is subjected to data association and fusion to obtain fused geographic information data; wherein the fused geographic information data includes geographic coordinates, topography and landforms, and water system distribution.

[0018] Furthermore, the urban underlying surface classification is performed based on the fused geographic information data to identify the urban underlying surface type of the target sponge city, and the underlying surface type and the underlying surface type topological relationship diagram corresponding to the underlying surface type are obtained, including:

[0019] Performing feature extraction on the fused geographic information data to obtain an extracted feature vector; wherein the extracted feature vector includes a shape feature vector, a spectral feature vector, a texture feature vector and a humidity gradient vector;

[0020] Determine the vegetation state of the target sponge city based on the spectral feature vector and the texture feature vector;

[0021] Based on the humidity gradient vector, a humidity gradient analysis is performed on the target sponge city to obtain a humidity gradient image; wherein the humidity gradient image is a soil humidity variation trend in different directions and regions;

[0022] By using the geographic coordinates, the fused geographic information data is classified into underlying surface types based on the humidity gradient image and the vegetation status, so as to obtain underlying surface types and positions corresponding to the underlying surface types; wherein the underlying surface types include hard surface data, permeable pavement data, natural ground data, water body data and building land data;

[0023] Determine the shape corresponding to the underlying surface type based on the shape feature vector and the texture feature vector;

[0024] Using a preset logical reasoning algorithm, the topological relationship of the target sponge city is constructed based on the shape, underlying surface type and the position corresponding to the underlying surface type to obtain a topological relationship diagram of the underlying surface type.

[0025] Furthermore, the rainwater runoff path simulation analysis is performed on the target sponge city based on the underlying surface type topological relationship diagram to obtain a rainwater runoff path network, including:

[0026] The terrain features are extracted by using a preset digital terrain analysis algorithm to obtain extracted terrain features; wherein the extracted terrain features include terrain slope, slope direction and drainage area terrain features;

[0027] Assigning resistance weights to underlying surface types in the underlying surface type topological relationship diagram to obtain a weighted topological relationship diagram;

[0028] Acquiring initial rainfall conditions and water boundary conditions, performing water flow simulation based on the extracted terrain features, the weighted topological relationship diagram, the initial rainfall conditions and the water boundary conditions, and obtaining initial water flow state data;

[0029] Tracking the motion trajectory of water flow particles in the initial water flow state data to obtain water flow particle path data;

[0030] Obtaining a runoff path set based on the water flow particle path data and the underlying surface type topological relationship diagram;

[0031] Using the network analysis algorithm, the rainwater runoff path network is obtained based on the runoff path set and initial water flow state data.

[0032] Furthermore, based on the underlying surface type and the rainwater runoff path network, the urban rainwater storage facility layout of the target sponge city is designed to obtain a rainwater storage facility layout plan, including:

[0033] Based on the underlying surface type and the rainwater runoff path network, the target sponge city is divided into a watershed area to obtain a watershed area unit set;

[0034] Calculating the rainwater storage demand for each catchment area unit to obtain the corresponding storage capacity demand;

[0035] Based on geospatial technology, the constructible area and suitability analysis of the target sponge city are carried out to obtain the suitable area for the construction of rainwater storage facilities;

[0036] Utilizing a preset flow peak analysis algorithm, extracting flow data in the rainwater runoff path network, and performing multi-scale analysis on the flow data to obtain multi-scale rainwater runoff information;

[0037] In the suitable area for the construction of rainwater storage facilities, the layout of rainwater storage facilities is carried out based on the multi-scale rainwater runoff information and the storage capacity demand, and a preliminary layout plan is obtained;

[0038] Based on the cost-benefit evaluation model, the preliminary layout plan was evaluated and adjusted to obtain the layout plan of rainwater storage facilities.

[0039] Furthermore, based on the underlying surface type and the rainwater runoff path network, the target sponge city is divided into a catchment area to obtain a catchment area unit set, including:

[0040] In the underlying surface type topological relationship diagram, performing a topological structure analysis on the hard surface data to obtain a topological relationship of the hard surface data;

[0041] Based on the topological relationship of the hard surface data and the water flow direction in the rainwater runoff path network, flow direction impact analysis is performed on the natural ground to obtain a natural ground water flow path;

[0042] Based on the natural surface water flow path and the water body data, a preliminary water catchment area is determined for the target sponge city to obtain a preliminary water catchment area;

[0043] Based on the preliminary catchment area, permeability analysis is performed on the different underlying surface types to obtain the underlying surface permeability coefficient distribution;

[0044] Calculating the water collection capacity of the underlying surface permeability distribution and the flow data to obtain a water collection capacity assessment result;

[0045] Based on the results of water catchment capacity assessment, the preliminary water catchment area is divided to obtain a set of water catchment area units.

[0046] Furthermore, through the preset BIM technology, a virtual sponge city model is constructed based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan, including:

[0047] Using the BIM technology, the fused geographic information data is subjected to three-dimensional terrain reconstruction to obtain a three-dimensional terrain model;

[0048] Based on the underlying surface type topological relationship diagram, the underlying surface position of the three-dimensional terrain model is mapped to obtain a surface feature model;

[0049] Performing rainwater runoff path simulation on the surface feature model based on the rainwater runoff path network to generate a hydrological dynamics model;

[0050] Based on the layout plan of rainwater storage facilities, the hydrological dynamics model is designed in three dimensions to obtain a sponge facility integration model;

[0051] The sponge facility integrated model is rendered and visualized to obtain a virtual sponge city model.

[0052] The present invention also provides a construction system of a sponge city model based on BIM technology, comprising:

[0053] An acquisition module is used to acquire geographic information data of a target sponge city and perform data fusion on the geographic information data to obtain fused geographic information data;

[0054] A classification module, used for classifying the urban underlying surface based on the fused geographic information data, and obtaining underlying surface types and underlying surface type topological relationship diagrams corresponding to the underlying surface types;

[0055] A simulation module, used to simulate and analyze the rainwater runoff path of the target sponge city based on the underlying surface type topological relationship diagram to obtain a rainwater runoff path network; wherein the rainwater runoff path network is the relationship between the water flow direction and flow rate between different underlying surface types;

[0056] A design module is used to design the layout of urban rainwater storage facilities of the target sponge city based on the underlying surface type and the rainwater runoff path network, and obtain a layout plan of rainwater storage facilities;

[0057] The construction module is used to construct a virtual sponge city model based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan through a preset BIM technology.

[0058] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods when executing the computer program.

[0059] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0060] The method for constructing a sponge city model based on BIM technology provided by the present invention comprises the following steps: acquiring geographic information data of a target sponge city, and fusing the geographic information data to obtain fused geographic information data; classifying the urban underlying surface based on the fused geographic information data to obtain underlying surface types and underlying surface type topological relationship diagrams corresponding to the underlying surface types; simulating and analyzing the rainwater runoff path of the target sponge city based on the underlying surface type topological relationship diagram to obtain a rainwater runoff path network; wherein the rainwater runoff path network is the relationship between water flow directions and flow rates between different underlying surface types; based on the underlying surface type and the rainwater runoff path network, designing the layout of urban rainwater storage facilities in the target sponge city to obtain to the layout plan of rainwater storage facilities; through the preset BIM technology, a virtual sponge city model is constructed based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan. The above technical means solve the technical problems that the traditional method is difficult to fully consider the complex and changeable urban topography, land use and other factors, the classification of urban underlying surfaces is not fine enough, and it is impossible to reflect the impact of different types of ground covers on the rainwater runoff path. Through the use of BIM technology, the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan are integrated together to build a highly simulated virtual sponge city model. This method is not only convenient for urban managers to intuitively understand and operate, but also provides strong technical support for future urban planning and construction, and promotes the beneficial effects of the development of smart city construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the steps of a method for constructing a sponge city model based on BIM technology in one embodiment of the present invention;

[0062] Figure 2 It is a structural block diagram of a device for constructing a sponge city model based on BIM technology in one embodiment of the present invention;

[0063] Figure 3 It is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0064] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0066] like Figure 1 As shown, Figure 1 It is a schematic diagram of the steps of a method for constructing a sponge city model based on BIM technology in one embodiment of the present invention;

[0067] In one embodiment of the present invention, a method for constructing a sponge city model based on BIM technology is provided, comprising the following steps:

[0068] Step S1, obtaining geographic information data of a target sponge city, and performing data fusion on the geographic information data to obtain fused geographic information data.

[0069] Specifically, in the process of building a sponge city model based on BIM technology, it is first necessary to obtain the geographic information data of the target sponge city and fuse these geographic information data to obtain fused geographic information data. This process involves information collection and integration work in multiple aspects. For example, geographic information data can be obtained from multiple channels such as satellite remote sensing images, topographic maps, underground pipeline distribution maps, etc. These data contain information in multiple dimensions such as urban landforms, land use, and groundwater levels. In order to ensure the consistency and accuracy of the data, data fusion technology is needed to process data from different sources and eliminate inconsistencies between data, such as coordinate system conversion and data format unification, so as to form a complete and accurate geographic information database. For example, in practical applications, suppose we are building a sponge city model for a coastal city, which is facing serious rainstorm waterlogging problems. At this time, it is necessary to collect information such as rainfall records, drainage network layout, and ground cover types in the area. By fusing this information, such as using spatial analysis software to overlay and analyze different data layers, ensure that all data are aligned under the same geographic coordinate system, and thus construct a fused geographic information data set that can fully reflect the hydrological characteristics of the area. This dataset will become an important basis for subsequent steps such as urban underlying surface classification and rainwater runoff path simulation, providing strong support for the realization of intelligent management of sponge cities.

[0070] Step S2, classifying the urban underlying surface based on the fused geographic information data, and obtaining underlying surface types and underlying surface type topological relationship diagrams corresponding to the underlying surface types.

[0071] Specifically, classifying the urban underlying surface based on the fused geographic information data, obtaining the underlying surface type and the underlying surface type topological relationship diagram corresponding to the underlying surface type, is one of the key steps in the process of building a sponge city model. This process involves using the fused geographic information data to identify and distinguish different types of ground cover in the city, such as hard paved areas, green spaces, water areas, etc., through specific classification algorithms or rules. Specifically, remote sensing image interpretation technology can be combined with ground survey data to subdivide urban areas into several categories of underlying surface types according to different reflectivity, texture characteristics and other parameters. At the same time, in order to more accurately describe the spatial relationship between various underlying surfaces and their impact on the rainwater runoff path, it is necessary to further construct a topological relationship diagram of the underlying surface type. For example, in the aforementioned application scenario of coastal cities, we can use the classification tools on the GIS platform based on the fused geographic information data to conduct a detailed classification of the ground cover in the entire city and identify the main underlying surface types, such as concrete roads, park green spaces, residential lawns, etc. Then, by analyzing the spatial distribution characteristics of these different types of underlying surfaces, we draw a relationship diagram of their interconnection, that is, a topological relationship diagram of the underlying surface types. In this way, we can not only clearly show the geographical location and area size of each underlying surface type, but also intuitively reflect the possible water flow direction and path between different underlying surface types, providing important basic information for subsequent rainwater runoff path simulation and storage facility layout design.

[0072] Step S3, based on the underlying surface type topological relationship diagram, a rainwater runoff path simulation analysis is performed on the target sponge city to obtain a rainwater runoff path network; wherein the rainwater runoff path network is the relationship between water flow direction and flow rate between different underlying surface types.

[0073] Specifically, based on the topological relationship diagram of the underlying surface type, the target sponge city is simulated and analyzed to obtain the rainwater runoff path network, which is an important part of building the sponge city model. In this process, the established topological relationship diagram of the underlying surface type is first used as input data, which shows in detail the spatial distribution of various underlying surface types in the city and their connection relationships. Next, through professional hydrology and hydraulic model software, such as SWMM (Storm Water Management Model) or MIKE SHE, the data of these underlying surface types are combined with relevant parameters such as terrain elevation and soil permeability to simulate the flow direction and flow changes between various underlying surface types under different rainfall conditions. For example, in the coastal city case we mentioned earlier, by importing the topological relationship diagram containing detailed underlying surface type information into the SWMM software, different rainfall intensity and duration scenarios can be set to simulate how rainwater flows from hard pavement to natural water bodies such as green space, wetlands or rivers after rainfall occurs. On this basis, the water flow transfer path between each underlying surface unit is analyzed, the specific flow value is calculated, and finally a complete rainwater runoff path network is formed. This network not only reflects the direction of water flow between different underlying surface types, but also quantifies the flow size on each path, providing a scientific basis for the subsequent layout design of urban rainwater storage facilities. In this way, the flow pattern of rainwater in the city can be predicted more accurately, thus providing strong support for the construction and management of sponge cities.

[0074] Step S4, based on the underlying surface type and the rainwater runoff path network, design the layout of the urban rainwater storage facilities of the target sponge city to obtain a rainwater storage facility layout plan.

[0075] Specifically, based on the underlying surface type and the rainwater runoff path network, the layout of the urban rainwater storage facilities of the target sponge city is designed to obtain the layout plan of the rainwater storage facilities, which is a crucial step in the process of building a sponge city model. After completing the underlying surface classification and rainwater runoff path simulation, designers can use these results, combined with the actual needs and development plans of the city, and comprehensively consider the functional positioning, capacity configuration, location selection and other aspects of the rainwater storage facilities to formulate a scientific and reasonable layout plan. For example, in the application scenario of the aforementioned coastal city, the design team can identify key catchment areas and places prone to waterlogging based on the different underlying surface types that have been determined and the runoff paths between them. Subsequently, by analyzing the terrain characteristics, land use status and possible future development trends of these areas, appropriate locations are selected to lay out rainwater gardens, permeable pavements, underground water storage tanks and other storage facilities. At the same time, the synergy between facilities must also be considered to ensure that an effective rainwater collection, storage and reuse system is formed throughout the city. For example, near commercial blocks, large underground water storage devices can be set up to collect and store rainwater from large areas of hardened ground, while in residential areas, small rain gardens and green roofs can be scattered to beautify the environment and increase rainwater infiltration. In addition, for low-lying areas near rivers or lakes, wetland parks can be planned and built to purify water quality using natural ecological functions while providing leisure and entertainment space for the city. Through such a layout design, it can not only effectively reduce the pressure on the urban drainage system and prevent waterlogging disasters, but also promote the recycling of water resources and improve the ecological environment quality of the city. In short, the design scheme based on the underlying surface type and the rainwater runoff path network has laid a solid foundation for achieving the construction goal of sponge cities.

[0076] Step S5, through the preset BIM technology, a virtual sponge city model is constructed based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan.

[0077] Specifically, through the preset BIM technology, the construction of a virtual sponge city model based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan is a key step in realizing the intelligent management of sponge cities. At this stage, all the preliminary preparations, including the collection and fusion of geographic information data, the accurate classification of underlying surface types, the simulation analysis of rainwater runoff paths and the scientific layout of storage facilities, will be integrated into a highly complex three-dimensional digital model. Specifically, using the powerful functions of BIM technology, these diversified information can be converted into visual digital objects, each of which contains not only geometric shapes and spatial positions, but also rich attribute information, such as materials, performance parameters, etc. For example, in the case of the aforementioned coastal city, the design team can import the processed geographic information data into the BIM software to build a three-dimensional model of the entire city, and then assign corresponding material attributes to different types of ground covers according to the underlying surface type topological relationship diagram to ensure the authenticity and accuracy of the model. Then, combined with the data of the rainwater runoff path network, the flow process of rainwater under different rainfall conditions can be dynamically displayed in the model, helping designers to intuitively evaluate the effectiveness of the existing storage facility layout plan and make necessary adjustments accordingly. In addition, through BIM technology, the full life cycle management of rainwater storage facilities can be achieved. All aspects from design, construction to operation and maintenance can be simulated and optimized in the virtual model, thereby improving the overall efficiency and sustainability of the project. The virtual sponge city model constructed in this way not only provides a powerful decision-making support tool for urban planners and managers, but also creates conditions for the public to participate in urban construction and environmental protection, truly realizing the intelligent and green development of cities.

[0078] In a specific embodiment, the acquiring of geographic information data of the target sponge city and performing data fusion on the geographic information data to obtain fused geographic information data includes:

[0079] The topography of the target sponge city is collected by using a preset drone aerial photography technology to obtain an original geographic information image;

[0080] Preprocessing the original geographic information image to obtain a clean geographic information image;

[0081] Performing pixel-level segmentation on the clean geographic information image using a preset U-Net architecture to extract boundary information of different types of land features in the target sponge city from the clean geographic information image to obtain a land feature classification map;

[0082] Performing spatial interpolation processing on the land feature classification map to obtain an interpolated land feature classification map;

[0083] The interpolated feature classification map is subjected to data association and fusion to obtain fused geographic information data; wherein the fused geographic information data includes geographic coordinates, topography and landforms, and water system distribution.

[0084] Specifically, first, the topography and landforms of the target sponge city are collected by using the preset drone aerial photography technology, which can efficiently obtain large-scale, high-resolution original geographic information images. Drone aerial photography technology is widely used in the field of urban surveying and mapping due to its flexibility and cost-effectiveness, especially in complex terrain or difficult-to-reach areas, where drones can easily capture high-quality image data. For example, in the sponge city construction project in coastal cities, drones can complete aerial scanning of the entire urban area in a short time, including those areas that are difficult to cover by traditional ground measurement methods, such as both sides of the river and between dense buildings. These original geographic information images not only contain rich surface feature information, but also record the specific geographical location and timestamp when shooting, providing a basis for subsequent data processing. Secondly, the original geographic information image is preprocessed to obtain a clean geographic information image. The preprocessing steps usually include noise removal, correction of geometric distortion, color correction, etc., with the aim of improving image quality and enhancing the recognizability of ground features. In this process, a variety of image processing algorithms and techniques may be used, such as median filters for denoising and affine transformations for correcting image deformation. Taking coastal cities as an example, due to the influence of factors such as sea fog and air pollution in coastal areas, the quality of original aerial images is not high. This situation can be significantly improved through preprocessing, making the subsequent classification of objects more accurate. Again, the clean geographic information image is segmented at the pixel level using the preset U-Net architecture to extract the boundary information of different types of objects in the target sponge city in the clean geographic information image, and obtain the object classification map. U-Net is a deep learning model that is particularly suitable for medical image segmentation tasks and has also been widely used in the field of remote sensing image processing in recent years. By training the U-Net model, various types of objects in the clean geographic information image, such as buildings, roads, green spaces, waters, etc., can be automatically identified and marked, and their boundaries can be accurately depicted. In the case of coastal cities, using the U-Net model for object classification can help quickly and accurately identify which areas belong to hardened ground and which areas are green spaces or wetlands, which is crucial for the subsequent simulation of rainwater runoff paths. Then, the object classification map is spatially interpolated to obtain an interpolated object classification map. Spatial interpolation is a method of inferring the value of unknown data points based on known data points. It is very common in geographic information systems (GIS). Through spatial interpolation processing, the blank areas in the feature classification map can be filled to make the entire image more complete and continuous. For example, in the feature classification map of coastal cities, there may be some areas that are not correctly classified due to shadows or cloud cover. Spatial interpolation can effectively restore the feature types in these areas to ensure the integrity of the classification results. Finally, the interpolated feature classification map is data-associated and fused to obtain fused geographic information data.This process involves integrating the classification information of objects from different sources and scales into the same geographic coordinate system to form a unified data set. The fused geographic information data not only contains detailed classification information of objects, but also includes precise geographic coordinates, topographic features and water system distribution. For example, in the sponge city project in coastal cities, the fused geographic information data can clearly show which areas are low-lying areas prone to water accumulation and which areas are important water source protection areas, providing an important reference for the subsequent layout design of urban rainwater storage facilities. In summary, through the above series of steps to obtain and integrate the geographic information data of the target sponge city, it can not only provide accurate and detailed basic data for the planning and design of the sponge city, but also lay a solid foundation for subsequent advanced applications such as rainwater runoff path simulation and storage facility layout. The application of this method is conducive to improving the scientificity and rationality of sponge city construction and promoting the sustainable development of cities.

[0085] In a specific embodiment, the urban underlying surface classification is performed based on the fused geographic information data to identify the urban underlying surface type of the target sponge city, and the underlying surface type and the underlying surface type topological relationship diagram corresponding to the underlying surface type are obtained, including:

[0086] Performing feature extraction on the fused geographic information data to obtain an extracted feature vector; wherein the extracted feature vector includes a shape feature vector, a spectral feature vector, a texture feature vector and a humidity gradient vector;

[0087] Determine the vegetation state of the target sponge city based on the spectral feature vector and the texture feature vector;

[0088] Based on the humidity gradient vector, a humidity gradient analysis is performed on the target sponge city to obtain a humidity gradient image; wherein the humidity gradient image is a soil humidity variation trend in different directions and regions;

[0089] By using the geographic coordinates, the fused geographic information data is classified into underlying surface types based on the humidity gradient image and the vegetation status, so as to obtain underlying surface types and positions corresponding to the underlying surface types; wherein the underlying surface types include hard surface data, permeable pavement data, natural ground data, water body data and building land data;

[0090] Determine the shape corresponding to the underlying surface type based on the shape feature vector and the texture feature vector;

[0091] Using a preset logical reasoning algorithm, the topological relationship of the target sponge city is constructed based on the shape, underlying surface type and the position corresponding to the underlying surface type to obtain a topological relationship diagram of the underlying surface type.

[0092] Specifically, the urban underlying surface classification is performed based on the fused geographic information data to identify the urban underlying surface type of the target sponge city, and the underlying surface type and the underlying surface type topological relationship diagram corresponding to the underlying surface type are obtained, including feature extraction of the fused geographic information data to obtain extracted feature vectors; wherein the extracted feature vectors include shape feature vectors, spectral feature vectors, texture feature vectors and humidity gradient vectors. This process is achieved through advanced image processing technology and machine learning algorithms, aiming to extract key features that can effectively characterize different underlying surface types from fused geographic information data. For example, in sponge city construction projects in coastal cities, remote sensing images and drone aerial images can be used as data sources, and shape features, spectral features, texture features and humidity gradient features in these images can be extracted through computer vision technology. The shape feature vector describes the geometric form of the object, such as area, perimeter, aspect ratio, etc.; the spectral feature vector reflects the reflectivity characteristics of the object in different bands, which is an important basis for distinguishing different types of surface cover; the texture feature vector captures the texture information of the surface of the object, such as roughness and smoothness; the humidity gradient vector is used to describe the changing trend of soil moisture, which is of great significance for identifying wetlands, water bodies, etc. The vegetation status of the target sponge city is determined based on the spectral feature vector and the texture feature vector. The identification of vegetation status is an important link in the classification of urban underlying surfaces, because the presence or absence of vegetation and its health directly affect the hydrological characteristics of the city. By analyzing the spectral feature vector, vegetation can be distinguished from other types of objects, because vegetation has a higher reflectivity in the near-infrared band; and the texture feature vector helps to further refine the classification of vegetation types, such as distinguishing grasslands, woodlands, etc. For example, in coastal cities, the combination of spectral and texture features can accurately identify vegetation areas such as park green spaces and street tree canopies, and evaluate their growth conditions, which is crucial for formulating reasonable rainwater management measures. Based on the humidity gradient vector, a humidity gradient analysis is performed on the target sponge city to obtain a humidity gradient image; wherein the humidity gradient image is the soil moisture change trend in different directions and regions. Humidity gradient analysis can reveal the law of surface moisture distribution in the city, and plays an important role in identifying potential rainwater collection areas and leakage areas. In the application scenario of coastal cities, a humidity gradient image can be generated by analyzing the humidity gradient vector, showing the change trend of soil moisture in various areas of the city. For example, areas with high surface humidity such as wetlands and river banks will appear dark in the image, while dry hard surfaces will appear light. This information is very useful for planning the location and scale of rainwater storage facilities.Through the geographic coordinates, the fused geographic information data is classified into underlying surface types based on the humidity gradient image and the vegetation status, and the underlying surface type and the corresponding position of the underlying surface type are obtained; wherein the underlying surface type includes hard surface data, permeable pavement data, natural ground data, water body data and building land data. This classification process is completed on the GIS platform. The urban area is divided into different underlying surface types by using the extracted feature vectors and humidity gradient images, combined with vegetation status information, and supervised or unsupervised classification algorithms. For example, parks and green spaces can be classified as natural ground data, asphalt roads and cement floors can be classified as hard surface data, sidewalks paved with permeable bricks can be classified as permeable pavement data, lakes and rivers can be classified as water body data, and buildings such as houses and factories can be classified as building land data. Each type of classification result has precise geographic coordinates, which is convenient for subsequent spatial analysis and application. The shape corresponding to the underlying surface type is determined based on the shape feature vector and the texture feature vector. Shape features and texture features not only help to classify the type of land features, but also provide detailed information about the morphology of land features. For example, shape feature vectors can be used to identify buildings and roads of different shapes, while texture feature vectors can help distinguish different types of vegetation cover. In the case of coastal cities, the extraction of these features helps to build a more sophisticated urban underlying surface model and provide more accurate input data for the simulation of rainwater runoff paths. Using a preset logical reasoning algorithm, the topological relationship of the target sponge city is constructed based on the shape, underlying surface type and the corresponding position of the underlying surface type, and a topological relationship diagram of the underlying surface type is obtained. The topological relationship diagram describes the spatial connection and interaction between different underlying surface types, and is the basis for simulating rainwater runoff paths and designing the layout of storage facilities. The logical reasoning algorithm can automatically identify which areas are adjacent and which areas are connected based on the known underlying surface type and location information, thereby constructing a complete topological relationship network. For example, in coastal cities, the topological relationship diagram can show which green spaces are connected to rivers and which hard surfaces lead directly to drainage systems. This information is extremely important for predicting rainwater flow paths during heavy rains and formulating emergency measures. In summary, by extracting features, analyzing humidity gradients, classifying underlying surface types, and constructing topological relationships on fused geographic information data, scientific data support can be provided for the planning and construction of sponge cities. The application of this method not only improves the accuracy of urban hydrological analysis, but also provides new ideas and technical means for the effective management and utilization of urban rainwater, which helps promote the sustainable development of sponge cities.

[0093] In a specific embodiment, the rainwater runoff path simulation analysis is performed on the target sponge city based on the underlying surface type topological relationship diagram to obtain a rainwater runoff path network, including:

[0094] The terrain features are extracted by using a preset digital terrain analysis algorithm to obtain extracted terrain features; wherein the extracted terrain features include terrain slope, slope direction and drainage area terrain features;

[0095] Assigning resistance weights to underlying surface types in the underlying surface type topological relationship diagram to obtain a weighted topological relationship diagram;

[0096] Acquiring initial rainfall conditions and water boundary conditions, performing water flow simulation based on the extracted terrain features, the weighted topological relationship diagram, the initial rainfall conditions and the water boundary conditions, and obtaining initial water flow state data;

[0097] Tracking the motion trajectory of water flow particles in the initial water flow state data to obtain water flow particle path data;

[0098] Obtaining a runoff path set based on the water flow particle path data and the underlying surface type topological relationship diagram;

[0099] Using the network analysis algorithm, the rainwater runoff path network is obtained based on the runoff path set and initial water flow state data.

[0100] Specifically, the process of simulating and analyzing the rainwater runoff path of the target sponge city based on the underlying surface type topological relationship diagram to obtain the rainwater runoff path network is achieved through a series of complex calculation and analysis steps, aiming to deeply understand the hydrological response mechanism of the city when encountering rainfall events. First, it is necessary to extract the features of the topography and landforms through a preset digital terrain analysis algorithm to obtain the extracted terrain features, which include terrain slope, slope aspect and terrain features of the catchment area. The work at this stage is mainly to obtain basic terrain information that affects the direction and speed of water flow. For example, in coastal cities, using DEM (digital elevation model) data and terrain analysis tools in GIS software, the slope value and slope aspect angle of each grid cell can be calculated, and the depressions or river starting points that may form the catchment area can be identified. This information forms the basis for water flow simulation. Next, resistance weights are assigned to the underlying surface types in the underlying surface type topological relationship diagram to obtain a weighted topological relationship diagram. This is because different types of underlying surfaces have different degrees of influence on water flow. For example, hard surfaces such as concrete pavement have less resistance and faster water flow speed; while ground covered with vegetation will increase the resistance of water flow and slow down the water flow speed. By assigning a resistance weight value to each underlying surface type, the behavior of water flow in actual situations can be more realistically reflected. For example, in the simulation of coastal cities, hard surfaces may be assigned lower resistance weight values, while vegetation-covered areas will be assigned higher resistance weight values, so that the water flow path and speed can be predicted more accurately during the simulation process. Then, the initial rainfall conditions and water boundary conditions are obtained, and water flow simulation is performed based on the extracted terrain features, the weighted topological relationship diagram, the initial rainfall conditions and water boundary conditions to obtain the initial water flow state data. This means that a specific rainfall scenario needs to be set, such as short-term heavy rainfall or continuous light rain, as well as the way the water flows out of the study area, such as flowing into rivers or out of the urban drainage system. Under these conditions, combined with the terrain features and the weighted underlying surface type, a hydrological model (such as SWMM, MIKE SHE, etc.) is used to simulate the water flow, and the output result will be the state information such as the water flow depth and speed of each grid unit at a specific time point. For example, when simulating the impact of a sudden short-term heavy rainfall on coastal cities, it can be predicted which areas may quickly accumulate water and where the water flow speed will accelerate. Next, the movement trajectory of the water flow particles in the initial water flow state data is tracked to obtain the water flow particle path data. This means that during the simulation process, some representative water flow particles are selected and their position information changing over time is recorded to track the specific path of the water flow. This method helps to more intuitively show how water flows from one place to another, especially under complex terrain conditions, the diversity of water flow paths is particularly obvious. For example, in the case of coastal cities, it can be observed how water flows from highlands to low-lying areas, or how to bypass obstacles and continue to move forward.Finally, the runoff path set is obtained based on the water flow particle path data and the underlying surface type topological relationship diagram, and then the network analysis algorithm is used to obtain the rainwater runoff path network based on the runoff path set and the initial water flow state data. This process integrates all the information obtained previously to build a complete water flow path network model, which can not only show the main path of the water flow, but also reflect the distribution characteristics of the water flow in the network. For example, in coastal cities, by building such a network model, it is possible to clearly see how the water flow inside the city is gathered into the main river or drainage system, and whether there are risk points that may cause floods in this process. In summary, through a series of steps such as digital terrain analysis, underlying surface type weighting, water flow simulation, particle path tracing, and network analysis, the target sponge city can be effectively simulated and analyzed for the rainwater runoff path. The final rainwater runoff path network not only provides an important reference for the design and optimization of the urban drainage system, but also provides scientific data support for responding to extreme weather events. The application of this method is of great significance for improving the city's flood control and drainage capacity, protecting the lives and property of residents, and promoting the sustainable development of cities.

[0101] In a specific embodiment, the layout of urban rainwater storage facilities of the target sponge city is designed based on the underlying surface type and the rainwater runoff path network to obtain a layout plan of rainwater storage facilities, including:

[0102] Based on the underlying surface type and the rainwater runoff path network, the target sponge city is divided into a watershed area to obtain a watershed area unit set;

[0103] Calculating the rainwater storage demand for each catchment area unit to obtain the corresponding storage capacity demand;

[0104] Based on geospatial technology, the constructible area and suitability analysis of the target sponge city are carried out to obtain the suitable area for the construction of rainwater storage facilities;

[0105] Utilizing a preset flow peak analysis algorithm, extracting flow data in the rainwater runoff path network, and performing multi-scale analysis on the flow data to obtain multi-scale rainwater runoff information;

[0106] In the suitable area for the construction of rainwater storage facilities, the layout of rainwater storage facilities is carried out based on the multi-scale rainwater runoff information and the storage capacity demand, and a preliminary layout plan is obtained;

[0107] Based on the cost-benefit evaluation model, the preliminary layout plan was evaluated and adjusted to obtain the layout plan of rainwater storage facilities.

[0108] Specifically, the layout of the urban rainwater storage facilities of the target sponge city is designed based on the underlying surface type and the rainwater runoff path network to obtain a layout plan of the rainwater storage facilities, including dividing the catchment area of ​​the target sponge city based on the underlying surface type and the rainwater runoff path network to obtain a set of catchment area units. This process is to divide the city into multiple independent catchment area units by comprehensively considering the characteristics of topography, surface cover type and rainwater runoff path, and the rainwater runoff path and flow characteristics in each unit are similar. For example, in the sponge city construction project in coastal cities, the city can be divided into several catchment area units by using the terrain slope, slope information and the topological relationship diagram of the underlying surface type through the zoning tool in the GIS software. The division of these units is helpful for the subsequent calculation of storage demand and facility layout design to ensure that each area can be effectively managed. The rainwater storage demand is calculated for each catchment area unit to obtain the corresponding storage capacity demand. The storage demand calculation is to estimate the required storage capacity under different rainfall scenarios based on the area, surface type, rainfall intensity and other factors of each catchment unit. This process usually requires the use of hydrological models, such as SWMM (Storm Water Management Model), to input the geographic information and rainfall data of the catchment unit, simulate the runoff process under different rainfall intensities, and thus calculate the maximum runoff of each unit under different rainfall scenarios. For example, in a catchment unit in a coastal city, if the area is mainly composed of hard surfaces and the terrain is relatively flat, then when encountering short-term heavy rainfall, the runoff in the area will be very large, so a larger storage capacity is required to prevent waterlogging. Based on geospatial technology, the target sponge city is analyzed for constructible areas and suitability, and the suitable area for the construction of rainwater storage facilities is obtained. This analysis aims to identify areas in the city that are suitable for the construction of rainwater storage facilities, taking into account factors such as land use status, geological conditions, and transportation convenience. For example, in coastal cities, GIS software can be used to overlay multiple layers of data such as land use maps, geological maps, and transportation network maps to evaluate the construction suitability of each area. Low-lying areas prone to waterlogging, or public open spaces such as green spaces and parks are generally considered to be ideal places for building rainwater storage facilities. At the same time, it is also necessary to avoid building storage facilities in areas with unstable geological conditions or heavy traffic, so as not to affect the safety of the facilities and the efficiency of urban operations. Using a preset flow peak analysis algorithm, the flow data in the rainwater runoff path network is extracted, and the flow data is subjected to multi-scale analysis to obtain multi-scale rainwater runoff information. The flow peak analysis algorithm is used to identify the nodes and paths with the largest flow in the runoff path network. These nodes and paths are often the key areas for the layout of rainwater storage facilities. Multi-scale analysis examines flow changes at different time and spatial scales in order to more comprehensively understand the hydrological characteristics of the city.For example, in the case of coastal cities, the peak flow analysis algorithm can be used to find several key nodes with the largest flow in heavy rainfall events, and then storage facilities can be arranged around these nodes to effectively intercept and store rainwater. At the same time, multi-scale analysis can help identify areas of waterlogging that may occur during long-term rainfall, providing a basis for the long-term operation of storage facilities. In the suitable area for the construction of rainwater storage facilities, the layout of rainwater storage facilities is carried out based on the multi-scale rainwater runoff information and the storage capacity requirements to obtain a preliminary layout plan. The work at this stage is to determine the specific location and scale of the storage facilities based on the previous steps, taking into account the storage requirements, construction suitability and flow characteristics. For example, in a low-lying catchment area unit in a coastal city, if the multi-scale rainwater runoff information shows that the area is prone to waterlogging in both short-term heavy rainfall and long-term rainfall, and the land use status and geological conditions in the area are suitable for the construction of storage facilities, then a larger-scale storage pool or artificial wetland can be arranged in this area first. In addition, rain gardens and permeable pavements can be set up in the surrounding park green spaces to increase the infiltration and evaporation of rainwater and reduce the burden on the drainage system. Based on the cost-benefit evaluation model, the preliminary layout plan is evaluated and adjusted to obtain the layout plan of rainwater storage facilities. The cost-benefit evaluation model is used to compare the economy and effectiveness of different layout plans to ensure that the final plan can not only meet the storage needs but also has a high cost-effectiveness. For example, in projects in coastal cities, a cost-benefit evaluation model including construction cost, operation and maintenance cost, storage effect and other indicators can be established to comprehensively evaluate the preliminary layout plan. In the evaluation process, not only the construction cost and operation and maintenance cost of the storage facilities should be considered, but also the storage effect of the facilities under different rainfall scenarios and the impact on the surrounding environment should be evaluated. Through multiple iterations and optimizations, a layout plan for rainwater storage facilities that is both economical and efficient is finally determined. In summary, through a series of steps such as watershed division, storage demand calculation, construction suitability analysis, flow peak analysis, preliminary layout design and cost-benefit evaluation, the layout plan of rainwater storage facilities in the target sponge city can be scientifically and reasonably designed. The application of this method not only helps to improve the level of urban rainwater management, but also effectively alleviates the problem of urban waterlogging and promotes the sustainable development of cities.

[0109] In a specific embodiment, the watershed area of ​​the target sponge city is divided based on the underlying surface type and the rainwater runoff path network to obtain a watershed area unit set, including:

[0110] In the underlying surface type topological relationship diagram, performing a topological structure analysis on the hard surface data to obtain a topological relationship of the hard surface data;

[0111] Based on the topological relationship of the hard surface data and the water flow direction in the rainwater runoff path network, flow direction impact analysis is performed on the natural ground to obtain a natural ground water flow path;

[0112] Based on the natural surface water flow path and the water body data, a preliminary water catchment area is determined for the target sponge city to obtain a preliminary water catchment area;

[0113] Based on the preliminary catchment area, permeability analysis is performed on the different underlying surface types to obtain the underlying surface permeability coefficient distribution;

[0114] Calculating the water collection capacity of the underlying surface permeability distribution and the flow data to obtain a water collection capacity assessment result;

[0115] Based on the results of water catchment capacity assessment, the preliminary water catchment area is divided to obtain a set of water catchment area units.

[0116] Specifically, the process of dividing the catchment area of ​​the target sponge city based on the underlying surface type and the rainwater runoff path network to obtain a collection of catchment area units is a multi-step, systematic analysis method, which aims to scientifically and rationally divide the urban catchment area by comprehensively considering the topography, surface cover type and rainwater runoff path, and provide a basis for the subsequent layout of rainwater storage facilities. This process includes the following key steps: First, in the underlying surface type topological relationship diagram, the hard surface data is topologically analyzed to obtain the hard surface data topological relationship. This analysis is to understand the spatial distribution of hard surfaces (such as roads, squares, buildings, etc.) in the city and their interconnection methods. Hard surfaces are usually the main source of rainwater runoff, so their topological structure has an important impact on the rainwater runoff path. For example, in the case of coastal cities, the network analysis tool in the GIS software can be used to identify the connection relationship between all hard surfaces and generate a hard surface data topological relationship diagram. This diagram not only shows the distribution of hard surfaces, but also reveals the path of rainwater flowing from one hard surface to another. Next, the flow direction impact analysis of the natural ground is performed based on the topological relationship of the hard surface data and the water flow direction in the rainwater runoff path network to obtain the natural ground water flow path. This analysis is to determine the path of rainwater entering the natural ground (such as green space, wetland, etc.) after flowing through the hard surface. By combining the topological relationship of the hard surface data and the water flow direction information in the rainwater runoff path network, the flow process of rainwater in the city can be simulated, especially how rainwater is transferred from the hard surface to the natural ground. For example, in a certain area of ​​a coastal city, if the data topological relationship of the hard surface shows that rainwater mainly flows to the green space on the west side, it can be determined that the water flow path of the natural ground is from east to west. Then, based on the natural ground water flow path and the water body data, the water catchment area of ​​the target sponge city is initially judged to obtain a preliminary water catchment area. This preliminary judgment is to identify areas in the city where rainwater may gather, which are usually the intersection of natural ground and water bodies. By analyzing the natural ground water flow path and water body data, a preliminary water catchment area can be delineated. For example, in a low-lying area in a coastal city, if the natural surface water flow path shows that rainwater eventually flows into a nearby river or lake, then this low-lying area can be designated as a preliminary catchment area. Next, based on the preliminary catchment area, a permeability analysis is performed on the different underlying surface types to obtain the underlying surface permeability coefficient distribution. Permeability analysis is to evaluate the ability of different underlying surface types to penetrate rainwater, which is crucial to determining the actual catchment capacity of the catchment area. A permeability coefficient can be assigned to each underlying surface type by consulting data such as soil type and vegetation coverage, combined with laboratory test results. For example, in the preliminary catchment area of ​​a coastal city, the permeability coefficient of green space may be higher, while the permeability coefficient of hard surfaces may be lower. This information will be used for subsequent catchment capacity calculations.Subsequently, the water collection capacity is calculated for the underlying surface permeability distribution and the flow data to obtain a water collection capacity assessment result. The water collection capacity calculation is to evaluate the actual water collection volume of each preliminary water collection area under different rainfall conditions. By combining the underlying surface permeability distribution and the flow data in the rainwater runoff path network, the water collection volume of each water collection area under different rainfall intensities can be calculated. For example, in a preliminary water collection area in a coastal city, if the flow data shows that under short-term heavy rainfall conditions, the flow in the area is large and the permeability is low, then the water collection capacity of the area may be weak and more storage facilities are needed to supplement it. Finally, the preliminary water collection area is divided based on the water collection capacity assessment results to obtain a water collection area unit set. This division is to further subdivide the preliminary water collection area into smaller management units, and the water collection capacity and storage requirements in each unit are similar. By comprehensively considering the water collection capacity assessment results and the actual topographic and geomorphic characteristics, the preliminary water collection area can be divided into multiple water collection area units. For example, in a preliminary catchment area of ​​a coastal city, it can be divided into several catchment units, and the catchment capacity and storage requirements in each unit are similar, which is convenient for the subsequent layout design of storage facilities. In summary, through the topological structure analysis of hard surface data, the impact analysis of natural ground flow direction, the delineation of preliminary catchment areas, the permeability analysis of underlying surfaces, the calculation of catchment capacity and the final division of catchment units, the catchment area of ​​the target sponge city can be scientifically and reasonably divided. The application of this method not only helps to gain a deeper understanding of the characteristics of urban rainwater runoff, but also provides a scientific basis for the rational layout of rainwater storage facilities, thereby improving the level of urban rainwater management, reducing the risk of waterlogging, and promoting the sustainable development of cities.

[0117] In a specific embodiment, a virtual sponge city model is constructed based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan through the preset BIM technology, including:

[0118] Using the BIM technology, the fused geographic information data is subjected to three-dimensional terrain reconstruction to obtain a three-dimensional terrain model;

[0119] Based on the underlying surface type topological relationship diagram, the underlying surface position of the three-dimensional terrain model is mapped to obtain a surface feature model;

[0120] Performing rainwater runoff path simulation on the surface feature model based on the rainwater runoff path network to generate a hydrological dynamics model;

[0121] Based on the layout plan of rainwater storage facilities, the hydrological dynamics model is designed in three dimensions to obtain a sponge facility integration model;

[0122] The sponge facility integrated model is rendered and visualized to obtain a virtual sponge city model.

[0123] Specifically, the process of constructing a virtual sponge city model based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the layout plan of the rainwater storage facilities through the preset BIM technology is a systematic and multi-step modeling method. This method aims to integrate various geographic information and hydrological characteristics of the city into a highly realistic three-dimensional digital model, providing a powerful tool for the planning, design and management of sponge cities. The following is a detailed explanation of this process: First, the fused geographic information data is reconstructed into a three-dimensional terrain model using the BIM technology. This step is the basis for building a virtual sponge city model, and it is necessary to convert the terrain information in the fused geographic information data into a three-dimensional form. For example, in the sponge city project of a coastal city, DEM (digital elevation model) data can be imported through BIM software, and these data can be used to generate a three-dimensional terrain model of the city. The three-dimensional terrain model not only contains the city's altitude information, but also can truly reflect the ups and downs of the terrain, providing an accurate spatial framework for subsequent modeling work. Through this model, the natural landform features such as hills, plains, and rivers in the city can be intuitively seen, laying a solid foundation for the subsequent underlying surface position mapping and rainwater runoff path simulation. Next, the underlying surface position mapping of the three-dimensional terrain model is performed based on the underlying surface type topological relationship diagram to obtain a surface feature model. This mapping process is to accurately place different types of underlying surfaces (such as hard surfaces, permeable pavement, natural ground, water bodies, etc.) to the corresponding positions in the three-dimensional terrain model. For example, in the three-dimensional terrain model of a coastal city, the underlying surface type topological relationship diagram can be used to map the hard surface data to the location of urban roads and buildings, the natural ground data to the location of parks and green spaces, and the water body data to the location of rivers and lakes. Through this process, the three-dimensional terrain model becomes richer and more detailed, forming a three-dimensional model containing various surface features, which provides accurate basic data for the subsequent rainwater runoff path simulation. Then, the surface feature model is simulated for rainwater runoff path based on the rainwater runoff path network to generate a hydrodynamic model. This simulation process is to dynamically display the flow path and flow changes of rainwater under different rainfall conditions in the surface characteristic model. For example, in the surface characteristic model of coastal cities, the data of the rainwater runoff path network can be used to simulate the process of rainwater flowing from hard surfaces to green spaces, wetlands or rivers. By setting different rainfall intensities and durations, the flow path, accumulation areas and flow changes of rainwater in the city can be observed, thereby generating a detailed hydrological dynamic model. This model not only shows the flow path of rainwater, but also reflects the impact of different underlying surface types on water flow, providing a scientific basis for the layout of regulation and storage facilities. Subsequently, the hydrological dynamic model is designed in three dimensions based on the layout plan of rainwater regulation and storage facilities to obtain a sponge facility integration model.This design process is to specifically arrange the location and scale of rainwater storage facilities in the hydrodynamic model to ensure that these facilities can play an effective role in rainfall events. For example, in the hydrodynamic model of coastal cities, large underground water storage tanks can be arranged in low-lying areas, rainwater gardens and permeable pavements can be set up in parks and green spaces, and green roofs can be installed on building roofs, etc. Through three-dimensional layout design, the specific location and form of these facilities in the city can be intuitively displayed, helping designers and managers to better understand and optimize the design plan. In addition, this model can also be used to evaluate the effects of different layout plans and select the optimal layout plan for storage facilities. Finally, the sponge facility integrated model is rendered and visualized to obtain a virtual sponge city model. Rendering visualization is to convert the sponge facility integrated model into high-quality images or animations to make it more intuitive and easy to understand. For example, in projects in coastal cities, the sponge facility integrated model can be converted into realistic images or animations through the rendering function of BIM software to show the flow process of rainwater under different rainfall conditions and the working status of storage facilities. These visualization results not only help designers and managers to evaluate and optimize the scheme, but also can be used to show the construction results of sponge cities to the public and improve the public's understanding and support for the concept of sponge cities. Through rendering visualization, the advantages of sponge cities in rainwater management can be more intuitively demonstrated to promote the sustainable development of cities. In summary, by using BIM technology to perform three-dimensional terrain reconstruction, underlying surface location mapping, rainwater runoff path simulation, three-dimensional layout design and rendering visualization on fused geographic information data, a highly realistic virtual sponge city model can be constructed. This model can not only fully display the city's topography, surface cover type and rainwater runoff path, but also intuitively display the layout and working status of rainwater storage facilities, providing strong technical support for the planning, design and management of sponge cities. Through the application of this method, the level of urban rainwater management can be improved, the risk of waterlogging can be reduced, and the sustainable development of cities can be promoted.

[0124] The above describes the construction method of the sponge city model based on BIM technology in the embodiment of the present invention. The following describes the construction system of the sponge city model based on BIM technology in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a system for constructing a sponge city model based on BIM technology includes:

[0125] The acquisition module 21 is used to acquire geographic information data of the target sponge city and perform data fusion on the geographic information data to obtain fused geographic information data;

[0126] A classification module 22, for classifying the urban underlying surface based on the fused geographic information data, and obtaining underlying surface types and underlying surface type topological relationship diagrams corresponding to the underlying surface types;

[0127] A simulation module 23 is used to simulate and analyze the rainwater runoff path of the target sponge city based on the underlying surface type topological relationship diagram to obtain a rainwater runoff path network; wherein the rainwater runoff path network is the relationship between the water flow direction and flow rate between different underlying surface types;

[0128] A design module 24 is used to design the layout of urban rainwater storage facilities of the target sponge city based on the underlying surface type and the rainwater runoff path network, and obtain a layout plan of rainwater storage facilities;

[0129] The construction module 25 is used to construct a virtual sponge city model based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan through the preset BIM technology.

[0130] In this embodiment, for the specific implementation of each unit in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0131] Reference Figure 3 The present invention also provides a computer device in an embodiment, wherein the internal structure of the computer device can be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0132] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0133] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented. It can be understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0134] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM.

[0135] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0136] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for constructing a sponge city model based on BIM technology, characterized in that: The following steps are involved: Acquire geographic information data of the target sponge city, and perform data fusion on the geographic information data to obtain fused geographic information data; Based on the fused geographic information data, urban underlying surfaces are classified to obtain underlying surface types and underlying surface type topological relationship diagrams corresponding to the underlying surface types; Based on the topological relationship diagram of the underlying surface types, a rainwater runoff path simulation analysis is performed on the target sponge city to obtain a rainwater runoff path network; wherein the rainwater runoff path network is the relationship between the water flow direction and flow rate between different underlying surface types; Based on the underlying surface type and the rainwater runoff path network, design the layout of urban rainwater storage facilities in the target sponge city to obtain a layout plan of rainwater storage facilities; By using the preset BIM technology, a virtual sponge city model is constructed based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the layout plan of the rainwater storage facilities; The step of acquiring geographic information data of the target sponge city and fusing the geographic information data to obtain fused geographic information data includes: The topography of the target sponge city is collected by using a preset drone aerial photography technology to obtain an original geographic information image; Preprocessing the original geographic information image to obtain a clean geographic information image; Performing pixel-level segmentation on the clean geographic information image using a preset U-Net architecture to extract boundary information of different types of land features in the target sponge city from the clean geographic information image to obtain a land feature classification map; Performing spatial interpolation processing on the land feature classification map to obtain an interpolated land feature classification map; Performing data association and fusion on the interpolated feature classification map to obtain fused geographic information data; wherein the fused geographic information data includes geographic coordinates, topography and landforms, and water system distribution; The urban underlying surface classification is performed based on the fused geographic information data to identify the urban underlying surface type of the target sponge city, and the underlying surface type and the underlying surface type topological relationship diagram corresponding to the underlying surface type are obtained, including: Performing feature extraction on the fused geographic information data to obtain an extracted feature vector; wherein the extracted feature vector includes a shape feature vector, a spectral feature vector, a texture feature vector and a humidity gradient vector; Determine the vegetation state of the target sponge city based on the spectral feature vector and the texture feature vector; Based on the humidity gradient vector, a humidity gradient analysis is performed on the target sponge city to obtain a humidity gradient image; wherein the humidity gradient image is a soil humidity variation trend in different directions and regions; By using the geographic coordinates, the fused geographic information data is classified into underlying surface types based on the humidity gradient image and the vegetation status, so as to obtain underlying surface types and positions corresponding to the underlying surface types; wherein the underlying surface types include hard surface data, permeable pavement data, natural ground data, water body data and building land data; Determine the shape corresponding to the underlying surface type based on the shape feature vector and the texture feature vector; Using a preset logical reasoning algorithm, a topological relationship of the target sponge city is constructed based on the shape, underlying surface type and the position corresponding to the underlying surface type, to obtain a topological relationship diagram of the underlying surface type; The rainwater runoff path simulation analysis is performed on the target sponge city based on the underlying surface type topological relationship diagram to obtain a rainwater runoff path network, including: The terrain features are extracted by using a preset digital terrain analysis algorithm to obtain extracted terrain features; wherein the extracted terrain features include terrain slope, slope direction and drainage area terrain features; Assigning resistance weights to underlying surface types in the underlying surface type topological relationship diagram to obtain a weighted topological relationship diagram; Acquiring initial rainfall conditions and water boundary conditions, performing water flow simulation based on the extracted terrain features, the weighted topological relationship diagram, the initial rainfall conditions and the water boundary conditions, and obtaining initial water flow state data; Tracking the motion trajectory of water flow particles in the initial water flow state data to obtain water flow particle path data; Obtaining a runoff path set based on the water flow particle path data and the underlying surface type topological relationship diagram; Using the network analysis algorithm, the rainwater runoff path network is obtained based on the runoff path set and initial water flow state data.

2. The method for constructing a sponge city model based on BIM technology according to claim 1 is characterized in that: The method of designing the urban rainwater storage facility layout of the target sponge city based on the underlying surface type and the rainwater runoff path network to obtain a rainwater storage facility layout plan includes: Based on the underlying surface type and the rainwater runoff path network, the target sponge city is divided into a watershed area to obtain a watershed area unit set; Calculating the rainwater storage demand for each catchment area unit to obtain the corresponding storage capacity demand; Based on geospatial technology, the constructible area and suitability analysis of the target sponge city are carried out to obtain the suitable area for the construction of rainwater storage facilities; Utilizing a preset flow peak analysis algorithm, extracting flow data in the rainwater runoff path network, and performing multi-scale analysis on the flow data to obtain multi-scale rainwater runoff information; In the suitable area for the construction of rainwater storage facilities, the layout of rainwater storage facilities is carried out based on the multi-scale rainwater runoff information and the storage capacity demand, and a preliminary layout plan is obtained; Based on the cost-benefit evaluation model, the preliminary layout plan was evaluated and adjusted to obtain the layout plan of rainwater storage facilities.

3. The method for constructing a sponge city model based on BIM technology according to claim 2 is characterized in that: The watershed area of ​​the target sponge city is divided based on the underlying surface type and the rainwater runoff path network to obtain a watershed area unit set, including: In the underlying surface type topological relationship diagram, performing a topological structure analysis on the hard surface data to obtain a topological relationship of the hard surface data; Based on the topological relationship of the hard surface data and the water flow direction in the rainwater runoff path network, flow direction impact analysis is performed on the natural ground to obtain a natural ground water flow path; Based on the natural surface water flow path and the water body data, a preliminary water catchment area is determined for the target sponge city to obtain a preliminary water catchment area; Based on the preliminary catchment area, permeability analysis is performed on the different underlying surface types to obtain the underlying surface permeability coefficient distribution; Calculating the water collection capacity of the underlying surface permeability distribution and the flow data to obtain a water collection capacity assessment result; Based on the results of water catchment capacity assessment, the preliminary water catchment area is divided to obtain a set of water catchment area units.

4. The method for constructing a sponge city model based on BIM technology according to claim 1 is characterized in that: Through the preset BIM technology, a virtual sponge city model is constructed based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan, including: Using the BIM technology, the fused geographic information data is subjected to three-dimensional terrain reconstruction to obtain a three-dimensional terrain model; Based on the underlying surface type topological relationship diagram, the underlying surface position of the three-dimensional terrain model is mapped to obtain a surface feature model; Performing rainwater runoff path simulation on the surface feature model based on the rainwater runoff path network to generate a hydrological dynamics model; Based on the layout plan of rainwater storage facilities, the hydrological dynamics model is designed in three dimensions to obtain a sponge facility integration model; The sponge facility integrated model is rendered and visualized to obtain a virtual sponge city model.

5. A construction system of a sponge city model based on BIM technology, characterized in that: A method for constructing a sponge city model based on BIM technology according to any one of claims 1 to 4, comprising: An acquisition module is used to acquire geographic information data of a target sponge city and perform data fusion on the geographic information data to obtain fused geographic information data; A classification module, used for classifying the urban underlying surface based on the fused geographic information data, and obtaining underlying surface types and underlying surface type topological relationship diagrams corresponding to the underlying surface types; A simulation module, used to simulate and analyze the rainwater runoff path of the target sponge city based on the underlying surface type topological relationship diagram to obtain a rainwater runoff path network; wherein the rainwater runoff path network is the relationship between the water flow direction and flow rate between different underlying surface types; A design module is used to design the layout of urban rainwater storage facilities of the target sponge city based on the underlying surface type and the rainwater runoff path network, and obtain a layout plan of rainwater storage facilities; A construction module, used to construct a virtual sponge city model based on the fused geographic information data, the underlying surface type topological relationship diagram, the rainwater runoff path network and the rainwater storage facility layout plan through a preset BIM technology; The step of acquiring geographic information data of the target sponge city and fusing the geographic information data to obtain fused geographic information data includes: The topography of the target sponge city is collected by using a preset drone aerial photography technology to obtain an original geographic information image; Preprocessing the original geographic information image to obtain a clean geographic information image; Performing pixel-level segmentation on the clean geographic information image using a preset U-Net architecture to extract boundary information of different types of land features in the target sponge city from the clean geographic information image to obtain a land feature classification map; Performing spatial interpolation processing on the land feature classification map to obtain an interpolated land feature classification map; Performing data association and fusion on the interpolated feature classification map to obtain fused geographic information data; wherein the fused geographic information data includes geographic coordinates, topography and landforms, and water system distribution; The urban underlying surface classification is performed based on the fused geographic information data to identify the urban underlying surface type of the target sponge city, and the underlying surface type and the underlying surface type topological relationship diagram corresponding to the underlying surface type are obtained, including: Performing feature extraction on the fused geographic information data to obtain an extracted feature vector; wherein the extracted feature vector includes a shape feature vector, a spectral feature vector, a texture feature vector and a humidity gradient vector; Determine the vegetation state of the target sponge city based on the spectral feature vector and the texture feature vector; Based on the humidity gradient vector, a humidity gradient analysis is performed on the target sponge city to obtain a humidity gradient image; wherein the humidity gradient image is a soil humidity variation trend in different directions and regions; By using the geographic coordinates, the fused geographic information data is classified into underlying surface types based on the humidity gradient image and the vegetation status, so as to obtain underlying surface types and positions corresponding to the underlying surface types; wherein the underlying surface types include hard surface data, permeable pavement data, natural ground data, water body data and building land data; Determine the shape corresponding to the underlying surface type based on the shape feature vector and the texture feature vector; Using a preset logical reasoning algorithm, a topological relationship of the target sponge city is constructed based on the shape, underlying surface type and the position corresponding to the underlying surface type, to obtain a topological relationship diagram of the underlying surface type; The rainwater runoff path simulation analysis is performed on the target sponge city based on the underlying surface type topological relationship diagram to obtain a rainwater runoff path network, including: The terrain features are extracted by using a preset digital terrain analysis algorithm to obtain extracted terrain features; wherein the extracted terrain features include terrain slope, slope direction and drainage area terrain features; Assigning resistance weights to underlying surface types in the underlying surface type topological relationship diagram to obtain a weighted topological relationship diagram; Acquiring initial rainfall conditions and water boundary conditions, performing water flow simulation based on the extracted terrain features, the weighted topological relationship diagram, the initial rainfall conditions and the water boundary conditions, and obtaining initial water flow state data; Tracking the motion trajectory of water flow particles in the initial water flow state data to obtain water flow particle path data; Obtaining a runoff path set based on the water flow particle path data and the underlying surface type topological relationship diagram; Using the network analysis algorithm, the rainwater runoff path network is obtained based on the runoff path set and initial water flow state data.

6. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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