Method and system for generating planning scheme of old village transformation and storage medium

Abstract

The embodiment of the invention provides an old village transformation planning scheme generation method and system and a storage medium. The method comprises the steps of obtaining multi-source data of a to-be-transformed old village; constructing a pre-transformation GIS model of the old village to be transformed according to the multi-source data, so that the pre-transformation GIS model visually displays the multi-source data on a map; analyzing the multi-source data based on the GIS model before transformation to obtain a target transformation area of the old village to be transformed; generating a first multi-dimensional transformation scheme of the target transformation area according to the transformation demand; after superposing the first multi-dimensional reconstruction scheme to a live-action map corresponding to the target reconstruction area, simulating the first multi-dimensional reconstruction scheme to obtain a simulation result; and correcting the first multi-dimensional reconstruction scheme according to the simulation result to obtain a second multi-dimensional reconstruction scheme. A transformation scheme is automatically generated according to the multi-source data, and the planning efficiency is high; by simulating and correcting the modification scheme, the accuracy and completeness of the modification scheme are ensured.

Description

Technical Field

[0001] The present invention relates to, but is not limited to, the field of data processing technologies, and in particular, to a method, a system, and a storage medium for generating a planning scheme for the transformation of old villages. Background Art

[0002] The transformation of old villages is a comprehensive deployment for studying the future development of rural areas, the rational layout of rural areas, and the arrangement of various rural construction projects. It is a blueprint for rural development within a certain period, an important part of rural management, and the basis for rural construction and management.

[0003] The existing planning schemes for the transformation of old villages are obtained through manual analysis, with low planning efficiency. In view of the complex data and the single and complex working process, it is easy to lead to imperfect planning. Summary of the Invention

[0004] The following is an overview of the subject matter described in detail in this document. This overview is not intended to limit the scope of protection of the claims.

[0005] The main purpose of the embodiments of the present invention is to propose a method, a system, and a storage medium for generating a planning scheme for the transformation of old villages, which can improve the planning efficiency and perfection of the old village planning scheme.

[0006] In a first aspect, the embodiments of the present invention provide a method for generating a planning scheme for the transformation of old villages, including: Obtaining multi-source data of the old village to be transformed, where the multi-source data includes building distribution data, road network data, vegetation water system data, infrastructure data, and historical and cultural data; Constructing a pre-transformation GIS model of the old village to be transformed according to the multi-source data, so that the multi-source data can be visually displayed on the map by the pre-transformation GIS model; Analyzing the multi-source data based on the pre-transformation GIS model to obtain the target transformation area of the old village to be transformed; Generating a first multi-dimensional transformation scheme for the target transformation area according to the transformation requirements; After superimposing the first multi-dimensional transformation scheme on the real-scene map corresponding to the target transformation area, simulating the first multi-dimensional transformation scheme to obtain a simulation result; Correcting the first multi-dimensional transformation scheme according to the simulation result to obtain a second multi-dimensional transformation scheme, and transporting the second multi-dimensional transformation scheme to the operation and maintenance GIS platform.

[0007] In some optional embodiments, the constructing a pre-transformation GIS model of the old village to be transformed according to the multi-source data includes: Obtaining the terrain data of the old village to be transformed; Construct a terrain model of the old village to be renovated according to the terrain data; Generate a building model on the terrain model according to the building distribution data, and display the building location, building shape, building facilities, and building aging degree through the building model; Generate a road model on the terrain model according to the road network data, and display the road grade, road alignment, road traffic capacity, and road signs through the road network; Generate a vegetation and water system model on the terrain model according to the vegetation and water system data, and display the vegetation type, vegetation shape, vegetation coverage area, and water system through the vegetation and water system model; Generate an infrastructure model on the terrain model according to the infrastructure data, and display the infrastructure type, infrastructure location, and infrastructure aging degree through the infrastructure model; After labeling the corresponding historical and cultural information on the building model, the road model, the vegetation and water system model, and the infrastructure model according to the historical and cultural data, obtain the pre-renovation GIS model of the old village to be renovated.

[0008] In some alternative embodiments, before generating a building model on the terrain model according to the building distribution data, it further includes: Remove noise data, duplicate data, and outliers from the multi-source data through a spatial data quality control algorithm to obtain first intermediate data; Perform spatial matching on the first intermediate data through a feature matching algorithm to make the first intermediate data have spatial coordinates and obtain second intermediate data; Construct a data prediction model based on historical data, where the historical data represents the second intermediate data in each period; Predict and supplement the missing data in the second intermediate data through the data prediction model to obtain third intermediate data. The building distribution data for generating the building model, the road network data for generating the road model, the vegetation and water system data for generating the vegetation and water system model, and the historical and cultural data for labeling the historical and cultural information all belong to the third intermediate data.

[0009] In some alternative embodiments, analyzing the multi-source data based on the pre-renovation GIS model to obtain the target renovation area of the old village to be renovated includes: Determine the fire protection coefficient and traffic coefficient of each area according to the road network data and the building distribution data corresponding to each area on the pre-renovation GIS model. The fire protection coefficient represents the fire protection ability of each area, and the traffic coefficient represents the traffic capacity of each area; Generate a geological disaster risk distribution map based on the geological feature data corresponding to each region on the GIS model before transformation, and determine the geological disaster risk coefficients of each region on the GIS model before transformation based on the geological disaster risk distribution map; Determine the building quality coefficients of each region according to the building distribution data corresponding to each region on the GIS model before transformation; Determine the infrastructure improvement coefficients of each region according to the infrastructure data corresponding to each region on the GIS model before transformation; Determine the greening coefficients of each region according to the vegetation and water system data corresponding to each region on the GIS model before transformation; Determine the historical and cultural value coefficients of each region according to the historical and cultural data corresponding to each region on the GIS model before transformation; Determine the transformation coefficients of each region on the GIS model before transformation according to the fire protection coefficients, traffic coefficients, geological disaster risk coefficients, building quality coefficients, infrastructure improvement coefficients, greening coefficients, and historical and cultural value coefficients of each region on the GIS model before transformation; Configure the regions with the transformation coefficients greater than or equal to the preset coefficient as the target transformation regions.

[0010] In some alternative embodiments, after configuring the regions with the transformation coefficients greater than or equal to the preset coefficient as the target transformation regions, it further includes: Determine the first priority ranking of each target sub-region according to the transformation coefficients corresponding to each target sub-region in the target transformation region; After evaluating the transformation benefits of each target sub-region through a preset economic benefit model, obtain the benefit index of each target sub-region; Modify the first priority ranking according to the benefit index to obtain the second priority ranking; Determine the influence coefficients between each target sub-region through the analytic network process; Modify the second priority ranking according to the influence coefficients to obtain the third priority ranking, so that each target sub-region is transformed in sequence according to the third priority ranking.

[0011] In some alternative embodiments, the generating the first multi-dimensional transformation plan for the target transformation region according to the transformation requirements includes: Determine the first requirement level of each requirement index in the transformation requirements according to the preset requirement degree and regional transformation objectives; Modify the first requirement level according to the public demand data to obtain the second requirement level, and the public demand data is collected through a public demand collection system; Compare the index difference spectrum of the requirement index and the target index in sequence according to the first requirement level, where the target index represents the index corresponding to the requirement index in the target renovation area; Generate the first multi-dimensional renovation plan of the optimal building layout, optimal road network, optimal greening layout, optimal infrastructure and optimal historical and cultural protection measures according to the index difference spectrum;

[0012] In some alternative embodiments, the generating the first multi-dimensional renovation plan of the optimal building layout, optimal road network, optimal greening layout, optimal infrastructure and optimal historical and cultural protection measures according to the index difference spectrum includes: Determine the building renovation target according to the building index difference in the index difference spectrum; Determine the optimal building layout of the target renovation area according to the building renovation target and the building differential renovation strategy, where the building differential renovation strategy represents the retention, repair, demolition or new construction strategy formulated according to the building quality and the renovation requirements; Determine the road renovation target according to the road index difference in the index difference spectrum; Calculate the optimal road network according to the road renovation target, the shortest path algorithm and the minimum spanning tree algorithm; Determine the greening renovation target according to the greening index difference in the index difference spectrum; Calculate the optimal greening layout according to the greening renovation target and the greening layout algorithm; Determine the infrastructure renovation target according to the infrastructure index difference in the index difference spectrum; Calculate the optimal infrastructure according to the infrastructure renovation target, the pipe network system planning algorithm and the sponge city planning algorithm; Determine the historical and cultural renovation target according to the historical and cultural index difference in the index difference spectrum; Determine the optimal historical and cultural protection measures according to the historical and cultural renovation target and the differential buildings;

[0013] In some alternative embodiments, after superimposing the first multi-dimensional renovation plan on the real scene map corresponding to the target renovation area, simulating the first multi-dimensional renovation plan to obtain a simulation result includes: Superimpose the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure and the optimal historical and cultural protection measures of the first multi-dimensional renovation plan on the real scene map one by one, so that the real scene map is accurately matched with the first multi-dimensional renovation plan; The pre - transformation GIS model is reconstructed according to the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, the optimal historical and cultural protection measures, and the third - priority ranking in sequence to obtain the post - transformation GIS model; After performing spatial performance simulation, environmental performance simulation, traffic performance simulation, economic performance evaluation, and historical and cultural value evaluation on the post - transformation GIS model, a simulation evaluation report and a transformation score are obtained. The simulation results include the simulation evaluation report and the transformation score.

[0014] In a second aspect, an embodiment of the present invention provides a controller, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method for generating a renovation plan for an old village as described in the first aspect is implemented.

[0015] In a third aspect, an embodiment of the present invention provides a system for generating a renovation plan for an old village, including the controller involved in the second aspect above.

[0016] In a fourth aspect, a computer storage medium stores computer - executable instructions for executing the method for generating a renovation plan for an old village as described in the first aspect.

[0017] The beneficial effects of the present invention include: obtaining multi - source data of the old village to be renovated, where the multi - source data includes building distribution data, road network data, vegetation and water system data, infrastructure data, and historical and cultural data; constructing a pre - transformation GIS model of the old village to be renovated so that the multi - source data can be visually displayed on the map by the pre - transformation GIS model; analyzing the multi - source data based on the pre - transformation GIS model to obtain the target renovation area of the old village to be renovated; generating a first multi - dimensional renovation plan for the target renovation area according to the renovation requirements; after superimposing the first multi - dimensional renovation plan on the real - scene map corresponding to the target renovation area, simulating the first multi - dimensional renovation plan to obtain simulation results; correcting the first multi - dimensional renovation plan according to the simulation results to obtain a second multi - dimensional renovation plan, and transmitting the second multi - dimensional renovation plan to the operation and maintenance GIS platform. Automatically generating a pre - transformation GIS model according to the multi - source data of the old village to be renovated, and obtaining a specific target renovation area after corresponding data analysis, so as to generate a corresponding first multi - dimensional renovation plan according to specific renovation requirements, with high planning efficiency of the renovation plan; by superimposing the first multi - dimensional renovation plan on the real - scene map for simulation, the first multi - dimensional plan is corrected, ensuring the accuracy and perfection of the renovation plan.

[0018] Other features and advantages of the present invention will be set forth in the following description, and in part will be obvious from the description, or may be learned by practice of the present invention. The objectives and other advantages of the present invention can be realized and attained by the structure particularly pointed out in the specification, claims as well as the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flowchart showing the steps of a method for generating a planning scheme for the transformation of old villages provided by an embodiment of the present invention; Figure 2 is a schematic diagram of a controller provided by an embodiment of the present invention.

[0020] Reference numerals: controller 1000, processor 1100, memory 1200. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to 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 used to limit the present invention.

[0022] It should be noted that although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order from the module division in the device or the order in the flowchart. Terms such as "first" and "second" in the specification, claims or the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence.

[0023] In the distribution network, immersion batteries are widely used in various grid equipment, such as distribution transformers, reactive power compensation devices, etc. It can provide stable voltage support, improve the operation efficiency and reliability of equipment, reduce the number of power outages, and enhance the user experience.

[0024] However, when existing backup power sources such as immersion batteries are started, due to the sudden start of the equipment, a large inrush current will be generated, resulting in a sudden drop in the battery voltage; in some special application scenarios, such as in outdoor environments with relatively low ambient temperatures, the temperature of the battery itself is relatively low, and its internal resistance will increase accordingly. In this case, the pressure difference during the startup of the backup power source will become larger, and it is very easy to trigger the battery low-voltage protection mechanism. Once the low-voltage protection is triggered, the battery will experience a power supply failure, thus affecting the normal operation of the entire backup power system and being unable to play its due backup function at critical moments, posing a potential hazard to the continuous operation of related equipment.

[0025] To solve the above problems, the present application provides a method, system and storage medium for generating a planning scheme for the transformation of old villages.

[0026] In this application, a method, a system and a storage medium for generating a planning scheme for the transformation of old villages are provided, and will be described in detail one by one in the following embodiments.

[0027] As Figure 1 shown, an embodiment of the present invention provides a method for generating a planning scheme for the transformation of old villages, including: S100. Obtain multi-source data of the old village to be transformed, where the multi-source data includes building distribution data, road network data, vegetation and water system data, infrastructure data, and historical and cultural data; S200. Construct a pre-transformation GIS model of the old village to be transformed according to the multi-source data, so that the multi-source data can be visually displayed on the map by the pre-transformation GIS model; S300. Analyze the multi-source data based on the pre-transformation GIS model to obtain the target transformation area of the old village to be transformed; S400. Generate a first multi-dimensional transformation scheme for the target transformation area according to the transformation requirements; S500. After superimposing the first multi-dimensional transformation scheme on the real-scene map corresponding to the target transformation area, simulate the first multi-dimensional transformation scheme to obtain a simulation result; S600. Modify the first multi-dimensional transformation scheme according to the simulation result to obtain a second multi-dimensional transformation scheme, and transmit the second multi-dimensional transformation scheme to the operation and maintenance GIS platform.

[0028] Specifically, the data types of the multi-source data in this application include satellite data, 3D scan data, photo data, video data, text description data, audio data, and professional surveying and mapping data, etc. The specific data types and data contents are not limited here. For example, using the unmanned aerial vehicle oblique photography technology, obtain the three-dimensional stereo images of the buildings in the old village to be transformed, and accurately record the spatial information such as the location, height, contour, and number of floors of the buildings; at the same time, combine the field research data and the building information pre-stored in the system to obtain the attribute information such as the use function, construction age, and structure type of the buildings. If the building is a residential building, the number of residents and the type of residents in the residential building will also be obtained, so as to facilitate determining the corresponding transformation scheme of the residential building in combination with the number of residents and the type.

[0029] Among them, the acquisition of the road network data includes: extracting the center line and boundary information of the roads in the old village to be transformed through satellite remote sensing image data; at the same time, collecting detailed data such as the width, material, slope, and traffic signs of the roads through a vehicle-mounted mobile measurement system; referring to the road planning materials of the transportation department to ensure the integrity and accuracy of the data.

[0030] The acquisition of vegetation and water system data specifically includes: obtaining high-resolution satellite images of the old village to be renovated based on high-resolution satellites and obtaining orthophoto images of the old village to be renovated based on unmanned aerial vehicles. Then, through remote sensing image classification, identify the vegetation types, distribution ranges, and coverage areas in the high-resolution satellite images and orthophoto images; at the same time, through spatial analysis, extract information such as the location, flow direction, length, and width of the water system in the high-resolution satellite images and orthophoto images, and combine with the hydrological data of the water conservancy department to supplement dynamic information such as water level and flow rate.

[0031] The acquisition of infrastructure data includes: obtaining the laying drawings and related data of the underground pipe network, including the types, pipe diameters, burial depths, connection methods, etc. of the pipe network, by accessing the systems of departments such as electricity, communication, water supply and drainage; at the same time, through on-site detection data, correct and improve the data to ensure the accuracy of the data; and collect the location and distribution data of above-ground infrastructure such as street lights, trash cans, fire hydrants, etc.

[0032] The acquisition of historical and cultural data includes: obtaining relevant information about historical buildings, cultural relics, and traditional streets and alleys, including names, ages, historical evolutions, cultural values, etc., through local chronicles and archival materials; and recording their current status and preservation conditions through professional surveying and mapping data obtained by professional personnel through on-site investigation and surveying.

[0033] Perform processing such as format conversion, coordinate system unification, and data cleaning on the acquired multi-source data to remove noise and incorrect data, and ensure the consistency and accuracy of the data. Import the processed multi-source data into geographic information system software, and then select a suitable data model, such as a vector model or a raster model, according to the type and characteristics of the data for the organization and storage of spatial data; then construct a topological relationship to ensure the logical consistency of the spatial data.

[0034] Associate spatial data such as buildings, roads, vegetation, and infrastructure with corresponding attribute data, and achieve two-way query and update of spatial data and attribute data through a unique identifier; establish an attribute database to store and manage detailed attribute information. Through the geographic information system, perform 3D modeling, rendering, and symbolization on the constructed data model and attribute database to obtain a GIS (Geographic Information System) model before renovation. By setting different colors, line types, symbols, etc., visually display various types of data of the old village; provide multiple perspectives and browsing methods, such as 2D maps, 3D scenes, bird's-eye views, etc., to facilitate observation and analysis from different dimensions.

[0035] By using spatial analysis tools of Geographic Information System (GIS), such as buffer analysis, overlay analysis, network analysis, etc., comprehensively analyze the multi-source data in the pre-transformation GIS model; for example, determine the service scope of fire protection facilities through buffer analysis and identify areas with insufficient coverage; through overlay analysis, identify areas with poor building quality, imperfect infrastructure and potential for transformation. According to the goals and requirements of the old village transformation, establish a corresponding evaluation index system, including aspects such as building quality, infrastructure supporting, traffic convenience, ecological environment, historical and cultural protection, etc.; use methods such as Analytic Hierarchy Process and Delphi method to determine the weights of each index and highlight the key transformation directions. Combine the spatial analysis results with the evaluation index system to conduct a comprehensive evaluation and grading of each area of the old village; according to the evaluation scores, divide the areas into key transformation areas, general transformation areas and reserved protection areas, etc., so as to obtain the target transformation areas that need to be focused on for transformation.

[0036] For the target transformation areas, multiple different transformation plans can be formulated to meet the transformation needs from different angles and levels; use multi-criteria decision analysis methods to conduct a comprehensive evaluation and comparison of each plan, considering factors such as economic benefits, social benefits and environmental benefits; according to the evaluation results, further optimize and improve the selected plan to determine the final first multi-dimensional transformation plan.

[0037] Through technologies such as UAV oblique photography and ground 3D scanning, obtain high-precision real-scene maps of the target transformation areas; conduct data processing on the real-scene maps, including point cloud filtering, texture mapping, model optimization, etc., to improve the quality and visualization effect of the real-scene maps. Overlay various data in the first multi-dimensional transformation plan, such as building models, road designs, greening layouts, etc., on the real-scene maps; perform spatial registration and data fusion to ensure the accurate matching and seamless connection between the plan and the real-scene maps. Use the simulation analysis function of GIS to conduct multi-dimensional simulations on the overlaid plan, including spatial layout simulation, traffic flow simulation, sunlight analysis, wind environment simulation, ecological environment impact simulation, etc.; through the simulations, evaluate the effects and possible problems of the plan in actual applications. According to the simulation results, evaluate and analyze the first multi-dimensional transformation plan, find out the problems and deficiencies in the first multi-dimensional transformation plan, so as to revise and improve the first multi-dimensional transformation plan to form the second multi-dimensional transformation plan.

[0038] Transfer the second multi-dimensional transformation plan to the operation and maintenance GIS platform to achieve the docking and sharing of the plan data with the operation and maintenance GIS platform; on the operation and maintenance GIS platform, store, manage and display the plan for subsequent construction, operation and maintenance and management decision-making.

[0039] In some alternative embodiments, the revised second multi-dimensional renovation plan is submitted to relevant departments and stakeholders for review. According to the feedback, the second multi-dimensional renovation plan is further improved to ensure that it complies with policy requirements and meets actual needs.

[0040] In some alternative embodiments, constructing the pre-renovation GIS model of the old village to be renovated based on the multi-source data includes: S210. Obtain the topographic data of the old village to be renovated; S220. Construct the topographic model of the old village to be renovated according to the topographic data; S230. Generate a building model on the topographic model according to the building distribution data, and display the building location, building shape, building facilities, and building aging degree through the building model; S240. Generate a road model on the topographic model according to the road network data, and display the road grade, road alignment, road traffic capacity, and road signs through the road network; S250. Generate a vegetation-water system model on the topographic model according to the vegetation-water system data, and display the vegetation type, vegetation shape, vegetation coverage area, and water system through the vegetation-water system model; S260. Generate an infrastructure model on the topographic model according to the infrastructure data, and display the infrastructure type, infrastructure location, and infrastructure aging degree through the infrastructure model; S270. Mark the corresponding historical and cultural information on the building model, the road model, the vegetation-water system model, and the infrastructure model according to the historical and cultural data, and then obtain the pre-renovation GIS model of the old village to be renovated.

[0041] It should be noted that in this application, high-precision topographic data is obtained through satellite remote sensing, unmanned aerial vehicle (UAV) aerial survey, terrestrial three-dimensional laser scanning, etc. Satellite remote sensing can obtain the general topographic situation of the old village to be renovated; UAV aerial survey can collect high-resolution data of the old village terrain with a flexible flight route; terrestrial three-dimensional laser scanning is used for key areas to obtain centimeter-level or even millimeter-level accurate topographic point cloud data. In addition, existing topographic survey results of the surveying and mapping department, such as contour maps, digital elevation models (DEMs), etc., can be combined to supplement and improve the data. The specific acquisition of topographic data is not limited in this application.

[0042] The collected topographic data is imported into GIS software. Through the topographic modeling function of GIS software, a digital terrain model (DTM) is constructed based on data such as contour lines and elevation points. Through interpolation algorithms, such as inverse distance weighting method, Kriging interpolation method, etc., the discrete elevation data is processed to generate a continuous terrain surface model, restoring topographic features such as the terrain undulation, slope, and aspect of the old village.

[0043] Specifically, after generating the terrain model, based on the coordinate information in the building distribution data, the position of each building is accurately determined on the terrain model. For the building shape, according to the contour line data of the building, through operations such as extrusion and lofting in 3D modeling software, the 2D contour is transformed into a 3D building model to visually display the appearance of the building. For buildings with regular shapes, parametric modeling methods can be used to quickly generate models by setting parameters such as the length, width, and height of the building; for buildings with complex shapes, reverse modeling can be carried out using the point cloud data obtained by laser scanning to ensure the accuracy of the model. Combining the internal facility layout data of the building, corresponding facility models, such as doors, windows, stairs, elevators, pipelines, etc., are added to the building model. For large public buildings, the internal functional zoning can also be refined, such as different business areas of a shopping mall, functions of each floor, etc., and the distribution of the equipped facilities of the building is clearly displayed by means of hierarchical display or color differentiation.

[0044] The degree of building aging is represented by assigning different colors, textures, or markings to the building model. For example, the degree of building aging is divided into good, general, poor, etc. For buildings in good condition, bright and complete textures are used; for general buildings, the textures are slightly old; for poor buildings, damaged and peeling texture effects are added, and at the same time, text information on the degree of aging can be marked on the model for easy visual understanding of the current situation of the building. Or the degree of aging of different parts of the building is displayed through corresponding aging coefficients, and the specific aging display is not limited here.

[0045] According to the road grade information in the road network data, the orientation and alignment of the road are planned on the terrain model. For high-grade roads, such as main roads, wider road models are used and multiple lanes are set; for low-grade roads, such as alleys and branch roads, narrower road models are used, and the specific width is determined according to the corresponding modeling scale and is not limited here. The road alignment is determined by drawing curves or straight line segments in 3D space based on design drawings or actual measurement data to ensure that the slope, curve radius, etc. of the road conform to the actual road. On the road model, the traffic capacity of the road is represented by setting different colors, widths, or lane line styles. For example, roads with high traffic capacity are represented by wider lane lines and bright colors; roads with low traffic capacity are represented by narrower lane lines and dull colors. At the same time, road sign models, such as traffic lights, road signs, and road plates, are added to accurately display the traffic information and guiding information of the road.

[0046] Generate corresponding vegetation models on the terrain model according to the vegetation types and distribution information in the vegetation-water system data. For large areas of green spaces, forests, etc., the batch generation method can be adopted. By setting parameters such as the density and height of the vegetation, the vegetation community can be quickly generated. For individual trees or special vegetation, the fine modeling method can be used to simulate their real shapes and appearances. Different vegetation types are distinguished by different colors and shapes, such as green grasslands, dark green forests, colorful flowers, etc., and the boundaries of the vegetation coverage areas are marked. According to the water system data, draw the shapes and positions of the water systems on the terrain model: For large water bodies such as rivers and lakes, 3D water body models can be generated through operations such as stretching and lofting, and the attributes such as the color and transparency of the water body are set to simulate the real water surface effect. For smaller water systems such as brooks and ditches, line or tubular models can be used to represent them, and the flow directions and names of the water systems are marked.

[0047] Locate various infrastructures accurately on the terrain model according to the information in the infrastructure data, such as power facilities (substations, utility poles), communication facilities (base stations, optical cables), water supply and drainage facilities (water pipes, sewers), etc. Create corresponding infrastructure models through 3D modeling software and adjust them according to their actual sizes and shapes to ensure the consistency between the models and the actual facilities, thereby improving the accuracy of the subsequent renovation plan generation. Similar to the method of representing the degree of building aging, different appearance features are given to the infrastructure models to represent the degree of aging. For example, rust and cracks can be added to the texture of the aging water pipes; the old utility poles can be set in an inclined and damaged form, and at the same time, the description of the aging degree of the infrastructure is marked to facilitate understanding of the operating conditions of the facilities.

[0048] Sort out and classify the historical and cultural data, clarify the historical and cultural information related to buildings, roads, vegetation-water systems, and infrastructures, such as the names, ages, and cultural values of historical buildings, the historical evolution of traditional roads, the legend stories of vegetation or water systems with cultural significance, and historical events related to infrastructures. On the constructed building models, road models, vegetation-water system models, and infrastructure models, mark the corresponding historical and cultural information by adding text annotations, icons, hyperlinks, etc. For example, mark the name and brief introduction of the historical building on the historical building model and add a hyperlink, and click to view detailed historical materials and pictures; set icons and text beside the traditional road to explain its historical background; mark the relevant legend stories on the vegetation or water system models with cultural value, etc., so that the GIS model before renovation not only shows the current situation of the old village, but also inherits and displays its historical and cultural connotations.

[0049] In some embodiments, before generating the building model on the terrain model according to the building distribution data, it further includes: S221. After removing noise data, duplicate data, and outliers from the multi-source data through a spatial data quality control algorithm, first intermediate data is obtained; S222. Perform spatial matching on the first intermediate data through a feature matching algorithm to obtain second intermediate data after the first intermediate data has spatial coordinates; S223. Construct a data prediction model based on historical data, where the historical data represents the second intermediate data in each period; S224. Predict and supplement the missing data in the second intermediate data through the data prediction model to obtain third intermediate data. The building distribution data for generating the building model, the road network data for generating the road model, the vegetation water system data for generating the vegetation water system model, and the historical and cultural data for annotating the historical and cultural information all belong to the third intermediate data.

[0050] Specifically, the spatial data quality control algorithm of the present application specifically adopts a spatial filtering algorithm to process the multi-source data. The spatial filtering algorithm can effectively identify and eliminate noise points generated by factors such as measurement errors and sensor interference. For discrete noise points in the building distribution data, a distance threshold can be set, and isolated points that deviate from the main building area (i.e., points whose distance from the main building area is greater than the distance threshold) are regarded as noise and removed. The method of combining spatial position matching and attribute feature comparison is used to identify duplicate data. For records with similar spatial positions and highly similar attribute information, such as two completely overlapping road segments or multiple identical facilities marked at the same position, one complete record is retained, and the remaining duplicates are deleted to avoid interference caused by data redundancy to subsequent analysis. Outliers are detected based on statistical analysis and spatial clustering algorithms. For example, the Z-score (standard score) method is used to identify outliers in building height data. If the height of a certain building exceeds the mean by 3 standard deviations, its rationality can be judged by combining on-site investigations or historical data, and the truly incorrect data is corrected or removed. For outliers whose spatial positions are significantly deviated from the normal distribution, such as building points located in water bodies, they can be corrected after spatial topological relationship analysis. After removing noise points, deleting duplicate data, and removing outliers, the first intermediate data is obtained.

[0051] Extract and match the features of data from different sources through feature point matching algorithms, such as SIFT (Scale-Invariant Feature Transform) or SURF (Speeded-Up Robust Features) algorithms. Find stable feature points in image data with different resolutions and perspectives, and achieve spatial matching of data by calculating the spatial relationships between feature points. Establish a unified coordinate system and transform all data into this coordinate system. For data obtained from different surveying and mapping units, there are likely to be inconsistent coordinate systems. Therefore, perform the transformation through coordinate transformation parameters, so as to transform the first intermediate data into the same coordinate system, and thus match different data of the first intermediate data to different spatial positions.

[0052] Collect and organize the second intermediate data of each period, and analyze the time series characteristics and spatial evolution laws of the data. For example, study the change trend of building distribution, the aging curve of buildings, the expansion process of road networks, the assembly of infrastructure, etc., extract key features and patterns from them, and provide data basis for the construction of prediction models. According to the characteristics of the data and prediction requirements, select appropriate prediction models, such as time series analysis models (ARIMA, LSTM, etc.), spatial interpolation models (Kriging interpolation, inverse distance weighted interpolation, etc.) or machine learning models (random forest, support vector machine, etc.). Taking the building distribution data as an example, if there is missing building information in some areas, the building distribution in the missing areas can be predicted based on the building characteristics and historical development trends of the surrounding areas using a spatial interpolation model. Or if there is missing building aging information in some areas, an aging curve of the buildings in the missing areas can be constructed based on the historical aging information (that is, the prediction curve in the data prediction model), and the building aging information in the missing areas can be predicted based on the aging curve.

[0053] After inputting the second intermediate data into the trained data prediction model, predict and supplement the missing data in it. After the prediction and supplementation are completed, verify by comparing with the known data to evaluate the accuracy and reliability of the prediction results. For areas with large prediction errors, manual correction can be carried out in combination with expert knowledge and field research to ensure the integrity and accuracy of the third intermediate data. It is easy to know that the building distribution data for generating building models, the road network data for generating road models, the vegetation and water system data for generating vegetation and water system models, and the historical and cultural data for annotating historical and cultural information all belong to the third intermediate data.

[0054] In some embodiments, obtaining the target transformation area of the old village to be transformed by analyzing the multi-source data based on the GIS model before transformation includes: S310. Determine the fire protection coefficient and traffic coefficient of each area based on the road network data and building distribution data corresponding to each area on the GIS model before transformation. The fire protection coefficient represents the fire protection ability of each area, and the traffic coefficient represents the traffic capacity of each area; S320. Generate a geological disaster risk distribution map according to the geological feature data corresponding to each area on the GIS model before transformation, and determine the geological disaster risk coefficient of each area on the GIS model before transformation based on the geological disaster risk distribution map; S330. Determine the building quality coefficient of each area according to the building distribution data corresponding to each area on the GIS model before transformation; S340. Determine the infrastructure improvement coefficient of each area according to the infrastructure data corresponding to each area on the GIS model before transformation; S350. Determine the greening coefficient of each area according to the vegetation and water system data corresponding to each area on the GIS model before transformation; S360. Determine the historical and cultural value coefficient of each area according to the historical and cultural data corresponding to each area on the GIS model before transformation; S370. Determine the transformation coefficient of each area on the GIS model before transformation according to the fire protection coefficient, traffic coefficient, geological disaster risk coefficient, building quality coefficient, infrastructure improvement coefficient, greening coefficient and historical and cultural value coefficient of each area on the GIS model before transformation; S380. Configure the areas with the transformation coefficient greater than or equal to the preset coefficient as the target transformation areas.

[0055] Specifically, due to the narrow roads and old buildings in the old village, the fire protection ability and road traffic capacity are both difficult to meet the fire protection requirements and traffic needs. According to the road network data (road width, turning radius, clearance height) and building distribution data (building spacing, height, density), through GIS network analysis, calculate the shortest path from the nearest fire station to each building by fire truck. If the path width < 4m or the turning radius < 9m, points will be deducted; through buffer analysis, check whether the building spacing meets the corresponding requirements (such as if the spacing between multi-storey buildings < 6m, points will be deducted); based on the fire hydrant distribution data, generate a 50m service buffer zone and calculate the water source coverage rate of the buildings in the area. The specific calculation of the fire protection coefficient is as follows: .

[0056] Calculation of road traffic capacity: Determine the corresponding main road traffic capacity according to the road grade; combine the historical traffic flow data and the traffic demand generated by the buildings to simulate the congestion situation during the morning and evening rush hours; evaluate the perfection of the sidewalk width, crossing facilities and barrier-free passages. The calculation formula of the traffic coefficient is: 。

[0057] The geological feature data of this application include terrain slope, rock and soil layer type, groundwater level, distribution of historical disaster points (landslides, collapses, debris flows), etc., without specific limitations. The weight distribution is carried out by the Analytic Hierarchy Process (AHP): such as slope (0.3), stability of rock and soil layers (0.25), groundwater level (0.2), historical disasters (0.25). Different factor scores are determined by slopes, stabilities of rock and soil layers, groundwater levels and historical disaster loose rocks with different values. After superimposing and calculating the factor scores and weights of different regions, the corresponding risk distribution map is obtained. The risk distribution map can clearly show the geological disaster risk coefficients of each region on the GIS model before transformation.

[0058] For the calculation of the building quality coefficient, the quality can be initially assigned according to the age of the building; the secondary assignment is carried out in combination with the structural type of the building; the third assignment is carried out according to the degree of damage of the building, so as to determine the corresponding building quality coefficient according to the three assignments.

[0059] For the calculation of the infrastructure improvement coefficient, comprehensive consideration can be made through the aging and layout of the infrastructure. For example, for the water supply and drainage pipe network (diameter < 100 mm deducts 0.3, aging and rusting deduct 0.2, full score is 1); for power facilities (insufficient transformer capacity deducts 0.3, messy lines deduct 0.2, full score is 1); for communication networks (fiber optic coverage rate < 50% deducts 0.4, full score is 1), etc. The specific infrastructure and scoring items are set according to actual needs and are not limited here. The corresponding improvement coefficient can be calculated according to the score after deduction.

[0060] For the calculation of the greening coefficient, scoring can be carried out through the green space rate (current green space rate / planned standard green space rate, exceeding 1.2 is assigned 1, 0.8 - 1.2 is assigned proportionally, < 0.8 is linearly deducted), tree coverage rate (crown projection area / total area of the region, > 30% is assigned 0.8, 10% - 30% is assigned proportionally, < 10% is assigned 0.2) and water system integrity (proportion of the occupied length of natural water systems, each 10% occupation deducts 0.1). Thus, the greening coefficient is determined according to the total score.

[0061] For the calculation of the historical and cultural value coefficient, comprehensive scoring can be carried out through cultural relics protection units (national level 1.0, provincial level 0.8, municipal level 0.6), integrity of the traditional building style (style integrity > 80% is assigned 0.7, 50% - 80% is assigned 0.4, < 50% is assigned 0.1), and relevance to intangible cultural heritage (having intangible cultural heritage projects above the provincial level is assigned 0.5, municipal level 0.3). Thus, the historical and cultural value coefficient is determined according to the specific score.

[0062] By assigning different full weights to different coefficients, such as a fire protection coefficient (0.2), a traffic coefficient (0.15), a geological disaster risk coefficient (0.15), a building quality coefficient (0.15), an infrastructure improvement coefficient (0.1), a greening coefficient (0.1), and a historical and cultural value coefficient (0.15), the renovation coefficient is calculated by weighting.

[0063] Through the GIS symbolization function, the areas with a renovation coefficient > 0.6 are marked in red, those with a coefficient of 0.4 - 0.6 are marked in yellow, and those with a coefficient < 0.4 are marked in green. Finally, the red areas are extracted as the target renovation areas.

[0064] In some alternative embodiments, after configuring the areas with a renovation coefficient greater than or equal to the preset coefficient as the target renovation areas, the following steps are further included: S381. Determine the first priority ranking of each target sub - area according to the renovation coefficient corresponding to each target sub - area in the target renovation area; S382. After evaluating the renovation benefits of each target sub - area through a preset economic benefit model, obtain the benefit index of each target sub - area; S383. After correcting the first priority ranking according to the benefit index, obtain the second priority ranking; S384. Determine the influence coefficient between each target sub - area through the analytic network process; S385. After correcting the second priority ranking according to the influence coefficient, obtain the third priority ranking, so that each target sub - area is renovated in sequence according to the third priority ranking.

[0065] Specifically, the renovation coefficients of each target sub - area in the target renovation area reflect the urgency of renovation in multiple aspects such as fire protection, traffic, and geological disaster risk in the sub - area. The higher the value, the more urgent the renovation need. Based on this, a preliminary ranking is carried out to obtain the first priority ranking and clarify the initial renovation order. Specifically, after extracting the renovation coefficients of each target sub - area, they are arranged in descending order, and a corresponding ranking number is assigned to each sub - area. For example, the sub - area with the highest renovation coefficient is ranked 1, and so on, forming a first priority ranking list.

[0066] The preset economic benefit model evaluates the renovation benefits of each target sub-region by quantitatively analyzing the renovation input and output, obtains the benefit index, measures the feasibility and value of the renovation from an economic perspective, and provides an economic basis for priority adjustment. The economic benefit model comprehensively considers indicators such as construction costs, expected returns, and investment payback periods. Construction costs cover land acquisition, building demolition, material procurement, labor costs, etc.; expected returns include land appreciation, property appreciation, increased commercial income, and the economic benefits transformed from the social benefits brought by the improvement of public service facilities. The benefit index is calculated through a preset formula, such as benefit index = present value of expected return / present value of construction cost, to obtain the benefit index of each target sub-region. The first-priority ranking is corrected in combination with the benefit index, so that the renovation order not only considers the urgency of regional renovation but also takes into account economic rationality, avoids waste of resources caused by blind renovation, and ensures the maximization of the economic benefits of renovation projects. The specific method for determining the second-priority ranking is: comprehensively analyze the benefit index and the renovation coefficient in the first-priority ranking, and adopt a weighted fusion method to assign a weight to the renovation coefficient α， Benefit index weight β ( α+β= 1), New priority =α × Renovation coefficient ranking score +β × Benefit index ranking score, recalculate the priority scores of each target sub-region, adjust the ranking according to the score, and obtain the second-priority ranking 。

[0067] Determining the influence coefficient includes: considering the mutual influence relationship between target sub-regions through the Analytic Network Process (ANP), and determining the influence coefficient by analyzing factors such as resource flow, functional complementarity, and traffic connection between regions, which reflects the driving or restricting effect of regional renovation on other regions. Specifically, an ANP model containing a control layer (renovation goals, principles, etc.) and a network layer (each target sub-region and their mutual relationships) is constructed. According to the preset scoring rules, pairwise comparison and scoring are carried out on the influence degree between each sub-region to construct a judgment matrix. The influence coefficient between each target sub-region is obtained through matrix operation to form an influence coefficient matrix. The second-priority ranking is corrected again according to the influence coefficient, and the sub-regions with a strong driving effect on the surrounding regions are preferentially renovated (such as preferentially renovating the sub-regions on both sides of the road; or preferentially renovating the outermost sub-regions and renovating them sequentially along the road, etc., which are not specifically limited), promoting regional coordinated development, improving the overall renovation effect, and realizing the optimal allocation of resources

[0068] The specific method for determining the third-priority ranking is: Incorporate the influence coefficient into the calculation of the second-priority ranking score. On the basis of the original calculation, add the influence coefficient weight γ ( α + β + γ=1), the final priority = α × the sorting score of the transformation coefficient + β × the sorting score of the benefit index + γ × the sorting score of the influence coefficient. Recalculate the priority scores of each target sub-region, adjust the sorting according to the new scores, and obtain the third priority sorting. Each target sub-region carries out the transformation work in turn according to the third priority sorting, so as to ensure the scientific, orderly and efficient progress of the transformation work.

[0069] In some embodiments, generating the first multi-dimensional transformation plan for the target transformation region according to the transformation requirements includes: S410. Determine the first requirement level of each requirement index in the transformation requirements according to the preset requirement degree and the regional transformation goal; S420. Obtain the second requirement level after correcting the first requirement level according to the public demand data, and the public demand data is collected through the public demand collection system; S430. Compare the index difference map of the requirement index and the target index in turn according to the first requirement level, and the target index represents the index corresponding to the requirement index in the target transformation region; S440. Generate the first multi-dimensional transformation plan of the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure and the optimal historical and cultural protection measures according to the index difference map.

[0070] Specifically, the requirement indexes can be divided into mandatory requirements (such as fire protection specifications, safety standards), guiding requirements (such as greening coverage rate, public service facility configuration) and flexible requirements (such as characteristic style shaping, industrial development). At the same time, based on the corresponding construction specifications and combined with local policy documents, the benchmark values and ideal values of each index are determined, that is, the preset requirement degree is obtained.

[0071] Determine the priority of each index according to the regional transformation goal. For example, if the transformation goal is "ecologically livable", the priority of ecological and environmental protection indexes (such as green space rate, sponge city construction) is improved; if the transformation goal is "historical and cultural inheritance", the weights of indexes such as historical building protection and traditional street pattern are increased.

[0072] Use the analytic hierarchy process (AHP) to construct the requirement index hierarchy structure and score to determine the weight of each index. For example: Safety requirements (0.3): Fire passage width (0.15), building spacing (0.15); Functional requirements (0.25): Public service facility coverage rate (0.12), traffic accessibility (0.13); Ecological requirements (0.2): Green space rate (0.1), carbon emission control (0.1); Cultural requirements (0.15): Historical building retention rate (0.08), integrity of traditional style (0.07); Economic demands (0.1): Return on investment (0.06), land use efficiency (0.04).

[0073] The collection and correction of public demand data include: collecting suggestions through the corresponding mobile questionnaire system and opinion collection system to determine public demands; and / or collecting suggestions through offline research to determine public demands; and / or obtaining corresponding public demands through big data analysis of public comments, requests, etc.

[0074] Classify and quantify public opinions, incorporate frequently mentioned demands into the indicator system, and thus obtain the second demand level after correcting the first demand level according to public demand data.

[0075] Divide the target renovation area into multiple grid cells to ensure that each cell contains complete analysis elements; construct the spatial topological relationship of elements such as buildings, roads, and greenery to ensure data consistency. Perform dimensionless processing on quantitative indicators (such as green space rate, floor area ratio) using Z-score standardization; perform hierarchical quantification on qualitative indicators (such as historical feature integrity), e.g., "complete" = 4 points, "relatively complete" = 3 points, "average" = 2 points, "poor" = 1 point. Overlay the ideal value of the demand indicator and the current indicator value spatially, calculate the indicator difference of each grid cell; generate a heat map visualization result (i.e., the indicator difference map) to visually display the spatial distribution of the demand gap.

[0076] Generate a differentiated renovation plan based on the target indicator difference related to buildings and based on building quality assessment (intact, repaired, demolished, newly built); apply the genetic algorithm to optimize the building layout, with the spatial utilization rate, sunshine spacing, and ventilation conditions as the objective functions to generate the optimal building layout.

[0077] Based on the target indicator difference related to roads and based on land use function and population size, predict the traffic generation volume after renovation, simultaneously apply a traffic model to simulate traffic flow, apply graph theory algorithms to analyze the connectivity of the road network, identify bottleneck sections, and construct a multi-level road system (arterial road - sub-arterial road - branch road - alleyway) to ensure full coverage of fire lanes, thereby obtaining the optimal road network.

[0078] Based on the target indicator difference related to greenery and based on ecological sensitivity analysis, identify ecological source areas and ecological corridors; apply the Minimum Cumulative Resistance Model (MCR) to plan the green space system. Apply the SWMM (Storm Water Management Model) model to simulate rainwater runoff and optimize the layout of facilities such as sunken green spaces and rain gardens to generate the optimal greenery layout.

[0079] Optimize the pipe network routes of water supply and drainage, electricity, communication, etc. according to the difference in target indicators related to infrastructure, and based on terrain analysis and building layout; apply a hydraulic model to calculate the pipe diameter and slope to ensure that the drainage capacity meets the rainstorm standard, and then generate the optimal infrastructure.

[0080] According to the difference in target indicators related to historical culture, and based on the evaluation of historical buildings and space syntax analysis, delimit the core protection area, construction control zone, and landscape coordination zone, establish a digital archive of historical buildings, record building information and renovation suggestions, and then obtain the optimal historical and cultural protection measures.

[0081] In some embodiments, the first multi-dimensional transformation plan for generating the optimal building layout, optimal road network, optimal greening layout, optimal infrastructure, and optimal historical and cultural protection measures according to the index difference map includes: S441. Determine the building transformation target according to the building index difference in the index difference map; S442. Determine the optimal building layout of the target transformation area according to the building transformation target and the building differentiation transformation strategy, and the building differentiation transformation strategy represents a retention, renovation, demolition, or new construction strategy formulated according to the building quality and the transformation requirements; S443. Determine the road transformation target according to the road index difference in the index difference map; S444. Calculate the optimal road network according to the road transformation target, the shortest path algorithm, and the minimum spanning tree algorithm; S445. Determine the greening transformation target according to the greening index difference in the index difference map; Calculate the optimal greening layout according to the greening transformation target and the greening layout algorithm; S446. Determine the infrastructure transformation target according to the infrastructure index difference in the index difference map; S447. Calculate the optimal infrastructure according to the infrastructure transformation target, the pipe network system planning algorithm, and the sponge city planning algorithm; S448. Determine the historical and cultural transformation target according to the historical and cultural index difference in the index difference map; S449. Determine the optimal historical and cultural protection measures according to the historical and cultural transformation target and the differentiated buildings.

[0082] Specifically, extract the differences between the current values and target values of indicators such as building density, floor area ratio, sunshine spacing, and building height from the indicator difference map. For example, if the current building density is 60% and the target value is 45%, then determine "reduce building density" as the building renovation goal. Through GIS spatial overlay, identify the specific areas where the building density exceeds the standard, and combine with building quality assessment (such as structural safety and service life) to form a map of priority renovation areas of "high density + low quality", and generate the optimal building layout in combination with building differentiation renovation strategies: for buildings with good building quality and in line with the plan, retain the main structure and only carry out facade renovation and function optimization; for buildings with average building quality, adopt measures such as strengthening the foundation and replacing damaged components, and at the same time improve the seismic fortification level; for buildings with poor building quality or violating the plan, formulate the demolition schedule and synchronously plan the temporary resettlement plan; in the demolition area or idle land, use parametric design to generate a new building model that meets the requirements of sunshine and spacing. For example: floor area ratio control, through genetic algorithm optimization, maximize the building area on the premise of meeting the sunshine standard; housing type ratio, based on population structure data (such as the aging rate), give priority to configuring age-friendly housing types.

[0083] The generation of the optimal road network includes: first, extract the differences in indicators such as road width, traffic capacity, and fire access coverage rate to obtain the road renovation goal. For example, if the width of the current main road is less than 12m (target value 15m) and the fire access coverage rate is only 60% (target value 100%), then determine "widen the main road + densify the fire access" as the road renovation goal.

[0084] Then, starting from the fire station, calculate the shortest path to each building, identify the bottleneck sections with a width < 4m, and generate a mandatory widening list; combine with traffic flow prediction (such as the traffic flow during morning and evening rush hours), and plan parallel alternative routes on congested sections (travel time > 20 minutes). Regard the current roads as the edges of the graph and the construction cost (land acquisition cost + construction cost) as the weights to generate the minimum-cost road network connecting all groups; give priority to retaining the sections with high grade and good road conditions in the current roads to reduce the renovation cost; thus generate the optimal road network.

[0085] The generation of the optimal greening layout includes: extracting the differences in indicators such as green space ratio (e.g., current 20% → target 35%), tree coverage rate (e.g., current 15% → target 25%), and ecological corridor integrity (e.g., current 5 break points → target 0), and determining the greening transformation goals. Based on terrain and water system data, the Minimum Cumulative Resistance Model (MCR) is used to identify ecological source areas (such as contiguous forest land) and potential corridors, and greening connection belts with a width ≥ 10m are preferentially planned at the break points; the Voronoi diagram is applied to divide the service scope of green spaces to ensure that the coverage rate within a service radius of 500m (only as an example, not limited) is increased from the current 60% to 85% (only as an example, not limited), thereby generating the optimal greening layout.

[0086] The generation of the optimal infrastructure includes: extracting the differences in indicators such as the diameter of the drainage pipe network (e.g., current pipe diameter 300 mm → target pipe diameter 500 mm), sewage treatment rate (e.g., current 40% → target 90%), and the proportion of renewable energy (e.g., current 5% → target 20%), and determining the infrastructure transformation goals. Then, based on terrain elevation data, a hydraulic model is used to simulate stormwater runoff to increase the drainage capacity from once-in-a-year to once-in-three-years; a topological analysis of the current pipe network is carried out to identify pipe segments with insufficient diameter and reverse slope, and corresponding pipe network transformation plans are generated. After determining all the infrastructure transformation plans, the optimal infrastructure can be obtained.

[0087] The generation of the optimal historical and cultural protection measures includes: extracting the differences in indicators such as the retention rate of historical buildings (e.g., current 30% → target 80%), the integrity of traditional streets and alleys (e.g., current 40% → target 70%), and the proportion of cultural display spaces (e.g., current 5% → target 15%), and determining the corresponding historical and cultural transformation goals. Then, the "authentic restoration" strategy (the specific strategy is not limited) is adopted, traditional materials (such as blue bricks and wood) and techniques are used, and the building form is prohibited from being changed; internal function transformation is allowed for historical buildings (such as from residential to cultural display), but the exterior facade and structural system must remain unchanged; the height of traditional style buildings can be appropriately adjusted (≤ 2 floors), but the style characteristics of "whitewashed walls and black tiles" must be continued; subsequently, based on space syntax analysis, "high-integration" nodes in traditional streets and alleys (such as historical squares and bridgeheads) are identified and preferentially transformed into cultural display spaces, thereby generating the optimal historical and cultural protection measures.

[0088] In some embodiments, after superimposing the first multi-dimensional transformation plan on the real-scene map corresponding to the target transformation area, simulating the first multi-dimensional transformation plan to obtain a simulation result includes: S510. Overlay the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, and the optimal historical and cultural protection measures of the first multi-dimensional renovation plan onto the real-scene map one by one, so that the real-scene map is precisely matched with the first multi-dimensional renovation plan; S520. Reconstruct the pre-renovation GIS model in sequence according to the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, the optimal historical and cultural protection measures, and the third-priority ranking to obtain a post-renovation GIS model; S530. Conduct spatial performance simulation, environmental performance simulation, traffic performance simulation, economic performance evaluation, and historical and cultural value evaluation on the post-renovation GIS model to obtain a simulation evaluation report and a renovation score. The simulation results include the simulation evaluation report and the renovation score.

[0089] Specifically, overlay the spatial coordinates corresponding to the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, and the optimal historical and cultural protection measures of the first multi-dimensional renovation plan onto the real-scene map one by one, so that the first multi-dimensional renovation plan is displayed on the specific real-scene map. This can not only ensure the precise matching of the real-scene map with the first multi-dimensional renovation plan but also more intuitively display the specific renovation plan. Update the pre-renovation GIS model according to the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, and the optimal historical and cultural protection measures of the first multi-dimensional renovation plan to obtain a post-renovation GIS model. It is easy to know that the post-renovation GIS model shows the GIS model of the old village after renovation through the first multi-dimensional renovation plan. Overlaying the first multi-dimensional renovation plan onto the real-scene map is to correspond the post-renovation GIS model to the specific real-scene space. Thus, corresponding spatial position corrections can be made according to the matching degree between the real-scene space and the first multi-dimensional renovation plan (for example, if area A of the first multi-dimensional renovation plan matches area B of the real-scene space, then swap area A and area B of the first multi-dimensional renovation plan with each other).

[0090] The spatial performance simulation conducted on the post-renovation GIS model includes: space syntax analysis, calculating the integration degree based on the axis model, and evaluating the change in spatial accessibility after renovation; sunlight and ventilation simulation, determining the ventilation performance between buildings by simulating the full-window sunlight duration on the winter solstice and conducting fluid simulation; and then obtaining the spatial performance simulation results.

[0091] The traffic performance simulation of the reconstructed GIS model includes dynamic traffic flow simulation and parking demand prediction, so as to obtain the corresponding traffic performance simulation results. The environmental performance simulation includes calculating carbon emissions through a carbon footprint calculation model and determining the corresponding rainwater drainage function through rainwater management simulation, so as to generate environmental performance simulation results. The economic performance evaluation includes cost-benefit analysis and analysis of related economic factors to obtain economic performance evaluation results. The historical and cultural value evaluation includes evaluation of the integrity index of the style and features and evaluation of the vitality of the cultural space, and then generates historical and cultural value evaluation results. The corresponding simulation evaluation report and reconstruction score are generated based on the traffic performance simulation results, environmental performance simulation results, economic performance evaluation results, and historical and cultural value evaluation results, so as to determine the corresponding correction items and correction values according to the simulation evaluation report and reconstruction score, and then correct to obtain the second multi-dimensional reconstruction plan.

[0092] In some alternative embodiments, the differences between the old village to be reconstructed before and after reconstruction are dynamically displayed through the reconstructed GIS model. Specifically, the dynamic simulation of the reconstruction process can be displayed according to requirements, or the corresponding sub-regions can be selected for dynamic simulation of the reconstruction, or multiple sub-regions can be selected for dynamic simulation of the reconstruction at different simulation speeds.

[0093] The beneficial effects of the present invention include: obtaining multi-source data of the old village to be reconstructed, where the multi-source data includes building distribution data, road network data, vegetation and water system data, infrastructure data, and historical and cultural data; constructing a pre-reconstruction GIS model of the old village to be reconstructed based on the multi-source data, so that the pre-reconstruction GIS model visually displays the multi-source data on the map; analyzing the multi-source data based on the pre-reconstruction GIS model to obtain the target reconstruction area of the old village to be reconstructed; generating a first multi-dimensional reconstruction plan for the target reconstruction area according to the reconstruction requirements; after superimposing the first multi-dimensional reconstruction plan on the real-scene map corresponding to the target reconstruction area, simulating the first multi-dimensional reconstruction plan to obtain simulation results; correcting the first multi-dimensional reconstruction plan according to the simulation results to obtain a second multi-dimensional reconstruction plan, and transporting the second multi-dimensional reconstruction plan to the operation and maintenance GIS platform. Automatically generating a pre-reconstruction GIS model according to the multi-source data of the old village to be reconstructed, and obtaining a specific target reconstruction area after corresponding data analysis, so as to generate a corresponding first multi-dimensional reconstruction plan according to specific reconstruction requirements, and the planning efficiency of the reconstruction plan is high; by superimposing the first multi-dimensional reconstruction plan on the real-scene map for simulation, the first multi-dimensional plan is corrected, ensuring the accuracy and perfection of the reconstruction plan.

[0094] As Figure 2 shown, Figure 2The structural block diagram of a controller 1000 provided according to an embodiment of the present application is shown. The components of the controller 1000 include but are not limited to a memory 1200 and a processor 1100. The processor 1100 is connected to the memory 1200 via a bus, and the memory 1200 is used to store data.

[0095] The controller 1000 further includes an access device, which enables the controller 1000 to communicate via one or more networks. Examples of these networks include the Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or a combination of communication networks such as the Internet. The access device 340 may include one or more of any type of wired or wireless network interfaces (e.g., Network Interface Card (NIC)), such as IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, Worldwide Interoperability for Microwave Access (Wi-MAX) interface, Ethernet interface, Universal Serial Bus (USB) interface, cellular network interface, Bluetooth interface, Near Field Communication (NFC) interface, and so on.

[0096] The controller 1000 can be any type of stationary or mobile electronic device, including mobile computers or mobile electronic devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable electronic devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary electronic devices such as desktop computers or PCs. The controller 1000 can also be a mobile or stationary server.

[0097] Among them, the processor 1100 is used to execute the computer-executable instructions of the planning scheme generation method for the renovation of old villages.

[0098] The above is a schematic solution of a controller in this embodiment. It should be noted that the technical solution of this controller and the technical solution of the above planning scheme generation method for the renovation of old villages belong to the same concept. For the details not described in the technical solution of the controller, reference can be made to the description of the technical solution of the above planning scheme generation method for the renovation of old villages.

[0099] According to an embodiment of the present application, there is also provided a system for generating a planning scheme for the transformation of old villages. The system for generating a planning scheme for the transformation of old villages includes a hospital bed, in which a controller 1000 is installed, or the hospital bed is communicatively connected to the controller 1000, so that the adjustment of the hospital bed is realized through the controller 1000. It should be noted that the technical solution of the system for generating a planning scheme for the transformation of old villages and the technical solution of the above-mentioned method for generating a planning scheme for the transformation of old villages belong to the same concept. For the details not described in detail in the technical solution of the computing device, reference can be made to the description of the technical solution of the above-mentioned method for generating a planning scheme for the transformation of old villages.

[0100] An embodiment of the present application also provides a storage medium, which is a computer-readable storage medium. The storage medium stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned method for generating a planning scheme for the transformation of old villages.

[0101] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor through a network. Examples of the above networks include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and may be located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0102] Those of ordinary skill in the art will understand that all or some of the steps and systems disclosed in the above methods can be implemented as software, firmware, hardware, and their appropriate combinations. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or can be implemented as hardware, or can be implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include a computer storage medium (or non-transitory medium) and a communication medium (or transitory medium). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those of ordinary skill in the art that communication media typically includes computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium.

[0103] The above is a specific description of the preferred embodiments of the present application, but the present application is not limited to the above embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present application, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present application.

Claims

1. A method for generating a planning scheme for the renovation of old villages, characterized in that Including: Obtain multi-source data of the old village to be transformed, where the multi-source data includes building distribution data, road network data, vegetation water system data, infrastructure data, and historical and cultural data; Construct a pre-transformation GIS model of the old village to be transformed according to the multi-source data, so that the pre-transformation GIS model visually displays the multi-source data on the map; Based on the pre-transformation GIS model, analyze the multi-source data to obtain the target transformation area of the old village to be transformed; Generate a first multi-dimensional transformation plan for the target transformation area according to the transformation requirements; After superimposing the first multi-dimensional transformation plan on the real-scene map corresponding to the target transformation area, simulate the first multi-dimensional transformation plan to obtain a simulation result; Modify the first multi-dimensional transformation plan according to the simulation result to obtain a second multi-dimensional transformation plan, and transmit the second multi-dimensional transformation plan to the operation and maintenance GIS platform.

2. The method for generating a planning scheme for the renovation of old villages according to claim 1, characterized in that, The constructing the pre-transformation GIS model of the old village to be transformed according to the multi-source data includes: Obtain the terrain data of the old village to be transformed; Construct a terrain model of the old village to be transformed according to the terrain data; Generate a building model on the terrain model according to the building distribution data, and display the building location, building shape, building facilities, and building aging degree through the building model; Generate a road model on the terrain model according to the road network data, and display the road grade, road alignment, road traffic capacity, and road signs through the road network; Generate a vegetation water system model on the terrain model according to the vegetation water system data, and display the vegetation type, vegetation shape, vegetation coverage area, and water system through the vegetation water system model; Generate an infrastructure model on the terrain model according to the infrastructure data, and display the infrastructure type, infrastructure location, and infrastructure aging degree through the infrastructure model; After marking the corresponding historical and cultural information on the building model, the road model, the vegetation water system model, and the infrastructure model according to the historical and cultural data, obtain the pre-transformation GIS model of the old village to be transformed.

3. The method for generating a renovation plan for old villages according to claim 2, wherein Before generating the building model on the terrain model according to the building distribution data, it further includes: Remove noise data, duplicate data, and outliers from the multi-source data through a spatial data quality control algorithm to obtain first intermediate data; Perform spatial matching on the first intermediate data through a feature matching algorithm to make the first intermediate data have spatial coordinates to obtain second intermediate data; Construct a data prediction model based on historical data, where the historical data represents the second intermediate data in each period; Predict and supplement the missing data in the second intermediate data through the data prediction model to obtain third intermediate data. The building distribution data for generating the building model, the road network data for generating the road model, the vegetation water system data for generating the vegetation water system model, and the historical and cultural data for marking the historical and cultural information all belong to the third intermediate data.

4. The method for generating a planning scheme for the renovation of old villages according to claim 1, wherein Analyzing the multi-source data based on the pre-transformation GIS model to obtain the target transformation area of the old village to be transformed, including: Determining the fire protection coefficient and traffic coefficient of each area according to the road network data and building distribution data corresponding to each area on the pre-transformation GIS model. The fire protection coefficient represents the fire protection ability of each area, and the traffic coefficient represents the traffic capacity of each area; Generating a geological disaster risk distribution map according to the geological feature data corresponding to each area on the pre-transformation GIS model, and determining the geological disaster risk coefficient of each area on the pre-transformation GIS model based on the geological disaster risk distribution map; Determining the building quality coefficient of each area according to the building distribution data corresponding to each area on the pre-transformation GIS model; Determining the infrastructure improvement coefficient of each area according to the infrastructure data corresponding to each area on the pre-transformation GIS model; Determining the greening coefficient of each area according to the vegetation water system data corresponding to each area on the pre-transformation GIS model; Determining the historical and cultural value coefficient of each area according to the historical and cultural data corresponding to each area on the pre-transformation GIS model; Determining the transformation coefficient of each area on the pre-transformation GIS model according to the fire protection coefficient, traffic coefficient, geological disaster risk coefficient, building quality coefficient, infrastructure improvement coefficient, greening coefficient, and historical and cultural value coefficient of each area on the pre-transformation GIS model; Configuring the areas with the transformation coefficient greater than or equal to the preset coefficient as the target transformation areas.

5. The method for generating a planning scheme for the renovation of an old village according to claim 4, wherein, After configuring the areas with the transformation coefficient greater than or equal to the preset coefficient as the target transformation areas, it further includes: Determining the first priority ranking of each target sub-area according to the transformation coefficient corresponding to each target sub-area in the target transformation area; Evaluating the transformation benefits of each target sub-area through a preset economic benefit model to obtain the benefit index of each target sub-area; Correcting the first priority ranking according to the benefit index to obtain the second priority ranking; Determining the influence coefficient between each target sub-area through the network analysis method; Correcting the second priority ranking according to the influence coefficient to obtain the third priority ranking, so that each target sub-area is transformed in sequence according to the third priority ranking.

6. The method for generating a planning scheme for the renovation of old villages according to claim 5, wherein Generating the first multi-dimensional transformation plan for the target transformation area according to the transformation requirements, including: Determining the first requirement level of each requirement index in the transformation requirements according to the preset requirement degree and regional transformation goal; Correcting the first requirement level according to the public demand data to obtain the second requirement level, and the public demand data is collected through the public demand collection system; Sequentially comparing the index difference map of the requirement index and the target index according to the first requirement level, and the target index represents the index corresponding to the requirement index in the target transformation area. Generate the first multi-dimensional renovation plan for the optimal building layout, optimal road network, optimal greening layout, optimal infrastructure, and optimal historical and cultural protection measures based on the index difference map.

7. The method for generating a renovation plan for old villages according to claim 6, characterized in that The first multi-dimensional renovation plan for generating the optimal building layout, optimal road network, optimal greening layout, optimal infrastructure, and optimal historical and cultural protection measures based on the index difference map includes: Determine the building renovation objectives based on the building index differences in the index difference map; Determine the optimal building layout of the target renovation area according to the building renovation objectives and the building differentiation renovation strategy, where the building differentiation renovation strategy represents the retention, repair, demolition, or new construction strategy formulated based on the building quality and the renovation requirements; Determine the road renovation objectives based on the road index differences in the index difference map; Calculate the optimal road network according to the road renovation objectives, the shortest path algorithm, and the minimum spanning tree algorithm; Determine the greening renovation objectives based on the greening index differences in the index difference map; Calculate the optimal greening layout according to the greening renovation objectives and the greening layout algorithm; Determine the infrastructure renovation objectives based on the infrastructure index differences in the index difference map; Calculate the optimal infrastructure according to the infrastructure renovation objectives, the pipe network system planning algorithm, and the sponge city planning algorithm; Determine the historical and cultural renovation objectives based on the historical and cultural index differences in the index difference map; Determine the optimal historical and cultural protection measures according to the historical and cultural renovation objectives and the differentiated buildings.

8. The method for generating a planning scheme for the renovation of an old village according to claim 6, wherein, After superimposing the first multi-dimensional renovation plan on the real-scene map corresponding to the target renovation area, simulating the first multi-dimensional renovation plan to obtain simulation results, including: Superimpose the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, and the optimal historical and cultural protection measures of the first multi-dimensional renovation plan on the real-scene map one by one to make the real-scene map match the first multi-dimensional renovation plan precisely; Reconstruct the pre-renovation GIS model in sequence according to the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, the optimal historical and cultural protection measures, and the third priority ranking to obtain the post-renovation GIS model; Conduct spatial performance simulation, environmental performance simulation, traffic performance simulation, economic performance evaluation, and historical and cultural value evaluation on the post-renovation GIS model to obtain a simulation evaluation report and a renovation score. The simulation results include the simulation evaluation report and the renovation score.

9. A planning scheme generation system for the renovation of old villages, characterized in that, Includes a controller, and the controller includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the planning scheme generation method for the renovation of old villages described in any one of claims 1-8.

10. A computer storage medium, characterized in that, The computer storage medium stores computer-executable instructions for executing the planning scheme generation method for the renovation of old villages described in any one of claims 1-8.

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