CN120373911B

CN120373911B - Old village reconstruction planning scheme generation method, system and storage medium

Info

Publication number: CN120373911B
Application number: CN202510847958.2A
Authority: CN
Inventors: 杨明江; 张均可; 李玉明; 曾磊帅; 肖传起; 王金; 沈良帅; 陈景涛
Original assignee: PowerChina Kunming Engineering Corp Ltd; PowerChina Urban Planning and Design Institute Co Ltd
Current assignee: PowerChina Kunming Engineering Corp Ltd; PowerChina Urban Planning and Design Institute Co Ltd
Priority date: 2025-06-24
Filing date: 2025-06-24
Publication date: 2025-09-09
Anticipated expiration: 2045-06-24
Also published as: CN120373911A

Abstract

The embodiment of the invention provides a planning scheme generation method, a system and a storage medium for old village reconstruction, wherein the method comprises the steps of obtaining multi-source data of an old village to be reconstructed, constructing a pre-reconstruction GIS model of the old village to be reconstructed according to the multi-source data, enabling the pre-reconstruction GIS model to visually display the multi-source data on a map, analyzing the multi-source data based on the pre-reconstruction GIS model to obtain a target reconstruction area of the old village to be reconstructed, generating a first multi-dimensional reconstruction scheme of the target reconstruction area according to reconstruction requirements, overlapping the first multi-dimensional reconstruction scheme to a real 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. The method automatically generates the reconstruction scheme according to the multi-source data, has high planning efficiency, and ensures the accuracy and the completeness of the reconstruction scheme by simulating and correcting the reconstruction scheme.

Description

Old village reconstruction planning scheme generation method, system and storage medium

Technical Field

The invention relates to the technical field of data processing, in particular to a method, a system and a storage medium for generating a planning scheme for transformation of an old village.

Background

The old village reconstruction is the comprehensive deployment for researching the future development of villages and reasonable layout and arrangement of various engineering construction of the villages, is a blueprint for the development of the villages in a certain period, is an important component of village management, and is the basis for the construction and management of the villages.

The existing planning scheme for the transformation of the old village is obtained after manual analysis, the planning efficiency is low, and in view of complex data and single and complex working process, the incomplete planning is easy to cause.

Disclosure of Invention

The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

The main purpose of the embodiment of the invention is to provide a method, a system and a storage medium for generating a planning scheme for old village reconstruction, which can improve the planning efficiency and the completeness of the old village planning scheme.

In a first aspect, an embodiment of the present invention provides a method for generating a planning scheme for modification of an old village, including:

acquiring multi-source data of an old village to be modified, wherein the multi-source data comprises building distribution data, road network data, vegetation water system data, infrastructure data and historical culture data;

Constructing a pre-reconstruction GIS model of the old village to be reconstructed according to the multi-source data, so that the pre-reconstruction GIS model can visually display 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 reconstruction scheme of the target reconstruction area according to reconstruction requirements;

The first multi-dimensional reconstruction scheme is overlapped to a live-action map corresponding to the target reconstruction area, and then simulation is carried out on the first multi-dimensional reconstruction scheme to obtain a simulation result;

And correcting the first multi-dimensional transformation scheme according to the simulation result to obtain a second multi-dimensional transformation scheme, and conveying the second multi-dimensional transformation scheme to an operation and maintenance GIS platform.

In some optional embodiments, the constructing the pre-reconstruction GIS model of the old village to be reconstructed according to the multi-source data includes:

acquiring the topographic data of the old village to be modified;

Constructing a terrain model of the old village to be remodeled according to the terrain data;

Generating a building model on the terrain model according to the building distribution data, and displaying building positions, building shapes, building equipment facilities and building aging degrees through the building model;

Generating a road model on the terrain model according to the road network data, and displaying road grade, road alignment, road traffic capacity and road identification through the road network;

Generating a vegetation water system model on the terrain model according to the vegetation water system data, and displaying vegetation type, vegetation shape, vegetation coverage area and water system through the vegetation water system model;

generating an infrastructure model on the terrain model according to the infrastructure data, and displaying the type of the infrastructure, the position of the infrastructure and the aging degree of the infrastructure through the infrastructure model;

And marking corresponding historical culture information on the building model, the road model, the vegetation water system model and the infrastructure model according to the historical culture data to obtain the GIS model before transformation of the old village to be transformed.

In some alternative embodiments, before generating the building model on the terrain model from the building distribution data, further comprising:

removing noise data, repeated data and abnormal values from the multi-source data through a spatial data quality control algorithm to obtain first intermediate data;

performing space matching on the first intermediate data through a feature matching algorithm so that the first intermediate data has space coordinates to obtain second intermediate data;

constructing a data prediction model based on historical data, wherein the historical data represents the second intermediate data of each period;

And predicting and supplementing missing data in the second intermediate data through the data prediction model to obtain third intermediate data, wherein the third intermediate data is used for generating the building distribution data of the building model, the road network data of the road model, the vegetation water system data of the vegetation water system model and the historical culture data marked with the historical culture information.

In some optional embodiments, the obtaining the target reconstruction area of the old village to be reconstructed based on the pre-reconstruction GIS model after analyzing the multi-source data includes:

Determining fire control coefficients and pass coefficients of all areas according to the road network data and the building distribution data corresponding to all areas on the GIS model before transformation, wherein the fire control coefficients represent the fire control capacity of all areas, and the pass coefficients represent the pass capacity of all areas;

Generating a geological disaster risk distribution map according to geological feature data corresponding to each region on the GIS model before transformation, and determining geological disaster risk coefficients of each region on the GIS model before transformation based on the geological disaster risk distribution map;

determining building quality coefficients of all areas according to the building distribution data corresponding to all areas on the GIS model before transformation;

determining infrastructure improvement coefficients of all areas according to the infrastructure data corresponding to all areas on the GIS model before transformation;

determining greening coefficients of all areas according to the vegetation water system data corresponding to all areas on the GIS model before transformation;

Determining the historical culture value coefficients of all the areas according to the historical culture data corresponding to all the areas on the GIS model before transformation;

Determining transformation coefficients of all areas on the GIS model before transformation according to the fire control coefficients, the pass coefficients, the geological disaster risk coefficients, the building quality coefficients, the infrastructure improvement coefficients, the greening coefficients and the historical cultural value coefficients of all areas on the GIS model before transformation;

and configuring the area with the transformation coefficient larger than or equal to a preset coefficient as the target transformation area.

In some optional embodiments, after the configuring the area with the modification coefficient greater than or equal to the preset coefficient as the target modification area, the method further includes:

determining a first priority ranking of each target subarea according to the transformation coefficient corresponding to each target subarea in the target transformation area;

The improvement benefits of the target subareas are evaluated through a preset economic benefit model, and then the benefit index of each target subarea is obtained;

Correcting the first priority order according to the benefit index to obtain a second priority order;

determining the influence coefficient between the target subareas through a network analysis method;

And correcting the second priority order according to the influence coefficient to obtain a third priority order, so that each target subarea is modified according to the third priority order in sequence.

In some alternative embodiments, the generating the first multi-dimensional reconstruction scheme of the target reconstruction region according to reconstruction requirements includes:

determining a first demand level of each demand index in the reconstruction demand according to a preset demand degree and a regional reconstruction target;

the first demand level is corrected according to the public demand data to obtain a second demand level, and the public demand data is collected by a public demand collection system;

sequentially comparing the index difference value maps of the demand index and a target index according to the first demand level, wherein the target index represents an index corresponding to the demand index in the target transformation area;

and generating the first multi-dimensional transformation scheme of the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure and the optimal historical culture protection measures according to the index difference value map.

In some optional embodiments, the generating the first multi-dimensional modification scheme of the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, and the optimal historical culture protection measure according to the index difference map includes:

determining a building reconstruction target according to the building index difference value in the index difference value map;

Determining the optimal building layout of the target transformation area according to the building transformation target and a building differential transformation strategy, wherein the building differential transformation strategy represents a reserved, repaired, dismantled or newly built strategy formulated according to building quality and transformation requirements;

determining a road transformation target according to the road index difference value in the index difference value map;

Calculating according to the road reconstruction target, a shortest path algorithm and a minimum spanning tree algorithm to obtain the optimal road network;

determining a greening transformation target according to a greening index difference value in the index difference value map;

Calculating according to the greening transformation target and a greening layout algorithm to obtain the optimal greening layout;

determining an infrastructure transformation target according to the infrastructure index difference value in the index difference value map;

Calculating according to the infrastructure transformation target, a pipe network system planning algorithm and a sponge city planning algorithm to obtain the optimal infrastructure;

Determining a historical culture transformation target according to the historical culture index difference value in the index difference value map;

and determining the optimal historical culture protection measures according to the historical culture transformation target and the differentiated building.

In some optional embodiments, after the first multi-dimensional transformation scheme is superimposed on the live-action map corresponding to the target transformation area, simulating the first multi-dimensional transformation scheme to obtain a simulation result includes:

The optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure and the optimal historical culture protection measures of the first multi-dimensional transformation scheme are respectively overlapped with the live-action map in a one-by-one corresponding mode, so that the live-action map is accurately matched with the first multi-dimensional transformation scheme;

Sequentially rebuilding the GIS model before reconstruction according to the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, the optimal historical culture protection measures and the third priority order to obtain a GIS model after reconstruction;

And performing spatial performance simulation, environmental performance simulation, traffic performance simulation, economic performance evaluation and historical cultural value evaluation on the modified GIS model to obtain a simulation evaluation report and a modification score, wherein the simulation result comprises the simulation evaluation report and the modification score.

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, where the processor implements the old village reconstruction planning scheme generation method according to the first aspect when executing the computer program.

In a third aspect, an embodiment of the present invention provides a planning scheme generating system for modification of an old village, including the controller according to the second aspect.

In a fourth aspect, a computer storage medium stores computer-executable instructions for performing the old village retrofit planning scheme generation method according to the first aspect.

The method has the advantages that multi-source data of an old village to be rebuilt are obtained, the multi-source data comprise building distribution data, road network data, vegetation water system data, infrastructure data and historical culture data, a pre-rebuilding GIS model of the old village to be rebuilt is built according to the multi-source data, the multi-source data are visually displayed on a map by the pre-rebuilding GIS model, a target rebuilding area of the old village to be rebuilt is obtained after the multi-source data are analyzed on the basis of the pre-rebuilding GIS model, a first multi-dimensional rebuilding scheme of the target rebuilding area is generated according to rebuilding requirements, after the first multi-dimensional rebuilding scheme is overlaid on a real map corresponding to the target rebuilding area, the first multi-dimensional rebuilding scheme is simulated to obtain a simulation result, a second multi-dimensional rebuilding scheme is obtained according to the simulation result, and the second multi-dimensional rebuilding scheme is conveyed to an operation GIS platform. The method comprises the steps of automatically generating a GIS model before transformation according to multi-source data of an old village to be transformed, analyzing corresponding data to obtain a specific target transformation area, generating a corresponding first multi-dimensional transformation scheme according to specific transformation requirements, and simulating the first multi-dimensional transformation scheme by superposing the first multi-dimensional transformation scheme on a live-action map, wherein the planning efficiency of the transformation scheme is high, so that the accuracy and the completeness of the transformation scheme are guaranteed.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Drawings

FIG. 1 is a block flow diagram of steps of a method for generating a planning scheme for old village modification according to an embodiment of the present invention;

fig. 2 is a schematic diagram of a controller according to an embodiment of the present invention.

Reference numeral controller 1000, processor 1100, memory 1200.

Detailed Description

The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

It should be noted that although functional block division is performed in a device diagram and a logic sequence is shown in a flowchart, in some cases, the steps shown or described may be performed in a different order than the block division in the device, or in the flowchart. The terms first, second and the like in the description, in the claims and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.

In power distribution networks, submerged batteries are widely used in various power grid equipment, such as distribution transformers, reactive power compensation devices, and the like. The device can provide stable voltage support, improve the operation efficiency and reliability of equipment, reduce the power failure times and improve the user experience.

In some special application scenarios, such as in outdoor environment and in places with lower ambient temperature, the temperature of the battery is relatively lower, the internal resistance of the battery is correspondingly increased, and in such cases, the pressure difference of the standby power supply during starting can become larger, thus easily triggering a battery low-voltage protection mechanism. Once the low-voltage protection is triggered, the battery can have power supply faults, so that the normal operation of the whole standby power supply system is affected, the due standby function of the standby power supply system cannot be exerted at key moments, and hidden danger is brought to the continuous operation of related equipment.

In order to solve the problems, the application provides a planning scheme generation method, a planning scheme generation system and a storage medium for old village reconstruction.

In the present application, a method, a system and a storage medium for generating a planning scheme for old village reconstruction are provided, and the detailed description is given in the following embodiments.

As shown in fig. 1, an embodiment of the present invention provides a method for generating a planning scheme for old village reconstruction, including:

S100, acquiring multi-source data of an old village to be modified, wherein the multi-source data comprise building distribution data, road network data, vegetation water system data, infrastructure data and historical culture data;

S200, constructing a pre-reconstruction GIS model of the old village to be reconstructed according to the multi-source data, so that the pre-reconstruction GIS model can visually display the multi-source data on a map;

S300, 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;

s400, generating a first multi-dimensional reconstruction scheme of the target reconstruction area according to reconstruction requirements;

s500, after the first multi-dimensional reconstruction scheme is overlapped to a live-action map corresponding to the target reconstruction area, simulating the first multi-dimensional reconstruction scheme to obtain a simulation result;

And S600, correcting the first multi-dimensional transformation scheme according to the simulation result to obtain a second multi-dimensional transformation scheme, and conveying the second multi-dimensional transformation scheme to an operation and maintenance GIS platform.

Specifically, the data types of the multi-source data of the present application include satellite data, 3D scan data, photo data, video data, text description data, audio data, professional mapping data, etc., and the specific data types and data contents are not limited herein. For example, by utilizing unmanned aerial vehicle oblique photography technology, three-dimensional images of buildings in old villages to be modified are acquired, spatial information such as positions, heights, outlines, layers and the like of the buildings are accurately recorded, meanwhile, by combining field investigation data and building information pre-stored in a system, attribute information such as using functions, building years, structure types and the like of the buildings is acquired, if the buildings are residential buildings, the number of residents and the types of residents of the residential buildings are also acquired, and accordingly, the corresponding modification scheme of the residential buildings is determined by combining the number of residents and the types.

The road network data acquisition method comprises the steps of extracting central line and boundary information of a road in an old village to be modified through satellite remote sensing image data, collecting detailed data such as width, material, gradient and traffic sign of the road through a vehicle-mounted mobile measurement system, and referencing road planning data of a traffic department to ensure the integrity and accuracy of the data.

The vegetation water system data acquisition specifically comprises the steps of acquiring a high-resolution satellite image of an old village to be rebuilt based on a high-resolution satellite and acquiring an unmanned aerial vehicle orthoimage of the old village to be rebuilt based on an unmanned aerial vehicle, classifying through remote sensing images, identifying vegetation types, distribution ranges and coverage areas in the high-resolution satellite image and the unmanned aerial vehicle orthoimage, extracting information such as positions, flow directions, lengths and widths of water systems in the high-resolution satellite image and the unmanned aerial vehicle orthoimage through spatial analysis, and supplementing dynamic information such as water levels, flow rates and the like by combining with hydrological data of a water conservancy department.

The acquisition of the infrastructure data comprises the steps of acquiring paving drawings and related data of an underground pipe network, including the type, pipe diameter, burial depth, connection mode and the like of the pipe network, simultaneously correcting and perfecting the data by detecting the data in the field to ensure the accuracy of the data, and acquiring the position and distribution data of the ground infrastructure, such as street lamps, garbage cans, fire hydrants and the like, by accessing systems of departments of electric power, communication, water supply and drainage and the like.

The historical cultural data is obtained by obtaining related information of historical buildings, cultural relics and tradition street and the like, including names, years, historical relics, cultural value and the like through local Shi Zhi and archival data, and recording the current situation and the preservation situation of professional mapping data of field investigation and mapping through professional personnel.

And performing format conversion, coordinate system unification, data cleaning and other processing on the acquired multi-source data, removing noise and error data, and ensuring the consistency and accuracy of the data. The processed multi-source data is imported into geographic information system software, so that a proper data model, such as a vector model or a grid model, is selected according to the type and characteristics of the data to organize and store the space data, and then a topological relation is constructed to ensure the logic consistency of the space data.

The method comprises the steps of associating space data such as buildings, roads, vegetation, infrastructure and the like with corresponding attribute data, realizing bidirectional inquiry and updating of the space data and the attribute data through unique identifiers, establishing an attribute database, and storing and managing detailed attribute information. The constructed data model and the attribute database are subjected to 3D modeling, rendering and symbolization through a geographic information system to obtain a GIS (Geographic Information System ) model before modification, various data of an old village are intuitively displayed through setting different colors, lines, symbols and the like, and various visual angles and browsing modes such as a two-dimensional map, a three-dimensional scene, a bird's-eye view and the like are provided, so that observation and analysis through different dimensions are facilitated.

The multi-source data in the GIS model before transformation is comprehensively analyzed by using a space analysis tool of a geographic information system, such as buffer area analysis, superposition analysis, network analysis and the like, for example, the service range of the fire-fighting facility is determined by the buffer area analysis, the area with insufficient coverage is found out, and the area with poor building quality, imperfect infrastructure and transformation potential is identified by the superposition analysis. According to the target and demand of the transformation of the old village, a corresponding evaluation index system is established, including building quality, infrastructure matching, traffic convenience, ecological environment, historical cultural protection and the like, and the weight of each index is determined by adopting a analytic hierarchy process, a Delphi method and the like, so that the key transformation direction is highlighted. And dividing the area into a key transformation area, a general transformation area, a reserved protection area and the like according to the evaluation score, thereby obtaining a target transformation area which needs key transformation.

Aiming at a target transformation area, a plurality of different transformation schemes can be formulated to meet transformation requirements from different angles and levels, a multi-criterion decision analysis method is used for comprehensively evaluating and comparing each scheme, economic benefits, social benefits, environmental benefits and other factors are considered, the optimal scheme is further optimized and perfected according to an evaluation result, and a final first multi-dimensional transformation scheme is determined.

And performing data processing on the live-action map, including point cloud filtering, texture mapping, model optimization and the like, so as to improve the quality and the visual effect of the live-action map. And (3) superposing various data in the first multi-dimensional reconstruction scheme, such as building models, road designs, greening layout and the like, on the live-action map, and carrying out space registration and data fusion to ensure accurate matching and seamless connection of the scheme and the live-action map. The simulation analysis function of the geographic information system is utilized to carry out multidimensional simulation on the superimposed scheme, wherein the multidimensional simulation comprises space layout simulation, traffic flow simulation, sunlight analysis, wind environment simulation, ecological environment influence simulation and the like, and the effect and possible problems of the scheme in practical application are evaluated through simulation. And according to the simulation result, evaluating and analyzing the first multi-dimensional reconstruction scheme to find out problems and defects in the first multi-dimensional reconstruction scheme, so as to correct and perfect the first multi-dimensional reconstruction scheme and form a second multi-dimensional reconstruction scheme.

The second multi-dimensional transformation scheme is conveyed to the operation and maintenance GIS platform, and the scheme data are butted and shared with the operation and maintenance GIS platform; and storing, managing and displaying the pattern on the operation and maintenance GIS platform so as to carry out subsequent construction, operation maintenance and management decision.

In some optional embodiments, the modified second multi-dimensional transformation scheme is submitted to relevant departments and stakeholders for auditing, and the second multi-dimensional transformation scheme is further perfected according to feedback opinion, so that the second multi-dimensional transformation scheme meets policy requirements and meets actual requirements.

s210, obtaining the topographic data of the old village to be rebuilt;

s220, constructing a terrain model of the old village to be remodeled according to the terrain data;

s230, generating a building model on the terrain model according to the building distribution data, and displaying building positions, building shapes, building equipment facilities and building aging degrees through the building model;

S240, generating a road model on the terrain model according to the road network data, and displaying road grade, road alignment, road traffic capacity and road identification through the road network;

s250, generating a vegetation water system model on the terrain model according to the vegetation water system data, and displaying vegetation type, vegetation shape, vegetation coverage area and water system through the vegetation water system model;

s260, generating an infrastructure model on the terrain model according to the infrastructure data, and displaying the type, the position and the aging degree of the infrastructure through the infrastructure model;

And S270, marking corresponding historical culture information on the building model, the road model, the vegetation water system model and the infrastructure model according to the historical culture data to obtain the GIS model before transformation of the old village to be transformed.

The application obtains high-precision topographic data through satellite remote sensing, unmanned aerial vehicle aerial survey, ground three-dimensional laser scanning and the like. The satellite remote sensing can acquire a large-scale terrain profile of the old village to be remodeled, the unmanned aerial vehicle aerial survey can acquire high-resolution data of the terrain of the old village by using a flexible flight route, and the ground three-dimensional laser scanning is used for acquiring terrain point cloud data with centimeter-level and even millimeter-level precision aiming at key areas. In addition, the application is not limited by the application, which can supplement and perfect data in combination with the existing topographic mapping results of mapping departments, such as contour map, digital Elevation Model (DEM) and the like.

The collected terrain data is imported into GIS software, and a Digital Terrain Model (DTM) is built based on the data of contour lines, heights Cheng Dian and the like through the terrain modeling function of the GIS software. Discrete elevation data is processed through interpolation algorithms such as an inverse distance weighting method, a Kriging interpolation method and the like to generate a continuous terrain surface model, and terrain features such as terrain relief, gradient, slope direction and the like of the old village are restored.

Specifically, after the terrain model is generated, the position of each building is accurately determined on the terrain model according to the coordinate information in the building distribution data. For the building shape, the two-dimensional outline can be converted into a three-dimensional building model according to outline data of the building through stretching, lofting and other operations of three-dimensional modeling software, and the appearance form of the building is intuitively displayed. For buildings with regular shapes, a parameterized modeling method can be adopted, a model is quickly generated by setting parameters such as length, width, height and the like of the building, and for buildings with complex shapes, point cloud data obtained by laser scanning can be used for reverse modeling, so that the accuracy of the model is ensured. In combination with the layout data of the internal facilities of the building, corresponding facility models such as doors and windows, stairs, elevators, pipelines and the like are added in the building models. For large public buildings, internal functional partitions such as different business areas of a mall, functions of each floor and the like can be thinned, and distribution conditions of building equipment facilities can be clearly displayed in a layering display or color distinguishing mode and the like.

The degree of aging of the building is represented by assigning different colors, textures or logos to the building model. For example, the aging degree of the building is divided into good, general, poor and the like, the good building adopts bright and complete textures, the general building textures are slightly old, the poor building has the damaged and peeled texture effect, and the model can be marked with the character information of the aging degree, so that the current situation of the building is conveniently and intuitively known. Or the aging degree of different parts of the building is displayed through corresponding aging coefficients, and specific aging display is not limited herein.

And planning the trend and the line shape of the road on the terrain model according to the road grade information in the road network data. For high-grade roads, such as arterial roads, a wider road model is adopted, multiple lanes are arranged, and for low-grade roads, such as minor lanes and branches, a narrower road model is adopted, and the specific width is determined according to the corresponding modeling proportion and is not limited. The road alignment is determined by drawing a curve or a straight line segment in a three-dimensional space according to a design drawing or actual measurement data, so that the gradient, the curve radius and the like of the road are ensured to be attached to the actual road. On the road model, road traffic capacity is represented by setting different colors, widths, or lane line patterns. For example, a road with high traffic capacity is represented by a wider lane line and a bright color, and a road with low traffic capacity is represented by a narrower lane line and a dim color. Meanwhile, a road identification model such as a traffic signal lamp, a road sign, a guideboard and the like is added to accurately display traffic information and guiding information of a road.

And generating a corresponding vegetation model on the terrain model according to vegetation type and distribution information in the vegetation water system data. For greenbelts, forests and the like with large areas, a batch generation mode can be adopted, and vegetation communities can be quickly generated by setting parameters such as density, height and the like of vegetation. For single trees or special vegetation, a fine modeling method can be adopted to simulate the actual shape and appearance of the single trees or special vegetation. Different vegetation types, such as green grasslands, dark green woods, colored flowers and the like, are distinguished by different colors and shapes, and boundaries of vegetation coverage areas are marked. Drawing the shape and position of the water system on the terrain model according to the water system data, namely generating a three-dimensional water body model for large water bodies such as rivers, lakes and the like through stretching, lofting and other operations, setting the properties such as the color, the transparency and the like of the water body, and simulating the real water surface effect. For smaller water systems such as streams and ditches, the water system can be represented by lines or tubular models, and the flow direction and the name of the water system are marked.

According to the information in the infrastructure data, various infrastructures such as electric power facilities (transformer stations, telegraph poles), communication facilities (base stations, optical cables), water supply and drainage facilities (water pipes, sewer pipes) and the like are accurately positioned on the terrain model. Corresponding infrastructure models are created through three-dimensional modeling software, and are adjusted according to the actual size and shape of the infrastructure models, so that consistency of the models and actual facilities is ensured, and the accuracy of the generation of a follow-up reconstruction scheme is improved. Similar to the method for representing the degree of aging of a building, the degree of aging is represented by giving the infrastructure model different appearance characteristics. For example, the aged water pipe can be added with textures such as rust, cracks and the like, the aged telegraph pole can be provided with inclined and damaged forms, and meanwhile, the aged degree explanation of the infrastructure is marked, so that the operation condition of the infrastructure can be conveniently known.

The historical cultural data is combed and classified, and the historical cultural information related to buildings, roads, vegetation water systems and infrastructures, such as names, years and cultural values of the historical buildings, historical religions of the traditional roads, legends of vegetation or water systems with cultural significance, historical events related to the infrastructures and the like are defined. Corresponding historical culture information is marked on the constructed building model, road model, vegetation water system model and infrastructure model by adding text marks, icons, hyperlinks and the like. For example, the name and brief introduction of the historical building model are marked, hyperlinks are added, detailed historical data and pictures can be checked by clicking, icons and words are arranged beside the traditional road to illustrate the historical background, and related story-telling and the like are marked on vegetation or a water system model with cultural value, so that the GIS model before transformation not only displays the current situation of an old village, but also inherits and displays the historical cultural connotation of the old village.

In some embodiments, before the generating the building model on the terrain model according to the building distribution data, the method further comprises:

s221, removing noise data, repeated data and abnormal values from the multi-source data through a spatial data quality control algorithm to obtain first intermediate data;

S222, performing space matching on the first intermediate data through a feature matching algorithm so that the first intermediate data has space coordinates to obtain second intermediate data;

S223, constructing a data prediction model based on historical data, wherein the historical data represents the second intermediate data of each period;

S224, predicting and supplementing missing data in the second intermediate data through the data prediction model to obtain third intermediate data, wherein the third intermediate data is used for generating the building distribution data of the building model, the road network data of the road model, the vegetation water system data of the vegetation water system model and the historical culture data marked with the historical culture information.

Specifically, the spatial data quality control algorithm of the application specifically adopts a spatial filtering algorithm, and the multi-source data is processed through the spatial filtering algorithm. The spatial filtering algorithm can effectively identify and eliminate noise points generated by measurement errors, sensor interference and other factors. For discrete noise points in the building distribution data, a distance threshold may be set, and isolated points that deviate from the subject building area (i.e., points that are more than the distance threshold from the subject building area) are treated as noise and rejected. And (3) identifying repeated data by using a method combining spatial position matching and attribute feature comparison, and for records with similar spatial positions and highly similar attribute information, such as two completely overlapped road segments or a plurality of identical facilities marked at the same position, reserving one complete record, deleting the rest repeated items and avoiding the interference of data redundancy on subsequent analysis. Outliers are detected based on statistical analysis and spatial clustering algorithms. For example, the abnormal value in the building height data is identified by using a Z-score method, if a building height exceeds the mean value by 3 standard deviations, the rationality of the building height data can be judged by combining with the field investigation or the historical data, and the truly erroneous data can be corrected or removed. Abnormal points with spatial positions which deviate from normal distribution obviously, such as building points in water, can be corrected after spatial topological relation analysis. And obtaining first intermediate data after noise point removal, repeated data deletion and abnormal point removal.

The feature extraction and matching of data from different sources is performed by feature point matching algorithms, such as SIFT (scale invariant feature transform) or SURF (speeded up robust feature) algorithms. And finding stable characteristic points in the image data with different resolutions and different visual angles, and realizing the spatial matching of the data by calculating the spatial relationship among the characteristic points. A unified coordinate system is established, and all data are converted into the coordinate system. For the data acquired from different mapping units, the situation that the coordinate systems are inconsistent is easy to exist, so that the first intermediate data are converted into the same coordinate system through the conversion of the coordinate conversion parameters, and different data of the first intermediate data can be matched to different spatial positions.

By collecting and sorting the second intermediate data of each period, the time series characteristics and the spatial evolution law of the data are analyzed. For example, the change trend of the building distribution, the aging curve of the building, the expansion process of the road network, the assembly of the infrastructure and the like are researched, key features and modes are extracted from the building distribution, and a data basis is provided for the construction of a prediction model. According to the characteristics of the data and the prediction requirements, a proper prediction model is selected, such as a time sequence analysis model (ARIMA, LSTM and the like), a spatial interpolation model (Kerling interpolation, inverse distance weighted interpolation and the like) or a machine learning model (random forest, support vector machine and the like). Taking building distribution data as an example, if building information of a partial area is missing, the building distribution situation of the missing area can be predicted by using a spatial interpolation model based on building characteristics and historical development trend of the peripheral area. Or the building aging information of the partial area is missing, the aging curve (namely the prediction curve in the data prediction model) of the building in the missing area can be constructed based on the historical aging information, and the building aging information of the missing area is predicted based on the aging curve.

And inputting the second intermediate data into a trained data prediction model, and predicting and supplementing the missing data in the second intermediate data through the data prediction model. After the prediction supplement is completed, the accuracy and the reliability of the prediction result are evaluated through comparison and verification with known data. For the region with larger prediction error, the method can combine expert knowledge and field investigation to carry out manual correction, and ensure the integrity and accuracy of the third intermediate data. It is easy to know that 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 history culture data for labeling the history culture information all belong to the third intermediate data.

In some embodiments, the obtaining the target reconstruction area of the old village to be reconstructed based on the pre-reconstruction GIS model after analyzing the multi-source data includes:

S310, determining fire control coefficients and pass coefficients of all areas according to the road network data and the building distribution data corresponding to all areas on the GIS model before transformation, wherein the fire control coefficients represent the fire control capacity of all areas, and the pass coefficients represent the pass capacity of all areas;

s320, generating a geological disaster risk distribution map according to geological feature data corresponding to each region on the GIS model before transformation, and determining geological disaster risk coefficients of each region on the GIS model before transformation based on the geological disaster risk distribution map;

s330, determining building quality coefficients of all areas according to the building distribution data corresponding to all areas on the GIS model before transformation;

s340, determining infrastructure improvement coefficients of all areas according to the infrastructure data corresponding to all areas on the GIS model before transformation;

S350, determining greening coefficients of all areas according to the vegetation water system data corresponding to all areas on the GIS model before transformation;

s360, determining the historical culture value coefficients of all the areas according to the historical culture data corresponding to all the areas on the GIS model before transformation;

S370, determining transformation coefficients of all areas on the GIS model before transformation according to the fire control coefficients, the pass coefficients, the geological disaster risk coefficients, the building quality coefficients, the infrastructure improvement coefficients, the greening coefficients and the historical cultural value coefficients of all areas on the GIS model before transformation;

s380, configuring the area with the transformation coefficient larger than or equal to a preset coefficient as the target transformation area.

Specifically, since the old village is narrow in road and old in building, the fire-fighting capability and the road traffic capability are difficult to meet the fire-fighting requirement and the traffic requirement. According to road network data (road width, turning radius, clearance height) and building distribution data (building spacing, height and density), calculating the shortest path of the fire engine from the nearest fire station to each building through GIS network analysis, buckling if the path width is less than 4m or the turning radius is less than 9m, checking whether the building spacing meets corresponding requirements (buckling if the multi-layer building spacing is less than 6 m) through buffer area analysis, generating a 50m service buffer area based on the hydrant distribution data, and calculating the water source coverage rate of the building in the area. The specific fire control coefficient is calculated as follows:。

the road traffic capacity calculation comprises the steps of determining the corresponding main road traffic capacity according to road grades, simulating the early and late peak congestion condition by combining historical flow data and traffic demands generated by buildings, and evaluating the pavement width, street crossing facilities and the perfection of barrier-free channels. The calculation formula of the pass coefficient is as follows: 。

The geological feature data of the application comprise terrain gradient, rock-soil layer type, groundwater level, historical disaster point distribution (landslide, collapse, mud-rock flow) and the like, and are not particularly limited. Weight distribution is performed by an Analytic Hierarchy Process (AHP), such as gradient (0.3), rock-soil layer stability (0.25), groundwater level (0.2) and historical disasters (0.25). And determining different factor scores through gradients of different values, stability of the rock and soil layers, underground water levels and scattered rocks of historical disasters, and performing superposition calculation on the factor scores and weights of different areas to obtain corresponding risk distribution diagrams. The risk distribution map can clearly display the geological disaster risk coefficient of each region on the GIS model before transformation.

The quality coefficient of the building is calculated, the quality assignment can be primarily performed according to the age of the building, the secondary assignment is performed by combining the structure type of the building, and the tertiary assignment is performed according to the damage degree of the building, so that the corresponding quality coefficient of the building is determined according to the tertiary assignment.

For the calculation of the infrastructure perfection coefficients, comprehensive consideration can be performed by aging, layout and the like of the infrastructure. For example, for a water supply and drainage pipe network (pipe diameter <100 mm buckle 0.3, ageing rust buckle 0.2, fully divided into 1), an electric power facility (transformer capacity is insufficient buckle 0.3, line clutter buckle 0.2, fully divided into 1), a communication network (optical fiber coverage rate <50% buckle 0.4, fully divided into 1), and the like, specific infrastructure and scoring items are set according to actual requirements, and are not limited herein. And calculating the corresponding perfection coefficient according to the deducted score.

For greening coefficient calculation, scoring can be performed by green space ratio (current green space ratio/planning standard green space ratio, over 1.2 assignment 1,0.8-1.2 assignment in proportion, <0.8 linear deduction), arbor coverage (crown projected area/total area, >30% assignment 0.8,10% -30% assignment in proportion, <10% assignment 0.2) and water system integrity (natural water system intrusion length ratio, per 10% deduction 0.1). And determining the greening coefficient according to the total score.

For the calculation of the historical cultural value coefficient, comprehensive scoring can be carried out through cultural relics protection units (national level 1.0, provincial level 0.8 and municipal level 0.6), traditional building feature integrity (feature integrity >80% assignment 0.7,50% -80% assignment 0.4, <50% assignment 0.1) and non-material cultural heritage relevance (non-heritage item assignment 0.5 above provincial level and municipal level 0.3). Thereby determining the historical cultural value coefficient according to the specific score.

Different full weights, such as a fire control 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 cultural value coefficient (0.15), are allocated to different coefficients, so that the transformation coefficient is calculated in a weighted mode.

Through the GIS symbolization function, the region with the transformation coefficient of more than 0.6 is marked red, the region with the transformation coefficient of more than 0.4 to 0.6 is marked yellow, the region with the transformation coefficient of less than 0.4 is marked green, and finally the red region is extracted as a target transformation region.

s381, determining a first priority ranking of each target subarea according to the transformation coefficients corresponding to each target subarea in the target transformation area;

s382, evaluating the transformation benefits of each target subarea through a preset economic benefit model to obtain benefit indexes of each target subarea;

S383, correcting the first priority order according to the benefit index to obtain a second priority order;

s384, determining the influence coefficients among the target subareas through a network analysis method;

S385, correcting the second priority order according to the influence coefficient to obtain a third priority order, so that each target subarea is modified according to the third priority order in sequence.

Specifically, the transformation coefficients of all target subareas in the target transformation area reflect the transformation urgency of the subareas in aspects such as fire fighting, passing, geological disaster risks and the like, the higher the numerical value is, the more urgent the transformation requirements are, the preliminary sequencing is carried out according to the urgent transformation demands, the first priority sequencing is obtained, and the preliminary sequence of transformation is defined. And specifically, extracting transformation coefficients of each target subregion, and then carrying out descending order arrangement to assign a corresponding ordering number to each subregion. For example, the subregion with the highest reconstruction coefficient is ordered to be 1, and so on, forming a first prioritized list.

The economic benefit model is preset, the input and the output of transformation are quantitatively analyzed, the transformation benefit of each target subarea is evaluated, the benefit index is obtained, the feasibility and the value of transformation are measured from the economic angle, and an economic basis is provided for priority adjustment. The economic benefit model comprehensively considers the indexes such as construction cost, expected income, investment recovery period and the like. Construction cost including land collection, building demolition, material purchase, labor cost and the like, and expected benefits including land increment, house property increment, business income increment, economic benefit of social benefit conversion caused by public service facility improvement and the like. And calculating the benefit index through a preset formula, wherein the benefit index is obtained by the benefit index = expected benefit current value/construction cost current value. And the first priority ranking is corrected by combining the benefit indexes, so that the reconstruction sequence not only considers the urgency of regional reconstruction, but also considers economic rationality, resource waste caused by blind reconstruction is avoided, and the maximization of the economic benefit of reconstruction projects is ensured. The specific second priority ranking determination method comprises the steps of comprehensively analyzing the benefit indexes and the transformation coefficients in the first priority ranking, endowing the transformation coefficients with a weight alpha and a benefit index weight beta (alpha+beta=1) in a weighted fusion mode, calculating new priority = alpha multiplied by the transformation coefficient ranking score + beta multiplied by the benefit index ranking score, and recalculating priority scores of all target subareas, and adjusting ranking according to the score to obtain the second priority ranking.

The determining of the influence coefficient comprises the steps of considering the mutual influence relation between target subareas through a network analysis method (ANP), determining the influence coefficient through analyzing factors such as resource flow, functional complementation, traffic connection and the like among the subareas, and reflecting the driving or restricting action of the area transformation on other areas. Specifically by constructing an ANP model comprising a control layer (engineering targets, principles, etc.) and a network layer (target sub-regions and interrelationships). And carrying out pairwise comparison scoring on the influence degree among all the subareas according to a preset scoring rule, and constructing a judgment matrix. And obtaining the influence coefficients among all the target subareas through matrix operation to form an influence coefficient matrix. And (3) revising the second priority sequence again according to the influence coefficient, preferentially reforming the subareas with a stronger driving effect on the peripheral area (such as preferentially reforming the subareas at two sides of the road, or preferentially reforming the outermost subareas, sequentially reforming along the road and the like, and specifically not limiting), promoting the collaborative development of the areas, improving the overall reforming effect and realizing the optimal allocation of resources.

The specific third prioritization determining method includes that the influence coefficient is integrated into the second prioritization score calculation. Based on the original calculation, the influence coefficient weight gamma (alpha+beta+gamma=1) is increased, the final priority = alpha×transformation coefficient sorting score+beta×benefit index sorting score+gamma×influence coefficient sorting score is recalculated, the priority score of each target subarea is regulated and sorted according to the new score, and the third priority sorting is obtained. And each target subarea sequentially carries out transformation work according to the third priority order, so that the transformation work is scientifically, orderly and efficiently carried out.

In some embodiments, the generating the first multi-dimensional reconstruction scheme of the target reconstruction region according to reconstruction requirements includes:

S410, determining a first demand level of each demand index in the reconstruction demand according to a preset demand degree and a regional reconstruction target;

s420, correcting the first demand level according to public demand data to obtain a second demand level, wherein the public demand data is collected by a public demand collection system;

S430, sequentially comparing the index difference value maps of the demand index and a target index according to the first demand level, wherein the target index represents an index corresponding to the demand index in the target transformation area;

S440, generating the first multi-dimensional transformation scheme of the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure and the optimal historical culture protection measures according to the index difference value map.

Specifically, the requirement indexes can be divided into mandatory requirements (such as fire protection specifications and safety standards), guided requirements (such as greening coverage rate and public service facility configuration) and elastic requirements (such as feature style modeling and industry development), and meanwhile, based on corresponding construction specifications and combined with local policy files, the standard value and ideal value of each index are determined, namely the preset requirement degree is obtained.

And determining the priority of each index according to the regional transformation target, wherein if the transformation target is 'ecological livability', the priority of ecological environment-friendly indexes (such as green land rate and sponge city construction) is improved, and if the transformation target is 'historical cultural inheritance', the index weights of the historical building protection, the traditional street and roadway pattern and the like are increased.

And constructing a demand index hierarchical structure by adopting an Analytic Hierarchy Process (AHP), and scoring and determining each index weight. For example:

The safety requirement (0.3) is that the width of the fire-fighting channel (0.15) and the building spacing (0.15);

Functional requirements (0.25) public service coverage (0.12), traffic reachability (0.13);

ecological requirements (0.2) green land rate (0.1) and carbon emission control (0.1);

Cultural requirements (0.15), historical building retention (0.08), traditional style integrity (0.07);

economic requirements (0.1) including return on investment (0.06) and land utilization efficiency (0.04).

The public demand data collection and correction comprises the steps of collecting suggestions through a corresponding mobile terminal questionnaire system and an opinion collecting system to determine the public demand, or determining the public demand through offline investigation and collection suggestions, or analyzing public comments, requests and the like through big data to obtain the corresponding public demand.

Classifying and quantifying public opinion, and incorporating the high-frequency mentioned demand into an index system, thereby obtaining a second demand level after correcting the first demand level according to public demand data.

Dividing the target transformation area into a plurality of grid cells, ensuring that each cell contains complete analysis elements, constructing space topological relations of elements such as buildings, roads, greening and the like, and ensuring data consistency. The quantitative indexes (such as greenbelt rate and volume rate) are subjected to dimensionless treatment, Z-score standardization is adopted, and qualitative indexes (such as historical landscape integrity) are subjected to grading quantification, such as 'complete' =4 points, 'more complete' =3 points, 'general' =2 points and 'worse' =1 point. And generating a heat map visual result (namely an index difference map), thereby intuitively displaying the spatial distribution of the demand gap.

And optimizing the building layout by applying a genetic algorithm and taking the space utilization rate, the sunlight interval and the ventilation condition as objective functions so as to generate the optimal building layout.

According to the target index difference value related to the road, based on land utilization function and population scale, the traffic generation amount after transformation is predicted, meanwhile, a traffic model is applied to simulate traffic flow, a graph theory algorithm is applied to analyze the connectivity of the road network, a bottleneck road section is identified, a multi-level road system (main road-secondary road-branch road-roadway) is constructed, the full coverage of a fire-fighting channel is ensured, and therefore the optimal road network is obtained.

And (3) identifying ecological source land and ecological corridor according to the greening related target index difference value and based on ecological sensitivity analysis, and planning a greenbelt system by applying a minimum accumulated resistance Model (MCR). And simulating the runoff of the rainwater by using a SWMM (Storm flood management Model) Model, and optimizing the layout of facilities such as a sinking green land, a rainwater garden and the like, thereby generating the optimal greening layout.

Optimizing the trend of pipe networks such as water supply and drainage, electric power, communication and the like according to the target index difference value related to the infrastructure and based on terrain analysis and building layout, calculating pipe diameter and gradient by applying a hydraulic model, ensuring that the drainage capacity meets the storm standard, and further generating the optimal infrastructure.

According to the target index difference value related to the historical culture, a core protection area, a construction control zone and a wind form coordination area are defined based on historical building evaluation and space syntactic analysis, a historical building digital file is established, building information and repair suggestions are recorded, and then optimal historical culture protection measures are obtained.

In some embodiments, the generating the first multi-dimensional modification of the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, and the optimal historical cultural protection measure according to the index difference map comprises:

s441, determining a building reconstruction target according to the building index difference value in the index difference value map;

S442, determining the optimal building layout of the target transformation area according to the building transformation target and a building differential transformation strategy, wherein the building differential transformation strategy represents a reserved, repaired, dismantled or newly built strategy formulated according to the building quality and the transformation requirement;

s443, determining a road transformation target according to the road index difference value in the index difference value map;

S444, calculating according to the road reconstruction target, a shortest path algorithm and a minimum spanning tree algorithm to obtain the optimal road network;

s445, determining a greening transformation target according to the greening index difference value in the index difference value map;

s446, determining an infrastructure transformation target according to the infrastructure index difference value in the index difference value map;

S447, calculating according to the infrastructure transformation target, a pipe network system planning algorithm and a sponge city planning algorithm to obtain the optimal infrastructure;

S448, determining a historical culture transformation target according to the historical culture index difference value in the index difference value map;

And S449, determining the optimal historical culture protection measures according to the historical culture transformation target and the differentiated building.

Specifically, the current value and the target value differences of the indexes such as the building density, the volume rate, the sunlight interval, the building height and the like are extracted from the index difference map. For example, if the current building density is 60% and the target value is 45%, it is determined that "lowering the building density" is the target of building modification. The method comprises the steps of identifying a specific area with overproof building density through GIS space superposition, combining building quality assessment (such as structural safety and service life), forming a high-density and low-quality preferential reconstruction area map, combining building differential reconstruction strategies to generate an optimal building layout, namely building with good building quality and meeting planning, retaining a main structure, only carrying out elevation repair and function optimization, adopting measures such as reinforcing foundations, replacing damaged components and the like for a building with general building quality, simultaneously improving earthquake-proof fortifying grades, formulating dismantling time sequences for the building with poor building quality or the building with planning violation, synchronously planning temporary arrangement schemes, adopting parameterization design to generate a newly built building model meeting requirements on sunshine and space in the dismantling area or idle land, such as volume rate control, optimizing through genetic algorithm, maximizing building area on the premise of meeting sunshine standards, housing type proportion, and preferentially configuring suitable aging housing types based on population structure data (such as aging rate).

The generation of the optimal road network comprises the steps of firstly extracting index differences of road width, traffic capacity, fire-fighting channel coverage rate and the like, so as to obtain a road transformation target. For example, if the current main road width is less than 12m (target value 15 m) and the fire-fighting channel coverage is only 60% (target value 100%), the "widening main road+encrypting fire-fighting channel" is determined as the road modification target.

And then calculating the shortest path to each building by taking the fire station as a starting point, identifying a bottleneck road section with the width of <4m, generating a forced widening list, and planning a parallel alternative route on a congestion road section (the journey time is more than 20 minutes) by combining traffic flow prediction (such as the peak traffic flow in the morning and evening). The construction cost (land-feature cost and construction cost) is regarded as weight to generate a minimum cost road network for connecting all groups, road sections with high grade and good road condition of the current road are reserved in priority, the transformation cost is reduced, and therefore the optimal road network is generated.

The optimal greening layout generation comprises the steps of extracting index differences of greenbelt rate (such as current 20% -target 35%), arbor coverage (such as current 15% -target 25%), ecological corridor integrity (such as current breaking point 5% -target 0) and the like, and determining a greening transformation target. On the basis of terrain and water system data, identifying ecological source land (such as a sheet-forming forest land) and a potential corridor by using a minimum accumulated resistance Model (MCR), planning a greening connecting belt with the width of more than or equal to 10m at a breaking point preferentially, dividing a green land service range by using a Voronoi (Wo Luo Nori) graph, ensuring that the coverage rate of a 500m (which is only used as an example and not limited) service radius is increased from 60% to 85% (which is only used as an example and not limited), and generating the optimal greening layout.

The generation of the optimal infrastructure comprises the steps of extracting index differences of pipe diameters of drainage pipe networks (such as current pipe diameter 300mm and target pipe diameter 500 mm), sewage treatment rate (such as current 40% -target 90%), renewable energy source ratio (such as current 5% -target 20%), and the like, and determining an infrastructure transformation target. And then simulating storm runoff by using a hydraulic model based on the terrain elevation data, lifting the drainage capacity from 1 year to 3 years, carrying out topology analysis on the current pipe network, and identifying pipe sections with insufficient pipe diameter and downhill gradient to generate a corresponding pipe network reconstruction scheme. And after all infrastructure improvement schemes are determined, the optimal infrastructure can be obtained.

The generation of the optimal historical culture protection measures comprises the steps of extracting index differences of historical building retention rate (such as 30% of current situation, namely 80% of target), traditional street integrity (such as 40% of current situation, namely 70% of target), culture display space ratio (such as 5% of current situation, namely 15% of target) and the like, and determining corresponding historical culture transformation targets. Then adopting a 'primordial restoration' strategy (the specific strategy is not limited), using traditional materials (such as green bricks and wood) and processes, prohibiting changing building forms, allowing internal function modification (such as living-culture display) of a historical building, keeping external elevation and a structural system unchanged, properly adjusting building height (less than or equal to 2 layers) of the traditional landscape building, continuing the landscape characteristic of 'pink wall tile', and then identifying 'high-integration' nodes (such as historical squares and bridge heads) in the traditional street and preferentially modifying the nodes into culture display spaces based on space syntactic analysis, so as to generate optimal historical culture protection measures.

In some embodiments, after the first multi-dimensional transformation scheme is superimposed on the live-action map corresponding to the target transformation area, the simulating the first multi-dimensional transformation scheme to obtain a simulation result includes:

s510, respectively and correspondingly superposing the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure and the optimal historical culture protection measure of the first multi-dimensional transformation scheme with the live-action map one by one so as to enable the live-action map to be accurately matched with the first multi-dimensional transformation scheme;

S520, reconstructing the GIS model before reconstruction according to the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure, the optimal historical culture protection measures and the third priority order in sequence to obtain a GIS model after reconstruction;

And S530, performing spatial performance simulation, environmental performance simulation, traffic performance simulation, economic performance evaluation and historical cultural value evaluation on the modified GIS model to obtain a simulation evaluation report and a modification score, wherein the simulation result comprises the simulation evaluation report and the modification score.

Specifically, the space coordinates corresponding to the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure and the optimal historical culture protection measures of the first multi-dimensional transformation scheme are respectively overlapped with the real map in a one-to-one correspondence mode, so that the first multi-dimensional transformation scheme is displayed on the specific real map, the accurate matching of the real map and the first multi-dimensional transformation scheme can be ensured, and the specific transformation scheme can be displayed more intuitively. And updating the GIS model before modification according to the optimal building layout, the optimal road network, the optimal greening layout, the optimal infrastructure and the optimal historical culture protection measures of the first multi-dimensional modification scheme, so that a modified GIS model is obtained, and the display of the modified GIS model is the GIS model after modification of the old village through the first multi-dimensional modification scheme. And superposing the first multi-dimensional reconstruction scheme on the live-action map, namely, corresponding the reconstructed GIS model to a specific live-action space, so that corresponding space position correction can be performed according to the matching property of the live-action space and the first multi-dimensional reconstruction scheme (if the A area of the first multi-dimensional reconstruction scheme is matched with the B area of the live-action space, the A area of the first multi-dimensional reconstruction scheme and the B area of the first multi-dimensional reconstruction scheme are mutually exchanged).

The space performance simulation of the modified GIS model comprises space syntax analysis, integration degree calculation based on an axis model, space accessibility change evaluation after modification, solar ventilation simulation, fluid simulation and determination of ventilation performance among buildings by simulating the solar time from winter to solar full window, and further a space performance simulation result.

The traffic performance simulation of the modified GIS model comprises dynamic traffic flow simulation and parking demand prediction, so that a corresponding traffic performance simulation result is obtained. The environmental performance simulation includes calculating carbon emissions through a carbon footprint calculation model and determining corresponding rain drainage functions through a rain management simulation, thereby generating environmental performance simulation results. Economic performance evaluation includes cost effectiveness analysis and associated economic factor analysis. The historical cultural value evaluation comprises a style integrity index evaluation and a cultural space vitality evaluation, and further a historical cultural value evaluation result is generated. And generating corresponding simulation evaluation reports and transformation scores by combining the traffic performance simulation results, the environmental performance simulation results, the economic performance evaluation results and the historical cultural value evaluation results, thereby determining corresponding correction items and correction values according to the simulation evaluation reports and the transformation scores, and further correcting to obtain a second multidimensional transformation scheme.

In some optional embodiments, the difference between the old village to be reformed before and after the reforming is dynamically displayed through the post-reforming GIS model, specifically, the dynamic simulation of the reforming process can be displayed according to the requirement, the corresponding subareas can be selected for the dynamic simulation of the reforming, or a plurality of subareas are selected for the dynamic simulation of the reforming with different simulation speeds.

As shown in fig. 2, fig. 2 shows a block diagram of a controller 1000 according to an embodiment of the present application. 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 for storing data.

The controller 1000 also includes an access device that enables the controller 1000 to communicate via one or more networks. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a 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 network interface, wired or wireless (e.g., a Network Interface Card (NIC)), such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.

The controller 1000 may be any type of stationary or mobile electronic device, including a mobile computer or mobile electronic device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile telephone (e.g., smart phone), wearable electronic device (e.g., smart watch, smart glasses, etc.), or other type of mobile device, or a stationary electronic device such as a desktop computer or PC. The controller 1000 may also be a mobile or stationary server.

Wherein the processor 1100 is configured to execute computer-executable instructions of a planning scheme generation method for old village modification.

The above is a schematic solution of a controller of the present embodiment. It should be noted that, the technical solution of the controller and the technical solution of the above-mentioned old village reconstruction planning solution generating method belong to the same concept, and details of the technical solution of the controller which are not described in detail can be referred to the description of the technical solution of the above-mentioned old village reconstruction planning solution generating method.

The application also provides a planning scheme generation system for old village reconstruction. The old village modified planning scheme generation system comprises a sickbed, wherein the controller 1000 is installed in the sickbed, or the sickbed is in communication connection with the controller 1000, so that the sickbed can be adjusted through the controller 1000. It should be noted that, the technical solution of the old village reconstruction planning solution generating system and the technical solution of the old village reconstruction planning solution generating method belong to the same concept, and details of the technical solution of the computing device which are not described in detail can be referred to the description of the technical solution of the old village reconstruction planning solution generating method.

The embodiment of the application also provides a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program which realizes the old village reconstruction planning scheme generation method when being executed by a processor.

The memory, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as 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, flash memory device, or other non-transitory solid state storage device. In some implementations, the memory may include memory that is remotely located relative to the processor, and the remote memory may be connected to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The apparatus embodiments described above are merely illustrative, in which the elements illustrated as separate components may or may not be physically separate, implemented to reside in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

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

While the preferred embodiment of the present application has been described in detail, the present application is not limited to the above embodiments, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit and scope of the present application, and these equivalent modifications or substitutions are included in the scope of the present application as defined in the appended claims.

Claims

1. A method for generating a planning scheme for old village modification, comprising:

The method specifically comprises the steps of analyzing the multi-source data based on a pre-transformation GIS model to obtain target transformation areas of old villages to be transformed, determining fire protection coefficients and passing coefficients of all areas according to the road network data and the building distribution data corresponding to all areas on the pre-transformation GIS model, characterizing the fire protection capacity of all areas by the fire protection coefficients, characterizing the passing capacities of all areas by the passing coefficients, generating a geological disaster risk distribution map according to the geological feature data corresponding to all areas on the pre-transformation GIS model, determining the geological disaster risk coefficients of all areas on the pre-transformation GIS model based on the geological disaster risk distribution map, determining the building quality coefficients of all areas according to the building distribution data corresponding to all areas on the pre-transformation GIS model, determining the infrastructure perfection coefficients of all areas according to the infrastructure data corresponding to all areas on the pre-transformation GIS model, determining the greening coefficients of all areas according to the GIS data corresponding to all areas on the pre-transformation GIS model, determining the geological disaster risk coefficients of all areas according to the pre-transformation GIS model, and the building coefficient of all areas according to the pre-transformation history coefficient;

Correcting the second priority sequence according to the influence coefficient to obtain a third priority sequence, so that each target subarea is modified according to the third priority sequence in sequence;

2. The old village reconstruction planning scheme generation method according to claim 1, wherein the constructing the pre-reconstruction GIS model of the old village to be reconstructed according to the multi-source data comprises:

acquiring the topographic data of the old village to be modified;

3. The old village retrofit planning scheme generation method according to claim 2, wherein before generating a building model on the terrain model according to the building distribution data, further comprising:

4. The old village reconstruction planning scheme generation method according to claim 1, wherein the generating the first multi-dimensional reconstruction scheme of the target reconstruction area according to the reconstruction requirement comprises:

sequentially comparing the index difference value maps of the demand index and a target index according to the second demand level, wherein the target index represents an index corresponding to the demand index in the target transformation area;

5. The method of generating a planning solution for old village modification of claim 4, wherein said generating said first multi-dimensional modification solution for optimal building layout, optimal road network, optimal greening layout, optimal infrastructure and optimal historical culture protection measures from said index difference map comprises:

6. The method for generating a planning solution for old village reconstruction according to claim 4, wherein after the first multi-dimensional reconstruction solution is superimposed on a live-action map corresponding to the target reconstruction area, simulating the first multi-dimensional reconstruction solution to obtain a simulation result comprises:

7. A old village-remodeled plan generation system comprising a controller including a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the old village-remodeled plan generation method as claimed in any one of claims 1 to 6 when the computer program is executed.

8. A computer storage medium having stored thereon computer executable instructions for performing the old village retrofit planning scheme generation method according to any one of claims 1-6.