Planning height control evaluation method and system related to historical and cultural heritage resources in urban update project

Abstract

The invention discloses a planning height control evaluation method for historical and cultural heritage resources involved in a city update project, and the method comprises the steps: obtaining project data and map data of the city update project, and the map data comprises three-dimensional building model data of the city update project; dividing the map data according to grids by using a software tool to generate a plurality of target analysis units; processing the unit data of the target analysis units to obtain index data of evaluation indexes of the target analysis units; obtaining a planning height control evaluation index system, wherein the planning height control evaluation index system comprises a plurality of evaluation indexes and weight values of the evaluation indexes; calculating a comprehensive score of each target analysis unit based on the index data of each target analysis unit and the weight value of each evaluation index; and based on K-means classification and the comprehensive score of each target analysis unit, classifying and evaluating each target analysis unit.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to a planning height control evaluation method and system involving historical and cultural heritage resources in an urban renewal project. Background Art

[0002] Building height plays an important role in urban form, determining the overall appearance of the city, as well as the space and scale within the city. With the rapid development of modern cities, the height of urban buildings has been continuously broken, and urban development and construction have caused impacts and damage to the city's historical and cultural heritage resources, which has become a common problem in the protection of historical and cultural heritage resources.

[0003] Urban height control has always been an important part of urban renewal planning. However, contemporary buildings in urban renewal projects have a certain impact on the city's historical and cultural heritage resources, such as the destruction of the city's characteristic historical landscapes, important historical landscape sights, and the spatial organization and layout of historical and cultural heritage resources.

[0004] Although the current urban renewal planning will have a high degree of control over the areas where the historical and cultural heritage resources are located, there is no relevant technology for the evaluation of the high degree of planning control in the existing technology, which fails to provide reasonable technical support and reference for planners. Therefore, it is necessary to provide an evaluation technology for the high degree of planning control in urban renewal projects. Summary of the invention

[0005] In order to overcome the above technical defects, the present invention provides a planning height control evaluation method and system for historical and cultural heritage resources in urban renewal projects.

[0006] In order to solve the above problems, the present invention is implemented according to the following technical solutions:

[0007] In a first aspect, the present invention provides a method for evaluating the planning height control of historical and cultural heritage resources in an urban renewal project, comprising the following steps:

[0008] Acquire project data and map data of the urban renewal project, wherein the map data includes three-dimensional building model data of the urban renewal project;

[0009] Use software tools to divide map data into grids to generate multiple target analysis units;

[0010] Assigning project data to a number of target analysis units to obtain unit data of the target analysis units;

[0011] Acquire a planning height control evaluation index system, wherein the planning height control evaluation index system includes a plurality of evaluation indicators and weight values ​​of the evaluation indicators;

[0012] Processing the unit data of the target analysis unit to obtain indicator data of the evaluation indicator of each target analysis unit;

[0013] Based on the indicator data of each target analysis unit and the weight value of each evaluation indicator, calculate the comprehensive score of each target analysis unit;

[0014] Based on K-means classification and the comprehensive score of each target analysis unit, each target analysis unit is classified and evaluated.

[0015] In combination with the first aspect, the present invention further provides a first preferred implementation of the first aspect, specifically, using a software tool to divide the map data into grids to generate a plurality of target analysis units, specifically including:

[0016] Obtain AOI data of historical and cultural heritage architectural resources;

[0017] Inserting the AOI data into the map data to generate a historical building resource area in the map data;

[0018] Use software tools to divide the map data into 50M*50M grids to obtain multiple grid units;

[0019] Using the historical building resource area, the part of each grid unit that overlaps with the historical building resource area is clipped to obtain the target analysis unit.

[0020] In combination with the first aspect, the present invention further provides a second preferred implementation of the first aspect, specifically, assigning project data to a plurality of target analysis units, specifically including:

[0021] Process the project data in a unified coordinate system to generate surface data;

[0022] Using the surface data, the surface attribute data is assigned to the target analysis unit to obtain the unit data of the target analysis unit.

[0023] In combination with the first aspect, the present invention further provides a third preferred implementation of the first aspect, specifically, based on the indicator data of each target analysis unit and the weight value of each evaluation indicator, calculating the comprehensive score of each target analysis unit, specifically including:

[0024] Obtain indicator data of the target analysis unit;

[0025] Standardizing the indicator data to obtain an indicator value for each evaluation indicator;

[0026] Based on the indicator value and weight value of the evaluation indicator, the comprehensive score of each target analysis unit is calculated.

[0027] In combination with the first aspect, the present invention further provides a fourth preferred implementation of the first aspect. Specifically, the calculation formula of the comprehensive score of the target analysis unit is:

[0028]

[0029] In the formula, S i is the comprehensive score of the i-th target analysis unit; P ij is the index value of the jth target analysis unit in the i-th target analysis unit; W j is the weight value of the jth evaluation indicator, and n represents the total number of indicators in the planning height control evaluation indicator system.

[0030] In combination with the first aspect, the present invention also provides a fifth preferred implementation scheme of the first aspect. Specifically, the evaluation indicators of the planning height control evaluation index system include the highest building height, average building height, current building height, distance from the center, building coverage rate, building development intensity, street view openness rate and sky openness.

[0031] In a second aspect, the present invention also provides a planning height control and evaluation system for historical and cultural heritage resources in an urban renewal project, comprising:

[0032] An acquisition module, which is used to acquire project data and map data of an urban renewal project, wherein the map data includes three-dimensional building model data of the urban renewal project;

[0033] A generation module, which is used to divide the map data into grids using a software tool to generate multiple target analysis units;

[0034] An assignment module, which is used to assign project data to a number of target analysis units to obtain unit data of the target analysis units;

[0035] An indicator system module, which is used to obtain a planning height control evaluation indicator system, wherein the planning height control evaluation indicator system includes a plurality of evaluation indicators and weight values ​​of the evaluation indicators;

[0036] A processing module, which is used to process the unit data of the target analysis unit to obtain the indicator data of the evaluation indicator of each target analysis unit;

[0037] A calculation module, which is used to calculate the comprehensive score of each target analysis unit based on the indicator data of each target analysis unit and the weight value of each evaluation indicator;

[0038] The classification and evaluation module is used to classify and evaluate each target analysis unit based on K-means classification and the comprehensive score of each target analysis unit.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention provides a planning height control evaluation method for historical and cultural heritage resources in an urban renewal project, comprising the following steps: obtaining project data and map data of the urban renewal project, wherein the map data includes three-dimensional building model data of the urban renewal project; using a software tool to divide the map data into grids to generate a plurality of target analysis units; assigning project data to a plurality of target analysis units to obtain unit data of the target analysis units; processing the unit data of the target analysis units to obtain index data of evaluation indexes of each target analysis unit; obtaining a planning height control evaluation index system, wherein the planning height control evaluation index system includes a plurality of evaluation indexes and weight values ​​of the evaluation indexes; calculating a comprehensive score of each target analysis unit based on the index data of each target analysis unit and the weight values ​​of each evaluation index; and classifying and evaluating each target analysis unit based on K-means classification and the comprehensive score of each target analysis unit.

[0041] The invention can effectively and objectively evaluate the planning height control of historical and cultural heritage resources involved in urban renewal projects, guide the planning height control in urban renewal projects, ensure that historical and cultural heritage are properly protected, and also meet the needs of urban development.

[0042] The technology provided by the present invention can provide the government with decision-making support and analysis tools for urban renewal planning, realize the effective protection of historical and cultural heritage resources in urban renewal projects, and achieve a balance between protection and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings, wherein:

[0044] Figure 1 It is a flow chart of a planning height control evaluation method involving historical and cultural heritage resources in an urban renewal project of the present invention;

[0045] Figure 2 It is a schematic diagram of the network structure of the encoding stage of the present invention;

[0046] Figure 3 It is a schematic diagram of the network structure of the decoding stage of the present invention;

[0047] Figure 4 It is a schematic diagram of the network structure in the fusion stage of the present invention. DETAILED DESCRIPTION

[0048] The following specifically illustrates the implementation mode of the present invention in conjunction with the accompanying drawings. The embodiments are provided for illustrative purposes only and cannot be understood as limiting the present invention. The accompanying drawings are provided for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0049] Regarding historical and cultural heritage resources, in the present invention, historical and cultural heritage resources specifically refer to historical buildings, historical building complexes, historical building sites, etc. in the city. These historical and cultural heritage resources are located in the city.

[0050] Urban height control has always been an important part of planning in urban renewal projects. However, contemporary buildings in urban renewal projects have a certain impact on the city's historical and cultural heritage resources, such as the destruction of the city's characteristic historical landscapes, important historical landscape sights, and the spatial organization and layout of historical and cultural heritage resources. Although the current urban renewal planning will carry out height control on the areas where historical and cultural heritage resources are located. However, in the existing technology, there is no relevant technology for the evaluation of planning height control, which fails to provide reasonable technical support and reference for planners. Therefore, it is necessary to provide an evaluation technology for planning height control in urban renewal projects.

[0051] For this purpose, refer to Figure 1 The embodiment of the present invention provides a flow chart of a method for evaluating the planning height control of historical and cultural heritage resources in urban renewal projects. The method of the present invention can effectively and objectively evaluate the planning height control of historical and cultural heritage resources in urban renewal projects, guide the planning height control in urban renewal projects, ensure that historical and cultural heritage is properly protected, and also meet the needs of urban development.

[0052] The method for evaluating the planning height control of historical and cultural heritage resources in urban renewal projects of the present invention can be performed by a system for evaluating the planning height control of historical and cultural heritage resources in urban renewal projects. The system can be implemented in the form of hardware and / or software, and the system can be configured in a computer. Figure 1 As shown, the method includes:

[0053] S100: Acquire project data and map data of an urban renewal project, wherein the map data includes three-dimensional building model data of the urban renewal project;

[0054] S200: using software tools to divide the map data into grids to generate multiple target analysis units;

[0055] S300: Assigning project data to a number of target analysis units to obtain unit data of the target analysis units;

[0056] S400: Acquire a planning height control evaluation index system, wherein the planning height control evaluation index system includes a plurality of evaluation indicators and weight values ​​of the evaluation indicators;

[0057] S500: Processing the unit data of the target analysis unit to obtain indicator data of the evaluation indicator of each target analysis unit;

[0058] S600: Calculate the comprehensive score of each target analysis unit based on the indicator data of each target analysis unit and the weight value of each evaluation indicator;

[0059] S700: Classify and evaluate each target analysis unit based on K-means classification and the comprehensive score of each target analysis unit.

[0060] The technology provided by the present invention can provide decision support and analysis tools for the government in urban renewal planning, realize the effective protection of historical and cultural heritage resources in urban renewal projects, and achieve a balance between protection and development. Specifically, this embodiment provides a detailed description of each step.

[0061] S100: Acquire project data and map data of an urban renewal project, wherein the map data includes three-dimensional building model data of the urban renewal project.

[0062] In specific implementation, the three-dimensional building model data of the urban renewal project is obtained by the urban planning department or the urban renewal project, and can also be generated based on the relevant design drawings of the urban renewal project. The map data comes from the Geographic Information System (GIS), which is the basis for subsequent analysis. The map data is the city map data where the urban renewal project involving historical and cultural heritage resources is located. In one example, the map data can include existing building information, such as building height, building site area, building name, etc.

[0063] Specifically, it can be the administrative area where the urban renewal project of historical and cultural heritage resources is located, or the street area, or the area within a 2-kilometer radius centered on the historical and cultural heritage resources.

[0064] Specifically, the 3D building model data can be derived from the BIM model, such as models generated by software such as Autodesk Revit, ArchiCAD, etc. The 3D building model data is input into ArcGIS and generated in the map data.

[0065] Specifically, project data may include basic project information (project name, project location, etc.), land use information (land ownership, land use right type, land use nature, land area, volume ratio, building density, green space ratio, etc.), building information (including building conditions, building area, building height, building structure, building function, etc.)

[0066] S200: Using software tools to divide the map data into grids to generate multiple target analysis units.

[0067] In the specific implementation, ArcGIS software is used to divide the map data into multiple grids or analysis units. Each grid represents an independent analysis area, providing a spatial basis for the subsequent project data assignment. The size of the grid is determined according to the scale and detail requirements of the project (e.g., each unit is 200m x 200m). Specifically, ArcGIS generates the target analysis unit by converting the map data into raster data.

[0068] In a specific implementation, S200: using a software tool to divide the map data into grids to generate a plurality of target analysis units, specifically includes the following steps:

[0069] S210: Acquire AOI data of historical and cultural heritage architectural resources.

[0070] In the present invention, AOI (Area of ​​Interest) data refers to land use types, functional zoning, etc. in a specific area. AOI (Area of ​​Interest) is the area of ​​interest in an electronic map.

[0071] In a specific implementation, the AOI data of historical and cultural heritage resources are usually provided by cultural heritage protection departments, urban planning departments or historical building databases.

[0072] S220: Inserting the AOI data into the map data, and generating a historical building resource area in the map data.

[0073] In one specific implementation, the AOI data is loaded into ArcGIS software and overlaid on existing map data to generate identifiable and distinguishable historic building resource areas.

[0074] S230: Using a software tool, the map data is divided into 50M*50M grids to obtain a plurality of grid units.

[0075] In the specific implementation, the grid generation tool of ArcGIS software is used to set the grid size to 300M*300M according to the project requirements and the size of the study area. The software will automatically generate evenly distributed grid cells on the map data.

[0076] S240: Using the historical building resource area, clipping the portion of each grid unit that overlaps with the historical building resource area to obtain a target analysis unit.

[0077] In one specific embodiment, the clipping tool of ArcGIS software is used to clip the overlapping grid cells with the historical building resource area as the clipping mask. The clipping operation will delete the overlapping part of the corresponding grid cell with the historical building resource area, thereby eliminating the historical building resource area of ​​the grid cell.

[0078] In the specific implementation, in ArcGIS software, different data layers are loaded into the GIS project. Data overlay: AOI data is combined with map data through overlay analysis. Grid generation: ArcGIS tools are used to create regular grids. Spatial clipping: The grid is clipped using spatial analysis tools, with the historical building resource area as the clipping mask, in order to exclude the historical building resource area from the analysis area.

[0079] In another implementation, the present invention also provides a specific method for generating AOI data of historical and cultural heritage resources. The AOI data can be generated by identifying remote sensing data of the administrative area where the urban renewal project is located. In the remote sensing image, the specific building classification is identified as the AOI by spectral characteristics. Specifically, the high-resolution satellite land cover user graphical interface (GID) data set of the administrative area where the urban renewal project is located is obtained, and the building classification network model (MSNet) is used for encoding, decoding and image fusion to obtain the final classification result, and the building type distribution map is output. The building type distribution map includes different AOIs such as roads, different buildings (for example, hospitals, schools, historical buildings, and residences).

[0080] Specifically, six channels are selected and calculated as the input data of the building classification network model (MSNet), which are 3 visible light bands of RGB, near infrared (NIR), normalized difference vegetation index (NDVI) and normalized difference water index (NDWI), and the classification results are output.

[0081] Among them, the near-infrared band NIR obtains effective information when the visible light band is affected by different lighting conditions and causes information loss; NDVI can detect the coverage of vegetation and play a role in eliminating some radiation errors in building classification.

[0082] The calculation formula of vegetation normalization index is: in, is the normalized difference vegetation index, Near infrared band, It is the red band.

[0083] Among them, the NDWI index can highlight the water body information in the image and can play a role in distinguishing water bodies in building classification.

[0084] The calculation formula of NDWI index is: in, is the normalized water index, The near-infrared band, It is the green band.

[0085] The building classification network model (MSNet) has a network structure of three stages: encoding, decoding, and fusion. The encoding stage is used to capture the deep features of the image; the decoding stage restores the details and spatial dimensions of the image; and the fusion stage fuses different features.

[0086] Specifically, the ResNet-50 network is used as the backbone network to encode image information. ResNet-50 is a residual network that is widely used in the field of image processing. Experiments have shown that using a convolution kernel with a size of 7×7, a number of 64, a step size of 2, and a padding of 3 in the convolution layer to extract features from data has better results and higher extraction efficiency. The batch normalization operation (BN) is used to accelerate the convergence rate, and the Relu activation function helps the network learn nonlinear relationships and reduce the dimension of the feature map through the maximum pooling layer.

[0087] like Figure 2 , Figure 3 and Figure 4 As shown in FIG. 1 , the convolutional layer set consisting of Conv2_x, Conv3_x, Conv4_x, and Conv5_x convolutional layers is the backbone of ResNet-50. Each layer retains the encoding result to obtain e1, e2, e3, and e4.

[0088] Specifically, to facilitate the decoding operation of the data, a decoding module is defined, with the input channel number C1 and the output channel number C2, and batch normalization, Relu function activation and upsampling are performed in sequence to restore the image resolution. There are 5 layers in the decoding stage. In the first layer, e5 is first passed through the decoding module to obtain a new feature map d5; in the next 4 layers, the feature map output by the decoding and the feature map retained in the encoding stage are spliced ​​according to dimension 1 to obtain the decoding results of d1, d2, d3, and d4. Through the design and optimization of the encoding stage, information loss can be minimized.

[0089] Specifically, a list of feature maps consisting of d1, d2, d3, and d4 is input, and convolution operations are performed on each of them to obtain f2, f3, and f4. The feature maps are upsampled using bilinear interpolation to keep the number of channels consistent. P1 is obtained by adding d1 to f2, P2 by adding f2 to f3, P3 by adding f3 to f4, and P4 is used alone as P4. A total of 4 feature maps are input into the image fusion module to obtain the final result. Through multi-layer feature fusion at the fusion layer, multi-level semantic information can be retained and fused, improving the quality and effect of image fusion.

[0090] In a preferred implementation, seven channels are selected and calculated as input data for the building classification network model (MSNet), namely, three visible light bands of RGB, near infrared (NIR), normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and POI kernel density map, and the classification results are output.

[0091] The POI (point of interest) kernel density map can reflect the distribution of points of interest in a specific area, which is of reference value for the division of urban functional areas and the identification of building types. The addition of the POI kernel density map can improve the refined identification of buildings: POI data can assist in more refined identification of building types.

[0092] Combining remote sensing images and POI data can improve the accuracy and credibility of building classification. Using the building classification network model (MSNet) to extract building information, and then through the kernel density analysis of POI data, urban information can be analyzed more carefully and high-precision classification of building functions can be achieved.

[0093] Specifically, the POI kernel density map is obtained by calculating the POI kernel density of POI data within the administrative area. Specifically, it includes data classification: reclassification according to the functional category of POI, such as hospitals, schools, historical buildings, residential buildings, industrial buildings, etc. Data cleaning: including cleaning duplicate data, deleting invalid data, pre-classifying data, etc., to improve the validity of the data. Kernel density calculation: use kernel density analysis tools, such as the "Kernel Density" tool in ArcGIS. Set the search radius (bandwidth) and output grid cell size. Select a suitable kernel function, commonly used is the Gaussian kernel function. Perform calculations to generate a kernel density map.

[0094] S300: Assign project data to a number of target analysis units to obtain unit data of the target analysis units.

[0095] In a specific implementation, step S300 assigns project data to a number of target analysis units, specifically including the following steps:

[0096] S310: Process the project data in a unified coordinate system to generate surface data.

[0097] In a specific implementation, the unified coordinate system processing can be parameterized and adjusted to the coordinates of the map data of the urban renewal project by using ArcGIS's SpatialAdajustment, and the accuracy meets the research needs.

[0098] S320: Using the surface data, assigning surface attribute data to the target analysis unit to obtain unit data of the target analysis unit.

[0099] In the specific implementation, the identify tool is used to superimpose the surface data into the target analysis unit to realize the surface attribute data assignment. The project data includes a lot of data content, which needs to be converted into surface data, and then associated with the target analysis unit to become the unit data of the target analysis unit.

[0100] S400: Acquire a planning height control evaluation index system, wherein the planning height control evaluation index system includes a plurality of evaluation indexes and weight values ​​of the evaluation indexes.

[0101] In a specific implementation, the evaluation indicators of the planning height control evaluation index system include the highest building height, average building height, current building height, distance from the center, building coverage, building development intensity, street view openness and sky openness. The planning height control evaluation index system is shown in Table 1.

[0102] Table 1 Planning height control evaluation index system

[0103]

[0104] Specifically, the center (centroid) of the target analysis unit can be obtained by generating the AOI. For example, the AOI data is input into a geographic information system (GIS), the AOI boundary is obtained through the geographic information system (GIS), and the centroid of the AOI is directly calculated by the geographic information system (GIS).

[0105] In a specific implementation, the street view openness rate refers to the visual openness rate of the original built environment of the target analysis unit, reflecting the building height of the original built environment in the target analysis unit. The larger the value, the higher the existing building height of the target analysis unit. The street view image data of the present invention is obtained from a third-party map service provider, such as Baidu Street View Map Open Platform. In a specific implementation, the area proportion of each type of environmental element in each sample point of the target analysis unit can be obtained through operations such as sampling point generation, street view image capture, image semantic recognition, and data space matching. Among them, the calculation formula of the street view openness rate is: VGR is the street view openness ratio; S i_sky is the pixel area of ​​the sky in the i-th street view image of the target analysis unit; S i_SV is the total pixel area of ​​the i-th street view image of the target analysis unit; m is the number of street view images in the site area.

[0106] In a specific implementation, the sky openness indicates the range of sky that pedestrians can see in the target analysis unit area, reflects the height of buildings of various types of land within the grid area of ​​the target analysis unit, and also reflects the travel environment friendliness of the target analysis unit. The calculation formula of sky openness is: Ω direction=sin 2 γ(α / 360°); where SVF i is the openness of the sky within the walking attraction range of station i; α is the azimuth step length; Ω direction is the shielding degree of the point at each orientation; γ is the maximum building height angle formed by the building at each orientation, which is used to calculate the shielding degree.

[0107] In the specific implementation, the weight value of the evaluation index can be obtained by the analytic hierarchy process. The analytic hierarchy process (AHP) is a commonly used decision analysis method, which determines the weight value of the evaluation index by constructing a judgment matrix and combining expert scoring. This method is suitable for solving complex decision-making problems with multiple objectives and multiple criteria, and can convert the subjective judgment of the decision maker into a numerical value that can be quantified.

[0108] In a specific implementation, the evaluation indicator needs to calculate the CR value and pass the test to meet the analysis requirements, as follows:

[0109] in, When CI is less than 0.1, the judgment matrix can accept consistency, otherwise it needs to be modified. When n ≥ 3, in order to eliminate the influence of CI on the order, it is necessary to introduce the average random consistency index RI of the judgment matrix, taking CR = CI / RI, and perform consistency test on the constructed judgment matrix.

[0110] It is generally believed that when CR < 0.1, the judgment matrix passes the consistency test, otherwise it does not have satisfactory consistency. Using the weighted combination of hierarchical single sorting, the weight of the previous layer is calculated to obtain the weight value of each single indicator in the evaluation system.

[0111] In calculating the weight values ​​of the evaluation indicators, the AHP method is implemented through the following steps:

[0112] 1. Establish a hierarchical model: decompose the decision problem into the target layer, criterion layer and indicator layer, as well as possible sub-criterion layers to form a multi-level hierarchical structure model.

[0113] 2. Construct a pairwise comparison matrix: Compare the factors in the criterion layer pairwise, construct a pairwise comparison matrix, and fill in the matrix elements. In this process, a 1-9 scale is usually used to quantify the relative importance of the factors.

[0114] 3. Calculate the weight vector and perform consistency check: Calculate the maximum eigenvalue and the corresponding eigenvector of the pairwise comparison matrix and perform consistency check. If the consistency ratio CR is less than 0.1, the consistency of the matrix is ​​considered acceptable, otherwise the judgment matrix needs to be readjusted.

[0115] 4. Total hierarchical ranking and consistency check: Calculate the combined weight vector of the lowest level for the target and perform a combined consistency check. If the check is passed, a decision can be made based on it.

[0116] 5. Result analysis: Based on the calculated weight values, sort and analyze the evaluation indicators to determine their relative importance.

[0117] The advantage of the AHP method is that it can combine the subjective judgment of decision makers with objective data, and is suitable for decision-making problems with incomplete or difficult to quantify data information. In addition, the calculation process of the AHP method is relatively simple, easy to understand and operate, allowing decision makers to quickly analyze and make decisions on complex problems.

[0118] S500: Processing the unit data of the target analysis unit to obtain indicator data of the evaluation indicator of each target analysis unit.

[0119] In a specific implementation, the unit data is composed of map data, project data, three-dimensional building model data, etc. The unit data of the target analysis unit is processed, including clustering, statistics, identification, calculation, etc., to obtain the index data of the evaluation index of each target analysis unit.

[0120] For example, using the statistical tools of ArcGIS software, the data within each grid cell can be aggregated, such as calculating the average building height, distance from the center, building density, building coverage, etc. The statistical results will be used for subsequent evaluations.

[0121] S600: Calculate the comprehensive score of each target analysis unit based on the indicator data of each target analysis unit and the weight value of each evaluation indicator.

[0122] In a specific implementation, based on the indicator data of each target analysis unit and the weight value of each evaluation indicator, the comprehensive score of each target analysis unit is calculated, which specifically includes:

[0123] S610: Obtain indicator data of the target analysis unit.

[0124] S620: Standardize the indicator data to obtain an indicator value of each evaluation indicator.

[0125] In a specific implementation, the standardization method includes minimum-maximum standardization, Z-score standardization, etc. In the present invention, the minimum-maximum standardization is used to convert the indicator data into a value between 0 and 1, and the formula is:

[0126] Among them, x is the indicator data of the evaluation indicator, xmin is the minimum value of the evaluation indicator, and xmax is the maximum value of the evaluation indicator.

[0127] S670: Calculate the comprehensive score of each target analysis unit based on the indicator value and weight value of the evaluation indicator.

[0128] In a specific implementation, the calculation formula of the comprehensive score of the target analysis unit is:

[0129]

[0130] In the formula, S i is the comprehensive score of the i-th target analysis unit; P ij is the index value of the jth target analysis unit in the i-th target analysis unit; W j is the weight value of the jth evaluation indicator, and n represents the total number of indicators in the planning height control evaluation indicator system.

[0131] S700: Classify and evaluate each target analysis unit based on K-means classification and the comprehensive score of each target analysis unit.

[0132] The grid cells are classified using the K-means clustering algorithm. First, the number of categories (k value) is determined, and then the algorithm groups the target analysis cells with similar comprehensive scores into one category. The clustering results will be used for evaluation and planning decisions.

[0133] In one example, the steps include:

[0134] S710: Obtain a comprehensive score for each target analysis unit.

[0135] S720: Determine the number of clusters (k value): Select an appropriate number of clusters k value, which is usually determined based on domain knowledge and actual needs. For example, if the planning height control is divided into extremely unreasonable planning height control, unreasonable planning height control, reasonable planning height control, and relatively good planning height control, then the k value should be 4.

[0136] S730: Execute K-means algorithm: Use K-means clustering algorithm to classify the target analysis units. Each analysis unit will be assigned to the nearest cluster center according to its comprehensive score to form k clusters. In GIS software, the cluster analysis tool in the spatial analysis toolbox can be used to perform this step.

[0137] S740: Evaluate clustering results: Check the clustering results to ensure that the analysis units within each cluster are geographically continuous and that there are clear boundaries between clusters. You can use the visualization tools of GIS software to help with the evaluation.

[0138] Develop height control strategies: Based on the clustering results, get the corresponding evaluation and develop corresponding building height control strategies for each cluster. For example, for clusters with higher comprehensive scores, stricter height restrictions can be developed to protect historical and cultural heritage or landscape corridors.

[0139] The present invention also provides a planning height control evaluation system for historical and cultural heritage resources in urban renewal projects, which is used to execute and implement the above-mentioned planning height control evaluation method for historical and cultural heritage resources in urban renewal projects. Specifically, the planning height control evaluation system includes:

[0140] An acquisition module, which is used to acquire project data and map data of an urban renewal project, wherein the map data includes three-dimensional building model data of the urban renewal project;

[0141] A generation module, which is used to divide the map data into grids using a software tool to generate multiple target analysis units;

[0142] An assignment module, which is used to assign project data to a number of target analysis units to obtain unit data of the target analysis units;

[0143] An indicator system module, which is used to obtain a planning height control evaluation indicator system, wherein the planning height control evaluation indicator system includes a plurality of evaluation indicators and weight values ​​of the evaluation indicators;

[0144] A processing module, which is used to process the unit data of the target analysis unit to obtain the indicator data of the evaluation indicator of each target analysis unit;

[0145] A calculation module, which is used to calculate the comprehensive score of each target analysis unit based on the indicator data of each target analysis unit and the weight value of each evaluation indicator;

[0146] The classification and evaluation module is used to classify and evaluate each target analysis unit based on K-means classification and the comprehensive score of each target analysis unit.

[0147] For other structures of the planning height control evaluation method and system involving historical and cultural heritage resources in an urban renewal project described in this embodiment, refer to the prior art.

[0148] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Therefore, any modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A planning height control and evaluation method for historical and cultural heritage resources in urban renewal projects, characterized in that: The following steps are involved: Acquire project data and map data of the urban renewal project, wherein the map data includes three-dimensional building model data of the urban renewal project; Use software tools to divide map data into grids to generate multiple target analysis units; Assigning project data to a number of target analysis units to obtain unit data of the target analysis units; Acquire a planning height control evaluation index system, wherein the planning height control evaluation index system includes a plurality of evaluation indicators and weight values ​​of the evaluation indicators; Processing the unit data of the target analysis unit to obtain indicator data of the evaluation indicator of each target analysis unit; Based on the indicator data of each target analysis unit and the weight value of each evaluation indicator, calculate the comprehensive score of each target analysis unit; Based on K-means classification and the comprehensive score of each target analysis unit, each target analysis unit is classified and evaluated.

2. According to claim 1, a planning height control and evaluation method for historical and cultural heritage resources in an urban renewal project is characterized in that: Use software tools to divide the map data into grids to generate several target analysis units, including: Obtain AOI data of historical and cultural heritage architectural resources; Inserting the AOI data into the map data to generate a historical building resource area in the map data; Use software tools to divide the map data into 50M*50M grids to obtain multiple grid units; Using the historical building resource area, the part of each grid unit that overlaps with the historical building resource area is clipped to obtain the target analysis unit.

3. The method for planning height control and evaluation of historical and cultural heritage resources in an urban renewal project according to claim 1 is characterized in that: Assign project data to several target analysis units, including: Process the project data in a unified coordinate system to generate surface data; Using the surface data, the surface attribute data is assigned to the target analysis unit to obtain the unit data of the target analysis unit.

4. According to claim 1, a planning height control evaluation method for historical and cultural heritage resources in an urban renewal project, based on the indicator data of each target analysis unit and the weight value of each evaluation indicator, calculates the comprehensive score of each target analysis unit, specifically including: Obtain indicator data of the target analysis unit; Standardizing the indicator data to obtain an indicator value for each evaluation indicator; Based on the indicator value and weight value of the evaluation indicator, the comprehensive score of each target analysis unit is calculated.

5. The method for planning height control and evaluation of historical and cultural heritage resources in an urban renewal project according to claim 4 is characterized by: The calculation formula of the comprehensive score of the target analysis unit is: In the formula, S i is the comprehensive score of the i-th target analysis unit; P ij is the index value of the jth target analysis unit in the Ith target analysis unit; W j is the weight value of the jth evaluation indicator, and n represents the total number of indicators in the planning height control evaluation indicator system.

6. The method for planning height control and evaluation of historical and cultural heritage resources in an urban renewal project according to claim 4 is characterized by: The evaluation indicators of the planning height control evaluation index system include the highest building height, average building height, current building height, distance from the center, building coverage rate, building development intensity, street view openness rate and sky openness.

7. A planning height control and evaluation system for historical and cultural heritage resources in urban renewal projects, characterized in that: include: An acquisition module, which is used to acquire project data and map data of an urban renewal project, wherein the map data includes three-dimensional building model data of the urban renewal project; A generation module, which is used to divide the map data into grids using a software tool to generate multiple target analysis units; An assignment module, which is used to assign project data to a number of target analysis units to obtain unit data of the target analysis units; An indicator system module, which is used to obtain a planning height control evaluation indicator system, wherein the planning height control evaluation indicator system includes a plurality of evaluation indicators and weight values ​​of the evaluation indicators; A processing module, which is used to process the unit data of the target analysis unit to obtain the indicator data of the evaluation indicator of each target analysis unit; A calculation module, which is used to calculate the comprehensive score of each target analysis unit based on the indicator data of each target analysis unit and the weight value of each evaluation indicator; The classification and evaluation module is used to classify and evaluate each target analysis unit based on K-means classification and the comprehensive score of each target analysis unit.

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