Multi-source data-based urban public space quality intelligent evaluation method and system

Abstract

The invention relates to an urban public space quality intelligent evaluation method and system based on multi-source data, and the method comprises the steps: obtaining a to-be-evaluated urban public region and a current evaluation precision level, which are set on a space evaluation interface by a space quality query main body; obtaining a pre-stored traffic evaluation coefficient and a pre-stored social activity evaluation coefficient according to the urban public area to be evaluated; obtaining a to-be-evaluated area building model corresponding to the to-be-evaluated urban public area and corresponding basic model data, and generating an updated area building model and updated basic model data; extracting road traffic data, road use data and social activity data; and generating an urban space quality evaluation score. According to the invention, on the basis of meeting the requirements of the space quality query main body and meeting the attention dimension of the city space use main body in the city public area to be evaluated, the generation of the city space quality score is realized, and the intelligent and comprehensive intelligent evaluation is realized.

Description

Technical Field

[0001] The present application relates to the field of urban planning technology, and in particular to a method and system for intelligently evaluating the quality of urban public spaces based on multi-source data. Background Art

[0002] Urban public space refers to the open space between building entities in a city or urban agglomeration. It is an open place for urban residents to conduct public interactions and hold various activities. Its purpose is to serve the general public.

[0003] At present, there are many evaluation methods for urban public spaces. For example, the Chinese invention patent with publication number CN115203803A disclosed a visualized urban street space quality evaluation and grading method on October 18, 2022, which includes the following steps: Step 1. Construct an urban street design quality evaluation method based on user perception experience; Step 2. Draw a street design space quality grading map, establish a street design quality database based on street space morphology data and street scene image data, and use a large amount of street scene image data and intelligent and digital technical means of machine learning score algorithms to establish a quantitative model between street design space quality evaluation indicators and influencing factors. By intelligently identifying all street scene images in the selected area, they are substituted into the above-mentioned urban street design quality evaluation model to obtain the quality scores of all streets and draw a scatter plot.

[0004] Although the technical solution in the above patent document can achieve in-depth analysis of the street space quality distribution and influencing factors in the study area and improve the accuracy of diagnosis of urban street quality problems, it is similar to other analysis methods in the prior art and is difficult to meet the needs of refined factor guidance and control. There are still problems of inaccurate and incomplete analysis due to analysis of larger areas. Summary of the invention

[0005] Based on this, it is necessary to provide an intelligent urban public space quality evaluation method and system based on multi-source data, which can conduct refined, multi-dimensional, high-precision, comprehensive and integrated quality evaluation of urban public spaces in smaller designated areas, in response to the above technical problems.

[0006] The technical solution of the present invention is as follows:

[0007] An intelligent evaluation method for urban public space quality based on multi-source data, the method comprising:

[0008] Obtain the urban public area to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface, and obtain the pre-stored traffic evaluation coefficient and social activity evaluation coefficient according to the urban public area to be evaluated;

[0009] Acquire the building model of the area to be evaluated and the corresponding basic model data corresponding to the public area of ​​the city to be evaluated, update the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level, and generate an updated area building model and updated basic model data;

[0010] Extracting road traffic data based on the updated regional building model, and extracting road use data and social activity data based on the updated basic model data;

[0011] Based on the traffic evaluation coefficient and the social activity evaluation coefficient, an urban space quality evaluation score is generated according to the road traffic data, the road use data and the social activity data.

[0012] Optionally, obtaining the urban public area to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface; including:

[0013] Obtain the initial urban public area and current evaluation accuracy level set by the space quality query subject on the space evaluation interface;

[0014] Acquire the query subject identity information of the space quality query subject, compare the query subject identity information with the pre-stored public area query grade library, and generate a sensitive public area corresponding to the space quality query subject;

[0015] Eliminating the initial urban public areas according to the pre-stored sensitive public areas, and generating a preliminary screening urban public area;

[0016] Generate an associated public area according to the initial screening public area, and aggregate the initial screening public area and the associated public area to generate a public area to be demarcated;

[0017] Acquire the regional planning data of the public area to be demarcated between the current measurement time and the preset quality evaluation setting time, and extract the estimated change space area from the regional planning data;

[0018] Extracting the estimated changed region area of ​​the estimated changed spatial region, and generating a changed region area ratio according to the total area of ​​the to-be-demarcated area of ​​the to-be-demarcated public area and the estimated changed region area;

[0019] Determining whether the flexible area ratio is greater than or equal to a preset standard area ratio;

[0020] If the judgment is yes, then generate a regional evaluation adjustment suggestion, send the regional evaluation adjustment suggestion to the space quality query subject, obtain the regional adjustment data of the space quality query subject, adjust the initially screened urban public area according to the regional adjustment data, and generate the urban public area to be evaluated after the adjustment;

[0021] If the judgment is no, then the urban public areas to be evaluated are set according to the initially screened urban public areas.

[0022] Optionally, obtaining a building model of the area to be evaluated and corresponding basic model data corresponding to the urban public area to be evaluated, updating the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level and generating an updated building model of the area and updated basic model data; comprising:

[0023] Acquire the building model of the area to be evaluated and the corresponding basic model data corresponding to the public area of ​​the city to be evaluated, and acquire the model update record data of the building model of the area to be evaluated;

[0024] In response to acquiring the model update record data, acquiring an update measurement time period and a model update qualified number of times according to the current evaluation accuracy level;

[0025] Extracting the actual number of model data updates within the update measurement time period from the model update record data;

[0026] Determine whether the actual update times of the model data is greater than or equal to the qualified model update times;

[0027] If the judgment is yes, the building model of the area to be evaluated and the basic model data are set as the updated building model of the area and the updated basic model data;

[0028] If the judgment is no, a model update instruction is generated, and the building model of the area to be evaluated and the basic model data are updated according to the model update instruction, and an updated regional building model and updated basic model data are generated.

[0029] Optionally, based on the traffic evaluation coefficient and the social activity evaluation coefficient, an urban space quality evaluation score is generated according to the road traffic data, the road use data and the social activity data; comprising:

[0030] Based on the traffic evaluation coefficient, generating a road traffic evaluation score according to the road traffic data and the road use data;

[0031] Based on the social activity evaluation coefficient, generating a social activity evaluation score according to the social activity data;

[0032] The road traffic evaluation score and the social activity evaluation score are added together to generate an urban space quality evaluation score.

[0033] Optionally, based on the traffic evaluation coefficient, generating a road traffic evaluation score according to the road traffic data and the road use data; comprising:

[0034] Extracting street used roads and road area information, road occupancy information, road bending information and road leveling information corresponding to each street used road from the road traffic data, wherein the number of street used roads is n, and the street used roads are streets that have been put into use in the public area of ​​the city to be evaluated;

[0035] Calculate the total individual road area of ​​used roads for each of said streets;

[0036] Extracting the road occupation area of ​​each street's used roads and the legally occupied total area of ​​each street's used roads from the road occupation information, wherein one street's used road corresponds to one road occupation area, the road occupation area is the area occupied by obstacles in the street's used roads, and the legally occupied total area is the sum of the areas occupied by the areas pre-demarcated by the road management department in the street's used roads;

[0037] Extracting actual road bends of used roads of each street according to the road bend information, and counting the actual number of bends of the actual road bends;

[0038] Screen out actual road bends corresponding to actual bend times greater than a preset standard bend time, record them as overload bends, and obtain the difference between the actual bend times corresponding to the overload bends and the standard bend times, and record them as the overload bend number, wherein the number of the overload bends is m, and one overload bend corresponds to one overload bend number;

[0039] Extracting the road smoothness of each of the used roads in the streets from the road smoothness information;

[0040] Based on the traffic evaluation coefficient, the road traffic evaluation score is generated using the following formula according to the total area of ​​each individual road, the road occupied area, the legal occupied total area, the number of overloaded bends, the number of standard bends and the road flatness:

[0041]

[0042] Among them, TF is the road traffic evaluation score, δ is the traffic evaluation coefficient, n is the number of used roads in the street, Wsdi is the total area of ​​individual roads in the used roads of the i-th street, Woci is the road occupation area of ​​the used roads of the i-th street, Wta is the total legal occupation area, m is the number of overload bends, Ctj is the number of overload bends of the j-th overload bend, Cs is the number of standard bends, and Tir is the road flatness.

[0043] Optionally, an intelligent evaluation system for urban public space quality based on multi-source data comprises:

[0044] An evaluation space determination module is used to obtain the urban public area to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface, and obtain the pre-stored traffic evaluation coefficient and social activity evaluation coefficient according to the urban public area to be evaluated;

[0045] The city model updating module is used to obtain the building model of the area to be evaluated and the corresponding basic model data corresponding to the public area of ​​the city to be evaluated, update the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level, and generate an updated regional building model and updated basic model data;

[0046] A spatial data extraction module, for extracting road traffic data based on the updated regional building model, and extracting road use data and social activity data based on the updated basic model data;

[0047] The quality evaluation generation module is used to generate an urban space quality evaluation score based on the traffic evaluation coefficient and the social activity evaluation coefficient according to the road traffic data, the road use data and the social activity data.

[0048] Optionally, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method for intelligent evaluation of urban public space quality based on multi-source data when executing the computer program.

[0049] Optionally, a computer-readable storage medium is also provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned method for intelligent evaluation of urban public space quality based on multi-source data are implemented.

[0050] The technical effects achieved by the present invention are as follows:

[0051] The above-mentioned intelligent evaluation method and system for urban public space quality based on multi-source data successively obtains the urban public area to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface, and obtains the pre-stored traffic evaluation coefficient and social activity evaluation coefficient according to the urban public area to be evaluated; obtains the building model of the area to be evaluated and the corresponding basic model data corresponding to the urban public area to be evaluated, updates the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level and generates an updated area building model and updated basic model data; extracts road traffic data according to the updated area building model, and extracts road use data and social activity data according to the updated basic model data; based on the traffic evaluation coefficient and the social activity evaluation coefficient, generates an urban space quality evaluation score according to the road traffic data, road use data and the social activity data. In order to solve the problem that the statistics of urban public space in the prior art are too general, the present invention adopts the regional delineation for the spatial quality query subject to refine the selection of urban public space to be evaluated. The spatial evaluation interface is used to display all selectable urban public spaces. The urban public area to be evaluated is the area selected by the spatial quality query subject for the urban space quality score to be conducted. The current evaluation accuracy level is set by the spatial quality query subject to indicate the accuracy of the evaluation of the currently selected area. The traffic evaluation coefficient is used to indicate the degree of concern of the urban space user in the urban public area to be evaluated for traffic, and the social activity evaluation coefficient is used to indicate the degree of concern of the urban space user in the urban public area to be evaluated for social activities. Next, in order to ensure that the current model is accurate and avoid the problem of inaccurate data acquisition caused by the failure to update the city model in time or the use of crawler-style data acquisition in the prior art, the building model of the area to be evaluated and the corresponding basic model data corresponding to the public area of ​​the city to be evaluated are first obtained, and then the building model of the area to be evaluated and the basic model data are updated according to the current evaluation accuracy level and the updated regional building model and updated basic model data are generated. By setting the current evaluation accuracy level, different degrees of model updates are performed to improve accuracy while meeting the customized needs of the space quality query subject. Next, road traffic data is extracted according to the updated regional building model, and road use data and social activity data are extracted according to the updated basic model data to achieve more refined spatial evaluation data acquisition.Finally, based on the traffic evaluation coefficient and the social activity evaluation coefficient, an urban space quality evaluation score is generated according to the road traffic data, road use data and the social activity data, thereby meeting the needs of the space quality query subject and meeting the focus dimensions of the urban space user in the public area of ​​the city to be evaluated, thereby achieving the generation of an urban space quality score and realizing intelligent and comprehensive smart evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a flowchart of an intelligent evaluation method for urban public space quality based on multi-source data in one embodiment;

[0053] Figure 2 It is a structural block diagram of an intelligent evaluation system for urban public space quality based on multi-source data in one embodiment. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0055] In one embodiment, a terminal is provided, which is used to: obtain the urban public area to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface, and obtain the pre-stored traffic evaluation coefficient and social activity evaluation coefficient according to the urban public area to be evaluated; obtain the building model of the area to be evaluated and the corresponding basic model data corresponding to the urban public area to be evaluated, update the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level and generate an updated area building model and updated basic model data; extract road traffic data according to the updated area building model, and extract road use data and social activity data according to the updated basic model data; based on the traffic evaluation coefficient and the social activity evaluation coefficient, generate an urban space quality evaluation score according to the road traffic data, road use data and the social activity data.

[0056] The terminal may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices.

[0057] In one embodiment, Figure 1 As shown, a method for intelligent evaluation of urban public space quality based on multi-source data is provided, the method comprising:

[0058] Step S100: obtaining the urban public area to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface, and obtaining the pre-stored traffic evaluation coefficient and social activity evaluation coefficient according to the urban public area to be evaluated;

[0059] Step S200: Acquire the building model of the area to be evaluated and the corresponding basic model data corresponding to the urban public area to be evaluated, update the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level, and generate an updated regional building model and updated basic model data;

[0060] Step S300: extracting road traffic data according to the updated regional building model, and extracting road use data and social activity data according to the updated basic model data;

[0061] Step S400: Based on the traffic evaluation coefficient and the social activity evaluation coefficient, an urban space quality evaluation score is generated according to the road traffic data, the road use data and the social activity data.

[0062] In this embodiment, in order to solve the problem that the statistics of urban public space in the prior art are too general, the regional delineation for the spatial quality query subject is adopted to refine the selection of urban public space to be evaluated, specifically, the urban public area to be evaluated and the current evaluation accuracy level set by the spatial quality query subject on the spatial evaluation interface are obtained, and the pre-stored traffic evaluation coefficient and social activity evaluation coefficient are obtained according to the urban public area to be evaluated. The spatial evaluation interface is used to display all selectable urban public spaces. The urban public area to be evaluated is the area selected by the spatial quality query subject for the urban space quality score to be conducted. The current evaluation accuracy level is set by the spatial quality query subject itself, which is used to indicate the accuracy of the evaluation of the currently selected area. The traffic evaluation coefficient is used to indicate the degree of concern of the urban space user in the urban public area to be evaluated for traffic, and the social activity evaluation coefficient is used to indicate the degree of concern of the urban space user in the urban public area to be evaluated for social activities. Next, in order to ensure that the current model is accurate and avoid the problem of inaccurate data acquisition caused by the failure to update the city model in time or the crawler-style data acquisition method in the prior art, the building model of the area to be evaluated and the corresponding basic model data corresponding to the public area of ​​the city to be evaluated are first obtained, and then the building model of the area to be evaluated and the basic model data are updated according to the current evaluation accuracy level to generate the updated regional building model and the updated basic model data. By setting the current evaluation accuracy level, different degrees of model updates are performed to improve the accuracy while meeting the customized needs of the space quality query subject. Next, by extracting road traffic data according to the updated regional building model, and extracting road use data and social activity data according to the updated basic model data, more refined spatial evaluation data is obtained. Finally, based on the traffic evaluation coefficient and social activity evaluation coefficient, the urban space quality evaluation score is generated according to the road traffic data, road use data and social activity data, so as to meet the needs of the space quality query subject and the concern dimensions of the urban space user in the public area of ​​the city to be evaluated, and realize the generation of urban space quality scores, and realize intelligent and comprehensive intelligent evaluation.

[0063] Specifically, a survey on the degree of concern about traffic and social activities is conducted on multiple urban space users, and feedback data on traffic and social activities of multiple urban space users are obtained, and traffic feedback scores and social activity feedback scores are generated according to the traffic concern feedback data; the average values ​​of the traffic feedback scores and the social activity feedback scores are calculated respectively, and different coefficients are set for different average values. The higher the average value, the higher the coefficient, that is, the higher the traffic evaluation coefficient and the social activity evaluation coefficient. In this way, by generating the traffic evaluation coefficient and the social activity evaluation coefficient, it is possible to evaluate the quality of urban public space based on the urban space users, which is more specific and more suitable for the urban space users.

[0064] In one embodiment, step S100: obtaining the urban public areas to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface; includes:

[0065] Step S110: obtaining the initial urban public area and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface;

[0066] Step S120: obtaining the query subject identity information of the space quality query subject, comparing the query subject identity information with the pre-stored public area query grade library, and generating a sensitive public area corresponding to the space quality query subject;

[0067] Step S130: Eliminate the initial urban public areas according to the pre-stored sensitive public areas, and generate a preliminary screening urban public area;

[0068] Step S140: generating an associated public area according to the primary screening public area, and aggregating the primary screening public area and the associated public area to generate a public area to be demarcated;

[0069] Step S150: acquiring the area planning data of the public area to be demarcated between the current measurement time and the preset quality evaluation setting time, and extracting the estimated change space area from the area planning data;

[0070] Step S160: extracting the estimated changed region area of ​​the estimated changed spatial region, and generating a changed region area ratio according to the total area of ​​the to-be-demarcated area of ​​the to-be-demarcated common region and the estimated changed region area;

[0071] Step S170: determining whether the flexible area ratio is greater than or equal to a preset standard area ratio;

[0072] Step S180: if the judgment is yes, then generate a regional evaluation adjustment suggestion, send the regional evaluation adjustment suggestion to the space quality query subject, obtain the regional adjustment data of the space quality query subject, adjust the initially screened urban public area according to the regional adjustment data, and generate the urban public area to be evaluated after the adjustment;

[0073] Step S190: If the judgment is no, then setting the urban public areas to be evaluated based on the initially screened urban public areas.

[0074] In this embodiment, the quality evaluation setting time is pre-set to prevent the problem that the area to be evaluated needs to be adjusted in a short period of time, which makes the current evaluation meaningless. It is generally set to a time between 3-6 months. In order to ensure that the area to be evaluated can be evaluated and the subsequent evaluation is accurate, the initial urban public area and the current evaluation accuracy level set by the spatial quality query subject on the spatial evaluation interface are first obtained, and then the query subject identity information of the spatial quality query subject is obtained, and the query subject identity information is compared with the pre-stored public area query level library, and a sensitive public area corresponding to the spatial quality query subject is generated. Among them, the public area query registration library pre-stores multiple standard identity levels and standard non-public areas corresponding to the standard identity levels. That is, a subject with a standard identity level corresponds to a standard non-public area. The standard non-public area is a pre-set area that is not open to the subject of the corresponding standard identity level. This setting enables only subjects of a specific level to query a specific area, so that the quality evaluation information of the spatial area is not leaked. After obtaining the query subject identity information of the space quality query subject, the query subject identity information can be used for analysis, specifically according to the preset identity evaluation dimension, the identity evaluation dimension includes name, affiliated unit, position, purpose of visit, etc. Each identity evaluation dimension corresponds to a score, and the total score can be obtained by adding the scores. The corresponding relationship between identity level and score is preset, so after obtaining the total score, the actual identity level of the space quality query subject can be generated according to the identity evaluation dimension. Then, the actual identity level is compared with the standard identity level in the public area query level library, and the standard identity level that is the same as the actual identity level is screened out, and then the standard non-public area corresponding to the screened standard identity level is set as the sensitive public area corresponding to the space quality query subject. The sensitive public area includes but is not limited to the public security bureau and police station. The sensitive public area can also include schools, confidential scientific research institutions and other areas. That is, if the space quality query subject is a general visitor, it is impossible to query the quality score of areas such as police stations and public security bureaus. Then, the initial urban public areas are eliminated according to the pre-stored sensitive public areas, and the preliminary screening urban public areas are generated; and the associated public areas are generated according to the preliminary screening public areas, and the preliminary screening public areas and the associated public areas are aggregated to generate the public areas to be demarcated. Among them, the associated public areas are areas that are connected to the preliminary screening public areas and have traffic interconnection and social interaction relationships. Traffic interconnection refers to the ability to conveniently connect the two areas through public transportation, and the commuting time is within 20 minutes. Social interaction refers to the ability to conveniently connect the social activities of the two areas through public transportation.By aggregating the initially screened public areas and the associated public areas to generate the public areas to be demarcated, the areas related to the areas to be evaluated are taken into consideration, thereby improving the accuracy and comprehensiveness of the evaluation areas. The regional planning data of the public areas to be demarcated between the current measurement time and the preset quality evaluation setting time are obtained, and the estimated change space area is extracted from the regional planning data; then the estimated change area area of ​​the estimated change space area is extracted, and the change area area ratio is generated according to the ratio of the total area of ​​the areas to be demarcated of the public areas to be demarcated to the estimated change area area; then it is determined whether the flexible area area ratio is greater than or equal to the preset standard area ratio; wherein, if it is determined to be yes, a regional evaluation adjustment suggestion is generated, and the regional evaluation adjustment suggestion is sent to the spatial quality query subject, and the regional adjustment data of the spatial quality query subject is obtained, and the initially screened urban public areas are adjusted according to the regional adjustment data and the urban public areas to be evaluated are generated after the adjustment. If the judgment is yes, that is, the area ratio of the flexible area is greater than or equal to the preset standard area ratio, it means that the area of ​​the variable area is larger at this time. This causes the corresponding subject using the area to be evaluated to generate data with excessive variability when using the area, making it impossible to accurately perform a high-precision quality evaluation on the collected data, or even if a quality evaluation is performed, it is only for reference for a short time and loses its reference value after the set time of the quality evaluation, resulting in useless quality evaluation work. Therefore, a suggestion is generated, suggesting that the spatial quality query subject reselect the area, change the selected area or stop the evaluation of the area, that is, sending the area evaluation adjustment suggestion to the spatial quality query subject, and obtaining the area adjustment data of the spatial quality query subject, adjusting the initially screened urban public area according to the area adjustment data, and generating the urban public area to be evaluated after the adjustment. If the judgment is no, then the urban public area to be evaluated is set according to the preliminary screening urban public area. In this step, if the judgment is no, it means that the area of ​​the planning change at this time has not reached the level of affecting the overall regional evaluation, so the regional evaluation can be carried out normally, and the accuracy of the quality evaluation will not be affected by the subsequent planning. Among them, the standard area ratio is preset, which can be set to 10%, generally less than 10%. Therefore, the urban public area to be evaluated can be directly set according to the preliminary screening urban public area.

[0075] In one embodiment, step S200: obtaining the building model of the area to be evaluated and the corresponding basic model data corresponding to the urban public area to be evaluated, updating the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level and generating an updated area building model and updated basic model data; comprising:

[0076] Step S210: obtaining the building model of the area to be evaluated and the corresponding basic model data corresponding to the urban public area to be evaluated, and obtaining the model update record data of the building model of the area to be evaluated;

[0077] Step S220: in response to obtaining the model update record data, obtaining an update measurement time period and a model update qualified number of times according to the current evaluation accuracy level;

[0078] Step S230: extracting the actual number of model data updates within the update measurement time period from the model update record data;

[0079] Step S240: determining whether the actual number of model data updates is greater than or equal to the qualified number of model updates;

[0080] Step S250: If the judgment is yes, the building model of the area to be evaluated and the basic model data are set as the updated regional building model and the updated basic model data;

[0081] Step S260: If the judgment is no, a model update instruction is generated, and the building model of the area to be evaluated and the basic model data are updated according to the model update instruction, and an updated regional building model and updated basic model data are generated.

[0082] In this embodiment, the urban public space model database is pre-collected and stored through data collection. Therefore, after obtaining the urban public area to be evaluated, it can be compared with the urban public space model database, and the architectural model of the area to be evaluated and the corresponding basic model data of the urban public area to be evaluated can be obtained. The architectural model of the area to be evaluated is updated in real time according to the settings of the actual management personnel. In order to meet the needs of current quality evaluation, it is necessary to judge whether the requirements of the number of updates are met according to different needs. Specifically, the model update record data of the architectural model of the area to be evaluated is first obtained, and then the update measurement time period and the number of qualified model updates are obtained according to the current evaluation accuracy level. The current evaluation accuracy level corresponds to the update measurement time period and the number of qualified model updates. The higher the current evaluation accuracy level, the higher the accuracy requirement, so the longer the time span of the update measurement time period. At the same time, the larger the value of the qualified model update number, that is, the higher the accuracy requirement, the longer the inspection time, and the more frequent the update is required to ensure that the model data currently used is more accurate. In the present application, the standard evaluation level and the corresponding standard measurement time period, as well as the number of standard updates corresponding to the standard measurement time period, are pre-set; when the current evaluation accuracy level is obtained, the standard measurement time period and the number of standard updates corresponding to the standard evaluation level that is the same as the current evaluation accuracy level can be set as the update measurement time period and the number of model updates by comparing with each standard evaluation level. Next, the actual number of model data updates within the update measurement time period is extracted from the model update record data, and then it is determined whether the actual number of model data updates is greater than or equal to the number of model updates. If the judgment is yes, it means that the number of model updates is large at this time, and the degree of refinement of the model update meets the standard, so the subsequent urban space quality evaluation can be carried out, so the architectural model of the area to be evaluated and the basic model data are set as the updated regional architectural model and the updated basic model data. If the judgment is no, it means that within a certain period of time, the model has been updated less frequently and the degree of refinement is not high, which affects the subsequent spatial quality evaluation. Therefore, the model needs to be updated immediately, so a model update instruction is generated, and the building model of the area to be evaluated and the basic model data are updated according to the model update instruction, and an updated regional building model and updated basic model data are generated.

[0083] In one embodiment, in step S260, the building model of the area to be evaluated and the basic model data are updated according to the model update instruction, and an updated building model of the area to be evaluated and updated basic model data are generated, including:

[0084] Step S261: obtaining the update number closest to the current measurement time among the actual update times of the model data according to the model update instruction, and setting the time of the update as the latest model update time, wherein the building model corresponding to the latest model update time is the building model to be updated, and the building model to be updated corresponds to the basic data to be updated;

[0085] Step S262: Acquire the building environment monitoring data uploaded by the urban space environment management subject during the period from the most recent model update time to the current measurement time;

[0086] Step S263: Generate a building environment update node according to the building environment monitoring data, and update the building model to be updated and the basic data to be updated according to the building environment update node to generate an updated regional building model and updated basic model data.

[0087] In this embodiment, the urban space environment management subject is a manager who monitors the urban public space through environmental monitoring sensors and manual monitoring. Therefore, on the basis of the existing basic model, in order to avoid the problems of low data processing efficiency, long processing time and repeated data collection caused by large-scale re-measurement of urban space data, the latest update time is obtained, and the model and data corresponding to the latest update time are updated. Specifically, the number of updates closest to the current measurement time in the actual number of updates of the model data is obtained according to the model update instruction, and the time of the update is set as the latest model update time, wherein the building model corresponding to the latest model update time is the building model to be updated, and the building model to be updated corresponds to the basic data to be updated. Among them, the number of updates closest to the current measurement time is the latest time. If the current measurement time is the current real-time time, the number of updates is 3, the first is 3 months ago, the second is 2 months ago, and the third is 15 days ago, then the latest update number is 15 days ago. Next, in order to save resources, the building environment monitoring data uploaded by the urban space environment management subject during the period from the most recent model update time to the current measurement time is obtained; then, a building environment update node is generated based on the building environment monitoring data. The building environment update node is a point where changes in the space environment are monitored, such as a changed road node, a newly added bus stop, a widened auxiliary road, etc. Then, the building model to be updated and the basic data to be updated are updated according to the building environment update node to generate an updated regional building model and updated basic model data.

[0088] In one embodiment, in step S263, after generating the updated regional building model and the updated basic model data, the following steps are further included:

[0089] First, a random environment comparison number is generated according to the total area of ​​the area to be demarcated. Then, a matching number of random comparison model areas are screened out from the updated regional building model according to the random environment comparison number, and the urban space environment management subject is instructed to conduct field monitoring and obtain field comparison building areas according to the random comparison model areas; then, the field comparison building areas are compared with the random comparison model areas, and a model comparison similarity is generated. It is determined whether the model comparison similarity reaches 98%. If it is determined to be yes, a current model qualification indication is generated. If it is determined to be no, the similarity difference between the model comparison similarity and 98% is obtained. When the similarity difference is greater than a preset similarity threshold, a model review indication is generated, and the urban space environment management subject is instructed to conduct model review and data update according to the model review indication. After the review and data update, the latest updated regional building model and updated basic model data are generated. In this way, through re-measurement, Shixin further accurately ensures that the acquired model data matches the actual building, saving the workload of model detection and data collection while ensuring accuracy, thereby improving the accuracy of subsequent urban space quality evaluation scores.

[0090] In one embodiment, step S400: based on the traffic evaluation coefficient and the social activity evaluation coefficient, generating an urban space quality evaluation score according to the road traffic data, the road use data and the social activity data; comprising:

[0091] Step S410: generating a road traffic evaluation score based on the traffic evaluation coefficient and the road traffic data and the road use data;

[0092] Step S420: generating a social activity evaluation score according to the social activity data based on the social activity evaluation coefficient;

[0093] Step S430: Add the road traffic evaluation score and the social activity evaluation score to generate an urban space quality evaluation score.

[0094] In this embodiment, a comprehensive evaluation of the urban space is achieved by evaluating the quality from the dimensions of road traffic and social life respectively. Specifically, based on the traffic evaluation coefficient, a road traffic evaluation score is generated according to the road traffic data and the road usage data; then, a social activity evaluation score is generated based on the social activity evaluation coefficient and the social activity data; finally, the road traffic evaluation score and the social activity evaluation score are added together to generate an urban space quality evaluation score.

[0095] In one embodiment, step S410: generating a road traffic evaluation score based on the traffic evaluation coefficient and the road traffic data and the road use data; comprises:

[0096] Step S411: extracting street used roads and road area information, road occupancy information, road bending information and road flatness information corresponding to each street used road from the road traffic data, wherein the number of street used roads is n, and the street used roads are streets that have been put into use in the public area of ​​the city to be evaluated;

[0097] Step S412: Calculate the total area of ​​each road in use on each street;

[0098] Step S413: extracting the road occupation area of ​​each street's used roads and the legally occupied total area of ​​each street's used roads from the road occupation information, wherein one street's used road corresponds to one road occupation area, the road occupation area is the area occupied by obstacles in the street's used roads, and the legally occupied total area is the sum of the areas occupied by the areas pre-demarcated by the road management department in the street's used roads;

[0099] For example, the area occupied by bus stops on each of the streets;

[0100] Step S414: extracting actual road bends of used roads of each street according to the road bend information, and counting the actual number of bends of the actual road bends;

[0101] Step S415: screening out actual road bends corresponding to actual bend times greater than a preset standard bend time, recording them as overload bends, and obtaining a difference between the actual bend times corresponding to the overload bends and the standard bend times, recording them as the overload bend number, wherein the number of the overload bends is m, and one overload bend corresponds to one overload bend number;

[0102] Step S416: extracting the road flatness of each of the streets from the road flatness information;

[0103] In this step, the road flatness is measured by the urban space environment management entity using a fixed-length ruler method, a cross-section depiction method, or a smooth and bumpy accumulation method.

[0104] Step S417: Based on the traffic evaluation coefficient, the road traffic evaluation score is generated using the following formula according to the total area of ​​each single road, the road occupied area, the legal occupied total area, the number of overloaded bends, the number of standard bends and the road flatness:

[0105]

[0106] Among them, TF is the road traffic evaluation score, δ is the traffic evaluation coefficient, n is the number of used roads in the street, Wsdi is the total area of ​​individual roads in the used roads of the i-th street, Woci is the road occupation area of ​​the used roads of the i-th street, Wta is the total legal occupation area, m is the number of overload bends, Ctj is the number of overload bends of the j-th overload bend, Cs is the number of standard bends, and Tir is the road flatness.

[0107] In this embodiment, in order to calculate the score for measuring road traffic, the road area information, road occupancy information, road bending information and road flatness information corresponding to the street used roads and each street used road are extracted from the road traffic data, and then the total area of ​​each individual road of the street used roads is calculated. The calculation can be performed digitally based on the obtained model, thereby improving data processing efficiency. Then, the total area of ​​each individual road of the used roads on each street is calculated, and then the road occupation area of ​​each used road on the street and the total legal occupation area of ​​each used road on the street are extracted from the road occupation information, wherein one used road on the street corresponds to one road occupation area. Finally, the actual road bends of each used road on the street are extracted according to the road bending information, and the actual number of bends of the actual road bends is counted; the actual road bends corresponding to the actual number of bends greater than the preset standard number of bends are screened out and recorded as overload bends, and the difference between the actual number of bends corresponding to the overload bends and the standard number of bends is obtained and recorded as the overload bend number. Then, the road smoothness of each used road on the street is extracted from the road smoothness information. Finally, based on the traffic evaluation coefficient, the road traffic evaluation score is generated using the following formula according to the total area of ​​each individual road, the road occupation area, the total legal occupation area, the number of overload bends, the standard number of bends and the road smoothness.

[0108] In one embodiment, step S420: generating a social activity evaluation score based on the social activity evaluation coefficient and the social activity data includes:

[0109] Step S421: extracting socially active blocks according to the socially active data, and obtaining activity information, number of participants, basic block information and store data information of each socially active block;

[0110] Step S422: extracting the average number of times the socially active block is held in a data collection period according to the event holding information, and obtaining an activity frequency score according to the average number of times held, wherein the data collection period is preset;

[0111] Step S423: extracting the average number of participants in the socially active block during the data collection period according to the number of participants information;

[0112] Step S424: extracting the actual area of ​​the block and the green area of ​​the block according to the basic information of the block, and generating the number of opened stores within a preset range of the socially active block according to the store data information;

[0113] Step S425: Based on the social activity evaluation coefficient, the social activity evaluation score is generated using the following formula according to the average number of events, the average number of participants, the actual area of ​​the block, the green area of ​​the block, and the number of opened stores:

[0114]

[0115] Among them, SA is the social activity evaluation score, ε is the social activity evaluation coefficient, N is the number of socially active blocks, Agk is the activity number score of the kth socially active block, Apk is the average number of participants in the kth socially active block during the data collection period, Bak is the actual block area of ​​the kth socially active block, and Gak is the block greening area of ​​the kth socially active block.

[0116] In this embodiment, the socially active block is an area for urban space users to rest and entertain. The socially active blocks are first extracted based on the socially active data, and then the event information, number of participants, basic block information and store data information of each socially active block are obtained. The event information is information when social activities such as parties and exhibitions are held in the socially active block. The participant information is information related to the participants obtained through registration information, camera collection and data processing when the event is held. The basic block information includes information related to the area area, green area, activity area, sanitary area, parking area, etc. related to the area. The store data information is information related to the opened store. Next, the average number of times the socially active block is held during the data collection period is extracted based on the event holding information, and the activity number score is obtained based on the average number of times held, wherein the data collection period is preset, such as one month, and data statistics are performed in units of one month, and the number of times held in each month is counted separately, and then the average number of times held is calculated, and finally the average number of times held is obtained. The average number of times held is obtained, and then the residents are surveyed based on the average number of times held, and the residents' satisfaction scores are obtained, and the average value is calculated based on each satisfaction score, and finally the activity number score is generated. Then, the average number of participants in the socially active block during the data collection period is extracted based on the number of participants information. Then, the actual area of ​​the block and the green area of ​​the block are extracted based on the basic information of the block, and the number of opened stores in the socially active block within the preset range is generated based on the store data information, and finally the social activity evaluation score is generated.

[0117] In one embodiment, after generating the urban space quality evaluation score, the method further comprises the following steps:

[0118] Firstly, the classic Deep Neural Networks (DNN) model in the artificial intelligence algorithm is selected to model and train the street quality measurement data that have been collected and used, such as road traffic data, road usage data and the social activity data, as well as the corresponding quality scoring results, i.e., the urban space quality evaluation score, and generate an intelligent evaluation model for street space quality.

[0119] The construction method of the street space quality intelligent evaluation model is as follows:

[0120] First, the overall model is constructed without considering the street type. Second, three sub-models are constructed respectively considering the differences in the three types of streets: landscape, living, and commercial.

[0121] Specifically, after specific debugging, the structural parameters of the neural network model can be set as follows: the all-type street quality prediction model has three hidden layers, containing 384, 64, and 32 neurons respectively, and a ReLU activation function and a dropout operation of 0.05 are set after each hidden layer. The last layer contains a fully connected layer with 32 inputs and 1 output.

[0122] The landscape, living and commercial street quality prediction model has three hidden layers, containing 168, 64 and 32 neurons respectively. A ReLU activation function and a dropout operation of 0.01 are set after each hidden layer. The last layer contains a fully connected layer with 32 inputs and 1 output.

[0123] In addition, the goodness of fit can be set as: all types of street space quality evaluation model = 0.58; landscape street space quality evaluation model = 0.52; commercial street space quality evaluation model = 0.52; living street space quality evaluation model = 0.50. Thus, the model can be used to learn the complex nonlinear relationship between the host and guest factors and the quality score, and the quality of the street space of other unused street spaces can be scored according to the scenario setting. Therefore, the efficient use of the data related to the quality of street urban space is achieved.

[0124] After generating the urban space quality evaluation score, an urban space quality analysis report can also be generated based on the data. For example, the urban space quality analysis report is as follows:

[0125] Appropriate flow of people can increase the vitality and quality of the street, but when the flow of people is overloaded, the quality of the street will decline. A commercial street about 200 meters long has the highest quality score when the instantaneous flow of people is less than 30. If there are 3-4 groups of people communicating and the rest of the people strolling in the front area of ​​the building, it is the best combination. For example, Xudong Street often attracts a large number of people because it is located in an intersection area. The complex and intertwined traffic flow lines seriously reduce the quality of Xudong Street.

[0126] In one embodiment, Figure 2 As shown, an intelligent evaluation system for urban public space quality based on multi-source data is also provided, the system comprising:

[0127] An evaluation space determination module is used to obtain the urban public area to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface, and obtain the pre-stored traffic evaluation coefficient and social activity evaluation coefficient according to the urban public area to be evaluated;

[0128] The city model updating module is used to obtain the building model of the area to be evaluated and the corresponding basic model data corresponding to the public area of ​​the city to be evaluated, update the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level, and generate an updated regional building model and updated basic model data;

[0129] A spatial data extraction module, for extracting road traffic data based on the updated regional building model, and extracting road use data and social activity data based on the updated basic model data;

[0130] The quality evaluation generation module is used to generate an urban space quality evaluation score based on the traffic evaluation coefficient and the social activity evaluation coefficient according to the road traffic data, the road use data and the social activity data.

[0131] In one embodiment, the evaluation space determination module is further used to:

[0132] Obtain the initial urban public area and the current evaluation precision grade set by the space quality query subject on the space evaluation interface; obtain the query subject identity information of the space quality query subject, compare the query subject identity information with the pre-stored public area query grade library, and generate the sensitive public area corresponding to the space quality query subject; eliminate the initial urban public area according to the pre-stored sensitive public area, and generate the preliminary screening urban public area; generate the associated public area according to the preliminary screening public area, and aggregate the preliminary screening public area and the associated public area to generate the public area to be demarcated; obtain the regional planning data of the public area to be demarcated between the current measurement time and the preset quality evaluation setting time, and An estimated change space region is extracted from the domain planning data; the estimated change area of ​​the estimated change space region is extracted, and a change area area ratio is generated according to the total area of ​​the to-be-demarcated area of ​​the to-be-demarcated public area and the estimated change area area; it is determined whether the flexible area area ratio is greater than or equal to a preset standard area ratio; if it is determined to be yes, a regional evaluation adjustment suggestion is generated, and the regional evaluation adjustment suggestion is sent to the space quality query subject, and the regional adjustment data of the space quality query subject is obtained, and the pre-screened urban public area is adjusted according to the regional adjustment data and the to-be-evaluated urban public area is generated after the adjustment; if it is determined to be no, the to-be-evaluated urban public area is set according to the pre-screened urban public area.

[0133] In one embodiment, the city model updating module is further used for:

[0134] Acquire the architectural model of the area to be evaluated and the corresponding basic model data corresponding to the urban public area to be evaluated, and acquire the model update record data of the architectural model of the area to be evaluated; in response to acquiring the model update record data, acquire the update measurement time period and the number of qualified model updates according to the current evaluation accuracy level; extract the actual number of model data updates within the update measurement time period from the model update record data; judge whether the actual number of model data updates is greater than or equal to the number of qualified model updates; if the judgment is yes, set the architectural model of the area to be evaluated and the basic model data as the updated regional architectural model and the updated basic model data; if the judgment is no, generate a model update instruction, and update the architectural model of the area to be evaluated and the basic model data according to the model update instruction, and generate the updated regional architectural model and the updated basic model data.

[0135] In one embodiment, the city model update module is also used to: obtain the update number closest to the current measurement time among the actual update times of the model data according to the model update instruction, and set the time of the update as the latest model update time, wherein the building model corresponding to the latest model update time is the building model to be updated, and the building model to be updated corresponds to the basic data to be updated; obtain the building environment monitoring data uploaded by the urban space environment management subject during the time period from the latest model update time to the current measurement time; generate a building environment update node according to the building environment monitoring data, and update the building model to be updated and the basic data to be updated according to the building environment update node to generate an updated regional building model and updated basic model data.

[0136] In one embodiment, the city model update module is also used to: generate a random environment comparison number according to the total area of ​​the area to be demarcated, then select a matching number of random comparison model areas from the updated regional building model according to the random environment comparison number, and instruct the urban space environment management subject to conduct field monitoring and obtain field comparison building areas according to the random comparison model areas; then, compare the field comparison building areas with the random comparison model areas, and generate model comparison similarity. Determine whether the model comparison similarity reaches 98%, if it is determined to be yes, generate a current model qualified indication. If it is determined not, obtain the similarity difference between the model comparison similarity and 98%, when the similarity difference is greater than the preset similarity threshold, generate a model review indication, and guide the urban space environment management subject to model review and data update according to the model review indication, and generate the latest updated regional building model and updated basic model data after review and data update.

[0137] In one embodiment, the quality evaluation generation module is also used to: generate a road traffic evaluation score based on the traffic evaluation coefficient and the road traffic data; generate a social activity evaluation score based on the social activity evaluation coefficient and the social activity evaluation score; and generate an urban space quality evaluation score by adding the road traffic evaluation score and the social activity evaluation score.

[0138] In one embodiment, the quality evaluation generation module is also used to: extract the street used roads and the road area information, road occupancy information, road bending information and road flatness information corresponding to each of the street used roads from the road traffic data, wherein the number of the street used roads is n, and the street used roads are streets that have been put into use in the urban public area to be evaluated; calculate the total area of ​​each individual road of each street used road; extract the road occupation area of ​​each street used road and the total legal occupied area of ​​each street used road from the road occupancy information, wherein one street used road corresponds to one road occupation area, the road occupation area is the area occupied by obstacles in the street used road, and the total legal occupied area is the area pre-determined by the road management department in each street used road. The sum of the areas occupied by the area; extracting the actual road bends of the used roads of each street according to the road bend information, and counting the actual number of bends of the actual road bends; screening out the actual road bends corresponding to the actual number of bends greater than the preset standard number of bends, recording them as overload bends, and obtaining the difference between the actual number of bends corresponding to the overload bends and the standard number of bends, and recording them as the number of overload bends, wherein the number of overload bends is m, and one overload bend corresponds to one overload bend number; extracting the road smoothness of the used roads of each street from the road smoothness information; based on the traffic evaluation coefficient, according to the total area of ​​each single road, the road occupied area, the legal total occupied area, the number of overload bends, the standard number of bends and the road smoothness, the following formula is used to generate the road traffic evaluation score:

[0139]

[0140] Among them, TF is the road traffic evaluation score, δ is the traffic evaluation coefficient, n is the number of used roads in the street, Wsdi is the total area of ​​individual roads in the used roads of the i-th street, Woci is the road occupation area of ​​the used roads of the i-th street, Wta is the total legal occupation area, m is the number of overload bends, Ctj is the number of overload bends of the j-th overload bend, Cs is the number of standard bends, and Tir is the road flatness.

[0141] In one embodiment, the quality evaluation generation module is also used to: extract socially active blocks according to the socially active data, and obtain the event holding information, number of participants, basic block information and store data information of each socially active block; extract the average number of events held in the socially active block during the data collection period according to the event holding information, and obtain the event number score according to the average number of events held, wherein the data collection period is preset; extract the average number of participants in the socially active block during the data collection period according to the number of participants information; extract the actual area of ​​the block and the green area of ​​the block according to the basic information of the block, and generate the number of opened stores in the socially active block within a preset range according to the store data information; based on the social activity evaluation coefficient, the social activity evaluation score is generated using the following formula according to the average number of events held, the average number of participants, the actual area of ​​the block, the green area of ​​the block and the number of opened stores:

[0142]

[0143] Among them, SA is the social activity evaluation score, ε is the social activity evaluation coefficient, N is the number of socially active blocks, Agk is the activity number score of the kth socially active block, Apk is the average number of participants in the kth socially active block during the data collection period, Bak is the actual block area of ​​the kth socially active block, and Gak is the block greening area of ​​the kth socially active block.

[0144] The quality evaluation generation module is also used to perform the following steps:

[0145] The overall model is constructed without considering the street type. Secondly, three sub-models are constructed respectively considering the differences in the three types of streets: landscape, living, and commercial.

[0146] Specifically, after specific debugging, the structural parameters of the neural network model can be set as follows: the all-type street quality prediction model has three hidden layers, containing 384, 64, and 32 neurons respectively, and a ReLU activation function and a dropout operation of 0.05 are set after each hidden layer. The last layer contains a fully connected layer with 32 inputs and 1 output.

[0147] The landscape, living and commercial street quality prediction model has three hidden layers, containing 168, 64 and 32 neurons respectively. A ReLU activation function and a dropout operation of 0.01 are set after each hidden layer. The last layer contains a fully connected layer with 32 inputs and 1 output.

[0148] In addition, the goodness of fit can be set as: all types of street space quality evaluation model = 0.58; landscape street space quality evaluation model = 0.52; commercial street space quality evaluation model = 0.52; living street space quality evaluation model = 0.50. Thus, the model can be used to learn the complex nonlinear relationship between the host and guest factors and the quality score, and the quality of the street space of other unused street spaces can be scored according to the scenario setting. Therefore, the efficient use of the data related to the quality of street urban space is achieved.

[0149] The quality evaluation generation module is also used to perform the following steps: an urban space quality analysis report can also be generated based on the data. For example, the urban space quality analysis report is as follows:

[0150] Appropriate flow of people can increase the vitality and quality of the street, but when the flow of people is overloaded, the quality of the street will decline. A commercial street about 200 meters long has the highest quality score when the instantaneous flow of people is less than 30. If there are 3-4 groups of people communicating and the rest of the people strolling in the front area of ​​the building, it is the best combination. For example, Xudong Street often attracts a large number of people because it is located in an intersection area. The complex and intertwined traffic flow lines seriously reduce the quality of Xudong Street.

[0151] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned method for intelligent evaluation of urban public space quality based on multi-source data are implemented.

[0152] In one embodiment, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for intelligent evaluation of urban public space quality based on multi-source data are implemented.

[0153] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0154] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0155] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. An intelligent evaluation method for urban public space quality based on multi-source data, characterized in that: The method comprises: Obtain the urban public area to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface, and obtain the pre-stored traffic evaluation coefficient and social activity evaluation coefficient according to the urban public area to be evaluated; Acquire the building model of the area to be evaluated and the corresponding basic model data corresponding to the urban public area to be evaluated, update the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level, and generate an updated area building model and updated basic model data; Extracting road traffic data based on the updated regional building model, and extracting road use data and social activity data based on the updated basic model data; Based on the traffic evaluation coefficient and the social activity evaluation coefficient, an urban space quality evaluation score is generated according to the road traffic data, the road use data and the social activity data.

2. The intelligent evaluation method for urban public space quality based on multi-source data according to claim 1 is characterized in that: Obtain the urban public areas to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface; including: Obtain the initial urban public area and current evaluation accuracy level set by the space quality query subject on the space evaluation interface; Acquire the query subject identity information of the space quality query subject, compare the query subject identity information with the pre-stored public area query grade library, and generate a sensitive public area corresponding to the space quality query subject; Eliminating the initial urban public areas according to the pre-stored sensitive public areas, and generating a preliminary screening urban public area; Generate an associated public area according to the initial screening public area, and aggregate the initial screening public area and the associated public area to generate a public area to be demarcated; Acquire the regional planning data of the public area to be demarcated between the current measurement time and the preset quality evaluation setting time, and extract the estimated change space area from the regional planning data; Extracting the estimated changed region area of ​​the estimated changed spatial region, and generating a changed region area ratio according to the total area of ​​the to-be-demarcated area of ​​the to-be-demarcated public area and the estimated changed region area; Determining whether the flexible area ratio is greater than or equal to a preset standard area ratio; If the judgment is yes, then generate a regional evaluation adjustment suggestion, send the regional evaluation adjustment suggestion to the space quality query subject, obtain the regional adjustment data of the space quality query subject, adjust the initially screened urban public area according to the regional adjustment data, and generate the urban public area to be evaluated after the adjustment; If the judgment is no, then the urban public areas to be evaluated are set according to the initially screened urban public areas.

3. The intelligent evaluation method for urban public space quality based on multi-source data according to claim 2 is characterized in that: Acquiring the building model of the area to be evaluated and the corresponding basic model data corresponding to the urban public area to be evaluated, updating the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level and generating an updated area building model and updated basic model data; including: Acquire the building model of the area to be evaluated and the corresponding basic model data corresponding to the public area of ​​the city to be evaluated, and acquire the model update record data of the building model of the area to be evaluated; In response to acquiring the model update record data, acquiring an update measurement time period and a model update qualified number of times according to the current evaluation accuracy level; Extracting the actual number of model data updates within the update measurement time period from the model update record data; Determine whether the actual update times of the model data is greater than or equal to the qualified model update times; If the judgment is yes, the building model of the area to be evaluated and the basic model data are set as the updated building model of the area and the updated basic model data; If the judgment is no, a model update instruction is generated, and the building model of the area to be evaluated and the basic model data are updated according to the model update instruction, and an updated regional building model and updated basic model data are generated.

4. The intelligent evaluation method for urban public space quality based on multi-source data according to claim 1 is characterized in that: Based on the traffic evaluation coefficient and the social activity evaluation coefficient, generating an urban space quality evaluation score according to the road traffic data, the road use data and the social activity data; comprising: Based on the traffic evaluation coefficient, generating a road traffic evaluation score according to the road traffic data and the road use data; Based on the social activity evaluation coefficient, generating a social activity evaluation score according to the social activity data; The road traffic evaluation score and the social activity evaluation score are added together to generate an urban space quality evaluation score.

5. The intelligent evaluation method for urban public space quality based on multi-source data according to claim 4 is characterized in that: Based on the traffic evaluation coefficient, generating a road traffic evaluation score according to the road traffic data and the road use data; comprising: Extracting street used roads and road area information, road occupancy information, road bending information and road leveling information corresponding to each street used road from the road traffic data, wherein the number of street used roads is n, and the street used roads are streets that have been put into use in the public area of ​​the city to be evaluated; Calculate the total individual road area of ​​used roads for each of said streets; Extracting the road occupation area of ​​each street's used roads and the legally occupied total area of ​​each street's used roads from the road occupation information, wherein one street's used road corresponds to one road occupation area, the road occupation area is the area occupied by obstacles in the street's used roads, and the legally occupied total area is the sum of the areas occupied by the areas pre-demarcated by the road management department in the street's used roads; Extracting actual road bends of used roads of each street according to the road bend information, and counting the actual number of bends of the actual road bends; Screen out actual road bends corresponding to actual bend times greater than a preset standard bend time, record them as overload bends, and obtain the difference between the actual bend times corresponding to the overload bends and the standard bend times, and record them as the overload bend number, wherein the number of the overload bends is m, and one overload bend corresponds to one overload bend number; Extracting the road smoothness of each of the streets from the road smoothness information; Based on the traffic evaluation coefficient, the road traffic evaluation score is generated using the following formula according to the total area of ​​each individual road, the road occupied area, the legal occupied total area, the number of overloaded bends, the number of standard bends and the road flatness: Among them, TF is the road traffic evaluation score, δ is the traffic evaluation coefficient, n is the number of used roads in the street, Wsdi is the total area of ​​individual roads in the used roads of the i-th street, Woci is the road occupation area of ​​the used roads of the i-th street, Wta is the total legal occupation area, m is the number of overload bends, Ctj is the number of overload bends of the j-th overload bend, Cs is the number of standard bends, and Tir is the road flatness.

6. The intelligent evaluation method for urban public space quality based on multi-source data according to claim 5 is characterized in that: Based on the social activity evaluation coefficient, generating a social activity evaluation score according to the social activity data includes: Extracting socially active blocks according to the socially active data, and obtaining event information, number of participants, basic block information, and store data information of each socially active block; Extracting the average number of times the socially active block is held in a data collection period according to the event holding information, and obtaining an event number score according to the average number of times held, wherein the data collection period is preset; Extracting the average number of participants in the socially active block during the data collection period according to the number of participants information; Extracting the actual area of ​​the block and the green area of ​​the block according to the basic information of the block, and generating the number of opened stores within a preset range of the socially active block according to the store data information; Based on the social activity evaluation coefficient, the social activity evaluation score is generated using the following formula according to the average number of events, the average number of participants, the actual area of ​​the block, the green area of ​​the block, and the number of opened stores: Among them, SA is the social activity evaluation score, ε is the social activity evaluation coefficient, N is the number of socially active blocks, Agk is the activity number score of the kth socially active block, Apk is the average number of participants in the kth socially active block during the data collection period, Bak is the actual block area of ​​the kth socially active block, and Gak is the block greening area of ​​the kth socially active block.

7. An intelligent evaluation system for urban public space quality based on multi-source data, characterized in that: The system comprises: An evaluation space determination module is used to obtain the urban public area to be evaluated and the current evaluation accuracy level set by the space quality query subject on the space evaluation interface, and obtain the pre-stored traffic evaluation coefficient and social activity evaluation coefficient according to the urban public area to be evaluated; The city model updating module is used to obtain the building model of the area to be evaluated and the corresponding basic model data corresponding to the public area of ​​the city to be evaluated, update the building model of the area to be evaluated and the basic model data according to the current evaluation accuracy level, and generate an updated regional building model and updated basic model data; A spatial data extraction module, for extracting road traffic data based on the updated regional building model, and extracting road use data and social activity data based on the updated basic model data; The quality evaluation generation module is used to generate an urban space quality evaluation score based on the traffic evaluation coefficient and the social activity evaluation coefficient according to the road traffic data, the road use data and the social activity data.

8. The urban public space quality intelligent evaluation system based on multi-source data according to claim 7 is characterized in that: The evaluation space determination module is also used for: Obtain the initial urban public area and the current evaluation precision grade set by the space quality query subject on the space evaluation interface; obtain the query subject identity information of the space quality query subject, compare the query subject identity information with the pre-stored public area query grade library, and generate the sensitive public area corresponding to the space quality query subject; eliminate the initial urban public area according to the pre-stored sensitive public area, and generate the preliminary screening urban public area; Generate an associated public area according to the initial screening public area, and aggregate the initial screening public area and the associated public area to generate a public area to be demarcated; Acquire the regional planning data of the public area to be demarcated between the current measurement time and the preset quality evaluation setting time, and extract the estimated change space area from the regional planning data; Extracting the estimated change area of ​​the estimated change space area, and generating a change area area ratio according to the total area of ​​the to-be-demarcated public area and the estimated change area area; judging whether the flexible area area ratio is greater than or equal to a preset standard area ratio; If the judgment is yes, a regional evaluation adjustment suggestion is generated and sent to the spatial quality query subject, and the regional adjustment data of the spatial quality query subject is obtained, and the initially screened urban public area is adjusted according to the regional adjustment data and the urban public area to be evaluated is generated after the adjustment; if the judgment is no, the urban public area to be evaluated is set according to the initially screened urban public area.

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

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images