Method and system for evaluating value of urban inefficient stock space

Abstract

The application relates to the technical field of urban stock space management, and discloses a value evaluation method and system for urban inefficient stock space, which comprises the following steps: acquiring evaluation basic data, forming a service task behavior chain, constructing an actual human flow network and an expected behavior network, determining effective mismatch edges and forming reasons corresponding to the edge relationship of the two networks, screening candidate stock spaces according to the effective mismatch edges, connecting the candidate stock spaces to the actual human flow network as public service nodes and reconnecting the service task behavior chain, and determining a value evaluation result according to the completion state of the behavior chain before and after the reconnection. The application can identify a public service task gap which does not form an actual human flow connection, and determine the public service undertaking, time-sharing use, channel repair or specific group service value of the gap according to the repair state of the candidate stock space on the gap.

Description

Technical Field

[0001] This invention relates to the field of urban stock space management technology, and in particular to a method and system for assessing the value of inefficient urban stock space. Background Technology

[0002] As urban development shifts from incremental development to stock renewal, a significant number of vacant buildings, underutilized ancillary facilities, elevated spaces, spaces attached to transportation facilities, enclosed courtyards, and marginal spaces have emerged within cities. These spaces already possess certain architectural structures or infrastructure conditions, but their existing functions, opening hours, or spatial connections cannot fully support the actual public service needs of the surrounding residents.

[0003] Related technologies typically assess the supply and demand of public services using factors such as facility quantity, service radius, population density, road distance, or existing pedestrian traffic, and determine whether existing space has potential for renewal and utilization based on the assessment results. Among these, the assessment method based on pedestrian networks can analyze the relationship between residential space and public service facilities using residents' actual travel records, and has a stronger behavioral expressive ability compared to the fixed service radius method.

[0004] However, existing pedestrian networks primarily record spatial connections that have already occurred. When a certain type of facility is lacking in the area to be assessed, or when residents cannot use the facility due to reasons such as blocked passageways, inaccessible entrances, or mismatched opening hours, the corresponding pedestrian connections will not form within the area. Judging directly based on existing pedestrian flow can easily lead to identifying service demands suppressed by spatial conditions as low demand. Furthermore, while related technologies can usually determine if a region has insufficient facility supply, it is difficult to correlate specific service gaps with specific inefficient existing spaces, and it is also difficult to verify whether connecting an existing space to the public service network can enable residents to fulfill their service tasks. A comprehensive evaluation based solely on spatial area, location, and the number of facilities cannot fully reflect the restorative role of existing spaces in addressing specific missing connections within the public service network. Summary of the Invention

[0005] The main purpose of this application is to provide a method and system for assessing the value of inefficient urban stock spaces, aiming to solve the technical problems that related technologies have difficulty identifying potential public service needs that have not formed actual pedestrian connections, and the inability to evaluate the value of inefficient stock spaces based on the recovery results of specific behavioral chains.

[0006] To achieve the above objectives, the present invention provides a method for assessing the value of inefficient urban existing spaces, the method comprising the following steps: Acquire basic assessment data for the area to be assessed, form a service task behavior chain, and construct an actual pedestrian flow network and a desired behavior network. The basic assessment data includes spatial data, existing spatial data, and resident activity data. By mapping the actual pedestrian flow network and the expected behavior network along edges, we can determine the effective mismatched edges with service task gaps and the reasons for their formation. Candidate stock spaces are determined based on effective mismatch edges and stock space data. These candidate stock spaces are then connected to the actual pedestrian flow network as public service nodes. The service task behavior chains corresponding to the effective mismatch edges are then reconnected. The value assessment results of candidate stock space are determined based on the completion status of the service task behavior chain before and after reconnection.

[0007] To achieve the above objectives, the present invention also provides a value assessment system for inefficient urban existing spaces, comprising: The network construction module is used to acquire the basic assessment data of the area to be assessed, form a service task behavior chain, and construct the actual pedestrian flow network and the expected behavior network. The basic assessment data includes spatial data, existing spatial data, and resident activity data. The mismatch identification module is used to perform edge relationship mapping between the actual pedestrian flow network and the expected behavior network, and to determine the effective mismatch edges with service task gaps and the reasons for the formation of the effective mismatch edges; The spatial access module is used to determine candidate existing spaces based on effective mismatch edges and existing space data, connect the candidate existing spaces as public service nodes to the actual pedestrian flow network, and reconnect the service task behavior chain corresponding to the effective mismatch edges. The results generation module is used to determine the value assessment results of candidate stock space based on the completion status of the service task behavior chain before and after reconnection.

[0008] One or more technical solutions proposed in this application have at least the following technical effects: This application expresses the service task connections that are typically formed under similar group, spatial and temporal conditions through expected behavior networks. It can identify service connections that have not been formed in the actual flow of people due to lack of facilities or limited space, thereby reducing the possibility of mistaking low flow of people for low demand.

[0009] This application identifies suspected mismatched edges by recording abnormal behaviors such as service task interruption, abnormal detours, leaving after waiting, repeated round trips, and cross-regional access. It can distinguish between stable service task gaps and occasional activity changes, thereby improving the usability of mismatched edge identification results.

[0010] This application effectively matches mismatched edges with specific existing spaces and filters candidate existing spaces according to spatial conditions, entrance conditions, service hours and target group requirements, thus excluding spaces that are only geographically close but cannot actually undertake service tasks.

[0011] This application connects candidate existing spaces to the actual pedestrian network as public service nodes and reprocesses the corresponding service task behavior chain. It can directly determine the value assessment result of existing spaces based on whether the service tasks are completed, whether cross-regional access is reduced, and whether the target group is reachable.

[0012] This application adopts necessary acceptance conditions to process candidate spaces. If the safety use conditions, entrance access conditions, or space openness conditions are not met, other space attributes cannot replace these conditions. This can reduce misjudgments caused by the substitution of different indicators during the comprehensive evaluation process.

[0013] The value assessment results output by this application include the existing space number, corresponding effective mismatch edge, cause of formation, applicable group, applicable time period, recoverable behavior chain and restricted use conditions, which can provide clear data results for urban renewal field surveys, configuration of public service facilities and adjustment of existing space functions. Attached Figure Description

[0014] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the accompanying drawings used in the description of the embodiments are briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0016] Figure 1 This is a schematic diagram illustrating the overall process of an embodiment of the urban inefficient stock space valuation method of this application. Figure 2 This is a schematic diagram illustrating the basic data processing and two-layer pedestrian flow network construction for the evaluation of this application; Figure 3 This is a schematic diagram illustrating the effective process for identifying and diagnosing the causes of mismatched edges in this application. Figure 4 This is a schematic diagram illustrating the matching of candidate stock space and the reconnection of service task behavior chains in this application; Figure 5 This is a schematic diagram illustrating the determination and output of the valuation results for this application; Figure 6 This is a schematic diagram of the pedestrian network before the access of the candidate existing space in a specific example of this application; Figure 7 This is a schematic diagram of the behavior chain reconnection after the candidate existing space is accessed in a specific example of this application; Figure 8 This is a comparative diagram of the behavior chain recovery results in a specific example of this application; Figure 9This is a schematic diagram of the value assessment system for inefficient urban stock spaces in this application.

[0017] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0018] It should be understood that the specific embodiments described herein are used to explain the technical solutions of this application and are not intended to limit this application. For those skilled in the art, equivalent substitutions or adaptive adjustments made based on the technical content disclosed in this application can all be used as executable implementation methods of this application.

[0019] To better understand the technical solution of this application, a detailed description is provided below in conjunction with the accompanying drawings and specific embodiments. The implementing entity of the embodiments of this application can be a server, workstation, urban information platform, or a data processing system composed of multiple computing devices, which has spatial data processing, graph relationship processing, and data storage functions. The following description uses an urban inefficient stock space value assessment system as the implementing entity.

[0020] The inefficient urban stock space referred to in this application refers to urban spaces that have been constructed or whose basic site development has been completed, but which are idle, partially idle, idle during specific periods, have low frequency of use of existing functions, or are incompatible with the needs of surrounding public services within a continuous statistical period. The inefficient urban stock space can be interior space of a building or outdoor space with clear boundaries and entrance conditions.

[0021] like Figure 1 As shown in the figure, this application provides a method for assessing the value of inefficient urban stock space, the method including steps S100 to S400.

[0022] Step S100: Obtain the basic assessment data of the area to be assessed, form a service task behavior chain, and construct the actual pedestrian flow network and the expected behavior network. The basic assessment data includes spatial data, existing spatial data, and resident activity data.

[0023] In this embodiment of the invention, spatial data is used to represent the physical spaces and their connections within the area to be evaluated that residents can access, pass through, or receive services from. Spatial data can be obtained from urban geographic information platforms, planning management platforms, building information models, road surveying results, public service facility registration systems, and on-site surveying results. The spatial data can at least determine the location of building outlines, building entrances, roads, pedestrian walkways, public transportation stops, public service facilities, and spatial obstacles affecting passage.

[0024] Specifically, the system treats buildings, public service facilities, public transportation facilities, and major public spaces as spatial nodes, and roads, sidewalks, pedestrian crossings, building passageways, and connecting spaces accessible to pedestrians as spatial connections. For large buildings or buildings with multiple independent entrances, they can be divided into multiple spatial nodes based on their internal independently usable areas and entrance correspondences. For facilities with only one registered location but multiple actual service entrances, different entrances can be treated as entrance nodes, and these entrance nodes can be associated with the same service facility node.

[0025] In one feasible implementation, spatial data is stored using a unified urban planar coordinate system. The system reads coordinate reference information from various data sources and transforms data represented in different coordinate systems to the same system. If there is a positional discrepancy between the building outline and road data, the system can correct the location based on the shortest accessible connection between the building entrance and the adjacent sidewalk. The corrected building entrance should fall within the building boundary or a preset distance from the building boundary and be connectable to the road network via pedestrian access edges.

[0026] It should be noted that spatial obstacles affecting passage include walls, fences, insurmountable green belts, waterways, boundaries of enclosed plots, construction-enclosed areas, and interior areas of buildings not open to the public. When generating spatial connections, the system truncates corresponding connection edges based on these spatial obstacles. The resulting passable network reflects the actual paths that people can choose under the current spatial conditions.

[0027] Existing space data is used to describe inefficient existing spaces within an area to be assessed that are suitable for valuation. This data can be derived from urban existing space surveys, public asset usage registration, property usage records, building access control statistics, personnel counting equipment, on-site inspections, and authorized access to building interior space data. Each existing space must at least record its space number, location, usable area, available entrances, current use, and usable time period.

[0028] Furthermore, existing space data can record net height, continuous usable area, number of entrances and exits, entrance and exit width, status of steps or ramps, water supply and drainage conditions, power supply conditions, ventilation conditions, safety exits, fire exits, and internal fixed facilities. This data is used to subsequently establish the necessary conditions for undertaking the target service and to determine whether candidate existing spaces can fulfill the target service tasks.

[0029] When only some floors or areas of a building are underutilized, the system divides them according to the principles of independent accessibility, independent accessibility, and the ability to form a continuous usable area. For example, if the east-facing room on the first floor of a community service building is vacant for a long time, while the west-facing room on the first floor and the second floor are in normal use, the system can register the east-facing room on the first floor, along with its corresponding corridors, entrances, and supporting facilities, as independent existing space nodes, avoiding treating the entire building as a single underutilized space.

[0030] Resident activity data is used to form chains of actual activity events and service tasks. This data may include anonymized mobile device location records, public transportation station entry and exit records, public service facility entry records, facility reservation records, entrance personnel counts, public bicycle start-up and finish line data, and facility queuing and service completion records. When receiving resident activity data, the system removes information that directly identifies individuals and uses random activity identifiers to connect the same continuous activity processes.

[0031] It's easy to understand that a single location record usually cannot directly indicate that a resident is receiving public services. The system needs to combine the dwell time, facility entrance location, time period of the activity, and preceding and following activity nodes to determine the activity type. For example, if an activity marker appears near the entrance of a childcare facility, then enters the facility and stays for a preset dwell time, the system can identify it as a childcare service access event; if the activity marker only moves continuously along the road outside the facility and the dwell time is less than the preset dwell time, it is identified as a passing event.

[0032] like Figure 2 As shown, the system performs coordinate unification and spatial node processing on spatial data and existing spatial data to establish a spatial node set containing existing spatial nodes. Nodes in the spatial node set can include residential nodes, service facility nodes, transportation nodes, public space nodes, and existing spatial nodes. Node attributes include at least node number, node type, spatial location, available entrance, and available time period. Existing spatial nodes may be in a non-service function state in the initial actual pedestrian flow network, and are subsequently converted into candidate public service nodes in step S300 based on the candidate space matching results.

[0033] The system maps resident activity data to a set of spatial nodes according to the time of occurrence. Specifically, the system reads the spatial location of each activity record and compares it with spatial nodes within a preset location range. When the activity location falls within the boundary of a building or facility, it is preferentially mapped to the corresponding building or facility node. When the activity location is near an entrance and subsequent records enter the building's area, the entrance is used as the entry connection point. When the activity location cannot be reliably mapped to a specific building, it is mapped to a road node or street node to avoid converting location errors into false facility visits.

[0034] The system arranges activity events sequentially according to the occurrence time of the same activity identifier, connecting adjacent activity events within a continuous activity cycle. A continuous activity cycle can start from the activity identifier leaving the residential node and end when it returns to the residential node, enters a long-stay node, or exceeds a preset inactivity time. In one executable implementation, the preset inactivity time can be set to 4 hours; for groups working continuously at night, the preset inactivity time can be adjusted to 6 hours based on their activity patterns.

[0035] The system identifies service task types based on facility type, access order, and time of occurrence. Service task types can include childcare pick-up and drop-off, community healthcare, senior day activities, cultural activities, public health, public transportation ancillary services, and convenience services. These service task types can also be expanded according to the public service classification rules of the city being evaluated.

[0036] For example, if an activity resident leaves the residential node at 7:10 AM, enters the childcare facility node at 7:25 AM, leaves the childcare facility node at 7:35 AM, and enters the rail transit station node at 7:50 AM, the system can form a childcare pick-up and drop-off service task behavior chain connecting the residential node, childcare facility node, and rail transit station node. As another example, if an activity resident enters a community medical facility from the residential node and returns to the residential node after completing their stay, the system can form a community medical service task behavior chain.

[0037] The system establishes actual pedestrian flow edges based on adjacent spatial nodes, time periods, and group types in the service task behavior chain. Each actual pedestrian flow edge records at least the starting node, ending node, service task type, time period, group type, number of behavior chains, typical path, and activity status. The time period can be divided into morning, daytime, evening, and nighttime, or other time periods can be set according to the needs of urban public service operation.

[0038] Group types can be categorized based on authorized demographic data, facility service recipients, or assistive device information. For example, childcare pick-up and drop-off behavior chains can correspond to childcare groups, stable behavior chains entering elderly service facilities can correspond to elderly service groups, and activity records using accessible entrances or accessible transportation facilities can correspond to groups with mobility assistance needs. The system can perform statistical processing based on group categories without retaining specific individual identities.

[0039] The system aggregates actual pedestrian flow edges within a preset statistical period to generate an actual pedestrian flow network. The preset statistical period can be 1 day, 1 week, or other time ranges that can reflect the patterns of public services. In one executable implementation, the system uses 30 consecutive days of data, including 20 working days and 10 rest days, and generates networks for weekday mornings, weekdays, weekday evenings, rest days, and nights, respectively.

[0040] To construct the desired behavior network, the system obtains the regional matching attributes of the candidate regions. The group composition in the regional matching attributes can include the age structure of the resident population, the number of service recipients, and the distribution of the main commuting groups; the spatial form can include building density, road connectivity, public transportation access conditions, and the distribution of residential nodes; the travel time can include the main time away from home, the time of accessing public services, and the time of returning to the residential node.

[0041] The system compares the regional matching attributes of the candidate region with the corresponding regional matching attributes of the region to be evaluated item by item. Each attribute can be pre-converted into a unified category or interval. For example, the proportion of elderly population can be divided into three intervals: low, medium, and high; the rail transit access status can be divided into no access, walking access, and transfer access; and the main commuting hours can be divided into 6:00 to 8:00, 7:00 to 9:00, and 8:00 to 10:00.

[0042] In one feasible implementation, if the difference between each matching attribute of a candidate region and its corresponding attribute in the region to be evaluated does not exceed a preset difference threshold, the candidate region is retained as a reference region. The preset difference threshold can be set according to the data precision. For example, the difference threshold for the proportion of major population groups can be set to 10 percentage points, the difference threshold for average building density can be set to 15%, and the difference threshold for the start time of major travel periods can be set to 30 minutes.

[0043] The system groups the service task behavior chains of the reference area according to the service task type and counts the number of statistical periods in which the connection relationship of each node appears. If multiple reference areas continuously show the connection relationship of "residential node to childcare facility node" and "childcare facility node to rail transit node" on weekday mornings, it indicates that the node connection relationship can represent the spatial connection that the corresponding group usually needs to form when completing the childcare pick-up and drop-off task.

[0044] The system converts node connections with a statistical period count reaching a preset period threshold into service task connection templates according to the order of the nodes. Each service task connection template records the starting node type, target service type, subsequent node types, group type, and occurrence time. For 30 consecutive days of data, the preset period threshold can be set to 12 working days; for cultural activity service tasks that occur only once or twice per week, the statistical unit can be adjusted to weeks, and the preset period threshold can be set to 3 weeks out of 4 consecutive weeks.

[0045] It should be noted that the starting node type indicates the spatial node type where the service task begins, the target service type indicates the type of public service that the service task needs to complete, and the subsequent node type indicates the type of spatial node to be reached after completing the public service. By converting the specific node numbers of the reference area into the above type attributes, service task behavior chains with different numbers of nodes, node numbers, and specific spatial locations in different reference areas can be expressed using the same service task connection template.

[0046] The system traverses the spatial nodes in the region to be evaluated, reading the node type, associated group, and corresponding activity time period of each spatial node. When the node type of a spatial node is the same as the starting node type of the service task connection template, and the associated group and activity time period of the spatial node match the group type and the occurrence time period, respectively, the system determines the spatial node as the starting node of the service task connection template in the region to be evaluated. When there are multiple spatial nodes in the region to be evaluated that meet the conditions, the system performs subsequent projection processing on each spatial node to form the expected behavior edges corresponding to each starting node.

[0047] For subsequent nodes of the task, the system queries service task behavior chains that are associated with the starting node and whose group type and occurrence time are the same as the service task connection template. From these service task behavior chains, spatial nodes with the same node type as the subsequent node are extracted, and the spatial node with the most frequent occurrences is identified as the subsequent node. If no matching service task behavior chain is found, the system searches along the actual traversable network for spatial nodes with the same node type as the subsequent node, and the spatial node with the shortest traversal path is identified as the subsequent node.

[0048] The system further determines the target service node. When a service facility of the same type as the target service exists within the preset access range corresponding to the starting node, the system determines the spatial node corresponding to the service facility with the shortest accessible path as the target service node. When multiple similar service facilities with different actual access counts exist, the spatial node corresponding to the service facility with the most actual access counts can also be determined as the target service node. When no service facility of the same type as the target service exists within the preset access range, the system establishes a virtual service node associated with the starting node and the target service type, and determines the virtual service node as the target service node.

[0049] The virtual service node is a data node used to represent the target service function that should be configured in the area to be evaluated. The virtual service node records the virtual node number, associated starting node, target service type, group type, occurrence time, and subsequent nodes of the task, and does not indicate that there are already physical service facilities in the area to be evaluated. In step S200, the system queries whether there is an actual pedestrian flow edge in the actual pedestrian flow network that points from the same starting node to the same target service type, based on the target service type recorded in the virtual service node.

[0050] The system connects the starting node and the target service node in the area to be evaluated according to the service task connection template, establishing expected behavior edges, and treating subsequent nodes as subsequent attributes of the expected behavior edges. Each expected behavior edge records at least the starting node number, the target service node number, the target service type, the subsequent node number, the group type, and the time period. Thus, the service task patterns in the reference area are converted into expected behavior edges with specific spatial nodes in the area to be evaluated as objects, and these expected behavior edges can correspond to the actual pedestrian flow edges in the area to be evaluated.

[0051] When comparing connection strength, the system first averages the number of behavioral chains connecting corresponding nodes in the reference region over a valid statistical period, and then converts this number into the average number of occurrences per target group within a unit statistical period based on the number of target groups in the reference region. Next, based on the number of corresponding target groups in the region to be evaluated and the valid observation period, the system determines the expected connection strength of the desired behavioral edge. The preset strength threshold is set based on the expected connection strength, thereby avoiding misjudgments of connection strength due to differences in population size or activity data coverage periods between the reference region and the region to be evaluated.

[0052] The system writes the expected behavior edges that have been projected into the expected behavior network according to the group type and the time period of occurrence. Thus, the starting node in the expected behavior network is a specific spatial node in the area to be evaluated, the target service node is a physical service facility node in the area to be evaluated or a virtual service node associated with the starting node, and the subsequent nodes are specific spatial nodes in the area to be evaluated. The actual pedestrian flow network is used to represent the node connections that have already occurred in the area to be evaluated. Both networks use the same starting node number, target service type, group type, and time period of occurrence for recording, thereby enabling edge relationship mapping in step S200.

[0053] Step S200: Perform edge relationship mapping between the actual pedestrian flow network and the expected behavior network to determine the effective mismatched edges with service task gaps and the reasons for their formation.

[0054] like Figure 3As shown, the system maps each desired behavior edge to actual pedestrian flow edges in the actual pedestrian flow network according to the starting node, target service type, group type, and occurrence time. Specifically, the system reads the starting node number, target service type, group type, occurrence time, and subsequent node number of the desired behavior edge, and queries the actual pedestrian flow network for actual pedestrian flow edges that originate from the same starting node, point to a service facility node with the same target service type, and have the same group type and occurrence time. When the target service node of the desired behavior edge is a virtual service node, the system uses the target service type recorded by the virtual service node for querying.

[0055] When there are actual pedestrian edges in the actual pedestrian network that point to the same target service type from the same starting node, the system continues to compare the connection strength and path status of the actual pedestrian edges, and checks whether it is possible to continue to reach the subsequent node of the task recorded by the expected behavior edge after completing the target service; when there are no corresponding actual pedestrian edges in the actual pedestrian network, the system checks whether the same service task is completed through nodes outside the region or distant nodes, thereby distinguishing between completely missing connections and abnormal connection spatial locations.

[0056] The connection strength can be represented by the number of behavioral chains that complete the corresponding service task within a preset statistical period. The preset strength threshold is set based on the expected connection strength of the expected behavioral edge. The expected connection strength is standardized according to the effective statistical period of the reference area and the number of target groups, and then determined according to the effective observation period and the number of target groups of the area to be evaluated. For example, after the above processing, if the expected connection strength of a certain type of expected behavioral edge in the area to be evaluated is 40 to 60 times per workday, while the corresponding actual pedestrian flow edge only appears 3 times per workday, then the actual pedestrian flow edge can be marked as having a connection strength lower than the preset strength threshold.

[0057] The actual path length represents the distance a resident needs to travel along the existing accessible network from the service task's starting node to the target service facility. Preset path thresholds can be set according to group type and service task. For example, a preset path threshold for daytime activities for the elderly can be set to 500 meters, while a path threshold for childcare pick-up and drop-off that requires further travel to a rail transit station can be determined by adding 300 meters to the normal commuting path.

[0058] When the actual pedestrian flow edge corresponding to the expected behavior edge is in any of the following states: missing connection, connection strength below a preset strength threshold, service task completed across regions, or actual path length exceeding a preset path threshold, the system identifies the expected behavior edge as a suspected mismatch edge. A suspected mismatch edge must at least record the expected starting range, starting node number, target service type, subsequent task node number, target group, time period, and edge abnormal state.

[0059] The system further obtains abnormal behavior records corresponding to suspected mismatched edges. Service task interruption refers to the behavior chain ending at the position where the target service node should appear or directly entering a subsequent node unrelated to the service task; abnormal detour refers to the behavior chain first deviating from the main travel direction to visit the target service facility, and then returning to the original main travel direction; waiting and leaving refers to the activity identifier staying at the facility entrance or queuing area for a preset waiting time and then leaving without forming a facility access event; repeated round trips refer to the same service task passing through the same road segment multiple times or returning to the same facility entrance multiple times within a preset time range.

[0060] In one feasible implementation, a waiting-and-leaving record can be generated if the waiting time at the facility entrance exceeds 15 minutes and no facility access event is generated; a repeated round-trip record can be generated if the same activity identifier passes through the same facility entrance more than twice within 60 minutes and returns to the original road node. The specific values ​​mentioned above can be adjusted according to the service type; different preset waiting times can be set for childcare facilities, medical facilities, and cultural activity facilities.

[0061] The system counts the number of times abnormal behavior records repeat within a preset statistical period. When an abnormal behavior record appears only on a single date, it can be kept as a record to be observed; when an abnormal behavior record repeats on multiple working days or multiple weeks, and the number of repetitions reaches a preset threshold, the suspected mismatch edge is identified as a valid mismatch edge. In the example data of 30 consecutive days, the preset threshold can be set to 8 times; for service tasks occurring weekly, the preset threshold can be set to 3 times.

[0062] Once the valid mismatch edge is identified, the system obtains the corresponding cause determination data. This cause determination data includes target service facility distribution data, facility service status data, facility opening hours data, route access data, facility entrance data, and entrance location identification data. All cause determination data should correspond to the service task type, target group, and time period of the valid mismatch edge.

[0063] When the target service facility is not found within the preset access range, and the number of behavior records pointing to similar service facilities outside the area reaches a preset threshold, the system will determine the cause as facility absence. The preset access range is determined along the actual traversable network, not using the straight-line distance between building center points. For example, if the straight-line distance between two spaces is 300 meters, but there is an inaccessible railway or enclosed area in between, the system will calculate the service range based on the actual traversable path.

[0064] When a target service facility exists within a preset access range, and the facility's service status data shows that the number of people waiting, the reservation occupancy status, or the service full load duration reaches a preset threshold, the system will determine the cause as insufficient service capacity. In one feasible implementation, if reservations are fully booked for at least 6 out of 10 consecutive working days, or if the number of people waiting during the target service period consistently exceeds the facility's simultaneous service capacity, the facility can be determined to be in a state of insufficient service capacity.

[0065] When the overlap between the service task's occurrence time and the target service facility's available opening time is less than a preset threshold, the system will determine the cause as a mismatch in opening times. For example, if residents' childcare pick-up and drop-off needs are concentrated between 7:00 and 8:30, but the existing service space is only open after 9:00, the service task's occurrence time and the available opening time do not meet the basic service duration overlap range.

[0066] When the passable path between the target service facility and the service task starting node is interrupted, or when the actual passable path exceeds a preset path threshold due to spatial restrictions such as walls, enclosed courtyards, or impassable roads, the system will determine the cause as path blockage. The system will also record the specific spatial location that caused the path interruption or path increase, for subsequent assessment of whether existing space has the value for passage repair.

[0067] When a passable path leads to the building where the target service facility is located, but the target group cannot access the facility entrance, the system will determine the cause as entrance inaccessible. For example, the facility entrance may only have steps and no available ramp, and the service recipients may include people using wheelchairs or strollers; or the entrance may be located in an internal area requiring specific access control, and the public cannot enter during service hours.

[0068] When a target service facility is available, but the main pedestrian flow path cannot connect to a usable entrance within the preset guidance range, the system will determine the cause as "service node difficult to identify." The preset guidance range can be determined by the number of turns required from the main pedestrian flow path to the entrance, the visible range of the entrance, and the coverage of guidance signs. For example, if residents need to leave the main road and pass through more than three unmarked turns to reach the facility entrance, that entrance can be determined as "difficult to identify."

[0069] A single valid mismatch edge can correspond to one primary cause and one or more secondary causes. For example, if a childcare facility exists within a community, but its entrance is only accessible through a gated courtyard and its opening hours are later than the main drop-off and pick-up times, then the inaccessibility of the entrance can be identified as the primary cause, and the mismatch in opening hours as a secondary cause. During subsequent matching of candidate existing spaces, the system prioritizes addressing the primary cause and checks whether the secondary causes are simultaneously improved.

[0070] After step S200, the system obtains valid mismatch edge data. Each valid mismatch edge includes at least the mismatch edge number, service task start range, target service type, target group, target service time period, edge abnormal status, abnormal behavior record, main cause of formation, and additional cause of formation.

[0071] Step S300: Based on the effective mismatch edges and existing space data, determine the candidate existing spaces, connect the candidate existing spaces as public service nodes to the actual pedestrian flow network, and reconnect the service task behavior chains corresponding to the effective mismatch edges.

[0072] like Figure 4 As shown, the system first determines the service task's starting range, target service type, target group, and target service time period based on valid mismatch edges. The service task's starting range can be determined by the set of residential nodes or public transportation nodes that generate abnormal behavior records. When multiple adjacent residential nodes generate the same valid mismatch edge, the system can merge them into a single service task starting range and retain the number of behavior chains corresponding to each residential node.

[0073] The system performs a path search along the actually accessible network from the starting area of ​​the service task. The path search only passes through roads, passageways, and entrances that are permitted for use by the target group. For adults, stairs, pedestrian bridges, and underpasses are permissible; for people with mobility assistance needs, the path search should exclude steps without alternative access, excessively narrow passageways, and discontinued vertical transportation facilities.

[0074] The preset route range is set based on the target service type and target group. For example, the preset route range for daily community convenience services can be set to 800 meters, for elderly daytime activity services to 500 meters, and for childcare pick-up and drop-off services to be set to a range of 300 meters on both sides of the main route from the residential node to the commuting node. All of the above ranges are calculated along the actual traversable network.

[0075] The system queries existing space nodes within a preset path range and identifies them as candidate existing spaces. Candidate existing spaces can be located near the service task's starting node or between the starting node and subsequent transportation nodes. For childcare pick-up and drop-off tasks, existing spaces located on the main path from residential nodes to rail transit stations typically reduce the need for backtracking after pick-up and drop-off; for elderly activity tasks, existing spaces located in the central area of ​​concentrated residential nodes with continuous walking paths can cover more starting nodes.

[0076] The system determines the space usage conditions, safety usage conditions, and supporting facility conditions based on the target service type. The space usage conditions are used to limit the continuous usable area, net height, internal passage range, and functional partitioning conditions; the safety usage conditions are used to limit safety exits, fire lanes, structural usage restrictions, and environmental safety status; and the supporting facility conditions are used to limit the access conditions for power supply, water supply and drainage, ventilation, sanitation facilities, and necessary equipment.

[0077] The system determines entrance access conditions based on the target group. Entrance access conditions include at least whether the entrance is connected to an accessible network, whether the entrance width is sufficient for the target group's passage, whether there is an elevation difference at the entrance that would prevent the target group from passing, and whether the entrance is subject to access control restrictions. For childcare services, stroller parking and two-way traffic conditions can also be checked; for elderly services, the presence of continuous handrails, rest areas, or safe pedestrian crossings near the entrance can also be checked.

[0078] The system determines the space opening conditions based on the target service period. These conditions determine whether the available time slots of the candidate existing spaces cover the period during which the effective mismatch edge occurs, and allow time for service preparation and termination. For example, if the target service period is from 7:00 to 8:30, and service preparation requires 20 minutes in advance, then the candidate existing spaces should be able to open before 6:40.

[0079] The system compares the usable area of ​​the candidate existing spaces with the space usage conditions. In one feasible implementation, the minimum continuous usable area for childcare pick-up and drop-off services can be set at 120 square meters, and there should be no unsecured vehicle access lanes within the main activity space; candidate spaces for community medical services can be required to have mutually independent waiting areas and service areas. Specific space conditions are set according to the technical requirements of the target service type.

[0080] The system compares the safety facility data of the candidate existing spaces with the safety usage conditions. If an existing space has no available safety exits, has structural usage restrictions that cannot be eliminated during the upgrade process, or if the fire escape route is occupied by other uses during the target service period, the candidate existing space will be eliminated, and the reason for not meeting the safety conditions will be recorded.

[0081] The system compares the facility access data of the candidate existing space with the supporting facility conditions. For example, if the target service function requires water supply and drainage, the system checks whether there are accessible pipelines inside the existing space or within the preset construction distance; if the target service function requires continuous ventilation, the system checks the location of existing ventilation equipment or where ventilation facilities can be installed. For short-term waiting nodes that do not require fixed water supply and drainage facilities, the corresponding supporting facility conditions can be reduced.

[0082] The system checks the available entrances to the candidate stock spaces along the actual passable network and compares the entrance check results with the entrance access conditions. The entrance check includes whether there is a continuous passable path from the service task start node to the entrance, whether the entrance is open during the target service period, whether the target group can pass through, and whether the main use area can be reached after entering the space.

[0083] The system compares the available time periods of the candidate storage space with the space opening conditions. When the candidate storage space is available throughout all target service periods, it is recorded as continuously available; when the candidate storage space is only available during some target service periods, it is recorded as time-limited; when the available time periods of the candidate storage space do not overlap with the target service periods for a preset duration, it is eliminated.

[0084] When a candidate space meets the conditions for space use, safe use, supporting facilities, access, and openness, the system retains it as a candidate space. When a candidate space only meets the necessary conditions for a specific group or time period, the system adds restrictions on its use. For example, a space that is available from 7:00 to 9:00 on weekdays and used for other activities during the day can be recorded as a space for morning use; a space that only has a regular pedestrian entrance can be recorded as unsuitable for people with mobility assistance needs.

[0085] The system incorporates candidate existing spaces as public service nodes into the actual pedestrian flow network. Each new public service node includes at least the candidate space number, candidate service type, eligible service groups, available opening hours, available entrances, allowed connection points to other spaces, and usage restrictions. The original identifiers of the candidate spaces' existing existing space nodes are retained to map the simulation results to specific spaces.

[0086] The system establishes candidate connection edges between public service nodes and the starting node of service tasks, and also establishes candidate connection edges between public service nodes and subsequent nodes of service tasks. Subsequent nodes of service tasks are determined based on the original service task behavior chain and can be rail transit stations, bus stations, residential nodes, or another public service node.

[0087] For valid mismatch edges caused by path blocking, candidate existing spaces can serve as access nodes to the actual pedestrian network. In this case, candidate existing spaces do not need to assume full public service functions. The system establishes access connections between the entrances of existing spaces and checks whether these connections enable the service task's starting node to reach the existing target service facility.

[0088] The system processes candidate connection edges according to path accessibility conditions, service time period conditions, group usage conditions, and service acceptance conditions. Path accessibility conditions are used to confirm that there are traversable paths from the starting node to the candidate public service node and from the candidate public service node to subsequent nodes; service time period conditions are used to confirm that the candidate public service node is in a serviceable state when the resident arrives; group usage conditions are used to confirm that the target group can enter and use the candidate space; and service acceptance conditions are used to confirm that the candidate space can complete the target service task.

[0089] The system reads the original service task behavior chain corresponding to the valid mismatch edge and re-searches for node connections starting from the original starting node. If the starting node can reach the candidate public service node through a traversable path during the target service period, and the candidate public service node can complete the target service task and continue to reach the original subsequent node after completing the service task, then the system marks the corresponding behavior chain as a recoverable behavior chain.

[0090] If a behavior chain can only be completed on certain dates, during certain time periods, or under certain target groups, the system marks it as a conditionally recoverable behavior chain and records the limiting conditions. For example, if a candidate space is only open on Monday to Friday mornings, then a behavior chain on rest days cannot be completed through that candidate space; if the candidate space entrance does not meet the access requirements of groups with mobility assistance needs, then the corresponding behavior chain for that group cannot be marked as recoverable.

[0091] If the starting node cannot reach the candidate public service node, the candidate public service node cannot complete the target service task, the open time period of the candidate space does not meet the requirements, or it cannot connect to the subsequent node after completing the service, the system will mark the corresponding behavior chain as an unrecovered behavior chain and record the failure location and failure reason.

[0092] For each candidate storage space, the system performs behavior chain reconnection processing. No attribute score comparison is performed between multiple candidate storage spaces; the system retains the specific behavior chain that can be recovered for each candidate space and its corresponding constraints. This allows the system to simultaneously identify a space suitable for continuous service, a space suitable for morning time-sharing service, and a space suitable as a transit node.

[0093] Step S400: Determine the value assessment result of the candidate stock space based on the completion status of the service task behavior chain before and after reconnection.

[0094] like Figure 5As shown, the system acquires behavioral chain status data before and after accessing the candidate existing space. Service task completion status indicates whether the behavioral chain has passed through the target service node and completed the preset stay or service record; cross-regional access status indicates whether the service task needs to pass through service facilities outside the area to be evaluated; path length status indicates whether the total path of the behavioral chain meets the preset path conditions corresponding to the target group; waiting status indicates whether waiting and leaving still occurs after accessing the candidate space; target group reachability status indicates whether the specified group can reach the service space through the actual entrance.

[0095] The system compares the status data of the behavior chain before and after the same service task behavior link is connected. If the service task can be completed after connection, there is no abnormal cross-region access, the path length meets the preset path conditions, there is no waiting time exceeding the preset time before leaving, and the target group can reach the candidate space, the behavior chain is determined to be a recoverable behavior chain.

[0096] A behavioral chain is defined as a conditionally recoverable behavioral chain when it only meets the above state conditions within a specified time period or under specified group conditions. For example, if the service task corresponding to an ordinary adult can be completed, but the group requiring mobility assistance still cannot pass through the entry point, then the behavioral chain corresponding to an ordinary adult can be a recoverable behavioral chain, while the behavioral chain corresponding to the group requiring mobility assistance is an unrecoverable behavioral chain, and the candidate space as a whole has group-restricted conditions.

[0097] When a behavior chain fails to complete the target service task, or still requires cross-regional access after access, still has abnormal detours exceeding the preset path threshold, still leaves after waiting, or the target group cannot reach the candidate space, the behavior chain is identified as an unrecovered behavior chain.

[0098] The system determines the repair status of effective mismatch edges based on the number of recoverable behavior chains and conditional recovery behavior chains. When the number of recoverable behavior chains reaches a preset recovery threshold, the effective mismatch edge is determined to be eliminated; when the total number of recoverable behavior chains and conditional recovery behavior chains reaches a preset recovery threshold, but the number of recoverable behavior chains does not reach the corresponding threshold, the effective mismatch edge is determined to be weakened; otherwise, the effective mismatch edge is determined to be unrepaired.

[0099] The preset recovery threshold can be set based on the number of stable behavior chains corresponding to the effective mismatch edges. In one executable implementation, when there are 100 stable service task behavior chains corresponding to the effective mismatch edges, 70 can be set as the preset recovery threshold. For service tasks targeting a small, specific group, a lower threshold can be used, requiring that most stable behavior chains in that group can be completed.

[0100] The system determines the value category based on the repair status of effective mismatch edges and the usability conditions in the existing space data. When effective mismatch edges have been eliminated and candidate existing spaces can continuously provide the target service during the target service period, they are identified as having direct public service undertaking value. This value category indicates that the candidate existing space can be directly used as a missing service facility.

[0101] When the effective mismatch has been eliminated or weakened, and the candidate stock space only provides the target service during the specified time period, it is determined to have time-sharing public service undertaking value. For example, if a community activity room undertakes fixed activities during the day, but can provide childcare pick-up and drop-off services on weekday mornings, then the space can have morning time-sharing public service undertaking value.

[0102] When candidate available space is used for waiting, pick-up / drop-off, service transfer, or temporary stay, and the effective mismatch edge has been weakened, it is identified as a service transfer node. This type of space may not complete all public service content, but it can enable previously interrupted service tasks to form a spatial connection that can continue to be performed.

[0103] When a candidate existing space enables residents to access existing service facilities through open internal passageways, courtyards, or elevated areas, it is identified as having accessibility value. The system records the starting node of the connection, existing service facilities, open entrances, and accessible times in the value assessment results.

[0104] When the effective mismatch edge has been eliminated or weakened for a specific group, it is identified as having service value for that specific group. For example, an existing space that enables people with mobility assistance needs to access community healthcare services by setting up accessible entrances can be identified as having service value for that specific group.

[0105] Candidate existing space is identified as a backup service node value when it can only meet the target service demand when existing service facilities are fully loaded or out of service. The backup service node value can be used to evaluate spaces that are used less frequently under normal conditions but can undertake service tasks during facility maintenance, peak service periods, or temporary closures.

[0106] If a valid mismatched edge is not repaired, it is determined to be unsuitable for hosting. The system records the specific reasons for the limitation, including unconnectable paths, unmet entry conditions, insufficient space, unmet security conditions, mismatched opening hours, or inability to connect to subsequent nodes after service completion. This record can be used to exclude unsuitable spaces or guide subsequent supplementary investigations.

[0107] The value assessment results should include at least the existing space number, spatial location, corresponding effective mismatch edge, main cause of formation, additional cause of formation, target service type, applicable group, applicable time period, number of recoverable behavior chains, number of conditionally recoverable behavior chains, number of unrecoverable behavior chains, value category, and restricted use conditions.

[0108] The system can write the value assessment results into the urban renewal management platform and generate spatial distribution maps, effective mismatch side maps, candidate space lists, and behavioral chain change maps. Managers can view the starting scope of service tasks, target groups, candidate access paths, and reasons for unrecoverable behavioral chains for each existing space based on its stock space number.

[0109] To more clearly explain this application, an implementation example is given below. In this example, the area to be evaluated is a residential community with 8 residential clusters, 1 rail transit station, and 2 bus stops. The system collects basic evaluation data for 30 consecutive days, including building and road data, public service facility data, data on 3 inefficient existing spaces, and anonymized resident activity data.

[0110] The three inefficient existing spaces are: Space A, located between residential cluster A and the rail transit station, is an empty ground floor space with an independent street-facing entrance, with a continuous usable area of ​​180 square meters, and is open from 6:30 am to 6 pm; Space B, located in the underground level in the middle of the community, has a usable area of ​​260 square meters, and the entrance is only a staircase; Space C is a community activity room with a usable area of ​​160 square meters, which has fixed activities from 9 am to 5 pm on weekdays and is open from 6:30 am to 8:30 am.

[0111] The system extracts weekday morning childcare pick-up and drop-off behavior chains from resident activity data. Service task behavior chains that stably connect residential nodes, childcare facility nodes, and rail transit nodes in the reference area are identified. The system converts this stable node connection relationship into a childcare pick-up and drop-off service task connection template. This template records the starting node type as a residential node, the target service type as childcare service, the subsequent node type as a rail transit node, the group type as a childcare group, and the occurrence time as a weekday morning.

[0112] The system traverses eight residential clusters in the area to be evaluated, identifying those with childcare groups and whose travel behavior chains occur on weekday mornings as starting nodes. The system extracts rail transit nodes from the actual behavior chains corresponding to each starting node, and identifies the rail transit station that appears most frequently as the subsequent node. Since there are no childcare facilities within the preset travel range of each starting node, the system establishes a virtual service node associated with childcare services for each starting node, connects each starting node to its corresponding virtual service node to form a desired behavior edge, and writes the rail transit station into the subsequent attribute of each desired behavior edge.

[0113] The system determines the average number of occurrences per unit group in the childcare service task connection template based on the effective statistical period and the number of childcare groups in the reference area. Then, based on the number of childcare groups in each residential cluster in the area to be evaluated and the effective observation period, it determines the expected connection strength of each expected behavior edge. The actual behavior chain in the area to be evaluated shows that some residents move from the community in the opposite direction to the rail transit station, visit childcare facilities outside the area, and then return to the rail transit station. This allows for a mapping between the expected behavior edges and the actual cross-regional childcare pick-up and drop-off behaviors occurring within the area to be evaluated.

[0114] like Figure 6 As shown, before the candidate space was accessed, the childcare pick-up and drop-off behavior chains corresponding to residential clusters A and B required cross-regional access and formed obvious back-and-forth paths. The system identified 64 cross-regional access records and 37 abnormal detour records over 20 consecutive working days. The number of these records all reached a preset threshold, thus confirming a valid mismatch between the residential nodes and the childcare service nodes, primarily due to facility deficiencies.

[0115] The system searches for available spaces along the actual accessible network from residential clusters to rail transit stations. Available spaces A, B, and C are all located within a preset path. The system establishes necessary conditions for childcare services, requiring a continuous usable area of ​​at least 120 square meters, an entrance accessible to childcare workers, morning opening hours, basic power and sanitation facilities, and safe exits that meet evacuation requirements.

[0116] Existing space A meets all necessary conditions for acceptance and is located near major commuting routes; therefore, the system retains it as a candidate existing space. Existing space B, while meeting the usable area requirements, has only a staircase at its entrance, which does not meet the access needs of groups with strollers; therefore, the system eliminates it and records its entrance as inaccessible. Existing space C can be used from 6:30 AM to 8:30 AM, meeting the needs of morning services, but cannot be continuously open during the day; therefore, the system retains it and adds the condition for morning time-slot use.

[0117] The system connects existing spaces A and C as candidate childcare service nodes to the actual pedestrian flow network. For existing space A, the system establishes candidate connection edges from residential clusters A and B to existing space A, and also establishes candidate connection edges from existing space A to the rail transit station. For existing space C, the system establishes connection edges of the same type, while restricting the service period to 6:30 am to 8:30 am.

[0118] like Figure 7 As shown, after the existing space A is connected, residential clusters A and B can reach the candidate childcare service node along their original commuting direction, complete the service task, and then continue to the rail transit station. The original cross-regional childcare facility is no longer a necessary node in the behavioral chain, and the abnormal turnaround path is eliminated.

[0119] The system reconnects 100 stable childcare pick-up and drop-off behavior chains. The existing space A enables 82 behavior chains to complete childcare pick-up and drop-off services. Among them, 78 chains meet all status conditions, 4 chains are marked as condition recovery behavior chains because the distance between the starting nodes is too far, and the remaining 18 chains are marked as unrecovered behavior chains because the path length still exceeds the preset path threshold.

[0120] The existing space C can provide services for 75 weekday morning behavior chains, but cannot handle service tasks after 8:30 AM. The system identifies 61 behavior chains as recoverable behavior chains and 14 behavior chains as conditionally recoverable behavior chains, and records the morning time-sharing usage conditions for the existing space C.

[0121] like Figure 8 As shown, after existing space A is connected, if the number of recoverable behavior chains corresponding to the effective mismatch edge reaches the preset recovery threshold, the system determines that the effective mismatch edge has been eliminated and identifies existing space A as having direct public service undertaking value. Existing space C can weaken the effective mismatch edge during a specified period, and the system identifies it as having time-sharing public service undertaking value. Existing space B is identified as unsuitable for undertaking because the entrance access conditions are not met.

[0122] The system ultimately outputs three assessment records for existing spaces. The assessment record for existing space A includes its direct public service acceptance value, applicable group (child caregivers), applicable time period (6:30 AM to 6:00 PM), 78 recoverable behavioral chains, 4 conditionally recoverable behavioral chains, and 18 unrecoverable behavioral chains. The assessment record for existing space C includes its morning time-slot public service acceptance value and corresponding opening restrictions. The assessment record for existing space B includes reasons for unsuitability for acceptance and inaccessibility at the entrance.

[0123] It should be noted that the specific values ​​mentioned above are only used to illustrate the execution process of the method in this application. In practical applications, the preset difference threshold, preset period threshold, preset path threshold, preset frequency threshold, and preset recovery quantity threshold can be adjusted according to city size, public service facility configuration standards, target group activity capacity, and data statistical cycle.

[0124] This application also provides a value assessment system for inefficient urban stock spaces; please refer to [reference needed]. Figure 9 The valuation system for inefficient urban stock spaces includes: The network construction module is used to acquire the basic assessment data of the area to be assessed, form a service task behavior chain, and construct the actual pedestrian flow network and the expected behavior network. The basic assessment data includes spatial data, existing spatial data, and resident activity data. The mismatch identification module is used to perform edge relationship mapping between the actual pedestrian flow network and the expected behavior network, and to determine the effective mismatch edges with service task gaps and the reasons for the formation of the effective mismatch edges; The spatial access module is used to determine candidate existing spaces based on effective mismatch edges and existing space data, connect the candidate existing spaces as public service nodes to the actual pedestrian flow network, and reconnect the service task behavior chain corresponding to the effective mismatch edges. The results generation module is used to determine the value assessment results of candidate stock space based on the completion status of the service task behavior chain before and after reconnection.

[0125] Compared with the prior art, the beneficial effects of the value assessment system for inefficient urban existing space provided in this application are the same as those of the value assessment method for inefficient urban existing space provided in the above embodiments, and other technical features of the value assessment system for inefficient urban existing space are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0126] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0127] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct or indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for assessing the value of inefficient urban stock space, characterized in that, The method includes the following steps: Acquire basic assessment data for the area to be assessed, form a service task behavior chain, and construct an actual pedestrian flow network and a desired behavior network. The basic assessment data includes spatial data, existing spatial data, and resident activity data. By mapping the actual pedestrian flow network and the expected behavior network along edges, we can determine the effective mismatched edges with service task gaps and the reasons for their formation. Candidate stock spaces are determined based on effective mismatch edges and stock space data. These candidate stock spaces are then connected to the actual pedestrian flow network as public service nodes. The service task behavior chains corresponding to the effective mismatch edges are then reconnected. The value assessment results of candidate stock space are determined based on the completion status of the service task behavior chain before and after reconnection.

2. The method for assessing the value of inefficient urban stock space as described in claim 1, characterized in that, The steps for obtaining basic assessment data for the area to be assessed, forming a service task behavior chain, and constructing the actual pedestrian flow network and the expected behavior network include: Obtain spatial data, existing space data, and resident activity data for the area to be evaluated; Perform coordinate unification and spatial node processing on the spatial data and the existing spatial data to establish a spatial node set containing the existing spatial nodes; The resident activity data is mapped to the spatial node set according to the occurrence time, adjacent activity events are connected and the service task type is labeled to form a service task behavior chain; Based on the adjacent spatial nodes, occurrence time and group type in the service task behavior chain, actual pedestrian flow edges are established to generate an actual pedestrian flow network. Extract the node connection relationships that recur within a preset number of statistical periods from the service task behavior chain of the preset reference area, establish a service task connection template, map the service task connection template to the spatial nodes of the area to be evaluated, establish expected behavior edges, and generate expected behavior network.

3. The method for assessing the value of inefficient urban stock space as described in claim 2, characterized in that, The steps of extracting node connections that recur within a preset number of statistical periods from the service task behavior chain of a preset reference area, establishing a service task connection template, mapping the service task connection template to the spatial nodes of the area to be evaluated, establishing expected behavior edges, and generating the expected behavior network include: Obtain the regional matching attributes of the candidate region, wherein the regional matching attributes include population composition, spatial morphology and travel time period; The region matching attributes of the candidate region are compared with the region matching attributes of the region to be evaluated item by item, and reference regions in which the differences of each attribute do not exceed the preset difference threshold are selected. The service task behavior chains of the reference area are grouped according to the service task type, and the number of statistical periods in which the connection relationship of each node occurs is counted. The node connection relationships that reach the preset period threshold in the number of statistical periods are converted into service task connection templates according to the order of the nodes. The service task connection templates include the starting node type, the target service type, the subsequent node type of the task, the group type, and the occurrence time period. Traverse the spatial nodes of the region to be evaluated, determine the starting node according to the starting node type, the group type and the occurrence time period, and determine the subsequent task nodes from the service task behavior chain of the region to be evaluated according to the subsequent task node type. When a service facility corresponding to the target service type exists within the preset access range corresponding to the starting node, the spatial node corresponding to the service facility is determined as the target service node; when it does not exist, a virtual service node associated with the starting node and the target service type is established, and the virtual service node is determined as the target service node. According to the service task connection template, the starting node is connected to the target service node to establish a desired behavior edge, the task follow-up node is used as the task follow-up attribute of the desired behavior edge, and the desired behavior edge is written into the desired behavior network according to the group type and the occurrence time period.

4. The method for assessing the value of inefficient urban stock space as described in claim 1, characterized in that, The steps of mapping edge relationships between the actual pedestrian flow network and the expected behavior network, and determining the effective mismatched edges with service task gaps and the reasons for their formation, include: According to the starting node, target service type, group type, and occurrence time, each expected behavior edge is mapped to the actual pedestrian flow edge in the actual pedestrian flow network that points from the same starting node to the same target service type; When the actual flow of people corresponding to the expected behavior edge is in a preset edge abnormal state, the expected behavior edge is identified as a suspected mismatch edge. The preset edge abnormal state includes missing connection, connection strength lower than a preset strength threshold, service task completed across regions, or actual path length exceeding a preset path threshold. Obtain abnormal behavior records corresponding to the suspected mismatched edge, and count the number of times the abnormal behavior records are repeated within a preset statistical period. The abnormal behavior records include service task interruption, abnormal detour, leaving after waiting, or repeated round trips. When the number of repetitions reaches a preset threshold, the suspected mismatched edge is determined as a valid mismatched edge; Obtain the cause determination data corresponding to the effective mismatch edge, compare the cause determination data with the preset cause determination conditions, and determine the cause of the formation of the effective mismatch edge.

5. The method for assessing the value of inefficient urban stock space as described in claim 4, characterized in that, The steps of obtaining the cause determination data corresponding to the effective mismatch edge, comparing the cause determination data with preset cause determination conditions, and determining the cause of the formation of the effective mismatch edge include: When there is no target service facility within the preset access range, and the number of behavior records pointing to similar service facilities outside the area reaches the preset threshold, the cause will be determined as facility missing. When there is a target service facility within the preset passage range, and the waiting state or service full load state of the target service facility reaches the preset state threshold, the cause will be determined as insufficient service capacity. When the overlap between the service task's occurrence time and the target service facility's available opening time is less than a preset time threshold, the cause will be determined as an opening time mismatch. When the passable path between the target service facility and the service task starting node is interrupted, or the length of the passable path exceeds the preset path threshold, the cause will be determined as path blockage. When a passable path can reach the building where the target service facility is located, but the target group cannot pass through the entrance of the target service facility, the cause will be determined as entrance inaccessible; When the target service facility is in a serviceable state, and the main pedestrian flow path cannot connect to the available entrance of the target service facility within the preset guidance range, the cause will be determined as the service node being difficult to identify.

6. The method for assessing the value of inefficient urban stock space as described in claim 1, characterized in that, Based on the effective mismatch edges and existing space data, candidate existing spaces are determined. These candidate existing spaces are then connected to the actual pedestrian flow network as public service nodes. The steps for reconnecting the service task behavior chains corresponding to the effective mismatch edges include: The starting scope, target service type, target group, and target service period are determined based on the effective mismatch edges; A path search is performed along the actual passable network from the starting range of the service task, and the existing spaces that are located within the preset path range and correspond to the existing space data are determined as candidate existing spaces. Based on the target service type, the target group, and the target service time period, necessary acceptance conditions are established. The spatial conditions of the candidate stock space are compared with the necessary acceptance conditions, and candidate stock spaces that meet the necessary acceptance conditions are retained. The candidate stock space is written into the actual flow network as a public service node, and candidate connection edges are established between the public service node and the service task start node and the service task subsequent node. The candidate connection edges are processed according to path access conditions, service time period conditions, group usage conditions, and service acceptance conditions to obtain the service task behavior chain after reconnection.

7. The method for assessing the value of inefficient urban stock space as described in claim 6, characterized in that, The steps of establishing necessary acceptance conditions based on the target service type, the target group, and the target service time period, comparing the spatial conditions of the candidate existing spaces with the necessary acceptance conditions, and retaining candidate existing spaces that meet the necessary acceptance conditions include: The space usage conditions, safety usage conditions, and supporting facility conditions are determined according to the target service type; the entrance access conditions are determined according to the target group; and the space opening conditions are determined according to the target service time period. The usable scope of the candidate existing space is compared with the space usage conditions, the safety facility data of the candidate existing space is compared with the safety usage conditions, and the facility access data of the candidate existing space is compared with the supporting facility conditions. Check the available entrances to the candidate storage space along the actual passable network, and compare the entrance check results with the entrance access conditions; The available time periods of the candidate existing spaces are compared with the space opening conditions; When the candidate existing space meets the conditions for space use, safe use, supporting facilities, access, and openness, the candidate existing space is reserved as a candidate existing space; when the candidate existing space only meets the necessary acceptance conditions during a specified period or only for a specified group, restrictive use conditions are added to the candidate existing space.

8. The method for assessing the value of inefficient urban stock space as described in claim 7, characterized in that, The steps to determine the value assessment results of candidate stock space based on the completion status of the service task behavior chain before and after reconnection include: Obtain behavioral chain status data before and after accessing the candidate existing space, wherein the behavioral chain status data includes service task completion status, cross-regional access status, path length status, waiting status, and target group reachability status; The behavior chain status data of the same service task behavior is compared item by item before and after. The service task behavior chain that can complete the service task and whose status meets the preset status conditions is determined as a recoverable behavior chain. The service task behavior chain that can only complete the service task under the specified time period or specified group conditions is determined as a conditional recovery behavior chain. The service task behavior chain that cannot complete the service task is determined as an unrecoverable behavior chain. When the number of recoverable behavior chains reaches a preset recovery quantity threshold, the effective mismatch edge is determined to be eliminated; when the total number of recoverable behavior chains and conditional recovery behavior chains reaches the preset recovery quantity threshold, the effective mismatch edge is determined to be weakened; otherwise, the effective mismatch edge is determined to be unrepaired. The value category is determined based on the repair status of the effective mismatched edge and the usability conditions in the stock space data, and the value assessment results of the candidate stock space are generated.

9. The method for assessing the value of inefficient urban stock space as described in claim 8, characterized in that, The steps for determining the value category and generating candidate stock space value assessment results based on the repair status of the effective mismatched edges and the usability conditions in the stock space data include: When the effective mismatch edge has been eliminated and the candidate stock space can continuously provide the target service during the target service period, the value category is determined as the direct public service undertaking value. When the effective mismatch edge has been eliminated or weakened, and the candidate stock space only provides the target service during the specified time period, the value category is determined as the time-sharing public service undertaking value; When the candidate stock space is used to complete waiting, pick-up and drop-off, service transfer or temporary stay, and the effective mismatch edge has been weakened, the value category is determined as the service transfer node value; When the candidate existing space enables residents to reach existing service facilities by providing access connections, the value category is determined as access restoration value; When the effective mismatch edge has been eliminated or weakened for the specified group, the value category is determined as the service value for the specific group; When the candidate stock space can meet the target service demand only when the existing service facilities are fully loaded or out of service, the value category is determined as the value of the backup service node. When the effective mismatch edge is not repaired, the value category will be determined as unsuitable for acceptance, and the stock space number, effective mismatch edge, cause of formation, value category, applicable group, applicable time period, recoverable behavior chain and restricted use conditions will be written into the value assessment result.

10. A value assessment system for inefficient urban stock spaces, characterized in that, The system includes: The network construction module is used to acquire the basic assessment data of the area to be assessed, form a service task behavior chain, and construct the actual pedestrian flow network and the expected behavior network. The basic assessment data includes spatial data, existing spatial data, and resident activity data. The mismatch identification module is used to perform edge relationship mapping between the actual pedestrian flow network and the expected behavior network, and to determine the effective mismatch edges with service task gaps and the reasons for the formation of the effective mismatch edges; The spatial access module is used to determine candidate existing spaces based on effective mismatch edges and existing space data, connect the candidate existing spaces as public service nodes to the actual pedestrian flow network, and reconnect the service task behavior chain corresponding to the effective mismatch edges. The results generation module is used to determine the value assessment results of candidate stock space based on the completion status of the service task behavior chain before and after reconnection.

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