A city greening state monitoring method based on digital mirror information

Abstract

The application discloses a kind of urban greening state monitoring methods based on digital mirror information, it is related to urban greening state monitoring technical field, including, real-time observation content of current monitoring period is backfilled to corresponding greening mirror unit, form current mirror state, and identify the deviation direction, deviation intensity and deviation position of current mirror state relative to counterfactual mirror state, generate mirror state residual error;Mirror state residual error is projected to greening topological mirror skeleton, when meeting deviation intensity continuous condition and not crossing state transmission boundary, mirror state residual error is connected according to the topological connection position between greening mirror unit, generates residual error chain segment, local residual error node, residual error confluence point and residual error fracture point, and constitutes topological residual error skeleton.The application forms the urban greening state with spatial receiving relationship and topological residual error structure.

Description

Technical Field

[0001] This invention relates to the field of urban greening status monitoring technology, and in particular to a method for monitoring urban greening status based on digital mirror information. Background Technology

[0002] With the development of refined urban governance, precise ecological space management, and digital twin technology, urban greening status monitoring technology has gradually shifted from manual inspections and periodic statistics to continuous monitoring based on spatial information, temporal observation, and computational models. Related technologies typically utilize remote sensing imagery, near-ground sensing, geospatial data, and historical maintenance records to identify green coverage, growth changes, degraded areas, and anomalies. Furthermore, leveraging the concept of digital twins, real-world greening objects are mapped into computable digital objects, enabling dynamic representation of urban green spaces, roadside green belts, area greening, and continuous vegetation spaces. As the spatial distribution of urban greening objects becomes increasingly fragmented, spatial representation and status tracking of greening objects based on digital mirror information has become an important development direction for urban greening status monitoring.

[0003] Existing technologies still have two main shortcomings: The primary problem is that the monitoring objects are mostly current observation patches, fixed regional units, or statistical grids, lacking mirror units that can accommodate changes in the state of greening objects before and after. After boundary changes, local occlusion, or morphological changes, the historical state and the current state of greening objects are easily disconnected, resulting in a lack of continuous basis for subsequent state judgments. The secondary problem is that existing methods mostly use fixed thresholds, historical averages, or single-point anomaly identification to judge the state of greening, failing to construct the expected control state for the current monitoring period in the digital mirror, and failing to project state deviations into the topological connection relationships between greening objects. Therefore, it is difficult to distinguish between local short-term fluctuations, abnormal states that continuously expand along the greening space, and residual convergence and break points that need to be carefully reviewed. The monitoring results tend to remain at the level of scattered point judgments. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a method for monitoring the status of urban greening based on digital mirror information to solve the problems that the status of greening objects is difficult to be continuously maintained and that deviations in status are difficult to be structurally judged by combining spatial topological relationships.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] This invention provides a method for monitoring the status of urban greening based on digital mirror information. The method includes: dividing greening objects within an urban greening area into greening mirror units, binding spatial identities and status inheritance relationships, and establishing a greening topological mirror skeleton; based on the mirror state of the greening mirror unit in the previous reliable period, performing baseline correction according to the connection direction and status transmission boundary in the greening topological mirror skeleton, combined with seasonal stage changes and historical normal evolution patterns, to deduce the counterfactual mirror state of the current monitoring period; and backfilling the real-time observation content of the current monitoring period into the corresponding greening mirror unit to form the current... The system identifies the mirror state and determines the direction, intensity, and location of deviation from the counterfactual mirror state, generating mirror state residuals. These residuals are then projected onto the greening topology mirror skeleton. When the deviation intensity continuity condition is met and the state transfer boundary is not crossed, the mirror state residuals are connected according to the topological connection positions between greening mirror units, generating residual chain segments, local residual nodes, residual confluence points, and residual breakpoints, thus forming the topology residual skeleton. Based on the topology residual skeleton, local fluctuation states, continuous abnormal states, and key verification states are identified, and the urban greening state is generated.

[0008] As a preferred embodiment of the urban greening status monitoring method based on digital mirror information described in this invention, the step of dividing the greening objects in the urban greening area into greening mirror units is as follows:

[0009] Collect spatial basic data and historical greening status records of urban greening areas, unify coordinates and trim the range of the spatial basic data, extract the boundaries of greening objects, and generate a base map of greening object boundaries;

[0010] Based on the boundary base map of greening objects, establish boundary continuity records, identify the continuation and interruption positions of state continuity, and generate a spatial boundary table.

[0011] Based on the boundary map of greening objects and the spatial boundary table, the greening objects in the urban greening area are spatially divided and written into greening mirror units to generate a greening mirror unit table.

[0012] As a preferred embodiment of the urban greening status monitoring method based on digital mirror information described in this invention, the establishment of the greening topological mirror skeleton is specifically as follows:

[0013] Spatial identities are generated based on the city greening area number and the greening mirror unit spatial sequence number, and spatial identities are bound to the greening mirror units based on the greening mirror unit table to generate a spatial identity binding table.

[0014] Establish a correspondence between the past and future based on the spatial identity binding table, and extract the mirror state of the previous trusted period by combining historical greening status records, and write it into the status succession relationship table.

[0015] Based on the state inheritance relationship table, the skeleton nodes, the topological connections between skeleton nodes, the state transmission boundaries, and the connection directions are written to generate a greening topology mirror skeleton.

[0016] As a preferred embodiment of the urban greening status monitoring method based on digital mirror information described in this invention, the step of deducing the counterfactual mirror status of the current monitoring period is as follows:

[0017] Using the greening topology mirror skeleton as the receiving object, the mirror state of the previous trusted period corresponding to the greening mirror unit is matched to the corresponding skeleton position in the greening topology mirror skeleton to form a state continuation base map.

[0018] The connection relationship between greening mirror units is traced along the connection direction in the state continuation base map, and the state transfer boundary is used as the cutoff position. The greening mirror units that are continuously connected between two adjacent cutoff positions are organized into state continuation segments.

[0019] By combining seasonal stage changes with historical normal evolution patterns, baseline correction is performed. The mirror state of the previous reliable cycle within the state extension segment is transferred to the greening mirror unit corresponding to the current monitoring cycle, and the state transmission order formed by the connection direction within the state extension segment is preserved to form the segment counterfactual state.

[0020] The counterfactual states of each segment are combined according to the spatial identity of the greening mirror unit, and the counterfactual states of the segments on both sides of the state transmission boundary are kept as independent control states to generate the counterfactual mirror state of the current monitoring period.

[0021] As a preferred embodiment of the urban greening status monitoring method based on digital mirror information according to the present invention, the formation of the current mirror state is specifically as follows:

[0022] Collect real-time observation data for the current monitoring period, and match the real-time observation data for the current monitoring period to the corresponding greening mirror unit according to spatial identity to form an observation backfill segment;

[0023] The greening performance in the observed backfill segments is transformed into the state expression of the corresponding greening mirror unit under the current monitoring period, and the state expression is bound to the corresponding spatial identity to form the current mirror state.

[0024] As a preferred embodiment of the urban greening status monitoring method based on digital mirror information described in this invention, the generation of mirror status residuals is specifically as follows:

[0025] The current mirror state and the counterfactual mirror state are compared in the same spatial identity to form a mirror comparison record.

[0026] Based on mirror isotopic control records, the deviation intensity was calculated, and the deviation direction and location were recorded;

[0027] The deviation direction, deviation intensity, and deviation position corresponding to the greening mirror unit are bound together, and the corresponding spatial identity and counterfactual mirror state are retained to generate mirror state residuals.

[0028] As a preferred embodiment of the urban greening status monitoring method based on digital mirror information described in this invention, the step of projecting the mirror status residual onto the greening topology mirror skeleton involves matching the mirror status residual to the corresponding greening mirror unit and the corresponding topology connection position in the greening topology mirror skeleton according to the spatial identity and deviation position in the mirror status residual, thereby forming a residual projection point.

[0029] As a preferred embodiment of the urban greening status monitoring method based on digital mirror information described in this invention, the generation of residual chain segments, local residual nodes, residual convergence points, and residual breakpoints is specifically as follows:

[0030] When the deviation intensity continuity condition is met and the state transfer boundary is not crossed, the residual projection points with the same deviation direction and located at adjacent topological connection positions are connected to form a continuous residual segment, and the residual projection points that are not connected with adjacent residual projection points are marked as local residual nodes.

[0031] Consecutive residual segments that are in the same connection direction and pass through multiple greening mirror units are merged into residual chain segments;

[0032] Mark the residual confluence points and residual break points based on the intersection and interruption relationships between residual chain segments.

[0033] As a preferred embodiment of the urban greening status monitoring method based on digital mirror information described in this invention, the topological residual skeleton is formed by combining residual chain segments, local residual nodes, residual confluence points, and residual break points according to their corresponding spatial identities and topological connection positions.

[0034] As a preferred embodiment of the urban greening status monitoring method based on digital mirror information according to the present invention, the generation of urban greening status is specifically as follows:

[0035] The greening mirror unit, spatial identity, topological connection position, deviation direction and deviation intensity corresponding to each type of residual structure in the topological residual skeleton are combined into a state discrimination object;

[0036] Locality discrimination is performed on local residual nodes in the state discrimination object to mark local fluctuation states, and continuity discrimination is performed on residual chain segments in the state discrimination object to mark continuous abnormal states;

[0037] Perform a verification judgment on the residual confluence points and residual break points in the state judgment object, and mark the key verification states;

[0038] The urban greening status is generated based on the spatial identity combination of local fluctuation status, continuous abnormal status, and key review status.

[0039] The beneficial effects of this invention are as follows: through the continuous processing of greening mirror units, counterfactual mirror states, mirror state residuals and topological residual skeletons, the state changes of urban greening objects are continuously inherited under a unified spatial identity, enabling the current mirror state and the counterfactual mirror state to achieve a corresponding comparison, and organizing the state deviation into residual chain segments, local residual nodes, residual convergence points and residual breakpoints, thereby forming an urban greening state with spatial inheritance relationship and topological residual structure. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart of a method for monitoring the status of urban greening based on digital mirror information.

[0042] Figure 2 A flowchart for generating the topological mirror skeleton and topological residual skeleton for greening.

[0043] Figure 3 The consistency rate of state labeling varies with the proportion of missing observations.

[0044] Figure 4 The distribution of false alarm rate for local fluctuations under high observation disturbance intensity. Detailed Implementation

[0045] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0046] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0047] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0048] Reference Figures 1-4 This is one embodiment of the present invention, which provides a method for monitoring the status of urban greening based on digital mirror information, including the following steps:

[0049] S1: Divide the green objects in the urban green area into green mirror units, bind spatial identity and status inheritance relationship, and establish a green topology mirror skeleton;

[0050] S1.1: Collect spatial basic data and historical greening status records of urban greening areas, unify coordinates and trim the range of spatial basic data, extract the boundaries of greening objects, and generate a greening object boundary base map;

[0051] Furthermore, spatial basic data and historical greening status records of urban greening areas are collected, the spatial basic data are converted to a unified coordinate reference corresponding to the boundary of urban greening areas, and the scope is cropped according to the boundary of urban greening areas to retain the spatial outline of greening objects participating in urban greening status monitoring within the urban greening area.

[0052] The spatial outline of the greening object is processed for boundary closure and boundary continuity verification. The spatial outline that can form an independent greening object range is extracted as the greening object boundary. The greening object boundary is matched with the spatial position in the historical greening status record to establish the correspondence between the greening object boundary and the historical greening status record, and the greening object boundary that is not matched with the historical greening status record is recorded.

[0053] By combining the boundaries, spatial locations, boundary verification results, historical greening status records, and unmatched records of greening objects, a base map of the greening object boundaries is generated.

[0054] S1.2: Based on the boundary base map of the greening object, establish boundary continuity records, identify the state continuity continuation position and the state continuity interruption position, and generate a spatial boundary table;

[0055] Furthermore, based on the boundary base map of the greening objects, the positions where the spatial continuity range is satisfied between the boundaries of adjacent greening objects are checked, and the corresponding positions are recorded as boundary continuity records; the boundary continuity records include the boundaries of the greening objects on both sides, the continuity position, the continuity length, and the corresponding historical greening status records;

[0056] The consistency of the transition is checked based on the historical greening status records on both sides of the boundary transition record. When the status changes on both sides continue in the same direction in adjacent monitoring cycles and the spatial relationship on both sides of the transition position remains continuous, the boundary transition record is marked as the status transition continuation position. When the status changes on both sides do not continue in the same direction and the spatial relationship on both sides of the transition position does not remain continuous, the boundary transition record is marked as the status transition interruption position.

[0057] By combining the boundary continuation records, the state continuation positions, and the state continuation interruption positions, a spatial boundary table is generated.

[0058] It should be noted that the spatial continuity range refers to the local area between adjacent green objects where the boundaries can be adjacent or continuous in space; the spatial continuity range does not require the two green objects to be completely merged into the same range, but is used to locate whether there is a continuity position between the two green objects that can be judged for state continuity.

[0059] "Continuity in the same direction" means that the historical greening status records on both sides of the boundary connection record have the same direction of status change or the same type of status change in adjacent monitoring periods.

[0060] S1.3: Based on the boundary base map of greening objects and the spatial boundary table, spatial boundary division is performed on the greening objects in the urban greening area, and the data is written into the greening mirror unit to generate the greening mirror unit table.

[0061] Furthermore, based on the greening object boundary base map and the spatial acceptance boundary table, the greening object boundary in the greening object boundary base map is spatially divided with the state acceptance interruption position as the dividing position; greening object boundaries within the same continuous boundary range that are not separated by the state acceptance interruption position are retained in the same acceptance range, while greening object boundaries separated by the state acceptance interruption position are assigned to different acceptance ranges respectively.

[0062] For each area of ​​acceptance, check the status acceptance continuation position. Write the greening objects that maintain boundary continuity through the status acceptance continuation position into the same greening mirror unit, and write the greening objects that do not form boundary continuity into different greening mirror units.

[0063] The greening mirror unit, the corresponding greening object boundary, the coverage area, the associated state continuity position, and the associated state interruption position are combined to generate a greening mirror unit table.

[0064] S1.4: Generate spatial identities according to the urban greening area number and the greening mirror unit spatial sequence number, and bind spatial identities to greening mirror units based on the greening mirror unit table to generate a spatial identity binding table;

[0065] Furthermore, based on the urban greening area number and the spatial sorting result of the greening mirror unit within the urban greening area, a spatial sequence number of the greening mirror unit is generated, and the urban greening area number and the spatial sequence number of the greening mirror unit are combined to form a spatial identity.

[0066] Bind the greening mirror unit to the corresponding spatial identity, and check whether there are duplicate bindings of the same spatial range or the same greening mirror unit lacking a spatial identity in the greening mirror unit table;

[0067] After verification, the greening mirror unit, spatial identity, corresponding greening object boundary and acceptance range are combined into a spatial identity binding table.

[0068] S1.5: Establish the correspondence between the past and future based on the spatial identity binding table, and extract the mirror state of the previous trusted period by combining the historical greening status records, and write it into the status inheritance relationship table.

[0069] Furthermore, based on the spatial identity binding table and historical greening status records, the spatial identity is used as an index to establish the correspondence between the same greening mirror unit in adjacent monitoring cycles; mirror statuses in historical greening status records that match the spatial identity and whose recording time is earlier than the current monitoring cycle are included in the trusted verification scope.

[0070] Trusted verification is performed on mirror states that are included in the trusted verification scope; mirror states that have continuous spatial identity, correspond to the spatial range of the greening mirror unit, have complete temporal sequence of status records, and do not cross the state transition interruption position pass the trusted verification.

[0071] Select the image state closest to the current monitoring period from the image states that have passed the trusted verification as the image state of the previous trusted period;

[0072] By combining spatial identity, previous and subsequent correspondence, the mirror state of the previous trusted cycle, and the trusted verification result, a state succession table is generated.

[0073] S1.6: Based on the state inheritance relationship table, write the skeleton nodes, the topological connections between skeleton nodes, the state transmission boundaries and the connection directions to generate the greening topology mirror skeleton;

[0074] Furthermore, based on the state acceptance relationship table, the greening mirror unit table, and the spatial acceptance boundary table, the greening mirror unit is written as a skeleton node, the spatial identity is bound to the corresponding skeleton node, and the state acceptance relationship is associated with the corresponding skeleton node.

[0075] Connect adjacent skeleton nodes corresponding to the state continuation position as topological connections, and write the state continuation interruption position as the state transmission boundary; determine the connection direction according to the spatial continuation order of the greening mirror unit in the greening object boundary base map;

[0076] By combining the skeleton nodes, topology connections, state propagation boundaries, connection directions, spatial identities, and the mirrored state from the previous trusted cycle, a greening topology mirror skeleton is generated.

[0077] S2: Based on the mirror state of the previous reliable cycle of the greening mirror unit, according to the connection direction and state transmission boundary in the greening topology mirror skeleton, and combined with the seasonal stage change and the normal evolution law of the same period in history, the baseline is corrected to infer the counterfactual mirror state of the current monitoring cycle.

[0078] S2.1: Using the greening topology mirror skeleton as the receiving object, match the mirror state of the previous trusted period corresponding to the greening mirror unit to the corresponding skeleton position in the greening topology mirror skeleton to form a state continuation base map.

[0079] Furthermore, using the skeleton nodes in the greening topology mirror skeleton as the skeleton positions, the greening mirror units corresponding to the skeleton nodes are searched according to spatial identities, and the mirror state of the previous trusted period corresponding to the same spatial identity is obtained from the state inheritance relationship table.

[0080] The obtained image state from the previous trusted period retains the original state content and does not change the connection direction and state transfer boundary already recorded in the green topology image skeleton.

[0081] The skeleton location, greening mirror unit, spatial identity, mirror state of the previous trusted period, connection direction and state transfer boundary are combined as the same continuation record; multiple continuation records are arranged in the spatial succession order in the greening topology mirror skeleton to form a state continuation base map.

[0082] S2.2: Trace the connection relationship between greening mirror units along the connection direction in the state continuation base map, and use the state transfer boundary as the cutoff position to organize the greening mirror units that are continuously connected between two adjacent cutoff positions into state continuation segments.

[0083] Furthermore, according to the connection direction recorded in the state continuation base map, the greening mirror units at adjacent skeleton positions are sequentially tracked; when there is a topological connection between adjacent greening mirror units and no state transfer boundary is marked, the adjacent greening mirror units are kept in the same continuous range; when a position marked with a state transfer boundary is tracked, the state transfer boundary is used as the cutoff position of the current continuous range.

[0084] Organize the continuous greening mirror units between two adjacent truncation positions into a state continuation segment; when a greening mirror unit is truncated by state transfer boundaries on both sides, or does not form a continuous connection with adjacent greening mirror units, organize the corresponding greening mirror unit into a separate state continuation segment.

[0085] Each state-sequential segment records the greening mirror unit within the segment, the segment's start and end skeleton positions, the connection direction within the segment, and the state transfer boundaries on both sides of the segment.

[0086] S2.3: The mirror state of the previous reliable period within the state extension segment is inherited to the greening mirror unit corresponding to the current monitoring period, and the state transmission order formed by the connection direction within the state extension segment is retained to form the segment counterfactual state;

[0087] Furthermore, the greening mirror units within each state continuation segment are arranged according to the connection direction within the segment, and the corresponding mirror state of the previous trusted cycle is obtained according to the spatial identity.

[0088] Identify the seasonal phase of the current monitoring period and retrieve the historical normal evolution patterns and seasonal phase changes corresponding to that seasonal phase.

[0089] Using the mirror state of the previous reliable cycle as a benchmark, and combining the seasonal stage changes with the normal evolution pattern of the same period in history, the baseline correction is calculated to obtain the normal evolution correction amount for the current monitoring cycle.

[0090] The normal evolution correction amount is algebraically superimposed with the mirror state of the previous reliable cycle, and then transferred to the greening mirror unit with the same spatial identity in the current monitoring cycle as the reference state content of the current monitoring cycle.

[0091] Within the state continuation segment, adjacent greening mirror units retain the sequential connection order according to the connection direction;

[0092] At the boundary of a state continuation segment, the mirror state of the previous reliable cycle outside the state propagation boundary does not enter the current state continuation segment.

[0093] The fragment's counterfactual state is formed by combining the greening mirror unit within the fragment, spatial identity, baseline-corrected control state content, and state transmission order.

[0094] It should be noted that baseline correction is used to eliminate the influence of natural phenological succession of plants and normal environmental cycles on the baseline drift of greening status; normal evolution correction is calculated by weighting the average change of the expression of status in the same historical period with the phenological coefficient corresponding to the current seasonal stage, so that the counterfactual mirror state can dynamically reflect the expected growth trajectory of greening objects under no abnormal interference, rather than statically extending historical data, thereby providing a dynamic and reasonable reference benchmark for subsequent deviation intensity calculation.

[0095] S2.4: Combine the counterfactual states of each segment according to the spatial identity of the greening mirror unit, and keep the counterfactual states of the segments on both sides of the state transmission boundary as independent control states to generate the counterfactual mirror state of the current monitoring period;

[0096] Furthermore, each segment counterfactual state is mapped to the greening mirror unit in the current monitoring period according to the spatial identity; when the same spatial identity corresponds to only one segment counterfactual state, the corresponding segment counterfactual state is used as the reference state of the corresponding greening mirror unit in the current monitoring period; when the same spatial identity is repeatedly mapped, the segment counterfactual state of the segment that is in the same state as the corresponding greening mirror unit is retained.

[0097] The counterfactual states of the segments located on both sides of the state transfer boundary are retained separately without cross-boundary merging; the spatial identity, the content of the reference state, the state extension segment to which each greening mirror unit belongs, the corresponding connection direction and the adjacent state transfer boundary are combined to generate the counterfactual mirror state of the current monitoring period.

[0098] S3: Backfill the real-time observation content of the current monitoring cycle into the corresponding greening mirror unit to form the current mirror state, and identify the deviation direction, deviation intensity and deviation position of the current mirror state relative to the counterfactual mirror state to generate mirror state residuals;

[0099] S3.1: Collect real-time observation content for the current monitoring period, match the real-time observation content for the current monitoring period to the corresponding greening mirror unit according to spatial identity, and form an observation backfill segment;

[0100] Furthermore, real-time observations for the current monitoring period are collected, converted to a unified coordinate reference for the urban greening area, and organized according to the collection time and spatial location information. Observations not falling within the spatial range of the greening mirror unit are not included in backfilling, while observations falling within the spatial range of the greening mirror unit are matched according to the corresponding relationship.

[0101] Using spatial identity as the backfill index, real-time observations of the current monitoring period that fall within the same greening mirror unit spatial range are classified under the same spatial identity; when the observation range spans multiple greening mirror units, they are classified into the corresponding spatial identities according to the overlap between the observation range and the spatial range of each greening mirror unit.

[0102] By combining spatial identity, corresponding greening mirror unit, observation range, collection time, and the observed content after inclusion, an observation backfill segment is formed.

[0103] S3.2: Transform the greening performance in the observed backfill segment into the state expression quantity of the corresponding greening mirror unit under the current monitoring period, and bind the state expression quantity with the corresponding spatial identity to form the current mirror state;

[0104] Furthermore, state features are extracted from the greening performance in the observation backfill segments to obtain the greening state features of the corresponding greening mirror units in the current monitoring period; uniform dimension processing is performed on the greening state features, and the processing results are used as state expression quantities, while the observation backfill segments and greening mirror units corresponding to the state expression quantities are retained.

[0105] Each state expression is bound to its corresponding spatial identity; when the same spatial identity corresponds to multiple state expressions, they are merged according to the spatial coverage relationship within the same greening mirror unit to obtain the state expression result of the corresponding greening mirror unit under the current monitoring period.

[0106] The spatial identity, greening mirror unit, and status expression result are combined to form the current mirror status.

[0107] S3.3: Compare the current mirror state with the counterfactual mirror state according to the same spatial identity to form a mirror comparison record;

[0108] Furthermore, the spatial identities in the current mirror state are checked one by one with the spatial identities in the counterfactual mirror state, and the greening mirror units corresponding to the same spatial identity are selected as the corresponding comparison objects; under the same spatial identity, the state expression results in the current mirror state and the comparison state content in the counterfactual mirror state are placed in the same comparison position, and no cross-comparison is performed between different spatial identities.

[0109] The spatial identity, greening mirror unit, state expression result in the current mirror state, comparison state content in the counterfactual mirror state, corresponding connection direction and corresponding state transmission boundary are combined to form a mirror same-position comparison record.

[0110] S3.4: Based on mirror isotopic control records, calculate the deviation intensity and record the deviation direction and location;

[0111] Furthermore, using mirror-image corresponding records as the calculation object, the first record is taken under the same spatial identity. Current mirror state of each greening mirror unit and counterfactual mirror state The deviation strength is calculated using the following expression:

[0112] ;

[0113] in, For the first Each greening mirror unit is in the current monitoring cycle Deviation intensity, For the first The current mirror state of each greening mirror unit For the first The counterfactual mirror state of a greening mirror unit;

[0114] It should be noted that the essence of the mirror state residual is the difference between the current mirror state of the same greening mirror unit and the counterfactual mirror state in the current monitoring period. Using the absolute value of the difference can remove the influence of the direction of increase or decrease on the magnitude judgment, so that the deviation intensity only expresses the degree of deviation; in the calculation, the first... Current mirror state of each greening mirror unit Counterfactual mirror state under the same spatial identity Subtract the two numbers and take the absolute value of the difference to obtain the first result. Each greening mirror unit is in the current monitoring cycle Deviation intensity This is used to characterize the magnitude by which the current state deviates from the counterfactual control state;

[0115] The deviation direction is obtained according to the direction of change of the current mirror state relative to the counterfactual mirror state, and the deviation position is obtained according to the spatial identity and topological connection position of the corresponding greening mirror unit.

[0116] S3.5: Bind the deviation direction, deviation intensity and deviation position corresponding to the greening mirror unit, retain the corresponding spatial identity and counterfactual mirror state, and generate mirror state residual;

[0117] Furthermore, the deviation direction, deviation intensity, and deviation position obtained in each greening mirror unit are bound to the corresponding spatial identity; only the deviation results corresponding to the same greening mirror unit are bound under the same spatial identity, and the deviation results between different spatial identities are not merged.

[0118] After binding is complete, the spatial identity, greening mirror unit, deviation direction, deviation intensity, deviation position and corresponding counterfactual mirror state are combined to generate mirror state residual.

[0119] S4: Project the mirror state residual onto the greening topology mirror skeleton. When the deviation intensity continuity condition is met and the state transfer boundary is not crossed, connect the mirror state residual according to the topology connection position between the greening mirror units to generate residual chain segments, local residual nodes, residual confluence points and residual break points, and form a topology residual skeleton.

[0120] S4.1: According to the spatial identity and deviation position in the mirror state residual, match the mirror state residual to the corresponding greening mirror unit and the corresponding topology connection position in the greening topology mirror skeleton to form the residual projection point;

[0121] Furthermore, the spatial identity in the mirror state residual is matched with the spatial identity bound to each skeleton node in the greening topology mirror skeleton to determine the greening mirror unit to which the mirror state residual belongs; then, based on the deviation position in the mirror state residual, the residual landing point is located at the topology connection position corresponding to the greening mirror unit.

[0122] The mirror state residual, the corresponding greening mirror unit, the corresponding topological connection position, the deviation direction, and the deviation intensity are combined into a residual projection point; mirror state residuals that do not match the corresponding spatial identity or the corresponding topological connection position do not enter the residual projection point.

[0123] S4.2: When the deviation intensity continuity condition is met and the state transfer boundary is not crossed, the residual projection points with the same deviation direction and located at adjacent topological connection positions are connected to form a continuous residual segment, and the residual projection points that are not connected with adjacent residual projection points are marked as local residual nodes.

[0124] Furthermore, after the residual projection points are formed, the adjacent topological connection positions are checked according to the connection direction in the greening topological mirror skeleton; the deviation intensity difference between adjacent residual projection points is calculated. When two residual projection points are located at adjacent topological connection positions and simultaneously satisfy the following conditions: the deviation direction is consistent, the deviation intensity difference is lower than the preset continuous threshold, and the connection path does not cross the state transmission boundary, a residual connection is established between the two residual projection points. Multiple residual projection points with continuous residual connections form a continuous residual segment.

[0125] Single-point marking is performed on residual projection points that have not formed residual connections; when there are no other residual projection points that meet the above connection conditions at adjacent topological connection positions, or when there is a state transfer boundary block between adjacent topological connection positions, the corresponding residual projection point is marked as a local residual node.

[0126] It should be noted that the deviation intensity continuity condition means that the difference in deviation intensity between adjacent residual projection points is lower than the preset continuity threshold (obtained based on the historical residual statistical distribution, and the value range is usually 5% to 20% of the normalized interval of the state expression). This is used to filter out intensity abrupt changes caused by sensor noise or local short-term disturbances, ensuring that the residual connection reflects the true abnormal spatial diffusion trend. Not crossing the state transmission boundary means that the residual connection path does not contain roads, water bodies or hard barriers corresponding to the state connection interruption position, so as to maintain the independence of state evolution in different greening management units or ecological microenvironments and avoid incorrect connections across units.

[0127] S4.3: Merge consecutive residual segments that are in the same connection direction and pass through multiple greening mirror units into a residual chain segment;

[0128] Furthermore, the continuity relationship between consecutive residual segments is checked along the connection direction in the greening topology mirror skeleton; when adjacent consecutive residual segments are located in the same connection direction and the greening mirror units passed through between adjacent consecutive residual segments are arranged consecutively at the topology connection position, the adjacent consecutive residual segments are merged.

[0129] The merged residual structure is denoted as a residual chain segment. The residual chain segment records the starting greening mirror unit, the ending greening mirror unit, the continuously passed greening mirror units, the corresponding topological connection position, the deviation direction, and the deviation intensity arranged along the connection direction. When they do not belong to the same connection direction, or when there is a topological connection position in the middle that has not formed a residual connection, the corresponding continuous residual segments are not merged into the same residual chain segment.

[0130] S4.4: Mark the residual confluence points and residual break points based on the intersection and interruption relationships between residual chain segments;

[0131] Furthermore, examine the positional relationship of each residual chain segment in the greening topology mirror skeleton; when two or more residual chain segments extend to the same greening mirror unit or the same topology connection position, and the corresponding deviation directions can be kept consistent at the intersection position, mark the intersection position as the residual convergence point; if the deviation directions on both sides of the intersection position are inconsistent, only the independent paths of each residual chain segment are retained and not marked as residual convergence points.

[0132] Check the termination position of each residual chain segment along the connection direction; when the residual chain segment stops extending before reaching the state transfer boundary, and the residual projection points before and after the termination position cannot continue to form a residual connection, mark the termination position as a residual break point; if the residual chain segment stops extending at the state transfer boundary, retain the truncation result according to the state transfer boundary and do not mark it as a residual break point.

[0133] S4.5: Combine residual chain segments, local residual nodes, residual merging points, and residual break points according to their corresponding spatial identities and topological connection positions to form a topological residual skeleton;

[0134] Furthermore, residual chain segments, local residual nodes, residual confluence points, and residual break points are respectively mapped to spatial identities and topological connection positions in the greening topology mirror skeleton; when there are multiple types of residual structures under the same spatial identity, the correspondence between each type of residual structure and the corresponding topological connection position is retained, and the residual structures are not merged or replaced.

[0135] After the correspondence is completed, the extension path of the residual chain segment, the single point position of the local residual node, the intersection position of the residual confluence point, and the interruption position of the residual break point are combined, and the deviation direction and deviation intensity corresponding to each residual structure are retained to form the topological residual skeleton.

[0136] S5: Based on the topological residual skeleton, identify local fluctuation states, continuous abnormal states, and key verification states, and generate urban greening status.

[0137] S5.1: Combine the greening mirror unit, spatial identity, topological connection position, deviation direction and deviation intensity corresponding to each type of residual structure in the topological residual skeleton into a state discrimination object;

[0138] Furthermore, residual chain segments, local residual nodes, residual confluence points, and residual break points are extracted from the topological residual skeleton. Based on the correspondence between each type of residual structure and the greening topological mirror skeleton, the greening mirror unit, spatial identity, and topological connection position corresponding to the residual structure are obtained.

[0139] For each type of residual structure, the corresponding deviation direction and deviation intensity are retained; when the same spatial identity corresponds to multiple types of residual structures, the structure type and corresponding position of each type of residual structure are retained separately. The residual structure type, greening mirror unit, spatial identity, topological connection position, deviation direction, and deviation intensity are combined into a state discrimination object.

[0140] S5.2: Perform locality discrimination on local residual nodes in the state discrimination object, mark local fluctuation states, and perform continuity discrimination on residual chain segments in the state discrimination object, mark continuous abnormal states;

[0141] Furthermore, locality discrimination is performed on the local residual nodes in the state discrimination object; when a local residual node is not included in the residual chain segment, does not correspond to the residual confluence point, does not correspond to the residual break point, and only corresponds to a single greening mirror unit or a single topological connection position, the greening mirror unit corresponding to the local residual node is marked as a local fluctuation state, and the corresponding spatial identity, deviation direction and deviation intensity are retained.

[0142] The continuity of residual chain segments in the state discrimination object is judged; when the residual chain segment passes through multiple greening mirror units continuously along the connection direction and the deviation direction within the residual chain segment remains consistent, the greening mirror unit corresponding to the residual chain segment is marked as a continuous abnormal state, and the starting greening mirror unit, ending greening mirror unit, the topological connection position passed through, and the deviation intensity arranged along the connection direction corresponding to the residual chain segment are retained.

[0143] S5.3: Perform a verification judgment on the residual confluence points and residual break points in the state judgment object, and mark the key verification states;

[0144] Furthermore, a verification judgment is performed on the residual convergence points in the state judgment object; when two or more residual chain segments intersect in the same greening mirror unit or the same topological connection position, and the deviation direction corresponding to the intersection position is consistent with the residual chain segment entering the intersection position, the greening mirror unit corresponding to the residual convergence point is marked as a key verification state, and the corresponding spatial identity, topological connection position and the number of residual chain segments entering the intersection position are retained;

[0145] The residual breakpoints in the state discrimination object are verified. When the residual chain segment stops extending before reaching the state transmission boundary and the deviation intensity before and after the stop extension position is discontinuous, the greening mirror unit corresponding to the residual breakpoint is marked as a key verification state, and the corresponding spatial identity, topological connection position and deviation intensity change are retained.

[0146] S5.4: Generate the urban greening status based on the spatial identity combination of local fluctuation status, continuous abnormal status, and key review status;

[0147] Furthermore, local fluctuation status, continuous abnormal status, and key review status are categorized according to spatial identity; when the same spatial identity corresponds to only one status, the corresponding status is directly taken as the urban greening status under that spatial identity; when the same spatial identity corresponds to multiple statuses at the same time, the priority status is retained in the order of key review status, continuous abnormal status, and local fluctuation status.

[0148] After completing the state aggregation, the spatial identity, corresponding greening mirror unit, preserved state, corresponding residual structure type, topological connection location, deviation direction and deviation intensity are combined to generate the urban greening state.

[0149] To examine the impact of missing observation data on the stability of urban greening status output, a validation sample dataset was constructed, including greening mirror units, spatial identities, status succession relationships, and urban greening status markers. The dataset was then subjected to an observational perturbation intensity of 6.0 × 10⁻⁶. -2 The normal evolution range is 5.0 × 10⁻⁶. -2 Under the given conditions, the methods of this invention, the fixed grid comparison method, the static benchmark comparison method, and the independent residual point comparison method were repeatedly run, and the consistency rate of state labels under different observation missing ratios was statistically analyzed. The results are as follows: Figure 3 As shown. Figure 3 The points in the diagram represent the mean of the consistency rate of the state markers obtained from repeated runs, and the error bars represent the discrete range of the repeated run results. Figure 3It is evident that as the proportion of missing observations increases, the consistency rate of state labeling in each method is affected to varying degrees. The method of this invention maintains a high consistency rate of state labeling under each proportion of missing observations, indicating that by maintaining spatial identity through greening mirror units and comparing the counterfactual mirror state with the current mirror state, the consistency of urban greening state output can be maintained even when the observation content is incomplete.

[0150] To examine the impact of local fluctuations on urban greening status markers under high observed disturbance intensity conditions, an observed disturbance intensity of 6.0 × 10⁻⁶ was used. -2 The normal evolution range is 5.0 × 10⁻⁶. -2 Under the given conditions, the false alarm rates of local fluctuations for the four processing methods were repeatedly tested and statistically analyzed. The results are as follows: Figure 4 As shown. Figure 4 The middle box represents the interquartile range, the horizontal line inside the box represents the median, the diamond represents the mean, and the hollow scatter points represent the results of a single run. Figure 4 It is evident that the false alarm rate distribution of local fluctuations corresponding to the method of the present invention is lower than that of the control methods, and the range of the box is narrower. This indicates that after the method of the present invention projects the mirror state residuals onto the topological residual skeleton, it can distinguish between local fluctuations formed by short-term observation disturbances and continuous abnormal states, reduce the probability of local fluctuations being incorrectly marked as abnormal states, and make the generated urban greening state have better stability and verifiability.

[0151] It should be noted that the fixed grid comparison method refers to dividing urban green areas into grids of fixed size, using the grid as the basic object for state recording and state comparison, and no longer establishing green mirror units based on the spatial identity and state inheritance relationship between green objects; the static benchmark comparison method refers to using a fixed historical benchmark state or initial state as the comparison object for the current observation content, and not inferring the counterfactual mirror state based on the mirror state of the previous reliable period and the green topological mirror skeleton; the independent residual point comparison method refers to, after obtaining the difference between the current state and the reference state, only independently judging the residual points at a single spatial location, without projecting the mirror state residuals to the topological residual skeleton, and without further organizing them into residual chain segments, local residual nodes, residual confluence points, and residual breakpoints. The above three comparison methods are respectively used to verify the spatial identity inheritance role of the green mirror unit, the co-position reference role of the counterfactual mirror state, and the residual structure organization role of the topological residual skeleton in this invention.

[0152] In summary, this invention, through the continuous processing of greening mirror units, counterfactual mirror states, mirror state residuals, and topological residual skeletons, enables the continuous inheritance of state changes of urban greening objects under a unified spatial identity, allowing the current mirror state to achieve a co-position comparison with the counterfactual mirror state, and organizing state deviations into residual chain segments, local residual nodes, residual convergence points, and residual breakpoints, thereby forming an urban greening state with spatial inheritance relationships and topological residual structures.

[0153] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for monitoring the status of urban greening based on digital mirror information, characterized in that, include: The greening objects in the urban greening area are divided into greening mirror units, and spatial identity and status inheritance relationship are bound to establish a greening topology mirror skeleton; Based on the mirror state of the previous reliable cycle of the greening mirror unit, the baseline is corrected according to the connection direction and state transmission boundary in the greening topology mirror skeleton, combined with the seasonal stage change and the normal evolution law of the same period in history, and the counterfactual mirror state of the current monitoring cycle is deduced. The real-time observation data of the current monitoring period is backfilled into the corresponding greening mirror unit to form the current mirror state, and the deviation direction, deviation intensity and deviation position of the current mirror state relative to the counterfactual mirror state are identified to generate mirror state residuals; The mirror state residual is projected onto the greening topology mirror skeleton. When the deviation intensity continuity condition is met and the state transmission boundary is not crossed, the mirror state residual is connected according to the topological connection position between the greening mirror units to generate residual chain segments, local residual nodes, residual confluence points and residual break points, and to form the topology residual skeleton. Based on the topological residual skeleton, local fluctuation states, continuous abnormal states, and key verification states are identified, and urban greening status is generated.

2. The urban greening status monitoring method based on digital mirror information as described in claim 1, characterized in that, The process of dividing green objects within urban green areas into green mirror units is as follows: Collect spatial basic data and historical greening status records of urban greening areas, unify coordinates and trim the range of the spatial basic data, extract the boundaries of greening objects, and generate a base map of greening object boundaries; Based on the boundary base map of greening objects, establish boundary continuity records, identify the continuation and interruption positions of state continuity, and generate a spatial boundary table. Based on the boundary map of greening objects and the spatial boundary table, the greening objects in the urban greening area are spatially divided and written into greening mirror units to generate a greening mirror unit table.

3. The urban greening status monitoring method based on digital mirror information as described in claim 2, characterized in that, The establishment of the greening topology mirror skeleton is as follows: Spatial identities are generated based on the city greening area number and the greening mirror unit spatial sequence number, and spatial identities are bound to the greening mirror units based on the greening mirror unit table to generate a spatial identity binding table. Establish a correspondence between the past and future based on the spatial identity binding table, and extract the mirror state of the previous trusted period by combining historical greening status records, and write it into the status succession relationship table. Based on the state inheritance relationship table, the skeleton nodes, the topological connections between skeleton nodes, the state transmission boundaries, and the connection directions are written to generate a greening topology mirror skeleton.

4. The urban greening status monitoring method based on digital mirror information as described in claim 1, characterized in that, The deduced counterfactual mirror state for the current monitoring period is as follows: Using the greening topology mirror skeleton as the receiving object, the mirror state of the previous trusted period corresponding to the greening mirror unit is matched to the corresponding skeleton position in the greening topology mirror skeleton to form a state continuation base map. The connection relationship between greening mirror units is traced along the connection direction in the state continuation base map, and the state transfer boundary is used as the cutoff position. The greening mirror units that are continuously connected between two adjacent cutoff positions are organized into state continuation segments. By combining seasonal stage changes with historical normal evolution patterns, baseline correction is performed. The mirror state of the previous reliable cycle within the state extension segment is transferred to the greening mirror unit corresponding to the current monitoring cycle, and the state transmission order formed by the connection direction within the state extension segment is preserved to form the segment counterfactual state. The counterfactual states of each segment are combined according to the spatial identity of the greening mirror unit, and the counterfactual states of the segments on both sides of the state transmission boundary are kept as independent control states to generate the counterfactual mirror state of the current monitoring period.

5. The urban greening status monitoring method based on digital mirror information as described in claim 1, characterized in that, The formation of the current mirror state is as follows: Collect real-time observation data for the current monitoring period, and match the real-time observation data for the current monitoring period to the corresponding greening mirror unit according to spatial identity to form an observation backfill segment; The greening performance in the observed backfill segments is transformed into the state expression of the corresponding greening mirror unit under the current monitoring period, and the state expression is bound to the corresponding spatial identity to form the current mirror state.

6. The urban greening status monitoring method based on digital mirror information as described in claim 5, characterized in that, The generation of the mirror state residual is as follows: The current mirror state and the counterfactual mirror state are compared in the same spatial identity to form a mirror comparison record. Based on mirror isotopic control records, the deviation intensity was calculated, and the deviation direction and location were recorded; The deviation direction, deviation intensity, and deviation position corresponding to the greening mirror unit are bound together, and the corresponding spatial identity and counterfactual mirror state are retained to generate mirror state residuals.

7. The urban greening status monitoring method based on digital mirror information as described in claim 1, characterized in that, The process of projecting the mirror state residual onto the greening topology mirror skeleton involves matching the mirror state residual to the corresponding greening mirror unit and the corresponding topology connection position in the greening topology mirror skeleton according to the spatial identity and deviation position in the mirror state residual, thus forming a residual projection point.

8. The urban greening status monitoring method based on digital mirror information as described in claim 7, characterized in that, The generation of residual chain segments, local residual nodes, residual confluence points, and residual breakpoints are specifically as follows: When the deviation intensity continuity condition is met and the state transfer boundary is not crossed, the residual projection points with the same deviation direction and located at adjacent topological connection positions are connected to form a continuous residual segment, and the residual projection points that are not connected with adjacent residual projection points are marked as local residual nodes. Consecutive residual segments that are in the same connection direction and pass through multiple greening mirror units are merged into residual chain segments; Mark the residual confluence points and residual break points based on the intersection and interruption relationships between residual chain segments.

9. The urban greening status monitoring method based on digital mirror information as described in claim 1 or 8, characterized in that, The topological residual skeleton is formed by combining residual chain segments, local residual nodes, residual merging points, and residual break points according to their corresponding spatial identities and topological connection positions.

10. The urban greening status monitoring method based on digital mirror information as described in claim 1, characterized in that, The generation of urban greening status is as follows: The greening mirror unit, spatial identity, topological connection position, deviation direction and deviation intensity corresponding to each type of residual structure in the topological residual skeleton are combined into a state discrimination object; Locality discrimination is performed on local residual nodes in the state discrimination object to mark local fluctuation states, and continuity discrimination is performed on residual chain segments in the state discrimination object to mark continuous abnormal states; Perform a verification judgment on the residual confluence points and residual break points in the state judgment object, and mark the key verification states; The urban greening status is generated based on the spatial identity combination of local fluctuation status, continuous abnormal status, and key review status.

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