70 results about "City area" patented technology

The invention discloses an autonomous decision-making system of a multi-level intelligent agent in an urban area and an operation method thereof. Each end-side decision-making unit broadcasts an equipment state variable to a side-side decision-making unit; the side decision-making unit determines a global reference state and generates a control instruction of each end decision-making unit; after the equipment executes the control instruction, each end-side decision-making unit updates an equipment state variable according to the real-time operation data of the equipment, and when an abnormal event is judged to occur, a side decision-making unit predicts a decision-making variable of each piece of equipment based on a collaborative optimization model of an equipment target and an urban area target; the cloud regulation and control platform predicts a global consistency variable based on the collaborative optimization model of all the side decision units; predicting a regulation and control instruction of each side decision-making unit according to a global dynamic optimization target under a system operation constraint; and the side decision-making unit decomposes the regulation and control instruction into the control instruction of each end decision-making unit, so that the problems that the global cooperative capability of the urban regional integrated energy system is weak and cooperative scheduling is not timely under extreme events are solved.

The invention discloses an old city boundary intelligent extraction and texture calculation system based on vector topology analysis and semantic segmentation. According to the method, the topological semantic association module provides a multi-dimensional association basis for boundary extraction by integrating spatial structure information of vector topology and functional attribute tags of semantic segmentation. In the coarse extraction stage, the objective space law of the topological features and the subjective function orientation of the semantic tags are mutually verified, so that the misjudgment of'similar forms but inconsistent functions' possibly caused by single dependence on the topological structure or the deviation of'tag coverage but space breakage 'possibly caused by only dependence on the semantic tags is avoided; in the fine correction stage, the module further dynamically calibrates the boundary range through historical-current situation space-time correlation and multi-source data conflict detection, so that the continuity of historical stable elements is reserved, the updating requirement of current situation semantic tags is included, the final boundary better fits the essential characteristics of'active inheritance 'of the old city, and the accuracy of the final boundary is improved. And human experience interference and errors are obviously reduced.

The invention discloses an urban scale rainfall absorption and vegetation configuration collaborative optimization evaluation method, which belongs to the field of urban rainfall flood management optimization, and comprises the steps of performing integration and rainfall event identification on basic data of an urban region; physical mechanism inference is carried out by constructing multiple physical gating such as energy consistency, wet surface dissipation and geometric radiation sensitivity, and underlying surface hydrological response characteristics are obtained; constructing and solving a robust optimization model in combination with the underlying surface hydrological response characteristics and a preset planning target, and determining an optimal vegetation configuration scheme; and carrying out back substitution on the optimal vegetation configuration scheme to carry out closed-loop check and effect evaluation. According to the method, the hydrological response characteristics of the urban underlying surface can be accurately quantified, the vegetation configuration scheme with the definite achievement probability and the controllable risk is formulated under the uncertain condition, and the scientificity and the reliability of urban water resource toughness planning are improved.

The invention belongs to the crossing field of water conservancy and computer vision, and provides an urban flood depth real-time monitoring method based on intelligent three-dimensional vision. According to the method, firstly, an unmanned aerial vehicle is adopted for aerial photography to collect multi-view images of scenery in an urban area, and refined three-dimensional reconstruction is carried out on the multi-view images; then, shooting a two-dimensional image of the scenery by using a camera, matching the two-dimensional image with the image shot by the unmanned aerial vehicle, and screening out a plurality of most similar images; dense feature comparison is carried out on the two-dimensional image and the three-dimensional information, and the pose of the camera is calculated according to the corresponding relation of feature points; and finally, through SAM2 segmentation and autoregressive mechanism optimization, extracting a water surface area with a stable time sequence, and in combination with a known camera pose, back-projecting a water surface edge to a three-dimensional space, obtaining the water depth of accumulated water around the scene, and realizing real-time monitoring of urban flood water depth data. The method provides important technical support for fine real-time early warning of urban flood, and has practical engineering application value.

The invention discloses an urban water supply system and method, and belongs to the technical field of urban water supply. The system comprises a first segmentation module used for dividing an urban area into a plurality of first blocks, each first block is correspondingly provided with a water storage unit, the water storage units are connected with a main water pipeline, the main water pipeline is connected with a plurality of water supply main pipes, the water supply main pipes are connected with a plurality of water supply branch pipes, and the water supply branch pipes are connected with a user side; the control unit is used for receiving the water consumption data and forming a data set; the storage unit is used for forming the water consumption of all the user sides of each water supply main pipe in different time periods; the first valve is arranged at the joint of the main water pipeline and the water supply main pipe; when water is supplied, the water consumption in the corresponding time period is extracted, and the opening degree of the first valve is controlled, so that water entering the water supply main pipe reaches the extracted water consumption in the time period, and therefore, the water supply capacity can be improved in the water peak period, and the excessive water supply capacity can be prevented in the water valley period.

The invention discloses an urban garbage treatment station site selection method and device, electronic equipment and a storage medium, and relates to the technical field of site selection. The method comprises the following steps: dividing a target city area into a plurality of grid areas; acquiring signaling data of each grid region, and estimating population distribution characteristic data; acquiring historical garbage clearance data and commercial interest point data, and processing to obtain garbage prediction data; obtaining road data, establishing a topological road network model, and performing traffic characteristic evaluation on the topological road network model to obtain traffic characteristic data; acquiring ecological data, and acquiring service coverage data of each garbage disposal station; based on the obtained data, obtaining a multi-dimensional evaluation result, and determining a plurality of preliminary site selection of the garbage disposal station; and determining a preset number of addresses from the plurality of preliminary addresses as a final address of the garbage disposal station of the target city. By implementing the technical scheme provided by the invention, the accuracy of site selection of the urban garbage treatment station can be improved.

The invention discloses an urban domain large-scale computational fluid mechanics analysis simplified modeling method and device, and belongs to the technical field of civil engineering computational fluid mechanics, and the method comprises the steps: obtaining geographic information system data of a target urban domain; dividing the target city area into a building area and a non-building area; for the building area, classifying the building area into a building dense area and a non-building dense area according to the building coverage rate; for the building dense area, modeling all buildings in the building dense area into a three-dimensional geometric model as a three-dimensional geometric model of the corresponding area; for a non-building dense area, constructing a three-dimensional geometric model of each building in the non-building dense area, and taking a combination of the three-dimensional geometric models of the buildings as a three-dimensional geometric model of a corresponding area; and carrying out assembling and attribute endowing on each three-dimensional geometric model to finish modeling of the computational fluid mechanics analysis model. According to the method, computational fluid mechanics efficient modeling can be carried out on a large-scale urban domain.

The invention discloses a city CTC-based running plan morning and evening point real-time adjustment method and device. The device comprises a running chart terminal arranged in a city railway dispatching command system and a city running chart background service. The running chart terminal is used for displaying and operating the running plan and sending running plan operation update to the city running chart background service in real time; and when receiving the train report point reported by the station, the city area working diagram background service performs morning and evening point adjustment processing on the operation plan after the train report point and / or the turn-back plan associated with the operation plan according to the morning and evening point relationship between the train report point and the corresponding operation plan, and updates the operation plan and / or the associated turn-back plan. According to the invention, on the basis of a dispatching command system framework, interconnection and public transportation operation requirements of urban railways are met, and the efficiency of dispatching operation plan morning and evening is improved.

The invention discloses a road safety monitoring method based on the Internet of Things, and relates to the technical field of road safety. A corresponding urban area traffic data center is arranged according to the urban area, and is in wireless communication connection with a traffic navigation system; constructing an urban regional vital communication line map model based on a traffic navigation system, and obtaining road information data; setting a camera data network, obtaining road video image data, sending the road video image data to an urban area traffic data center for storage, and generating an intersection road data set; a data processing model is constructed in an urban regional traffic data center, a road vehicle passing number set corresponding to the intersection road data set is obtained, and a congestion data value range is obtained; a congestion state level is obtained, and an urban regional traffic network system is constructed; and finally, acquiring scheduling data based on an urban area traffic network system, and managing and scheduling vital communication lines corresponding to the urban area according to the scheduling data. According to the invention, real-time monitoring and scheduling of urban roads are realized.

The invention relates to the technical field of spatial and temporal distribution reconstruction and early warning of VOCs, in particular to an urban area VOCs spatial and temporal distribution reconstruction and early warning method, which comprises the following steps: S1, collecting and preprocessing an urban area VOCs original data set; s2, according to the pollution type of the VOCs in the urban area; s3, constructing a regional VOCs reconstruction and prediction model based on the hybrid CNN-LSTM; s4, setting initial parameters of the model, and training the constructed model to obtain optimal model parameters; s5, performing precision verification on 10 DeepAir models generated after training by using the overall verification set in the step 2; s6, deploying the trained regional VOCs reconstruction and prediction model into the urban region; s7, using the regional VOCs reconstruction and prediction model to generate a complete VOCs concentration distribution reconstruction map in the region; according to the method, accurate reconstruction and prediction of the regional VOCs distribution diagram are realized, and urban regional VOCs spatial and temporal distribution monitoring and early warning required by current practical application can be met.

The invention discloses a path planning method based on a city engine and an unreal engine. The method comprises the following steps: completing basic data preparation, rule definition, model generation and visual presentation and analysis, and establishing a city model; secondly, constructing a vehicle motion model in an unreal engine, and simulating weather; the three-dimensional static model and a dynamic model in an unreal engine are fused to generate an urban environment; carrying out geographical gridding on the urban area; introducing a trafficability map and physical restrictions of the vehicle, and setting the trafficability map of the vehicle; an improved A * algorithm based on geographic gridding is introduced, path planning is conducted, the improved A * algorithm is used, and path optimization is achieved through a heuristic function and a penalty function; and outputting the generated path plan.

The application discloses a kind of city area photovoltaic cluster dynamic grid division methods based on space-time coupling tensor, comprising: synchronously collecting the active power time series and geographic coordinates of all photovoltaic nodes in city area;Build the heterogeneous space adjacency matrix considering electrical topology constraint, calculate the static space correlation degree between any two photovoltaic nodes;Build the time-shift cross-correlation matrix that captures the moving characteristics of weather system, quantify the dynamic time correlation degree between nodes;Perform space-time feature tensor fusion, obtain global space-time affinity matrix;Photovoltaic nodes are divided using improved spectral clustering algorithm, and the optimal grid number is adaptively determined by contour coefficient, finally generate photovoltaic cluster grid division scheme at this moment;According to grid drift threshold, trigger grid reconstruction.The application can effectively consider physical topology constraint and meteorological time delay characteristics, realize the accurate aggregation of photovoltaic cluster, significantly improve the accommodation capacity and regulation flexibility of distribution network to distributed energy.

The invention relates to the technical field of data processing, and discloses a ditch ecological restoration benefit evaluation method and system. The method comprises the following steps: inputting a ditch pollution source tracking data set into a ditch pollution transmission simulation algorithm, and calculating a ditch purification capability coefficient through ditch hydraulic retention time and a pollutant degradation rate to obtain a ditch self-purification efficiency matrix; a ditch bearing capacity comparison model before and after restoration is established according to the ditch self-purification efficiency matrix, the restoration gain proportion is calculated and determined through the ditch containing threshold value difference, and a ditch capacity improvement vector is obtained; and carrying out space coupling operation on the channel capacity improvement vector and a village-in-city building density distribution factor to generate a regional channel restoration contribution index, and obtaining a channel restoration efficiency quantification result. According to the method, the problem that environmental feature pertinence and quantitative analysis means are lacked in village-in-city ditch restoration benefit evaluation is solved, and the accuracy of restoration benefit evaluation is improved.

The present invention discloses a city optimization construction method based on the evaluation results of healthy cities in subtropical areas, comprising: constructing a subtropical healthy city evaluation index system based on existing healthy city evaluation indicators and subtropical city health influencing factors; dividing a target city area into multiple grids according to a scale; collecting data corresponding to the subtropical healthy city evaluation index system in the target city area, and calculating the values ​​of several indicators of each grid according to the data; standardizing the values ​​of several indicators and determining the weight of each indicator; calculating the healthy city comprehensive evaluation value of each grid based on the values ​​and weights of various indicators after the standardization of each grid; identifying grids whose healthy city comprehensive evaluation values ​​are less than an evaluation threshold to form several areas to be optimized, and optimizing the areas to be optimized, so as to establish a healthy city evaluation system for subtropical areas, and thus construct cities in subtropical areas.

The invention discloses an adaptive adjustment method and system for urban lighting under digital twinning, and relates to the technical field of urban intelligent lighting, and the method comprises the steps: carrying out the twinning reconstruction of a lighting equipment network in an urban region, and determining a lighting twinning body; through urban distributed sensing, state initialization is carried out on a lighting twinborn body, lamp control constraint elements are introduced, each lighting device is used as a light environment intelligent agent, local game decision is executed, a lighting strategy is determined, and the lamp control constraint elements at least comprise comfort income, energy-saving income and glare punishment; and performing multi-thread instruction generation according to the lighting strategy, and performing lighting management and control on the lighting equipment network. According to the invention, the technical problems that the traditional urban illumination regulation and control are difficult to accurately match the actual demand and cannot balance the multi-aspect targets are solved, and the technical effects of adaptively adjusting the urban illumination, balancing the multi-aspect targets and improving the accuracy and effectiveness of illumination management and control are achieved.

The invention discloses a data center computing power network resource scheduling method, and belongs to the technical field of cloud data processing, and the method comprises the steps: obtaining the total number of passenger-carrying vehicles in a preset city, carrying out the district division of the preset city, obtaining the number of passenger-carrying vehicles in each divided district in different time periods, and enabling the different time periods to be distinguished with each hour as a time period; a travel information request sent by a client is acquired in a preset city district, the information request comprises a departure place and a destination, network signal quality data of the preset city district is acquired, and network signal quality data of a preset passenger-carrying vehicle is acquired in the preset city district; according to the invention, through a data analysis scheduling technology, network signal quality data changes of a preset passenger-carrying vehicle in a preset city area can be calculated, and network signal quality data changes of a departure place can be collected in the preset city area according to each travel information request to be received by the preset passenger-carrying vehicle; therefore, prediction analysis is provided for the passenger-carrying vehicle, and the operation service efficiency is improved.

The present invention discloses a method for scheduling computing power network resources in a data center, belonging to the technical field of cloud data processing. It includes obtaining the total number of passenger vehicles in a preset city, dividing the preset city into areas, obtaining the number of passenger vehicles in each divided area at different time periods, where different time periods are distinguished by each hour as a time period; obtaining the travel information requests sent by clients in the preset city area, the information requests including the departure place and the destination, and obtaining the network signal quality data of the preset city area. It also includes obtaining the network signal quality data of preset passenger vehicles in the preset city area; through data analysis and scheduling technology, the present invention can calculate the change of the network signal quality data of the preset passenger vehicles in the preset city area, and can also collect the change of the network signal quality data of the departure place in each travel information request to be received by the preset passenger vehicles in the preset city area, so as to provide predictive analysis for passenger vehicles and improve the operation service efficiency.

The application discloses a three-dimensional map aided GNSS positioning method based on density clustering improvement, comprising the following steps: constructing a three-dimensional building model, generating a sky mask, pre-generating a sky mask database, judging satellite visibility, scoring the satellite visibility based on a shadow matching algorithm, optimizing candidate point screening rules, introducing an OPTICS clustering algorithm to sort, clean and select candidate points, and screening high-score points; taking the score of the high-score points as a weight, optimizing the calculation formula into a weighted average formula considering cluster weight, and calculating a final position. The positioning method can solve the problem of multiple adjacent peak candidate points in three-dimensional building model aided GNSS pseudorange single point positioning under similar geometric observation conditions in the vicinity of a city area in a complex urban environment, the OPTICS clustering algorithm is adopted to sort data points according to density, small clusters are removed, and effective cleaning and selection of candidate points are realized, so that the positioning precision is effectively improved.

The application discloses a city area railway underground station electromagnetic positioning type special-shaped middle floor assembly construction method, and construction steps are as follows: 1, prefabricating middle floors and all prefabricated structures; magnetic points are arranged on the side wall of each prefabricated structure near the lower end position on the side away from the platform, and the corresponding long side wall of the track top air duct near the lower end position on the side away from the platform; 2, electromagnetic force exciting devices are arranged below and / or on the side of the position where each prefabricated structure needs to be arranged; 3, each prefabricated structure is hoisted and fixed in position through the corresponding electromagnetic force exciting device; 4, the middle floor is hoisted and installed; 5, the middle floor and each prefabricated structure are fixed into a whole; and 6, all electromagnetic force exciting devices are removed. The application can avoid the defects of the cast-in-place method in the prior art, can realize simplification of the special-shaped floor, industrialized rapid installation, energy saving and environmental protection, and is more in line with the trend of green and low-carbon transformation in the city area railway construction field.

The invention relates to the technical field of passenger flow monitoring, and discloses a method for prompting scenic spot passenger flow hotspots in a metropolitan area based on big data, and the method comprises the steps: determining a touring path of a user in a city according to user identification information obtained by a service platform; combining all the sightseeing paths obtained on the day by taking the day as a cycle to obtain a tourist flow diagram in the city area range; determining weights of sightseeing path points in the graph; determining the matching between the weight between the touring path points in the graph and the planned path points; and prompting the scenic spots needing attention based on the difference part of the matching result. According to the method, through a big data technology, the passenger flow dynamic state of the scenic spot is accurately analyzed based on the actual sightseeing path, the flow direction and the scenic spot weight of the tourist, so that accurate passenger flow hotspot prompt is provided for the user.

The application discloses a city area train operation scheme optimization method for co-line operation with national railway trains, comprising the following steps: S1: determining a car bottom operation scheme based on known car bottom quantity, vehicle maintenance conditions and large-small loop operation quantity; S2: setting a train stop scheme based on the section and station co-line of the national railway and the city area train and the limited demand of the city area train operation number; S3: determining a national railway train and city area train flow distribution scheme of the co-line station in unit time; S4: determining a city area train timetable based on the train stop scheme, large-small loop scheme and car bottom operation scheme of the city area train; and S5: considering the difference between daily lines and weekend lines, drawing a track use scheme and fine-tuning the train timetable based on the city area train timetable. According to the application, different transport demands can be integrated, the overall network efficiency in the hub can be improved, and on the basis of guaranteeing the national railway train transport capacity, the comprehensive benefits of the city area train can be maximized.

The invention discloses an urban area traffic road network subarea outer boundary drawing method, which comprises the following steps of: based on intersection position information and road section information which are preset on a map, slicing and refining the whole road network according to a topological relation by utilizing a slicing principle, and taking two adjacent intersections with the topological relation as minimum topological units; taking a boundary external expansion range as a limiting condition for drawing a region boundary, and obtaining a region external boundary of a minimum topological unit by using an envelope principle and a Convex Hull convex hull algorithm; and performing de-duplication and union on the plurality of minimum topological units according to the road network topological relation, and finally forming a crawler-type boundary set of the traffic road network of the whole urban area. According to the method, the situation that different region boundaries are overlapped due to the fact that the region boundaries are caught in concave packet traps during region boundary drawing can be avoided, and high adaptability and flexibility are achieved; and meanwhile, different scene requirements are met by setting different boundary limit thresholds.

The embodiment of the invention discloses a data visualization display method and system based on a business model, and belongs to the technical field of digital cities. According to the embodiment of the invention, the three-dimensional surveying and mapping data including various types of data such as terrains, ground features and textures can be effectively processed, the visual element vectors are mined through the first model visual mapping network, accurate input is provided for subsequent rendering, and the visualization efficiency is improved. And the model visual rendering network performs rendering operation on the basis of the mined vectors to realize visual display of the target digital city area. The two networks are jointly debugged based on the first training error and the second training error, the network performance can be accurately optimized, the accuracy and fidelity of the visualization effect can be improved, the spatial features of the digital city can be better presented, and the requirements of multiple aspects such as city planning and management can be met.

The application discloses a kind of urban electric logistics truck team's cooperative scheduling optimization method and system, equipment, medium, it is based on Markov decision model to construct truck team cooperative scheduling model, by charging, distribution, transport capacity scheduling and receiving order are included into the action space of agent, comprehensively consider the influence of path planning, charging, freight demand, transport capacity scheduling and other factors to vehicle scheduling strategy, greatly improve the cooperative scheduling optimization effect;And, by the vehicle scheduling action selection mechanism in each region is converted into 0 / 1 programming problem, greatly improve the flexibility of action real-time selection, can be well adapted to the scheduling scene of delivery demand and charging cost change;Meanwhile, each grid area of city distribution area is taken as object and is scheduled and optimized, it is favorable to alleviate city area power load imbalance phenomenon.

The invention discloses a city-level parking resource optimization method and system, and relates to the technical field of intelligent transportation. The method comprises the following steps: acquiring real-time operation data and a geographic position of a parking lot in a target city area; constructing an urban parking topological graph which takes each parking lot as a node and takes a connecting road as a side; obtaining the real-time weight of each edge based on the real-time traffic data; calculating a real-time parking pressure value; nodes with the real-time parking pressure values larger than or equal to a first preset pressure value are high-pressure nodes, and nodes with the real-time parking pressure values smaller than the first preset pressure value are judged as potential nodes; performing pressure conduction simulation to obtain a simulated parking pressure value; the potential nodes and the high-pressure nodes with the simulated parking pressure values larger than the second preset pressure value and smaller than the first preset pressure value are determined as potential congestion clusters; and for each potential congestion cluster, calculating a price adjustment coefficient based on the simulated parking pressure value, obtaining a real-time parking rate, and generating a drainage instruction. According to the invention, the configuration accuracy of city-level parking resources can be improved.

The application relates to the technical field of urban planning, and provides a city facility deployment method and device based on reinforcement learning and electronic equipment, wherein the method comprises the following steps: acquiring a city area exchange graph corresponding to an initial city facility deployment scheme, and filtering low-quality edges with total deployment costs higher than a set cost threshold in the city area exchange graph to obtain a target city area exchange graph; based on a pre-trained city facility deployment model, a target city facility deployment scheme is generated according to the target city area exchange graph, and city facility deployment is performed according to the target city facility deployment scheme. According to the method, the low-quality edges in the city area exchange graph are filtered, the attention of the algorithm is guided to high-quality exchange operations, the precision of the target city facility deployment scheme is improved, the exchange operations are driven by the rapid reasoning of the graph neural network and the policy network to realize the city facility deployment, the heavy calculation is avoided, and the rapid generation of the target city facility deployment scheme is realized.

The invention relates to a road motor vehicle OD and city motor vehicle OD splicing method. The method comprises the steps that a traffic area is divided into an urban community, a toll station community and an external community; calculating a passenger flow volume proportion between the cells based on the mobile phone signaling data; and calculating the traffic flow between the urban communities and the external communities in combination with the entrance and exit directions of the toll stations. The method has the beneficial effects that the motor vehicle flow of the inner and outer regions of the city is accurately split by combining the in-out direction of the toll station and the passenger flow distribution proportion of the mobile phone signaling data, and the data blank between the city and the regional traffic model is filled. Moreover, a bidirectional flow splitting algorithm is adopted, so that the error of a single data source is effectively reduced, and the reliability of a calculation result is improved.

The invention discloses a city update intelligent monitoring method, system and platform based on double-branch cross fusion and multi-view dynamic attitude, and the method comprises the steps: generating and obtaining first data corresponding to a target city region, and generating corresponding second data in combination with cube projection; creating a first model corresponding to the first data, and based on the first model, generating corresponding third data in combination with a Cross-MTF feature fusion operator; establishing a second model corresponding to the first data, and generating corresponding fourth data; constructing a third model corresponding to the city, and generating corresponding fifth data based on the third model; based on the third data, the fourth data and the fifth data, performing fusion processing on the multi-view dynamic attitude index, and generating corresponding sixth data; wherein the sixth data is urban update thermodynamic diagram data, and the system and the platform corresponding to the method can realize automatic and refined perception and analysis of urban facade changes.

The invention provides a cross-department false information processing method based on urban social governance, and belongs to the technical field of false information processing, and the method comprises the steps: obtaining to-be-recognized first information; the first information is information obtained by standardizing the multi-source data; extracting risk features of the first information based on a predetermined standard feature library; the risk features comprise content features, main body features, propagation features, time features and regional features; inputting the risk feature into a pre-trained long-short-term memory network to obtain a risk level of the first information; and in response to the fact that the risk level is greater than a predetermined risk level, generating a cross-department disposal work order, and sending the cross-department disposal work order to a corresponding government affair department based on the department responsibility graph to realize cross-department false information processing. According to the invention, the processing efficiency of cross-department false information can be improved.

The application provides a city identification design performance evaluation method, relates to the technical field of performance evaluation, and introduces a solid angle quantitative index to describe the performance of identification design, so as to make up for the problem that quantitative indexes are lacked in the evaluation of the emergency response capability of a city area, has important theoretical value and practical significance for improving the safety resilience of a smart city, and the application also considers various city elements and the behavior capability of people when calculating, so that dynamic perception, group statistics and complex scene correction are realized. The application not only provides quantitative indexes for the evaluation of the emergency response capability of a city, but also can be used for guiding the design of an identification system by a chief engineer.