CN118096471A - Detection and evaluation system for city updating history item - Google Patents
Detection and evaluation system for city updating history item Download PDFInfo
- Publication number
- CN118096471A CN118096471A CN202410477905.1A CN202410477905A CN118096471A CN 118096471 A CN118096471 A CN 118096471A CN 202410477905 A CN202410477905 A CN 202410477905A CN 118096471 A CN118096471 A CN 118096471A
- Authority
- CN
- China
- Prior art keywords
- city
- data
- analysis processing
- update history
- history item
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 59
- 238000001514 detection method Methods 0.000 title abstract description 10
- 238000004458 analytical method Methods 0.000 claims abstract description 189
- 238000012545 processing Methods 0.000 claims abstract description 156
- 230000009466 transformation Effects 0.000 claims abstract description 81
- 230000000694 effects Effects 0.000 claims abstract description 75
- 238000007726 management method Methods 0.000 claims abstract description 62
- 238000010276 construction Methods 0.000 claims abstract description 15
- 230000006870 function Effects 0.000 claims description 28
- 230000008859 change Effects 0.000 claims description 24
- 238000012986 modification Methods 0.000 claims description 20
- 230000004048 modification Effects 0.000 claims description 20
- 238000013079 data visualisation Methods 0.000 claims description 14
- 230000006872 improvement Effects 0.000 claims description 10
- 101100117236 Drosophila melanogaster speck gene Proteins 0.000 claims description 8
- 238000009435 building construction Methods 0.000 claims description 4
- 238000013500 data storage Methods 0.000 claims description 4
- 238000005065 mining Methods 0.000 claims description 3
- 238000009411 base construction Methods 0.000 claims 1
- 238000013523 data management Methods 0.000 abstract description 5
- 238000013480 data collection Methods 0.000 abstract description 2
- 238000000034 method Methods 0.000 description 11
- 230000008569 process Effects 0.000 description 7
- 238000013210 evaluation model Methods 0.000 description 6
- 238000012544 monitoring process Methods 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 4
- 238000007405 data analysis Methods 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000012549 training Methods 0.000 description 3
- 238000003062 neural network model Methods 0.000 description 2
- 238000013439 planning Methods 0.000 description 2
- 238000012732 spatial analysis Methods 0.000 description 2
- 230000002411 adverse Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 238000011158 quantitative evaluation Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application belongs to the technical field of social management, and discloses a detection and evaluation system for an urban updating history project, which comprises a background analysis and processing module, a data base plate construction module, an urban updating history project acquisition module, an implementation effect evaluation module, a transformation potential map spot module and an urban decision support module; the data base plate construction module and the city update history item collection module are used for generating the current data base plate and updating the city update history item database, so that the cost of data collection and data management is reduced, the automatic iterative update of the city update history item database is realized, and the labor cost is reduced; the implementation condition of the urban updating historical project is quantitatively evaluated by using an implementation effect evaluation module, so that a management department can know the implementation effect of the urban updating historical project conveniently; the future city updating project implementation scale is predicted by the transformation potential map spot module and the city decision support module, so that data support for making a future implementation project plan can be provided for city managers.
Description
Technical Field
The application relates to the technical field of social management, in particular to a detection and evaluation system for an urban update history project.
Background
City updates are an important item of content for city work and social management. In the traditional management mode of the urban updating historical projects, different levels of management departments are combined with the self statistical requirements to respectively carry out the recording and archiving of the urban updating historical projects, systematic monitoring and evaluation of the urban updating historical projects are lacked, quantitative analysis of the urban updating historical projects is difficult to support, and formulation of urban updating policies is difficult to support.
The prior city update history project management system mainly aims at project information archiving, is mainly used for data input and attribute input, can meet project record and archiving requirements, but has the following defects or shortages:
1. The classification fusion function is lacking. Because the sources of the urban updating historical projects are numerous, and the project libraries of different levels (such as provinces, cities and regions) are managed respectively, the connotations are different, and the data are overlapped in a crossing way, the problem of repeated input of the urban updating historical projects with different calibers can occur, so that the project vector graphics have space topology conflict, the statistics is easy to be repeated in the success statistics process, and the true and accurate urban updating characteristics and the success cannot be reflected.
2. The information backtracking function is lacking. Because the existing system only performs city update history project information input, does not establish project information logic network and is not associated with other business data, quantitative evaluation of implementation conditions of city update history projects is difficult, implementation effects of city update history projects such as intensive saving level, transformation function direction, spatial distribution characteristics and the like are difficult to evaluate, and effective data analysis support is difficult to provide for city decision.
3. The iterative acquisition function is lacking. Because the existing system uses a business flow form to carry out project management and highly relies on manual information registration and entry, the management of the urban updating history project in each year needs to pay a large management cost, and more management funds and human resources are consumed.
4. Lacks an auxiliary decision making function. The current city updating history project data is only used for transformation effect statistics, past transformation results are analyzed, and future transformation decisions cannot be guided intuitively and quantitatively.
Accordingly, there is a need for improvement and advancement in the art.
Disclosure of Invention
The application aims to provide a detection and evaluation system for urban updating history projects, which aims to solve at least one technical problem in the background technology.
The application provides a detection and evaluation system for an urban update history project, which comprises the following components:
the background analysis processing module is used for providing data storage service, analysis processing service, data visualization service and data export service;
The data base plate construction module is used for importing land area spot data from the background analysis processing module, calling analysis processing service of the background analysis processing module and superposing land utilization current situation attribute and building situation attribute to the land area spot data to obtain a current situation data base plate;
the city updating history item acquisition module is used for importing remote sensing images within a target annual range from the background analysis processing module, and acquiring city updating history item range information and corresponding city updating history item management information through analysis processing services of the background analysis processing module so as to update a city updating history item database;
The implementation effect evaluation module is used for analyzing the implementation effect influence factors according to the city update history item database, evaluating the implementation effect of the city update history items according to the analysis result of the implementation effect influence factors, and calling the data visualization service and the data export service of the background analysis processing module to output a city update history item implementation effect evaluation report;
The transformation potential map spot module is used for generating transformation potential map spots through the analysis processing service of the background analysis processing module according to the current situation data base plate;
And the city decision support module is used for measuring and calculating the implementation scale of the update project in a preset time period in the future according to the transformation potential speck, the estimation result of the implementation effect and the input scene constraint parameter.
The current data base plate generation and the city update history item database update are carried out through the data base plate construction module and the city update history item acquisition module, so that the repeated input problem of multi-source data of the city update history item and the space topology conflict problem of the item vector graph are solved, city update history item acquisition rules and technical routes are unified, and the cost of data acquisition and data management is reduced; the city update history item collection module is utilized to carry out automatic iterative update of the city update history item database, so that the city update history item management cost of each year is greatly reduced, the working modes of manual management, individual case monitoring and individual case evaluation in the past are twisted, and the overall management funds and human resources of a management department are reduced; the implementation condition of the urban updating historical project is quantitatively evaluated through the implementation effect evaluation module, and a convenient and practical implementation effect evaluation report of the urban updating historical project is exported, so that a management department can know the implementation effect of the urban updating historical project conveniently; the future city updating project implementation scale is predicted by the transformation potential map spot module and the city decision support module, so that data support for making a future implementation project plan can be provided for city managers.
Preferably, the data base board construction module, when importing land area spot data from the background analysis processing module and calling the analysis processing service of the background analysis processing module, superimposes land use status attribute and building status attribute on the land area spot data to obtain the status data base board, executes:
Invoking a data export service of the background analysis processing module, and importing the map spot data from the background analysis processing module; the map spot data comprises a map spot data attribute table;
And calling an analysis processing service of the background analysis processing module, and additionally linking the land use current situation attribute and the building condition attribute of the initial year of the target year range and the latest land use current situation attribute and the latest building condition attribute to the map spot data attribute table to obtain a current data base plate.
By superimposing the land use presence attribute and the building condition attribute into the presence data backplane, more reference information is provided for subsequent generation of the transformed potential map spots, thereby enabling the generated transformed potential map spots to be more scientific and reliable.
Preferably, the land use presence attribute comprises at least one of residential land, business use land, industrial and mining storage land, public management and public service land, agricultural land; the building condition attribute includes at least one of building structure, number of floors of building, building height.
Preferably, the city update history item collection module is configured to, when importing the remote sensing image within the target annual range from the background analysis processing module, obtain city update history item range information and corresponding city update history item management information through the analysis processing service of the background analysis processing module, so as to update a city update history item database, perform:
Calling a data export service of the background analysis processing module, and importing remote sensing images of each year in a target annual range from the background analysis processing module;
Invoking analysis processing service of the background analysis processing module, and comparing remote sensing images of each year in a target annual range to identify change information of the remote sensing images so as to generate city update history project range information;
Invoking analysis processing service of the background analysis processing module, and hanging the place name address punctual space data attribute information of the corresponding POI interest point to the city updating history project range information;
Invoking analysis processing service of the background analysis processing module, and inquiring to obtain city update history item management information matched with the city update history item range information according to the place name address punctual space data attribute information of the POI interest point corresponding to the city update history item range information;
and taking the city update history item range information and the corresponding city update history item management information as a group of city update history item data to update a city update history item database.
The range information of the city update history item is obtained through automatic identification, and the corresponding city update history item management information is inquired to generate a group of city update history item data, so that the city update history item database is automatically updated, and management of the city update history item data is not needed to be carried out manually, thereby reducing the overall management funds and human resources of a management department.
Preferably, the city update history project management information includes at least one of a year of improvement, a capacity rate of improvement, a land use function before and after improvement, and an embodiment of improvement.
Preferably, the implementation effect evaluation module analyzes the implementation effect influence factors according to the city update history item database, evaluates the implementation effect of the city update history item according to the analysis result of the implementation effect influence factors, and invokes the data visualization service and the data export service of the background analysis processing module to output a city update history item implementation effect evaluation report, and performs:
Extracting city update history item data corresponding to a target annual range from the city update history item database, wherein the city update history item data is used for carrying out multidimensional transformation state analysis through a pre-established analysis model;
Analyzing implementation effect influence factors according to the multidimensional transformation state analysis result;
evaluating the implementation effect of the city update history item according to the analysis result of the implementation effect influence factors;
and calling a data visualization service and a data export service of the background analysis processing module to output a city update history item implementation success evaluation report.
Preferably, the multi-dimensional transformation state analysis comprises transformation type analysis, transformation direction analysis, transformation implementation nuclear density analysis, transformation front-to-back volume rate change analysis of different transformation years and land utilization function change analysis;
The implementation effect influencing factors comprise intensive saving level, modification function direction and spatial distribution characteristics.
Preferably, the transformation latent image spot module performs, when generating the transformation latent image spot according to the current status data base plate through the analysis processing service of the background analysis processing module:
Calling a current situation data base plate;
invoking analysis processing service of the background analysis processing module, and erasing the retrieved land utilization current spot data positioned in the range of the city updating history item in the current data base plate;
And calling analysis processing service of the background analysis processing module, and superposing reconstruction policy influence parameters, building construction year data and building land occupation area proportion data on a current data base plate after the current land utilization pattern spot data in the city update history project range is erased, so as to obtain a reconstruction potential pattern spot.
Preferably, the city decision support module performs when calculating the implementation scale of the update item in a preset future time period according to the transformation potential map spots, the estimation result of the implementation effect and the input scenario constraint parameter:
invoking the transformation potential map spots and the evaluation result of the implementation effect and acquiring input scene constraint parameters;
measuring and calculating the implementation scale of an update project in a future preset time period according to the transformation potential speck, the estimation result of the implementation effect and the scene constraint parameter by using a pre-established transformation scale prediction model;
and generating an implementation project plan in the future preset time period according to the implementation scale of the update project.
Preferably, the scenario constraint parameter includes at least one of a land supply amount, a real estate market state parameter, and an economic situation parameter.
The beneficial effects are that: the application provides a detection and evaluation system for an urban updating history project, which comprises a background analysis processing module, a data base plate construction module, an urban updating history project acquisition module, an implementation effect evaluation module, a transformation potential map spot module and an urban decision support module; the current data base plate generation and the city update history item database update are carried out through the data base plate construction module and the city update history item acquisition module, so that the repeated input problem of the city update history item multi-source data and the space topology conflict problem of the item vector graph are solved, the city update history item acquisition rules and the technical route are unified, and the cost of data acquisition and data management is reduced; the city update history item collection module is utilized to carry out automatic iterative update of the city update history item database, so that the city update history item management cost of each year is greatly reduced, the working modes of manual management, individual case monitoring and individual case evaluation in the past are twisted, and the overall management funds and human resources of a management department are reduced; the implementation condition of the urban updating historical project is quantitatively evaluated through the implementation effect evaluation module, and a convenient and practical implementation effect evaluation report of the urban updating historical project is exported, so that a management department can know the implementation effect of the urban updating historical project conveniently; the future city updating project implementation scale is predicted by the transformation potential map spot module and the city decision support module, so that data support for making a future implementation project plan can be provided for city managers.
Drawings
Fig. 1 is a general structure diagram of a detection and evaluation system for urban update history items according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of a background analysis processing module.
Description of the reference numerals: 1. a background analysis processing module; 101. an information storage sub-module; 102. a spatial analysis sub-module; 103. an attribute stacking sub-module; 104. a result output sub-module; 2. a data base plate construction module; 3. the city updating history item acquisition module; 4. implementing a success evaluation module; 5. modifying the latent image patch module; 6. and the urban decision support module.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, fig. 1 is a schematic diagram of a city update history item detection and evaluation system according to some embodiments of the present application, including:
The background analysis processing module 1 is used for providing data storage service, analysis processing service, data visualization service and data export service;
The data base plate construction module 2 is used for importing the land map spot data from the background analysis processing module 1, calling the analysis processing service of the background analysis processing module 1, and superposing the land utilization current situation attribute and the building condition attribute on the land map spot data to obtain a current situation data base plate;
the city update history item acquisition module 3 is used for importing remote sensing images within a target annual range from the background analysis processing module 1, and acquiring city update history item range information and corresponding city update history item management information through analysis processing services of the background analysis processing module 1 so as to update a city update history item database;
The implementation effect evaluation module 4 is used for analyzing the implementation effect influence factors according to the city update history item database, evaluating the implementation effect of the city update history item according to the analysis result of the implementation effect influence factors, and calling the data visualization service and the data export service of the background analysis processing module 1 to output a city update history item implementation effect evaluation report;
a transformation potential map spot module 5, configured to generate a transformation potential map spot according to the current status data base plate through the analysis processing service of the background analysis processing module 1;
The city decision support module 6 is used for measuring and calculating the implementation scale of the update project in a future preset time period according to the transformation potential speck, the estimation result of the implementation effect and the input scene constraint parameter.
The data base plate construction module 2 and the city update history item collection module 3 are used for generating a current data base plate and updating a city update history item database, so that the repeated input problem of multi-source data of the city update history item and the space topology conflict problem of an item vector graph are solved, city update history item collection rules and technical routes are unified, and the cost of data collection and data management is reduced; the city update history item collection module 3 is utilized to carry out automatic iterative update of the city update history item database, so that the city update history item management cost of each year is greatly reduced, the working modes of manual management, individual case monitoring and individual case evaluation in the past are twisted, and the overall management funds and human resources of a management department are reduced; the implementation condition of the urban updating historical project is quantitatively evaluated through the implementation effect evaluation module 4, and a convenient and practical implementation effect evaluation report of the urban updating historical project is exported, so that a management department can know the implementation effect of the urban updating historical project conveniently; by modifying the potential map spot module 5 and the city decision support module 6 to predict the future city update project implementation scale, a data support for planning future implementation projects can be provided for city administrators.
The objects served by the background analysis processing module 1 are other modules (a data base plate construction module 2, a city update history item acquisition module 3, an implementation success evaluation module 4, a transformation potential map spot module 5 and a city decision support module 6). The background analysis processing module 1 is at least in communication connection with the data base plate construction module 2, the city update history item acquisition module 3, the implementation success evaluation module 4 and the transformation potential speck module 5.
Specifically, the analysis processing service includes an analysis processing service for spatial data in GIS (Geographic Information System ) data and an analysis processing service for non-spatial data in GIS data; wherein, GIS data refers to all data about the earth's surface stored, processed and managed in a geographic information system, GIS data generally comprises three parts of data: spatial data (position, form, size, etc. of an object), non-spatial attribute information, time information.
The analysis processing service for the space data in the GIS data comprises an intersection processing service, an erasure processing service, a merging processing service, an image identification processing service and a space association processing service.
The intersection processing service is a process of calculating a geometric intersection of input elements.
The erasure processing service is a process of removing a portion intersecting the erasure element from the input element to form a new vector data layer. The erasing elements may be dots, lines and planes, the dot erasing elements are used only to erase the dots in the input element, the line erasing elements may be used to erase the lines and dots in the input element, and the plane erasing elements may be used to erase the dots, lines and planes in the input element.
The merge processing service is a process of calculating a union of input elements.
The image recognition processing service is a process for extracting the characteristics of the image based on a deep learning algorithm, and can compare whether the two images have differences or not and recognize the basic outline range of the building.
The spatial association processing service assigns the hooking object of the attribute table based on the selected spatial relationship, and associates the attribute tables of the two spatial data.
The analysis processing service of the non-space data in the GIS data comprises an supplementing processing service, a deleting processing service, a modifying processing service, a query processing service and a linking processing service of the attribute table. The link processing service is to associate one or more information tables based on one or more attribute information, and aggregate the information tables to form one table.
In some embodiments, see fig. 2, the background analysis processing module 1 includes an information storage sub-module 101, a spatial analysis sub-module 102, an attribute stacking sub-module 103, and a result output sub-module 104; wherein the information storage sub-module 101 is configured to provide a data storage service and a data export service; the space analysis sub-module 102 is used for providing analysis processing service for space data in GIS data; the attribute superposition sub-module 103 is used for providing analysis processing service for non-space data in GIS data; the result output sub-module 104 is used for realizing data visualization and providing generating and outputting functions of reports, data graphs, reports and the like.
Specifically, the data base board construction module 2, when importing land map spot data from the background analysis processing module 1 and calling the analysis processing service of the background analysis processing module 1, superimposes land use presence attribute and building condition attribute on the land map spot data to obtain a presence data base board, executes:
Invoking a data export service of the background analysis processing module 1, importing the map spot data (which is stored in the information storage sub-module 101) from the background analysis processing module 1; the map spot data includes a map spot data attribute table (the map spot data specifically includes map spots and corresponding attribute tables, and the map spot data attribute table is an attribute table corresponding to map spots in the map spot data);
The analysis processing service (specifically, a link processing service) of the background analysis processing module 1 is called, and the land use present property and the building condition property of the starting year of the target year range and the latest land use present property and building condition property are additionally linked to the map spot data attribute table to obtain the present data base plate (namely, the present data base plate is the map spot data overlapped with the land use present property and the building condition property).
By superimposing the land use presence attribute and the building condition attribute into the presence data backplane, more reference information is provided for subsequent generation of the transformed potential map spots, thereby enabling the generated transformed potential map spots to be more scientific and reliable. The current data base plate for generating comprehensive land and building attributes can provide data support for city update history item collection (namely iterative update of city update history item data) and background analysis processing.
Wherein the attribute table is a geographic information system noun, and the attribute table is a table document comprising columns and columns, wherein each column represents a geographic element, and each column represents an attribute of the geographic element. The attribute fields of the map spot data attribute table comprise land area, rights holder, ownership and the like. The attribute field refers to a column attribute item in the attribute table.
Wherein the target annual range is an annual range to be evaluated, for example, the target annual range is 2009 to the current year, so that the initial year is 2009. The target annual range may be set by the user, and in general, the ending annual of the target annual range defaulted by the system is the current annual, and the user may set only the starting annual, so that when the user sets only the starting annual, the system defaults to set the target annual range as the starting annual to the current annual; in practice, the user may also set the start year and the end year autonomously, so that when the user sets the start year and the end year, the system sets the target year range to the start year to the end year.
Wherein the land use presence attribute comprises at least one of a residential site, a business administration site, an industrial and mining storage site, a public management and public service site, an agricultural site; the building condition attribute includes at least one of building structure, number of floors of building, building height.
The obtained current status data backplane may be recorded in the background analysis processing module 1 (recorded in the information storage sub-module 101) so as to be convenient for other modules to call.
Specifically, the city update history item collection module 3 performs, when importing the remote sensing image within the target annual range from the background analysis processing module 1, to obtain city update history item range information and corresponding city update history item management information through the analysis processing service of the background analysis processing module 1 to update the city update history item database:
calling a data export service of the background analysis processing module 1, and importing remote sensing images of each year in the target annual range from the background analysis processing module 1;
The analysis processing service of the background analysis processing module 1 is called (specifically, the image recognition processing service is called), remote sensing images of each year in the target annual range are compared to recognize the change information of the remote sensing images, and urban update history project range information is generated;
calling analysis processing service (specifically calling space association processing service) of a background analysis processing module, and hanging the place name address punctiform space data attribute information of the corresponding POI (Point of Interest) interest points to city update history project range information;
Calling analysis processing service of a background analysis processing module (specifically calling query processing service of an attribute table), and querying to obtain city update history item management information matched with city update history item range information according to the place name address punctual space data attribute information of the POI interest points corresponding to the city update history item range information;
the city update history item range information and the corresponding city update history item management information are used as a group of city update history item data to update a city update history item database.
The range information of the city update history item is obtained through automatic identification, and the corresponding city update history item management information is inquired to generate a group of city update history item data, so that the city update history item database is automatically updated, and management of the city update history item data is not needed to be carried out manually, thereby reducing the overall management funds and human resources of a management department.
Wherein the city update history item range information includes a region range to which the city update history item relates. Comparing the remote sensing images of each year within the target annual range to identify the change information of the remote sensing images, and generating the range information of the urban update history item, which specifically comprises the following steps: and sequentially comparing the remote sensing images of the other various years with the basic image by using the remote sensing image identification technology to identify the area where the land and/or the building change occurs in the remote sensing images of the other various years relative to the basic image, recording the area as a change area, and integrating the change areas corresponding to the remote sensing images of the other various years to obtain the area range related to the urban updating history project in the target annual range.
Further, in some embodiments, integrating the change areas corresponding to the remote sensing images of other years to obtain the area range related to the city update history item within the target annual range specifically includes: combining the mutually intersected change areas in the identified change areas of all the years (can call the combination processing service implementation of the background analysis processing module 1), clustering each change area by using a clustering algorithm according to the central point position of each change area after the combination is completed to obtain at least one group (change area group), and taking the set of the change areas of the same group as the area range related to the update history item of the same city.
The POI interest points are geographic information system nouns, and one POI interest point can be a house, a shop, a mailbox or a bus station. Each POI interest point has a corresponding place name (or called as an interest point noun) and an address, the POI interest point corresponding to the city update history item range information refers to the POI interest point falling in the area range related to the city update history item corresponding to the city update history item range information, and the place names and the addresses of the POI interest points form place name address point space data attribute information.
The city updating history project management information comprises at least one of a reconstruction year, a reconstruction volume rate, a land utilization function before and after reconstruction and a reconstruction implementation mode. The modification implementation mode comprises comprehensive modification, micro modification, mixed modification and the like, namely, the modification implementation mode corresponding to each city updating history project is one of the comprehensive modification, the micro modification, the mixed modification and the like. And when inquiring to obtain the city update history project management information matched with the city update history project range information according to the point name address punctual space data attribute information of the POI interest points corresponding to the city update history project range information, according to the point name and address of each POI interest point, matching each city update history project management information in a city update history project management information base (which is arranged in a background analysis processing module 1 and is established with the mapping relation between each city update history project management information and the point name and address of each POI interest point) so as to match the city update history project management information of each POI interest point. So that each group of city update history item data comprises city update history item range information and city update history item management information of corresponding POI interest points; generally, each group of city update history item data further includes a target annual range corresponding to the group of city update history item data and a time of generating the group of city update history item data, so as to facilitate information backtracking.
The city update history item database may be disposed in the background analysis processing module 1 (specifically, in the information storage sub-module 101) so as to facilitate query calls by other modules.
Specifically, the implementation effort evaluation module 4 performs, when analyzing the implementation effort influence factors according to the city update history item database and evaluating the implementation effort of the city update history item according to the analysis result of the implementation effort influence factors, and invoking the data visualization service and the data export service of the background analysis processing module 1 to output the city update history item implementation effort evaluation report:
Extracting city update history item data corresponding to a target annual range from a city update history item database, and performing multidimensional transformation state analysis through a pre-established analysis model;
Analyzing implementation effect influence factors according to the multidimensional transformation state analysis result;
evaluating the implementation effect of the city update history item according to the analysis result of the implementation effect influence factors;
and calling a data visualization service and a data export service of the background analysis processing module 1 to output a city update history item implementation success assessment report.
The multi-dimensional transformation state analysis comprises transformation type analysis, transformation direction analysis, transformation implementation mode nuclear density analysis, transformation front and back volume rate change analysis of different transformation years and land function change analysis. The transformation type analysis is to analyze the transformation type of the city update history item corresponding to the extracted city update history item data; the retrofit types include, for example, old villages, old workshops, old towns, etc. The reconstruction direction analysis is used for analyzing the reconstruction direction of the city update history item corresponding to the extracted city update history item data; the modification direction includes, for example, an industrial direction, a business direction, a public welfare direction, and the like. And performing nuclear density analysis on the reconstruction implementation mode corresponding to the extracted city update history project data. And analyzing the change of the volume rate before and after the transformation of different transformation years, namely analyzing the change of the volume rate before and after the transformation of each transformation year corresponding to the extracted urban updating history project data. And analyzing the land utilization function change, namely analyzing the change of the land utilization function corresponding to the extracted city update history project data.
Corresponding analysis models (specific principles, algorithms and/or structures of the respective analysis models can be set according to actual needs, and are not limited herein) can be established in advance for each transformation state analysis item, and the analysis models can be stored in the background analysis processing module 1, and the corresponding analysis models are called for analysis according to transformation state analysis items executed as required.
Among the implementation effort influencing factors include intensive savings levels, retrofit function direction and spatial distribution characteristics. The analysis methods of the intensive saving level, the transformation function direction and the spatial distribution characteristics can adopt the prior art, and are not described in detail herein.
When the implementation effect of the city updating history project is estimated according to the analysis result of the implementation effect influence factors, the analysis result of the intensive saving level, the transformation function direction and the spatial distribution characteristic can be input into a pre-trained implementation effect estimation model to obtain an implementation effect estimation value output by the implementation effect estimation model.
The implementation success assessment model can be obtained by the following way:
A1. Acquiring city update history item data corresponding to a plurality of city update history items, acquiring analysis results (specific process reference preamble) of corresponding implementation effect influence factors according to the city update history item data, and scoring the implementation effect of each city update history item by a professional; taking the analysis results (namely the analysis results of intensive saving level, transformation function direction and spatial distribution characteristics) of implementation effect influence factors corresponding to each city updating history item and the corresponding scoring values as one sample to obtain a data set containing a plurality of samples;
A2. Dividing the data set into a training set and a testing set;
A3. Constructing an implementation achievement evaluation model based on the neural network model;
A4. Sequentially inputting analysis results of implementation effect influence factors in all samples in a training set into the implementation effect evaluation model to obtain an implementation effect evaluation value output by the implementation effect evaluation model, and recording the implementation effect evaluation value as a first evaluation value;
A5. Calculating an objective function based on each of the first evaluation values and the score values in the corresponding samples (e.g., the objective function is a sum of squared differences of each of the score values and the corresponding first evaluation value, but is not limited thereto);
A6. If the objective function meets the preset condition (for example, the preset condition is that the objective function is smaller than the preset threshold), stopping training, otherwise, after adjusting the model parameters of the implementation success evaluation model according to the objective function, repeating the step A4-the step A6;
A7. And testing the implementation success evaluation model by using the test set, and obtaining a trained implementation success evaluation model after the test.
The urban update history item implementation effect evaluation report generally includes analysis results of implementation effect factors (i.e., analysis results of intensive saving level, transformation function direction and spatial distribution characteristics) recorded in the form of graphs (such as distribution charts, graphs, pie charts, bar statistical charts, etc.) or statistical tables, and evaluation results of implementation effect of the urban update history item. The graphs and the statistical tables are generated by calling a data visualization service of the background analysis processing module 1, and the final city update history project implementation success evaluation report is generated and output by calling a data export service of the background analysis processing module 1. The urban update history project implementation success assessment report can be generated by adopting a default template of the system or a user-defined template.
Specifically, the transformation potential map module 5 performs, when generating the transformation potential map by the analysis processing service of the background analysis processing module 1 according to the current status data base plate:
Calling a current situation data base plate;
Invoking analysis processing service (specifically invoking erasure processing service) of the background analysis processing module 1, and erasing the retrieved land utilization current spot data in the range of the city update history item in the current data base plate;
And (3) calling an analysis processing service (specifically calling a supplement processing service) of the background analysis processing module 1, and superposing reconstruction policy influence parameters, building construction year data and building land occupation area proportion data on a current data base plate after the current pattern data of the land utilization in the range of the city update history project is erased, so as to obtain the reconstruction potential pattern.
The land use status pattern data located in the area of the city update history item refers to land use status pattern data located in the area of the city update history item.
The transformation policy influence parameters comprise land planning scale, land cover proportion and the like.
Specifically, the city decision support module 6 performs, when calculating the implementation scale of the update project for the preset time period in the future according to the transformation potential map spots, the estimation result of the implementation effect and the inputted scenario constraint parameter:
Invoking transformation potential map spots and evaluation results of implementation results and acquiring input scene constraint parameters;
and (3) measuring and calculating the implementation scale of the update project in a future preset time period according to the transformation potential speck, the implementation effect and the scene constraint parameter by utilizing a pre-established transformation scale prediction model.
Wherein the scenario constraint parameter comprises at least one of land supply, real estate market state parameter, economic situation parameter. The land supply is a planned value or an estimated value of the land supply quantity in a preset time period in the future (wherein the planned value is formulated by a relevant authorities, the estimated value can be predicted by using a big data analysis method, when the planned value exists, the land supply adopts the planned value, otherwise, the land supply adopts the estimated value), the real estate market state parameter is a parameter reflecting the real estate market health level obtained by predicting the real estate market state in the preset time period in the future (can be predicted by using the big data analysis method), and the economic situation parameter is a parameter reflecting the social overall economic situation quality obtained by predicting the economic situation in the preset time period in the future (can be predicted by using the big data analysis method). The context constraint parameters are entered into the system by the user.
The future preset time period is generally 5 years, but is not limited thereto.
The transformation scale prediction model may be a neural network model, or a calculation formula model obtained through data statistics fitting (i.e., a calculation formula using transformation potential plaques, an evaluation result of implementation results and a scenario constraint parameter as inputs and taking an update item implementation scale of a future preset time period as an output).
After obtaining the implementation scale of the updated project in the future preset time period, the city manager can make a future implementation project plan according to the implementation scale of the updated project, so that data support is provided for making the future implementation project plan.
In some embodiments, the city manager may enter the formulated future implementation project plan into a system, which evaluates the rationality of the future implementation project plan to assist the city manager in making adjustments to the future implementation project plan. For example, in some embodiments, the city decision support module 6 is further to:
When a future implementation project plan formulated according to the calculated updated project implementation scale is received, extracting characteristic parameters of the future implementation project plan; for example, the characteristic parameters include the area of the modified land, the type and area of the building before modification of the modified land, the type and area of the building after modification of the modified land, and the like;
Estimating the reconstruction cost of a future implementation project plan according to the extracted characteristic parameters; for example, the transformation cost is the sum of the transformation budget amount and the social influence cost, the transformation budget amount can include a removal compensation budget amount, an old building dismantling budget amount and a new building construction budget amount, each transformation budget amount can be zero, and each budget amount can be estimated by using the existing budget calculation method (the existing budget calculation method is not limited herein); the social influence cost is the sum obtained by converting adverse influence (such as traffic jam, environmental damage and the like) caused by the modification process on society into economic loss, and the cost can be calculated according to the existing conversion method;
Acquiring characteristic parameters, actual transformation costs and implementation success evaluation results (for example, acquiring from a remote server or acquiring from the Internet through a crawler technology) corresponding to a plurality of city update history items of a plurality of cities;
matching a reference city update history item from the acquired city update history items according to the characteristic parameters (for example, calculating the similarity between the characteristic parameters of the future implementation project plan and the characteristic parameters of the acquired city update history items, and taking the city update history item with the highest similarity as the reference city update history item);
Acquiring the initial year of the reference city update history item, and correcting the actual reconstruction cost of the reference city update history item according to the initial year of the reference city update history item to obtain the reference reconstruction cost; for example, calculating a time interval between the current year and the initial year of the reference city update history item, calculating a expansion coefficient according to the time interval (for example, multiplying the time interval by a preset annual average expansion rate to obtain the expansion coefficient), and multiplying the expansion coefficient by the actual reconstruction cost of the reference city update history item to obtain the reference reconstruction cost;
Estimating the implementation effect evaluation result of the future implementation project plan according to the modification cost of the future implementation project plan, the reference modification cost and the implementation effect evaluation result of the reference city update history project; the estimation may be performed by a preset estimation formula, for example, the estimation may be performed by the following formula: p1=p0 (1-k (T1-T0)/T0), P1 is an estimated value of an implementation success evaluation result of the future implementation project plan, T1 is a modification cost of the future implementation project plan, P0 is an implementation success evaluation result of the reference city update history project, T0 is a reference modification cost, and k is a preset proportionality coefficient, but is not limited thereto;
Evaluating the rationality of the future implementation project plan according to the estimated value of the implementation success estimation result of the future implementation project plan; for example, different implementation success assessment result ranges (numerical value ranges) may be assigned different rationality levels, and the rationality level of the future implementation project plan may be determined based on the implementation success assessment result range within which the estimated value of the implementation success assessment result of the future implementation project plan falls.
Therefore, when the city manager can input the formulated future implementation project plan into the system, the system automatically outputs the rationality level of the future implementation project plan, and if the rationality level is too low, the city manager can adjust the future implementation project plan and input the system again to obtain the corresponding rationality level, and the cycle is performed until the satisfactory rationality level is obtained. Thereby assisting the city manager in making a more reasonable future implementation project plan.
In summary, the detection and evaluation system for the city update history item provided by the application has the following advantages:
1. The construction of the necessary functional modules solves the repeated input problem of the multi-source data of the urban updating historical project and the space topology conflict problem of the project vector graph, unifies the acquisition rules and the technical routes of the urban updating historical project, and reduces the cost of data acquisition and data management;
2. The city update history item collection module 3 is utilized to carry out automatic iterative update of the city update history item database, so that the city update history item management cost of each year is greatly reduced, the working modes of manual management, individual case monitoring and individual case evaluation in the past are twisted, and the overall management funds and human resources of a management department are reduced;
3. The implementation condition of the urban updating history project can be quantitatively evaluated, three core dimensions of intensive saving level, transformation function direction and space distribution characteristic are integrated, and a convenient and practical urban updating history project implementation effect evaluation report is derived;
4. the system has an auxiliary decision function, predicts the implementation scale of future city updating projects based on the implementation rules of city updating history projects, the supply and demand conditions of land and the like, and can provide data support for a city manager to formulate future implementation project plans.
Furthermore, functional modules in various embodiments of the present application may be integrated together to form a single portion, or each module may exist alone, or two or more modules may be integrated to form a single portion.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and variations will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A system for detecting and evaluating a city update history item, comprising:
the background analysis processing module is used for providing data storage service, analysis processing service, data visualization service and data export service;
The data base plate construction module is used for importing land area spot data from the background analysis processing module, calling analysis processing service of the background analysis processing module and superposing land utilization current situation attribute and building situation attribute to the land area spot data to obtain a current situation data base plate;
the city updating history item acquisition module is used for importing remote sensing images within a target annual range from the background analysis processing module, and acquiring city updating history item range information and corresponding city updating history item management information through analysis processing services of the background analysis processing module so as to update a city updating history item database;
The implementation effect evaluation module is used for analyzing the implementation effect influence factors according to the city update history item database, evaluating the implementation effect of the city update history items according to the analysis result of the implementation effect influence factors, and calling the data visualization service and the data export service of the background analysis processing module to output a city update history item implementation effect evaluation report;
The transformation potential map spot module is used for generating transformation potential map spots through the analysis processing service of the background analysis processing module according to the current situation data base plate;
And the city decision support module is used for measuring and calculating the implementation scale of the update project in a preset time period in the future according to the transformation potential speck, the estimation result of the implementation effect and the input scene constraint parameter.
2. The system according to claim 1, wherein the data base construction module, when importing land area spot data from the background analysis processing module and invoking the analysis processing service of the background analysis processing module, superimposes land use presence attribute and building condition attribute on the land area spot data to obtain a presence data base, performs:
Invoking a data export service of the background analysis processing module, and importing the map spot data from the background analysis processing module; the map spot data comprises a map spot data attribute table;
And calling an analysis processing service of the background analysis processing module, and additionally linking the land use current situation attribute and the building condition attribute of the initial year of the target year range and the latest land use current situation attribute and the latest building condition attribute to the map spot data attribute table to obtain a current data base plate.
3. The system for detecting and evaluating urban update history items according to claim 2, wherein the land use presence attribute comprises at least one of a residential site, a business administration site, an industrial and mining storage site, a public management and public service site, an agricultural site; the building condition attribute includes at least one of building structure, number of floors of building, building height.
4. The system according to claim 1, wherein the city update history item collection module is configured to, when importing the remote sensing image within the target annual range from the background analysis processing module, obtain city update history item range information and corresponding city update history item management information through the analysis processing service of the background analysis processing module to update the city update history item database, perform:
Calling a data export service of the background analysis processing module, and importing remote sensing images of each year in a target annual range from the background analysis processing module;
Invoking analysis processing service of the background analysis processing module, and comparing remote sensing images of each year in a target annual range to identify change information of the remote sensing images so as to generate city update history project range information;
Invoking analysis processing service of the background analysis processing module, and hanging the place name address punctual space data attribute information of the corresponding POI interest point to the city updating history project range information;
Invoking analysis processing service of the background analysis processing module, and inquiring to obtain city update history item management information matched with the city update history item range information according to the place name address punctual space data attribute information of the POI interest point corresponding to the city update history item range information;
and taking the city update history item range information and the corresponding city update history item management information as a group of city update history item data to update a city update history item database.
5. The system according to claim 4, wherein the city update history item management information includes at least one of a year of improvement, a capacity rate of improvement, a land use function before and after improvement, and an implementation of improvement.
6. The system according to claim 1, wherein the implementation effort evaluation module performs, when analyzing implementation effort factors according to the city update history item database and evaluating implementation effort of city update history items according to analysis results of the implementation effort factors, and invoking the data visualization service and the data export service of the background analysis processing module to output a city update history item implementation effort evaluation report:
Extracting city update history item data corresponding to a target annual range from the city update history item database, wherein the city update history item data is used for carrying out multidimensional transformation state analysis through a pre-established analysis model;
Analyzing implementation effect influence factors according to the multidimensional transformation state analysis result;
evaluating the implementation effect of the city update history item according to the analysis result of the implementation effect influence factors;
and calling a data visualization service and a data export service of the background analysis processing module to output a city update history item implementation success evaluation report.
7. The system of claim 6, wherein the multi-dimensional transformation status analysis includes transformation type analysis, transformation direction analysis, transformation implementation nuclear density analysis, transformation pre-and post-volume rate change analysis for different transformation years, and land use function change analysis;
The implementation effect influencing factors comprise intensive saving level, modification function direction and spatial distribution characteristics.
8. The system of claim 1, wherein the retrofit potential map spot module performs, when generating a retrofit potential map spot from the current data floor via an analysis processing service of the background analysis processing module:
Calling a current situation data base plate;
invoking analysis processing service of the background analysis processing module, and erasing the retrieved land utilization current spot data positioned in the range of the city updating history item in the current data base plate;
And calling analysis processing service of the background analysis processing module, and superposing reconstruction policy influence parameters, building construction year data and building land occupation area proportion data on a current data base plate after the current land utilization pattern spot data in the city update history project range is erased, so as to obtain a reconstruction potential pattern spot.
9. The system according to claim 1, wherein the city decision support module performs, when calculating the update project implementation scale for a predetermined time period in the future based on the transformation potential speck, the implementation result and the inputted scenario constraint parameter:
invoking the transformation potential map spots and the evaluation result of the implementation effect and acquiring input scene constraint parameters;
And measuring and calculating the implementation scale of the update project in a future preset time period according to the transformation potential speck, the estimation result of the implementation effect and the scene constraint parameter by using a pre-established transformation scale prediction model.
10. The system of claim 9, wherein the context constraint parameters include at least one of land supply, real estate market state parameters, and economic situation parameters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410477905.1A CN118096471A (en) | 2024-04-19 | 2024-04-19 | Detection and evaluation system for city updating history item |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410477905.1A CN118096471A (en) | 2024-04-19 | 2024-04-19 | Detection and evaluation system for city updating history item |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN118096471A true CN118096471A (en) | 2024-05-28 |
Family
ID=91160011
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410477905.1A Pending CN118096471A (en) | 2024-04-19 | 2024-04-19 | Detection and evaluation system for city updating history item |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118096471A (en) |
-
2024
- 2024-04-19 CN CN202410477905.1A patent/CN118096471A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11270397B2 (en) | Automatic urban land identification system integrating business big data with building form | |
| US9646275B2 (en) | Methods and apparatus for assessing risks associated with locate request tickets based on historical information | |
| KR101167653B1 (en) | Real estate development business destination positioning system using web-gis and control method thereof | |
| CN106448132A (en) | Conventional public traffic service index real-time evaluation system and method | |
| CN111612294A (en) | City physical examination system based on space-time big data | |
| CN115293570A (en) | GIS-based territorial space planning system and method | |
| CN111797188B (en) | Urban functional area quantitative identification method based on open source geospatial vector data | |
| Ward et al. | Improving CAMA models using geographic information systems/response surface analysis location factors | |
| KR101745321B1 (en) | Method for providing analysis information of traffic impact assessment based on 3D spacial data | |
| Bhatta et al. | Geographical Information System (GIS) as a Planning Support System (PSS) in Urban Planning: Theoretical Review and its Practice in Urban Renewal Process in Hong Kong | |
| CN112132611A (en) | Estimation method integrating geographic information system and building information model | |
| Al-Roumi et al. | Exploring the rate of adoption and implementation depth of building information modeling (BIM): A case of Kuwait | |
| CN107093018A (en) | Communication engineering project information method for visualizing and device based on health model | |
| CN118096471A (en) | Detection and evaluation system for city updating history item | |
| CN115271514A (en) | Communication enterprise monitoring method and device, electronic equipment and storage medium | |
| CN115239281A (en) | BIM + GIS-based road migration management system, method and storage medium | |
| CN112308382B (en) | Open TOD city big data monitoring analysis platform | |
| Zhong et al. | Solutions to cultural, organizational, and technical challenges in developing PECAS models for the cities of Shanghai, Wuhan, and Guangzhou | |
| Tecim | Geographical information system based decision support system for tourism planning and development | |
| CN117522192B (en) | Method and system for supporting intelligent map of urban physical examination and forming report | |
| CN114862276B (en) | Method and system for collaborative analysis and application of large data of producing city | |
| Ranganathan | Decision support systems for energy efficiency in buildings: a review of existing models and its potentials | |
| Perdeli | Developing a gis-based carbon footprint accounting methodology for residential buildings: The case study of Nilufer district in Bursa | |
| CN115880715A (en) | Layer label determining method and device, electronic equipment and storage medium | |
| Wang | Traffic Forecasting and Decision-making of Investment and Construction of Tourism Highway under the Background of Artificial Intelligence |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication |