WO2021103323A1 - 一种历史城市保护发展协同控制方案辅助设计*** - Google Patents
一种历史城市保护发展协同控制方案辅助设计*** Download PDFInfo
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Definitions
- the invention belongs to the technical field of data visualization, and particularly relates to an auxiliary design system for a collaborative control scheme for the protection and development of historical cities.
- the data assignment process is very cumbersome; subsequent GIS platforms need to perform a large number of overlay operations to obtain the weight layer, and these overlay operations involve the minimum overlap method , It also involves the superposition method of taking the maximum value, which is prone to errors.
- the present invention provides an auxiliary design system for a collaborative control scheme for the protection and development of historical cities. It can automatically obtain relevant data, data preprocessing and analysis methods according to the needs of users, effectively reducing the large amount of data preparation and preprocessing workload in the early stage of the project.
- one or more embodiments of the present invention provide the following technical solutions:
- a server that includes:
- the data storage subsystem is used to obtain and store various city factor data
- Method management subsystem used to pre-encapsulate data processing methods, related analysis methods and calculation formulas for multiple urban factor data
- Data analysis subsystem including:
- the data acquisition module is used to receive the user's designation of the data area range and data requirements, obtain the relevant city factor data from the data storage subsystem, and obtain the corresponding data processing method from the method management subsystem to process these city factor data;
- the old city population forecast and environmental population carrying capacity estimation module is used to obtain the urban factor data of the corresponding area in the old city, and match according to the spatial location parameters; receive the user's designation of the basic statistical unit, and obtain the relevant analysis methods for population prediction and environment respectively Population carrying capacity estimation;
- the new urban area development intensity prediction module obtains the urban factor data of the corresponding area in the suburbs, and matches according to the spatial location parameters; selects the site according to the total population pre-accommodated in the new urban area and the evaluation results of development suitability; In the suburban area, receive the user's designation of basic statistical units, obtain relevant analysis methods to estimate the environmental population carrying capacity, and predict the development intensity based on the population carrying capacity distribution;
- the old city protection plan formulation module including: according to the old city population forecast results and the environmental population carrying capacity, the estimated population overrun time is obtained, and the development and construction period is predicted according to the new urban development intensity forecast value; according to the old city population's estimated overrun time and the new urban area Development and construction period, calculate the time when the new area starts to be constructed
- the new urban development intensity prediction module includes:
- the new urban area auxiliary site selection unit is used to receive the total population pre-accommodated in the new urban area and calculate the area of the pre-opened new area; obtain the city factor data of the corresponding area in the suburbs, and match it according to the spatial location parameters; receive the user’s restrictive factors and the development Designation of non-restrictive factors to conduct development suitability evaluation; combined with the development suitability evaluation result map, generate new urban candidate addresses based on the area of pre-opened new districts; receive user adjustments to candidate addresses to determine the new urban construction area;
- the new urban area development intensity prediction unit estimates the environmental resource capacity of each basic statistical unit in the new urban area, and estimates the environmental population carrying capacity of the new urban area based on the environmental resource capacity estimation results; according to the distribution map of the environmental population carrying capacity of the new urban area, predict Estimate the total amount of urban development and the scale of construction of various facilities.
- modules for the formulation of the protection plan for the old city include:
- the population control index calculation unit based on the population forecast results of the old urban areas of each basic statistical unit and the environmental population carrying capacity, the estimated population overtime value and population decommissioning control indicators;
- the new urban area development and construction cycle forecast unit which combines the total urban development and the scale of various facilities to predict the development cycle
- the difference between the population over-limit time value and the new urban area development and construction cycle is the starting time for the construction of the new urban area based on the current time.
- the urban factor data includes: basic geographic data, socio-demographic data, socio-economic data, natural resources and environmental data, infrastructure design, and spatial system data.
- the server also includes a rights management subsystem for managing user information and corresponding rights.
- the data acquisition module also receives a weight assignment file, which is used to assign weights to a series of city factor layers, and obtain multiple raster layers with weight values as pixel values for population prediction analysis and development suitability analysis .
- the population prediction analysis method includes a population prediction method, an environmental capacity estimation method, and an environmental population carrying capacity estimation method.
- One or more embodiments provide a user terminal, which is connected to the server in communication, including:
- City factor data editing module used to upload local city factor data or city factor data in the server to the server after secondary processing
- the basic statistical unit designation module is used to designate the basic statistical unit for the old city and the new city and send it to the server;
- Method selection module used to select analysis methods and calculation formulas
- the visualization module is used to obtain and visualize the data generated in the analysis process.
- a weight editing module which is used to receive the user's designation of the influence weight value, restrictive factor, and non-restrictive factor of each city factor, and generate a weight assignment file.
- One or more embodiments provide an auxiliary design system for a collaborative control scheme for the protection and development of historical cities, including the server and the user terminal.
- the present invention pre-packages the population forecast of the old city, the inherent data of the system and related analysis algorithms on the server side, and cannot be downloaded at will, ensuring the safety of the data; the user uploads the data and related analysis algorithms edited and created by the user through the user terminal. After the server, only the user can use it without authorizing others. On the premise of ensuring data security, it also protects personal intellectual property rights.
- the server of the present invention can easily and fully obtain the data required for planning and design by establishing a communication connection with the server of the relevant department, avoiding a large amount of data preparation workload in the early stage of the planning project; and it is pre-configured with data preprocessing and layer overlay stages.
- Commonly used algorithms, and these algorithms can be customized and modified to meet the individual needs of users, avoiding a large amount of data preparation and preprocessing workload in the early stage of the project.
- the data analysis of the present invention can only be performed on the server side, which effectively prevents data leakage, and also reduces the hardware configuration requirements of the user terminal.
- the server of the present invention provides a variety of population prediction algorithms for the population prediction stage. Users can select and modify according to the specific conditions of the city. At the same time, in order to reduce the negative impact caused by the city dynamics, it also provides law analysis and result verification. A series of methods are used to assist users in revising the prediction model to obtain a model that can objectively and accurately predict the population.
- the present invention estimates the environmental population capacity of the old urban area and the new urban area respectively; based on the environmental population capacity and population prediction of the old urban area, determines the population overrun time, and estimates the development intensity of the new urban area based on the environmental population capacity of the new urban area.
- the start time of the development and construction of the new urban area was estimated to realize the protection of the old urban area.
- the present invention takes the urban environmental population carrying capacity as the quantitative basis for the collaborative control of the historic city protection planning, constructs the historic city protection planning collaborative control system, and uses the simulation model construction method to logically derive the urban population capacity as the protection of the old city and the new city Quantitative basis for collaborative control of district development.
- the use of environmental carrying capacity to estimate the time sequence and countermeasures for the overall protection and development of historical cities is scientific and manipulable.
- Figure 1 is a schematic diagram of a system framework in one or more embodiments of the present invention.
- Figure 2 is a schematic diagram of a population prediction process in one or more embodiments of the present invention.
- FIG. 3 is a schematic diagram of the hierarchical division of the old urban area based on the statistical unit of "street neighborhood committee" in one or more embodiments of the present invention
- Figure 4 shows the population density heat map of the new city development area based on the "geographic grid residential area” unit.
- This embodiment discloses an auxiliary design system for a collaborative control scheme for the protection and development of historical cities. Including: server and user terminal.
- the server includes:
- the data storage subsystem is used for the six major factors of the city. Specifically, it includes storing basic geographic data, social demographic data, socioeconomic data, natural resources and environmental data, infrastructure design, and spatial system data. specifically,
- Basic geographic data includes administrative division data, digital elevation data, high-resolution remote sensing images, and land use data.
- the vector graphics data is divided into layers according to land types. In this embodiment, it includes: water bodies, roads, vegetation coverage areas, residential land, park land, etc.
- the above-mentioned layers are among the three element forms of points, lines, and areas.
- Each layer of the vector graphics data corresponds to an attribute table, which is used to record all the attributes of each graphics unit on the layer.
- Socio-demographic data include: total urban population size at the end of the target year, population size of each urban area, average annual population growth rate, urban population density, population spatial distribution, population age structure, population gender structure, population ethnic structure, labor force composition, family population Composition, industrial population composition, population cultural composition, urban floating population scale. All kinds of population including total population and urban population and related basic data, including current and historical series of data within the planning scope, should be based on official statistical data. It mainly includes "Statistical Yearbook", statistical bulletin, census announcement, population sampling survey bulletin, etc.; other relevant data such as public security and family planning departments can be used as the basis and reference for verification.
- Natural resources and environmental data include: total urban ecological land area, annual standard value of ecological land area per capita, total urban available water resources, standard per capita water consumption, topography, roads, rivers, lakes, nature reserves, basic farmland, and geology , Plants, minerals, climate and other data; specifically can be divided into: land resource data, including agricultural land quality classification, soil database, etc.; water resource data, including the distribution of water resources in the old city, etc.; environmental data, including Environmental pollutant statistics, atmospheric and water environmental quality monitoring data, etc.; ecological data, including the spatial distribution of various vegetation coverage, parks, natural reserves, scenic spots, etc.; climate and meteorological data, Including the coordinates of the city and its surrounding weather stations, as well as data such as average wind speed, strong wind days, quiet wind days, precipitation, and temperature for many years.
- Infrastructure settings include: total urban road area, target value of per capita road area, total number of primary and secondary school degrees, target value of per capita number of primary and secondary school degrees, total number of hospital beds in medical facilities, target value of per capita hospital beds, total annual electricity supply in the city, and annual per capita Standard amount of electricity.
- Spatial system data includes: total urban construction land area, urban land classification and planning construction land standards, urban individual construction land standards; per capita urban construction land area, urban construction land structure, per capita total urban construction land quota index, urban per capita land use classification index , Per capita housing area in urban areas.
- the server establishes a communication connection with the servers of the resources and resources department, the agricultural department, the water conservancy department, the ecological environment department, the meteorological department and other relevant departments, and regularly obtains the latest data from the servers of the corresponding departments.
- the authority management subsystem is used to manage the access authority of the user terminal. This system can be used for decision-making assistance of government departments, analysis of scientific research projects of planning and design units and universities or research institutes. Therefore, the authority management subsystem receives and stores the registration information of the user terminal.
- the registration information includes the unit, name, and certificate. Number and other information.
- the analysis method management subsystem is used to store the preprocessing (missing data processing, normalization, spatial interpolation algorithm, etc.) of the factor data for the six major cities, associating with spatial data, layer overlay, population prediction, environmental carrying capacity, and environment Those skilled in the art can understand the relevant analysis and calculation formulas of population limit carrying capacity, development suitability analysis, urban construction scale, etc., these methods can be stored in the form of code files, and the file name is used to indicate which method is for a certain type of data.
- the population prediction methods specifically include: two types of mathematical predictions, including comprehensive growth rate method and regression model method; one type of socioeconomic prediction, that is, economic correlation analysis method; and one type of BP neural network model method.
- P t is the population size of the basic statistical unit in the forecast target year
- P o is the population size of the basic statistical unit in the base year
- r is the average annual comprehensive growth rate of the basic statistical unit population
- n is the predicted number of years (when n>5, take (5 years is a timing period)
- P t is the predicted population size in the target year t ;
- Y t is the total GDP predicted in the target year;
- a and b are parameters
- the six census data in the study area are used as the original data, and the population size prediction model is established based on the relationship between the changes in the data sets. Iterate repeatedly to obtain a prediction model that conforms to the actual conditions of the research city.
- Calculation method of environmental carrying capacity Based on the social and environmental conditions of the old city, six models are provided for the estimation of environmental capacity for multi-angle combination. There are three types of capacity research: water resources carrying capacity method, land resource carrying capacity method and environmental capacity method; three types of infrastructure carrying capacity research types: road carrying capacity method, educational facility carrying capacity method, and medical facility carrying capacity method. Specifically:
- P t is the population scale at the end of the forecast target year; St is the ecological land area in the forecast target year; st is the ecological land area per capita in the forecast target year
- P t is the population size at the end of the forecast target year
- D t is the total road area of the forecast target year
- d t is the road land area per capita in the forecast target year
- P t set the goal at the end of population size; S t to predict the total number of primary and secondary school degree target at the end; s t to predict the number of primary and secondary school places per capita late goal
- P t is the population size at the end of the forecast target year
- B t is the total number of hospital beds at the end of the forecast target year
- b t is the number of hospital beds per capita in the forecast target year.
- Result verification method Provide mutual check of multiple prediction models to judge the accuracy of the results. Specifically, two results verification methods are provided: comparative verification method and water resource capacity method.
- P K is the sample element of the sequence number K;
- P 1 is the sample element ranked first, also known as the top Urban elements;
- q is the rank scale index.
- y is a measure of the local or subsystem
- x is a measure of the system as a whole
- b is the allometric growth coefficient
- Equation 9 the relationship between urban population and area allometric growth can be expressed as:
- n is the total number of regional units involved in the analysis; x i and x j are respectively the observation values of a certain phenomenon x or a certain attribute characteristic x on spatial and regional units i and j; X is the average value of the research object x; W ij is the spatial weight matrix.
- n is the total number of regional units involved in the analysis; x i and x j are respectively the observation values of a certain phenomenon x or a certain attribute characteristic x on spatial and regional units i and j; X is the average value of the research object x; W ij is the spatial weight matrix.
- the remaining population carried by this unit can be calculated. According to the average annual growth rate of the urban population of this unit provided by the census, the time for the population of this unit to reach the environmental limit can be calculated;
- Su is the population surplus carried by the basic statistical unit
- St1 is the ultimate environmental population carrying capacity of the basic statistical unit
- S 0 is the actual population of the basic statistical unit.
- the average annual growth rate of the urban population in this unit provided by the census is expressed as:
- the calculation can get the time value t1 for the population of this statistical unit to reach the environmental limit carrying capacity:
- S t1 is the total population in t1; S 0 is the initial population; ⁇ is the average annual population growth rate; t1 is the time.
- Se is the population depopulation of the basic statistical unit
- S 0 is the actual population of the basic statistical unit
- S t1 is the ultimate environmental population carrying capacity of the basic statistical unit.
- TF is the comprehensive evaluation value of all non-linear factors
- Wi is the weight of a single non-restrictive factor
- Fi is the specific grading assignment of a single factor.
- the difference between the population over-limit time value t 1 and the new city development and construction period value t 2 is the starting point t development at which the construction of the new city should start based on the current time, which can coordinate the construction sequence of the new and old city as a whole.
- the formula is expressed as:
- t 1 is the time value of population over-limit
- t 2 is the time value of the new city development and construction cycle
- t development is the time starting point for the construction of the new city.
- the data analysis subsystem receives data analysis requests from the user terminal, creates analysis tasks for the user terminal, and performs corresponding analysis, including:
- the city factor data retrieval module is used to retrieve relevant city factor data in the designated area according to the selection of the user terminal, and after receiving the confirmation message from the user terminal, associate the relevant city factor data with the analysis task of the user terminal;
- the city factor data preprocessing module is used to preprocess the retrieved city factor data. Specifically, for population, socioeconomic data, retrieve the corresponding preprocessing method in the analysis algorithm management subsystem for preprocessing, mainly Including the filling of missing data and data normalization, etc.; for environmental (air pollution, etc.) and meteorological data that only have point values, because these data are spatially continuous, the preprocessing methods mainly include data normalization, spatial Interpolation processing, etc.;
- the spatial data preparation module is used to associate socio-economic data with administrative division data based on the received high-precision land use data and/or administrative division data, or based on the land use data and/or administrative division data that comes with the system
- the natural resource environment data is associated with the attribute data of the corresponding layer of the land use data according to the geographic coordinate information;
- the weighting module is used to receive a weighting file sent by the user terminal, and generating multiple raster layers with weight values as pixel values based on the weighting rules; the weighting file includes weighting for each layer A rule, the weight assignment rule includes the corresponding relationship between the condition to be satisfied and the weight value;
- the population prediction module of the old city area including:
- the population prediction unit of the old city area receives the basic statistical unit specified by the user via the user terminal and the year used for population prediction, associates the population data of the corresponding year with the corresponding basic statistical unit, and calls one or more populations specified by the user Prediction method to predict the population size in a specified year; and to receive model modifications made by the user terminal based on the verification result;
- the result verification unit receives the reference demographic data sent by the user terminal and the designation of the verification method, calculates the verification result, and feeds the verification result back to the user terminal;
- the environmental population carrying capacity estimation module includes:
- the environmental capacity estimation unit of the old urban area is used to estimate the corresponding environmental resource capacity of each basic statistical unit in the old urban area;
- the environmental population carrying capacity estimation unit is used to estimate the environmental population carrying capacity of the old urban area according to the estimation result of the environmental resource capacity
- the new urban development intensity prediction module includes:
- the area estimation unit of the new area receives the total population capacity of the new area sent by the user terminal, and calculates the area of the pre-opened new area;
- the urban resource population capacity estimation unit uses the urban resource population capacity estimation model to estimate the population capacity of the administrative districts around the old city, and ranks and ranks them. Specifically, according to the urban natural basic geographic information data, use the urban resource population capacity estimation theoretical model and GIS application model to conduct a comprehensive assessment of the environmental population carrying capacity;
- the new urban development suitability evaluation unit receives the user’s designation of restricted and non-restricted factors, conducts development suitability evaluation, and obtains a development suitability evaluation map with development suitability score as the pixel value;
- the new urban area candidate address generation unit analyzes the quantitative results of "environmental population carrying capacity estimation + environmental development suitability evaluation" as the basis for site selection in the new urban area; comprehensively ranked according to the evaluation results of the environmental carrying capacity conditions in each major area , To obtain the overall candidate area suitable for new city development; comprehensively rank and sort according to the environmental carrying capacity of each basic statistical unit, correlate graphical data and model results, and use three-dimensional visualization methods for intuitive expression, and obtain the expansion area based on the basic statistical unit.
- Schematic diagram of development suitability evaluation classification accept user's choice and delineate the red line of new urban construction;
- the urban axis distribution calculation unit sends the distribution map of the ultimate environmental population carrying capacity to the user terminal and performs a three-dimensional visualization simulation, which can present a fuzzy urban axis distribution relationship (primary and secondary axis relationship).
- This fuzzy evaluation result provides suitable for new district planning. Design quantitative basis for the survival and development needs of urban population;
- the total urban construction and development of the pre-opened new area is calculated based on the per capita urban construction land area (i.e. urban land standard, m/person); according to the urban per capita land use classification index (m/ Person), can calculate the per capita area of various types of land such as residence, public facilities, industry, road square, external transportation, storage, municipal public facilities, green space, special land, etc., and the product of the population can calculate the construction scale of various functional areas .
- the per capita urban construction land area i.e. urban land standard, m/person
- m/ Person urban per capita land use classification index
- the new area development intensity indicator calculation unit determines the total urban development and the scale of various facilities construction based on the urban population capacity distribution of each basic statistical unit in the new city development area, with the help of urban construction indicators. Form the planning logic of "population accounting + suitability evaluation” ⁇ “total urban development” ⁇ “facility development”. The ultimate carrying capacity of environmental population is positively correlated with the intensity of land and space development;
- Formulation modules of the protection plan for the old city area including:
- the population control index calculation unit is used to estimate the ultimate environmental population carrying capacity in each basic statistical unit of the old city. According to the population status of each basic unit, calculate the over-population time value and the population depopulation control index of each unit.
- the new area development and construction cycle forecasting unit based on the general plan and sub-plans, predicts the development and construction cycle, construction investment, and total amount of materials according to the project construction plan, plans the construction process, and provides data support for the development of the new city;
- the new area development time prediction module coordinates the overall time sequence of new and old city construction.
- the difference between the population over-limit time value and the new city development period value is the starting time for the construction of the new city area based on the current time.
- the server adopts a cloud server.
- the data upload and data retrieval of the relevant departments are through the encryption and decryption mechanism.
- the data is only used on the server side. No user can download it at will. This protects the security of the original data;
- the user opens up an independent storage space to store the data uploaded by the user or processed by the user, the analysis method and the data obtained during the analysis process, so that the user can trace the analysis process.
- the storage space of each user is limited to the user's own access, and may not be accessed by other users without authorization.
- the city factor data visualization module is used to retrieve and visualize city factor data from the server according to user requests.
- City factor data editing module used for secondary processing of city factor data and uploading to the server, for example, to retrieve the data processed by the server for review and revision; to digitize and visualize the retrieved high-resolution remote sensing image data Interpret and obtain high-precision land use data.
- land use data may also be prepared in advance, and directly uploaded to the server through this module for related subsequent analysis.
- the weight editing module uses the weight of evidence model to calculate the influence weight value of each city factor, as well as the designation of restrictive factors and non-restrictive factors, and generates weight assignment files.
- the basic statistical unit designation module is used to designate the basic unit for statistics.
- the administrative management unit-"street neighborhood committee" is defined as the basic statistical unit.
- the method selection module is used to select the calculation method used in the analysis process.
- the model editing module is used to modify the model parameters according to the verification results of the population prediction
- the visualization module is used to visualize the population prediction results, law analysis results, verification results, environmental resource capacity estimation results, environmental population carrying capacity estimation results, and population control indicators obtained in the analysis process.
- the visualization can set different visualization forms according to the content to be visualized.
- this embodiment uses the sixth population census data as the benchmark data to predict the population size in the future years.
- two or more different prediction methods are selected for prediction respectively, and multiple prediction schemes are obtained by adjusting the parameter assignment in the formula. Since there are many population forecasting methods, each forecasting method has its adaptability, advantages and limitations. It is necessary to choose a forecasting method that conforms to the characteristics of urban population and environmental resources, and according to the principles of easy operation and generalization. Generally choose two models: 1. Universal model; 2. Specific model. The comparative verification method is a universal method with strong adaptability and is suitable for all census regions.
- the rank-scale index analysis method is used to explore the correlation between elements and sequences in a certain area, reflect the distribution characteristics of urban elements at different levels, and also reflect the concentration or equilibrium degree of elements, and understand the distribution of urban population size and structure. Loose, ideal or concentrated, evaluate whether this population distribution is suitable for urban development; population-area allometric growth analysis method: predict the urban population and area, and calculate the urban population-area allometric scale factor year by year based on the forecast data.
- the change value of the scaling factor can obtain the change of urban population and area on the time axis; spatial autocorrelation analysis method: reveals the spatial distribution law and internal correlation of the static population distribution in the entire study area and various internal regions.
- the global index is used to verify the spatial pattern of the entire study area, and the calculation results indicate the overall characteristics of the spatial distribution of the population in the area (that is, the adjacent trend of the high and low density areas of the population distribution); while the local index is used to reflect a certain area on a regional unit.
- the calculation results indicate the characteristics of the population distribution in each local area (that is, the high and low density of specific areas of population distribution).
- the comparison verification method is to compare and modify models based on actual deviations, and the water resources capacity method uses the "water resources capacity method" (Equation 6) model, and introduces the relevant values of the target unit for calculation. See whether the calculation result is the same or similar to the model derivation results of other modules to judge the correctness of the multi-dimensional construction of the collaborative control model system.
- PCPM model multi-angle urban population prediction model
- one or more of the six models are selected to calculate the environmental capacity and combine them from multiple perspectives to construct a theoretical model (UECE model) for estimating the environmental resource capacity of the old city.
- UECE model a theoretical model
- the development suitability evaluation factors are divided into two categories: restrictive factors and non-restrictive factors. Extract roads, rivers, lakes, nature reserves, DEM and land use data from the basic geographic database, convert them into raster data, and then evaluate the suitability of development according to the technical process.
- the main considerations are the areas that are close to roads, water sources (river, lake) and slopes, and then assign values according to the pros and cons of conditions, and use the Delphi scoring method to comprehensively summarize. Find out the candidates that can be used as the location of the new city through spatial query. Finally, perform overlay analysis based on the distribution maps of restricted factors and non-restricted factors to obtain the development suitability evaluation chart, which provides a reference for the site selection of the new city (DAEM model).
- the present invention pre-packages the population forecast of the old city, the inherent data of the system and related analysis algorithms on the server side, and cannot be downloaded at will, ensuring the safety of the data; the user uploads the data and related analysis algorithms edited and created by the user through the user terminal. After the server, only the user can use it without authorizing others. On the premise of ensuring data security, it also protects personal intellectual property rights.
- the server of the present invention can easily and fully obtain the data required for planning and design by establishing a communication connection with the server of the relevant department, avoiding a large amount of data preparation workload in the early stage of the planning project; and it is pre-configured with data preprocessing and layer overlay stages.
- Commonly used algorithms, and these algorithms can be customized to meet the individual needs of users, avoiding a large amount of data preparation and preprocessing workload in the early stage of planning projects.
- the data analysis of the present invention can only be performed on the server side, which effectively prevents data leakage, and also reduces the hardware configuration requirements of the user terminal.
- the server of the present invention provides a variety of population prediction algorithms for the population prediction stage. Users can select and modify according to the specific conditions of the city. At the same time, in order to reduce the negative impact caused by the city dynamics, it also provides law analysis and result verification. A series of methods are used to assist users in revising the prediction model to obtain a model that can objectively and accurately predict the population.
- modules or steps of the present invention can be implemented by a general-purpose computer device. Alternatively, they can be implemented by a program code executable by the computing device, so that they can be stored in a storage device. The device is executed by a computing device, or they are separately fabricated into individual integrated circuit modules, or multiple modules or steps in them are fabricated into a single integrated circuit module for implementation.
- the present invention is not limited to any specific combination of hardware and software.
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Abstract
Description
Claims (10)
- 一种服务器,其特征在于,包括:数据存储子***,用于获取并存储多种城市因子数据;方法管理子***,用于预先封装针对多种城市因子数据的数据处理方法、相关分析方法和计算公式;数据分析子***,包括:数据获取模块,用于接收用户关于数据区域范围和数据需求的指定,从数据存储子***获取相关城市因子数据,从方法管理子***获取相应数据处理方法对这些城市因子数据进行处理;老城区人口预测和环境人口承载量估算模块,用于获取老城区相应区域的城市因子数据,按照空间位置参数进行匹配;接收用户关于基础统计单元的指定,获取相关分析方法分别进行人口预测和环境人口承载量估算;新城区开发强度预测模块,获取城郊相应区域的城市因子数据,按照空间位置参数进行匹配;根据获取的新城区预容纳的人口总量和开发适宜性评价结果进行选址;对于选址范围内的城郊区域,接收用户关于基础统计单元的指定,获取相关分析方法分别进行环境人口承载量估算,并根据人口承载量分布预测开发强度;老城区保护方案制定模块,包括:根据老城区人口预测结果和环境人口承载量得到人口预计超限时间,根据新城区开发强度预测值预测开发建设周期;根据老城区人口预计超限时间和新城区开发建设周期,计算新区开始建设时间。
- 如权利要求1所述的服务器,其特征在于,新城区开发强度预测模块,具体包括:新城区辅助选址单元,用于接收新城区预容纳的人口总量,推算预开辟新区面积;获取城郊相应区域的城市因子数据,按照空间位置参数进行匹配;接收用户关于开发的限制性因子和非限制性因子的指定,进行开发适应性评价;结合开发适宜性评价结果图,根据预开辟新区面积,生成新城区候选地址;接收用户对候选地址的调整,确定新城区建设区域;新城区开发强度预测单元,根据对新城区各基础统计单元相应的环境资源容量进行估算,以及根据环境资源容量估算结果,估算新城区环境人口承载量;根据新城区环境人口承载量分布图,预估城市开发总量及各类设施建设规模。
- 如权利要求1所述的服务器,其特征在于,老城区保护方案制定模块,具体包括:人口调控指标计算单元,基于各基础统计单元老城区人口预测结果和环境人口承载量,预计人口超限时间值和人口疏解控制指标;新城区开发建设周期预测单元,结合城市开发总量及各类设施建设规模,预测开发周期;新城区开发时间预测单元,人口超限时间值与新城区开发建设周期的差值,即为从当前时间为基准,开始进行新城区建设的时间起点。
- 如权利要求1所述的一种服务器,其特征在于,所述城市因子数据包括:基础地理数据、社会人口数据、社会经济类数据、自然资源环境类数据、基础设施设局、空间***数据。
- 如权利要求1所述的一种服务器,其特征在于,所述服务器还包括权限管理子***,用于管理用户信息和相应权限。
- 如权利要求1所述的一种服务器,其特征在于,所述数据获取模块还接收权重赋予文件,用于对一系列城市因子图层赋予权重,得到以权重值为像素值的多个栅格图层用于人口预测分析和开发适宜性分析。
- 如权利要求1所述的一种服务器,其特征在于,所述人口预测分析方法包括人口预测方法、环境容量估计方法和环境人口承载量估计方法。
- 一种用户终端,其特征在于,与权利要求1-7任一项所述服务器通信连接,包括:城市因子数据编辑模块,用于将本地城市因子数据或针对服务器中城市因子数据经二次加工上传至服务器;基础统计单元指定模块,用于针对老城区和新城区分别指定基础统计单元并发送至服务器;方法选择模块,用于针对分析方法和计算公式进行选择;可视化模块,用于获取分析过程中产生的数据并进行可视化。
- 如权利要求6所述的一种用户终端,其特征在于,还包括权重编辑模块,用于接收用户针对各城市因子影响权重值和限制性因子、非限制性因子的指定,生成权重赋予文件。
- 一种一种历史城市保护发展协同控制方案辅助设计***,其特征在于,包括如权利要求1-7任一项所述的服务器和如权利要求8-9任一项所述的用户终端。
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