Geographic information system (GIS) and cloud computing fused territorial space planning dynamic simulation method and system

Abstract

The invention discloses a GIS and cloud computing fused territorial space planning dynamic simulation method and system, and relates to the technical field of cloud computing. The GIS and cloud computing fused territorial space planning dynamic simulation method is characterized by comprising the steps of collecting territorial space information, performing spatial analysis on territorial space information data, constructing a territorial space planning dynamic simulation model, and inputting a territorial space analysis result into the territorial space planning dynamic simulation model. Analyzing the territorial space planning simulation scheme to obtain a territorial space dynamic simulation distribution diagram, and forming a territorial space planning evaluation diagram according to the territorial space planning requirement and the territorial space dynamic simulation distribution diagram; the territorial space information data can be quickly obtained through the GIS and the cloud computing technology, and the territorial space condition of the current region can be met when territorial space planning is carried out according to a territorial space dynamic simulation scheme.

Description

Technical Field

[0001] The present invention relates to the field of cloud computing technology, and in particular to a method and system for dynamic simulation of national land space planning by integrating GIS with cloud computing. Background Art

[0002] There is a lag in national land space planning. It takes a long time after the national land space information data is obtained before a national land space planning scheme can be formulated based on the previous national land space information data. After the implementation of the planning scheme, the national land space data has changed, making the scheme inapplicable. Nowadays, there is an urgent need for a system that can formulate national land space planning schemes based on real-time national land space information data. With the continuous development of cloud computing technology and GIS, cloud computing technology and GIS are integrated to quickly obtain and process various national land space information data, thereby improving planning efficiency and making planning timely. Summary of the invention

[0003] The present invention provides a dynamic simulation method for land space planning integrating GIS and cloud computing, comprising:

[0004] Step S1, the cloud platform collects land and space information data through the GIS system, establishes a land and space information database and pre-processes the database data information;

[0005] Step S2: The cloud platform performs spatial analysis on the land and space information data to obtain the land and space analysis results;

[0006] Step S3: The cloud platform constructs a dynamic simulation model of national land space planning according to national land space planning requirements;

[0007] Step S4: The cloud platform inputs the data information of the national land space analysis results into the national land space planning dynamic simulation model to obtain a national land space planning simulation plan;

[0008] Step S5: The cloud platform inputs the national land space planning simulation plan into the GIS system for analysis to obtain a dynamic simulation distribution map of the national land space;

[0009] Step S6: The cloud platform forms a national land space planning evaluation map based on the national land space planning requirements and the national land space dynamic simulation distribution map.

[0010] As described above, a dynamic simulation method for land space planning integrating GIS and cloud computing is described, wherein the cloud platform collects land space information data through the GIS system, establishes a land space information database, and pre-processes the database data information in the following sub-steps:

[0011] Step S11, the cloud platform collects land space information data using virtualization technology through the GIS system;

[0012] Step S12: The cloud platform stores the collected land space information data in a database;

[0013] Step S13: The cloud platform pre-processes the land and space information data through data cleaning, data integration, data simplification and data transformation to obtain pre-processed land and space information data.

[0014] As described above, a dynamic simulation method for land space planning integrating GIS and cloud computing is described, wherein the cloud platform performs spatial analysis on land space information data, and the sub-steps for obtaining the land space analysis results are as follows:

[0015] Step S21: The cloud platform performs spatial analysis on the population distribution information data to obtain population distribution analysis data;

[0016] Step S22: The cloud platform performs spatial analysis on the land use information data to obtain land use analysis data;

[0017] Step S23: The cloud platform performs spatial analysis on the ecological environment information data to obtain ecological environment analysis data;

[0018] Step S24: the cloud platform performs spatial analysis on the natural resource information data to obtain natural resource analysis data;

[0019] Step S25: The cloud platform stores the land and space analysis result information data in the database to obtain the land and space analysis result information database.

[0020] As described above, a method for dynamic simulation of national land space planning integrating GIS and cloud computing is described, wherein the sub-steps of the cloud platform constructing a dynamic simulation model of national land space planning according to the requirements of national land space planning are as follows:

[0021] Step S31, the cloud platform obtains national land space planning indicators according to national land space planning requirements;

[0022] Step S32: The cloud platform optimizes the population distribution analysis data in the analysis results according to the national land space population distribution planning indicators to obtain simulated population distribution data;

[0023] Step S33: the cloud platform optimizes the land use analysis data in the analysis results according to the national land use planning indicators to obtain simulated land use data;

[0024] Step S34: the cloud platform optimizes the ecological environment analysis data in the analysis results according to the national land space ecological environment planning indicators to obtain simulated ecological environment data;

[0025] Step S35: The cloud platform optimizes the natural resource analysis data in the analysis results according to the national land space natural resource planning indicators to obtain simulated natural resource data;

[0026] Step S36: The cloud platform generates a national land space planning simulation plan based on simulated population distribution data, simulated land use data, simulated ecological environment data, simulated natural resource data, and basic geographic information data.

[0027] As described above, a method for dynamic simulation of land space planning by integrating GIS and cloud computing is described, wherein the cloud platform inputs the land space planning simulation scheme into the GIS system for analysis, and the sub-steps for obtaining the dynamic simulation distribution map of land space are as follows:

[0028] Step S51, the cloud platform imports the data of the national land space planning simulation program into the GIS system;

[0029] Step S52: the cloud platform performs spatial analysis according to the national land space planning simulation scheme to obtain the analysis results of the national land space planning simulation scheme;

[0030] Step S53: The cloud platform generates a dynamic simulation distribution map of the national land space according to the analysis results of the national land space planning simulation scheme;

[0031] Step S54: The cloud platform updates the dynamic simulation distribution map of the national land space according to the continuously acquired national land space planning simulation plan.

[0032] As described above, a dynamic simulation method for land space planning integrating GIS and cloud computing is described, wherein the cloud platform forms a land space planning evaluation map based on a land space distribution map and preset indicator data of land space planning in the following sub-steps:

[0033] Step S61: The cloud platform sets an evaluation index system according to the dynamic simulation distribution map of national land space and the national land space planning requirements;

[0034] Step S62: The cloud platform summarizes and assigns values ​​to the evaluation indicators through principal component analysis and cluster analysis to determine the weight of each indicator;

[0035] Step S63: The cloud platform uses the spatial overlay method to superimpose data of different indicators to form a national land space planning evaluation map.

[0036] The present invention also provides a GIS and cloud computing integrated land space planning dynamic simulation system, including:

[0037] The information collection and processing module collects land and space information data through the GIS system, establishes a land and space information database, and pre-processes the database data;

[0038] The information analysis module performs spatial analysis on the land and space information data to obtain the land and space analysis results;

[0039] Model building module, which builds a dynamic simulation model of national land space planning according to national land space planning requirements;

[0040] The model execution module inputs the data information of the national land space analysis results into the national land space planning dynamic simulation model to obtain the national land space planning simulation plan;

[0041] The distribution map generation module inputs the national land space planning simulation plan into the GIS system for analysis to obtain the dynamic simulation distribution map of the national land space;

[0042] The evaluation map generation module forms a national land space planning evaluation map based on the national land space planning requirements and the national land space dynamic simulation distribution map.

[0043] As described above, a dynamic simulation system for land space planning integrating GIS and cloud computing, wherein the information collection and processing module specifically includes:

[0044] The information collection submodule collects land space information data through the GIS system using virtualization technology;

[0045] The information storage submodule stores the collected land and space information data into the database;

[0046] The information processing submodule pre-processes the national land and space information data through data cleaning, data integration, data simplification and data transformation to obtain pre-processed national land and space information data.

[0047] The above-mentioned GIS and cloud computing integrated land space planning dynamic simulation system, wherein the information analysis module specifically includes:

[0048] The population distribution analysis submodule performs spatial analysis on population distribution information data to obtain population distribution analysis data;

[0049] The land use analysis submodule performs spatial analysis on land use information data to obtain land use analysis data;

[0050] The ecological environment analysis submodule performs spatial analysis on ecological environment information data to obtain ecological environment analysis data;

[0051] The natural resource analysis submodule performs spatial analysis on natural resource information data to obtain natural resource analysis data;

[0052] The analysis result storage submodule stores the land and space analysis result information data into the database to obtain the land and space analysis result information database.

[0053] As described above, a dynamic simulation system for land space planning integrating GIS and cloud computing, wherein the model building module specifically includes:

[0054] The planning indicator acquisition submodule obtains the national land space planning indicators according to the national land space planning requirements;

[0055] The population distribution optimization submodule optimizes the population distribution analysis data in the analysis results according to the national land space population distribution planning indicators to obtain the simulated population distribution data;

[0056] The land use optimization submodule optimizes the land use analysis data in the analysis results according to the national land use planning indicators to obtain simulated land use data;

[0057] The ecological environment optimization submodule optimizes the ecological environment analysis data in the analysis results according to the national land space ecological environment planning indicators to obtain simulated ecological environment data;

[0058] The natural resource optimization submodule optimizes the natural resource analysis data in the analysis results according to the national land space natural resource planning indicators to obtain simulated natural resource data;

[0059] The scheme generation submodule generates a national land space planning simulation scheme based on simulated population distribution data, simulated land use data, simulated ecological environment data, simulated natural resources data, and basic geographic information data.

[0060] The above-mentioned GIS and cloud computing integrated land space planning dynamic simulation system, wherein the distribution map generation module specifically includes:

[0061] The data import submodule imports the data of the national land space planning simulation program into the GIS system;

[0062] The scheme analysis submodule performs spatial analysis based on the national land space planning simulation scheme and obtains the analysis results of the national land space planning simulation scheme;

[0063] The simulation distribution map generation submodule generates a dynamic simulation distribution map of national land space according to the analysis results of the national land space planning simulation scheme;

[0064] The data update submodule updates the dynamic simulation distribution map of national land space according to the continuously acquired national land space planning simulation plan.

[0065] As described above, a dynamic simulation system for national land space planning integrating GIS and cloud computing, wherein the evaluation map generation module specifically includes:

[0066] The indicator system setting submodule sets the evaluation indicator system according to the dynamic simulation distribution map of national land space and the requirements of national land space planning;

[0067] The indicator weight determination submodule summarizes and assigns values ​​to the evaluation indicators through principal component analysis and cluster analysis to determine the weight of each indicator;

[0068] The evaluation map generation sub-module uses the spatial overlay method to superimpose data of different indicators to form a national land space planning evaluation map.

[0069] The beneficial effects achieved by the present invention are as follows: Compared with the above-mentioned background technology, the present invention can quickly obtain national land space information data through GIS and cloud computing technology. When planning the national land space based on the national land space information data, the national land space information data is real-time data. When planning the national land space according to the national land space dynamic simulation plan, it can meet the national land space conditions of the area at that time, and there will be no mismatch between the plan and the actual area, thereby achieving the purpose of quickly planning and implementing the national land space. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0071] Figure 1 This is a flow chart of a dynamic simulation method for land space planning integrating GIS and cloud computing provided in Example 1 of the present application;

[0072] Figure 2 This is a schematic diagram of a dynamic simulation system for land space planning that integrates GIS and cloud computing, as provided in Example 2 of the present application. DETAILED DESCRIPTION

[0073] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0074] Embodiment 1

[0075] like Figure 1 As shown, the first embodiment of the present application provides a dynamic simulation method for land space planning integrating GIS and cloud computing, and the method includes the following steps:

[0076] Step S1, the cloud platform collects land and space information data through the GIS system, establishes a land and space information database and pre-processes the database data information.

[0077] Furthermore, the cloud platform collects land and space information data through the GIS system, establishes a land and space information database, and pre-processes the database data in the following sub-steps:

[0078] Step S11: The cloud platform collects land space information data using virtualization technology through the GIS system.

[0079] Specifically, national land space information data includes basic geographic information, population distribution information, land use information, ecological environment information, natural resource information, etc.

[0080] Step S12: The cloud platform stores the collected land and space information data in the database.

[0081] Step S13: The cloud platform pre-processes the land and space information data through data cleaning, data integration, data simplification and data transformation to obtain pre-processed land and space information data.

[0082] Step S2: The cloud platform performs spatial analysis on the land and space information data to obtain the land and space analysis results.

[0083] Specifically, the analysis results include population distribution analysis data, land use analysis data, ecological environment analysis data, natural resources analysis data, etc.

[0084] Furthermore, the cloud platform performs spatial analysis on the land and space information data, and the sub-steps for obtaining the land and space analysis results are as follows:

[0085] Step S21: The cloud platform performs spatial analysis on the population distribution information data to obtain population distribution analysis data.

[0086] Specifically, the population distribution information data is analyzed to obtain data such as population density, proportion, and percentage to obtain population distribution analysis data. The density of the population distribution in the population distribution analysis data is described by a population density value.

[0087] Furthermore, the expression of population density value is as follows:

[0088]

[0089] Among them, RM is the population density value, ZR is the regional population, TR is the total population, It represents the population ratio of the nth region, where n represents the number of regions, and the value range of n is 1 to n. The population density value RM ranges from (0, 1). The closer it is to 1, the more concentrated the population distribution is, and the closer it is to 0, the more dispersed the population distribution is.

[0090] Step S22: The cloud platform performs spatial analysis on the land use information data to obtain land use analysis data.

[0091] Specifically, land use analysis data reflects the use of land according to the land use rate, and is used to analyze the current status and changes of land use. Among them, land use rate includes cultivated land utilization rate, forest land utilization rate, water surface utilization rate, construction land utilization rate, and grassland carrying capacity. The grassland carrying capacity is obtained through remote sensing monitoring technology.

[0092] Furthermore, the expression of cultivated land utilization rate is as follows:

[0093]

[0094] Among them, GLSJ is the utilization rate of cultivated land, GTX is the national land space information data, SY is the cultivated land area that has been used, GTX(SY) means traversing the cultivated land area that has been used in the national land space information data, QB is the total cultivated land area, and GTX(QB) means traversing the total cultivated land area in the national land space information data.

[0095] Specifically, the above expressions are also applicable to the forest land utilization rate, water surface utilization rate and construction land utilization rate. For example: to calculate the forest land utilization rate, GLSJ is the forest land utilization rate, SY is the forest land area that has been utilized, GTX(SY) means traversing the forest land area that has been utilized in the national land space information data, QB is the total forest land area, and GTX(QB) means traversing the total forest land area in the national land space information data.

[0096] Step S23: The cloud platform performs spatial analysis on the ecological environment information data to obtain ecological environment analysis data.

[0097] Specifically, the ecological environment analysis data analyzes the ecological function according to the ecological environment quality index to ensure the rationality and sustainability of the planning. Among them, the ecological environment quality index is calculated by weighting the biological richness index, vegetation cover index, water network density index, land degradation index and environmental quality index. The biological richness index reflects the richness of the number of biological species; the vegetation cover index considers the area proportion of five types of forest land, grassland, farmland, construction land and unused land; the water network density index considers the total length of rivers, water area and the proportion of water resources in the regional area; the land degradation index assesses the degree of land degradation; and the environmental quality index reflects the situation of environmental pollution and ecological damage.

[0098] Furthermore, the expression of ecological environment quality index is as follows:

[0099] EI=0.25×SW+0.2×ZB+0.2×WM+0.2×TT+0.15×HJ

[0100] Among them, EI is the ecological environment quality index, SW is the biological richness index, ZB is the vegetation cover index, WM is the water network density index, TT is the land degradation index, and HJ is the environmental quality index. The biological richness index SW accounts for 25%, the vegetation cover index ZB accounts for 20%, the water network density index WM accounts for 20%, the land degradation index TT accounts for 20%, and the environmental quality index HJ accounts for 15%.

[0101] Step S24: The cloud platform performs spatial analysis on the natural resource information data to obtain natural resource analysis data.

[0102] Specifically, natural resource analysis data reflects the distribution, quantity and use of natural resources based on basic geographic information data and natural resource monitoring data. Geographic information data includes natural geographical feature data such as topography, landforms, and hydrology. Based on these data, a three-dimensional digital space is constructed to analyze the distribution of natural resources; natural resource monitoring data is monitoring data on natural resources such as minerals, water, wetlands, sea areas and islands, which evaluates the quantity and use of natural resources and obtains resource analysis data.

[0103] Step S25: The cloud platform stores the land and space analysis result information data in the database to obtain the land and space analysis result information database.

[0104] Step S3: The cloud platform constructs a dynamic simulation model of national land space planning according to national land space planning requirements.

[0105] Furthermore, the cloud platform constructs the following sub-steps of the dynamic simulation model of national land space planning according to the national land space planning requirements:

[0106] Step S31: The cloud platform obtains national land space planning indicators according to national land space planning requirements.

[0107] Specifically, national land space planning indicators include population distribution planning indicators, land use planning indicators, ecological environment protection planning indicators and natural resources planning indicators.

[0108] Step S32: The cloud platform optimizes the population distribution analysis data in the analysis results according to the national land space population distribution planning indicators to obtain simulated population distribution data.

[0109] Specifically, the national land space population distribution planning indicators are determined based on the regional population carrying capacity in the national land space planning requirements.

[0110] Furthermore, the expression of regional population carrying capacity is as follows:

[0111]

[0112] Among them, RKC is the regional population carrying capacity, JZ is the building area in the region, RM is the building area required by one person, min(RM) is the minimum building area required by one person, max(RM) is the maximum building area required by one person, SC is the ecological carrying capacity, RC is the ecological carrying capacity actually used by one person, min(RC) is the minimum ecological carrying capacity actually used by one person, max(RC) is the maximum ecological carrying capacity actually used by one person, TZ is the amount of land resources, RZ is the amount of land resources required by one person, min(RZ) is the minimum amount of land resources required by one person, and max(RZ) is the maximum amount of land resources required by one person.

[0113] Specifically, the predicted population density range is determined according to the regional population carrying capacity. If the population density value in the population distribution analysis data is within the predicted population density range, the original national land space population distribution data will be used. If it does not meet the predicted population density range, the population distribution data will be optimized according to the population distribution planning indicators to obtain simulated population distribution data.

[0114] Step S33: The cloud platform optimizes the land use analysis data in the analysis results according to the national land use planning indicators to obtain simulated land use data.

[0115] Specifically, the national land use planning indicators are determined based on the proportion of various land uses and the livestock carrying capacity of grasslands in the national land space planning requirements.

[0116] Among them, the proportion range of cultivated land, forest land, water surface, grassland and construction land to be used is obtained according to the national land space land use planning indicators and compared with the land use analysis data. If the land use analysis data is within the proportion range, the original national land space land use information data will be used; if it is not within the range, the simulated use area of ​​various lands will be calculated.

[0117] Furthermore, the expressions for the simulated use areas of various lands are as follows:

[0118] SYL=MJ×GT(YB)×GT(SQ)

[0119] Among them, SYL is the simulated usage area of ​​cultivated land, forest land, water surface, grassland and construction land, MJ is the national land area, GT is the national land planning indicator, YB is the required area ratio of cultivated land, forest land, water surface, grassland and construction land, GT(YB) means the required area ratio of cultivated land, forest land, water surface, grassland and construction land within the national land planning indicator, SQ is the required area ratio of cultivated land, forest land, water surface, grassland and construction land, GT(SQ) means the required area ratio of cultivated land, forest land, water surface, grassland and construction land within the national land planning indicator.

[0120] Among them, the grassland carrying capacity is calculated to obtain the minimum and maximum grassland carrying capacity, and the range of values ​​of the grassland carrying capacity is obtained. The grassland carrying capacity and grassland carrying capacity are compared. If the grassland carrying capacity is within the grassland carrying capacity range, the grassland carrying capacity data is used; if it is not within the range, the grassland carrying capacity is used.

[0121] Furthermore, the minimum livestock carrying capacity of grassland is expressed as follows:

[0122]

[0123] Among them, ZMX is the minimum carrying capacity of grassland, min(CL) is the minimum grass yield per hectare of grassland, min(LY) is the minimum utilization rate of grassland per hectare, min(SL) is the minimum daily grass consumption of livestock, and min(TS) is the minimum number of grazing days.

[0124]

[0125] Among them, ZMX is the maximum carrying capacity of grassland, max(CL) is the maximum grass production per hectare of grassland, max(LY) is the maximum utilization rate of grassland per hectare, max(SL) is the maximum daily grass consumption of livestock, and max(TS) is the maximum number of grazing days.

[0126] Specifically, the simulated land use data consist of various land use areas and grassland carrying capacity.

[0127] Step S34: The cloud platform optimizes the ecological environment analysis data in the analysis results according to the national land space ecological environment planning indicators to obtain simulated ecological environment data.

[0128] Specifically, the national land space ecological environment planning indicators are determined based on the biological richness index, vegetation cover index, water network density index, land degradation index and environmental quality index in the national land space planning requirements. The simulated ecological environment quality index range is calculated based on the planning indicators, and the ecological environment quality index in the ecological environment analysis data is compared with the simulated ecological environment quality index. If it is within the simulated ecological environment quality index range, the original national land space planning ecological environment data is used. If it is not within the range, the simulated ecological environment data is obtained according to the national land space planning indicators.

[0129] Step S35: The cloud platform optimizes the natural resource analysis data in the analysis results according to the national land space natural resource planning indicators to obtain simulated natural resource data.

[0130] Specifically, the national land space natural resource planning indicators are determined based on the natural resource requirements in the national land space planning. The natural resource requirements are obtained through remote sensing monitoring technology, and the natural resource requirements are compared with the existing data of natural resources such as minerals, water, wetlands, sea areas and islands in the natural resource analysis data. If the existing data of natural resources is greater than the natural resource requirements, the original national land space natural resource data is used. If the existing data of natural resources is less than the natural resource requirements, the simulated natural resource data is obtained according to the national land space planning indicators.

[0131] Step S36: The cloud platform generates a national land space planning simulation plan based on simulated population distribution data, simulated land use data, simulated ecological environment data, simulated natural resource data, and basic geographic information data.

[0132] Specifically, by simulating population distribution data, simulation plans such as transportation planning, housing planning, and commercial facilities planning are generated; by simulating land use data, simulation plans such as cultivated land use planning, forest land use planning, and grassland use planning are generated; by simulating ecological environment data, simulation plans such as ecological environment protection planning, ecological rational utilization planning, and ecological sustainable development planning are generated; by simulating natural resource data, simulation plans such as natural resource use planning and natural resource exploitation planning are generated.

[0133] Step S4: The cloud platform inputs the data information of the national land space analysis results into the dynamic simulation model of the national land space planning to obtain a national land space planning simulation plan.

[0134] Step S5: The cloud platform inputs the national land space planning simulation plan into the GIS system for analysis to obtain a dynamic simulation distribution map of the national land space.

[0135] Specifically, various information data are integrated, stored, updated, retrieved and scientifically analyzed through cloud computing technology to obtain a dynamic simulation distribution map of the national land space.

[0136] Furthermore, the cloud platform inputs the national land space planning simulation plan into the GIS system for analysis, and the sub-steps of obtaining the dynamic simulation distribution map of the national land space are as follows:

[0137] Step S51: The cloud platform imports the data of the national land space planning simulation plan into the GIS system.

[0138] Specifically, it includes simulated population distribution data, simulated land use data, simulated ecological environment data and simulated natural resource data, etc. Based on the basic geographic information data, the regional administrative boundaries, regional location units and other differences are extracted to determine the regional planning scope and surrounding elements.

[0139] Step S52: The cloud platform performs spatial analysis based on the national land space planning simulation plan to obtain the analysis results of the national land space planning simulation plan.

[0140] Specifically, the national land space planning simulation plan is spatially expressed and analyzed to identify the type, scope and intensity of changes in data such as population distribution, land use, ecological environment and natural environment. Combined with spatial statistics and model simulation methods, future trends of change are predicted, and key planning areas such as ecologically sensitive areas, nature reserves and basic farmland are marked to ensure that planning activities will not cause irreversible impacts on these areas.

[0141] Step S53: The cloud platform generates a dynamic simulation distribution map of the national land space based on the analysis results of the national land space planning simulation plan.

[0142] Specifically, the dynamic simulation distribution map of national land space includes the overall layout of the map, such as: map name, location diagram, compass, legend, scale, compiling unit and other annotation information.

[0143] Step S54: The cloud platform updates the dynamic simulation distribution map of the national land space according to the continuously acquired national land space planning simulation plan.

[0144] Specifically, the data of national land space is dynamic data that is continuously acquired through cloud computing and is updated in real time, so it is necessary to transmit the real-time data of step S2 to step S4 to generate an updated national land space planning simulation plan, and then transmit the updated national land space planning simulation plan to step S5, re-perform spatial analysis on the national land space planning simulation plan, update the national land space dynamic simulation distribution map, and ensure the timeliness of the national land space dynamic simulation distribution map.

[0145] Step S6: The cloud platform forms a national land space planning evaluation map based on the national land space planning requirements and the national land space dynamic simulation distribution map.

[0146] Specifically, the dynamic simulation plan of national land space will be evaluated according to the national land space planning evaluation map, and the rationality and feasibility of the planning plan will be explained to ensure the scientificity and feasibility of the planning plan.

[0147] Furthermore, the cloud platform forms the following sub-steps of the national land space planning evaluation map based on the national land space distribution map and the national land space planning preset indicator data:

[0148] Step S61: The cloud platform sets an evaluation index system based on the dynamic simulation distribution map of national land space and national land space planning requirements.

[0149] Specifically, the evaluation index system includes ecological environment quality indicators, land use efficiency indicators and economic development level indicators.

[0150] Step S62: The cloud platform summarizes and assigns values ​​to the evaluation indicators through principal component analysis and cluster analysis to determine the weight of each indicator.

[0151] Specifically, different indicators are analyzed through principal component analysis and cluster analysis to determine their importance in the indicator system, and the factor analysis method is used to determine the weight of each indicator according to different importance.

[0152] Step S63: The cloud platform uses the spatial overlay method to superimpose data of different indicators to form a national land space planning evaluation map.

[0153] Specifically, GIS is used for spatial analysis to ensure that the data of various indicators can be accurately superimposed in space to reflect the results of national land space evaluation. The national land space planning requirements and the national land space planning evaluation map are compared to check whether the national land space planning simulation plan meets the national land planning requirements. If it does not meet the requirements, step S1 is executed to re-collect national land space information data.

[0154] Embodiment 2

[0155] like Figure 2 As shown, the second embodiment of the present application provides a dynamic simulation system for land space planning integrating GIS and cloud computing, including:

[0156] The information collection and processing module 21 collects land and space information data through the GIS system, establishes a land and space information database and pre-processes the database data information.

[0157] Furthermore, the information collection and processing module 21 includes the following submodules:

[0158] The information collection submodule collects land space information data using virtualization technology through the GIS system.

[0159] Specifically, national land space information data includes basic geographic information, population distribution information, land use information, ecological environment information, natural resource information, etc.

[0160] The information storage submodule stores the collected land and space information data into the database.

[0161] The information processing submodule pre-processes the national land and space information data through data cleaning, data integration, data simplification and data transformation to obtain pre-processed national land and space information data.

[0162] The information analysis module 22 performs spatial analysis on the national land space information data to obtain the national land space analysis results.

[0163] Specifically, the analysis results include population distribution analysis data, land use analysis data, ecological environment analysis data, natural resources analysis data, etc.

[0164] Furthermore, the information analysis module 22 includes the following submodules:

[0165] The population distribution analysis submodule performs spatial analysis on population distribution information data to obtain population distribution analysis data.

[0166] Specifically, the population distribution information data is analyzed to obtain data such as population density, proportion, and percentage to obtain population distribution analysis data. The density of the population distribution in the population distribution analysis data is described by the population density value.

[0167] Furthermore, the expression of population density value is as follows:

[0168]

[0169] Among them, RM is the population density value, ZR is the regional population, TR is the total population, It represents the population ratio of the nth region, where n represents the number of regions, and the value range of n is 1 to n. The population density value RM ranges from (0, 1). The closer it is to 1, the more concentrated the population distribution is, and the closer it is to 0, the more dispersed the population distribution is.

[0170] The land use analysis submodule performs spatial analysis on land use information data to obtain land use analysis data.

[0171] Specifically, land use analysis data reflects the use of land according to the land use rate, and is used to analyze the current status and changes of land use. Among them, land use rate includes cultivated land utilization rate, forest land utilization rate, water surface utilization rate, construction land utilization rate, and grassland carrying capacity. The grassland carrying capacity is obtained through remote sensing monitoring technology.

[0172] Furthermore, the expression of cultivated land utilization rate is as follows:

[0173]

[0174] Among them, GLSJ is the utilization rate of cultivated land, GTX is the national land space information data, SY is the cultivated land area that has been used, GTX(SY) means traversing the cultivated land area that has been used in the national land space information data, QB is the total cultivated land area, and GTX(QB) means traversing the total cultivated land area in the national land space information data.

[0175] Specifically, the above expressions are also applicable to the forest land utilization rate, water surface utilization rate and construction land utilization rate. For example: to calculate the forest land utilization rate, GLSJ is the forest land utilization rate, SY is the forest land area that has been utilized, GTX(SY) means traversing the forest land area that has been utilized in the national land space information data, QB is the total forest land area, and GTX(QB) means traversing the total forest land area in the national land space information data.

[0176] The ecological environment analysis submodule performs spatial analysis on ecological environment information data to obtain ecological environment analysis data.

[0177] Specifically, the ecological environment analysis data analyzes the ecological function according to the ecological environment quality index to ensure the rationality and sustainability of the planning. Among them, the ecological environment quality index is calculated by weighting the biological richness index, vegetation cover index, water network density index, land degradation index and environmental quality index. The biological richness index reflects the richness of the number of biological species; the vegetation cover index considers the area proportion of five types of forest land, grassland, farmland, construction land and unused land; the water network density index considers the total length of rivers, water area and the proportion of water resources in the regional area; the land degradation index assesses the degree of land degradation; and the environmental quality index reflects the situation of environmental pollution and ecological damage.

[0178] Furthermore, the expression of ecological environment quality index is as follows:

[0179] EI=0.25×SW+0.2×ZB+0.2×WM+0.2×TT+0.15×HJ

[0180] Among them, EI is the ecological environment quality index, SW is the biological richness index, ZB is the vegetation cover index, WM is the water network density index, TT is the land degradation index, and HJ is the environmental quality index. The biological richness index SW accounts for 25%, the vegetation cover index ZB accounts for 20%, the water network density index WM accounts for 20%, the land degradation index TT accounts for 20%, and the environmental quality index HJ accounts for 15%.

[0181] The natural resource analysis submodule performs spatial analysis on natural resource information data to obtain natural resource analysis data.

[0182] Specifically, natural resource analysis data reflects the distribution, quantity and use of natural resources based on basic geographic information data and natural resource monitoring data. Geographic information data includes natural geographical feature data such as topography, landforms, and hydrology. Based on these data, a three-dimensional digital space is constructed to analyze the distribution of natural resources; natural resource monitoring data is monitoring data on natural resources such as minerals, water, wetlands, sea areas and islands, which evaluates the quantity and use of natural resources and obtains resource analysis data.

[0183] The analysis result storage submodule stores the land and space analysis result information data into the database to obtain the land and space analysis result information database.

[0184] The model building module 23 builds a dynamic simulation model of national land space planning according to the requirements of national land space planning.

[0185] Furthermore, the model building module 23 includes the following submodules:

[0186] The planning indicator acquisition submodule obtains the national land space planning indicators according to the national land space planning requirements.

[0187] Specifically, national land space planning indicators include population distribution planning indicators, land use planning indicators, ecological environment protection planning indicators and natural resources planning indicators.

[0188] The population distribution optimization submodule optimizes the population distribution analysis data in the analysis results according to the national land space population distribution planning indicators to obtain simulated population distribution data.

[0189] Specifically, the national land space population distribution planning indicators are determined based on the regional population carrying capacity in the national land space planning requirements.

[0190] Furthermore, the expression of regional population carrying capacity is as follows:

[0191]

[0192] Among them, RKC is the regional population carrying capacity, JZ is the building area in the region, RM is the building area required by one person, min(RM) is the minimum building area required by one person, max(RM) is the maximum building area required by one person, SC is the ecological carrying capacity, RC is the ecological carrying capacity actually used by one person, min(RC) is the minimum ecological carrying capacity actually used by one person, max(RC) is the maximum ecological carrying capacity actually used by one person, TZ is the amount of land resources, RZ is the amount of land resources required by one person, min(RZ) is the minimum amount of land resources required by one person, and max(RZ) is the maximum amount of land resources required by one person.

[0193] Specifically, the predicted population density range is determined according to the regional population carrying capacity. If the population density value in the population distribution analysis data is within the predicted population density range, the original national land space population distribution data will be used. If it does not meet the predicted population density range, the population distribution data will be optimized according to the population distribution planning indicators to obtain simulated population distribution data.

[0194] The land use optimization submodule optimizes the land use analysis data in the analysis results according to the national land use planning indicators to obtain simulated land use data.

[0195] Specifically, the national land use planning indicators are determined based on the proportion of various land uses and the livestock carrying capacity of grasslands in the national land space planning requirements.

[0196] Among them, the proportion range of cultivated land, forest land, water surface, grassland and construction land to be used is obtained according to the national land space land use planning indicators and compared with the land use analysis data. If the land use analysis data is within the proportion range, the original national land space land use information data will be used; if it is not within the range, the simulated use area of ​​various lands will be calculated.

[0197] Furthermore, the expressions for the simulated use areas of various lands are as follows:

[0198] SYL=MJ×GT(YB)×GT(SQ)

[0199] Among them, SYL is the simulated usage area of ​​cultivated land, forest land, water surface, grassland and construction land, MJ is the national land area, GT is the national land planning indicator, YB is the required area ratio of cultivated land, forest land, water surface, grassland and construction land, GT(YB) means the required area ratio of cultivated land, forest land, water surface, grassland and construction land within the national land planning indicator, SQ is the required area ratio of cultivated land, forest land, water surface, grassland and construction land, GT(SQ) means the required area ratio of cultivated land, forest land, water surface, grassland and construction land within the national land planning indicator.

[0200] Among them, the grassland carrying capacity is calculated to obtain the minimum and maximum grassland carrying capacity, and the range of values ​​of the grassland carrying capacity is obtained. The grassland carrying capacity and grassland carrying capacity are compared. If the grassland carrying capacity is within the grassland carrying capacity range, the grassland carrying capacity data is used; if it is not within the range, the grassland carrying capacity is used.

[0201] Furthermore, the minimum livestock carrying capacity of grassland is expressed as follows:

[0202]

[0203] Among them, ZMX is the minimum carrying capacity of grassland, min(CL) is the minimum grass yield per hectare of grassland, min(LY) is the minimum utilization rate of grassland per hectare, min(SL) is the minimum daily grass consumption of livestock, and min(TS) is the minimum number of grazing days.

[0204]

[0205] Among them, ZMX is the maximum carrying capacity of grassland, max(CL) is the maximum grass production per hectare of grassland, max(LY) is the maximum utilization rate of grassland per hectare, max(SL) is the maximum daily grass consumption of livestock, and max(TS) is the maximum number of grazing days.

[0206] Specifically, the simulated land use data consist of various land use areas and grassland carrying capacity.

[0207] The ecological environment optimization submodule optimizes the ecological environment analysis data in the analysis results according to the national land space ecological environment planning indicators to obtain simulated ecological environment data.

[0208] Specifically, the national land space ecological environment planning indicators are determined based on the biological richness index, vegetation cover index, water network density index, land degradation index and environmental quality index in the national land space planning requirements. The simulated ecological environment quality index range is calculated based on the planning indicators, and the ecological environment quality index in the ecological environment analysis data is compared with the simulated ecological environment quality index. If it is within the simulated ecological environment quality index range, the original national land space planning ecological environment data is used. If it is not within the range, the simulated ecological environment data is obtained according to the national land space planning indicators.

[0209] The natural resource optimization submodule optimizes the natural resource analysis data in the analysis results according to the national land space natural resource planning indicators to obtain simulated natural resource data.

[0210] Specifically, the national land space natural resource planning indicators are determined based on the natural resource requirements in the national land space planning. The natural resource requirements are obtained through remote sensing monitoring technology, and the natural resource requirements are compared with the existing data of natural resources such as minerals, water, wetlands, sea areas and islands in the natural resource analysis data. If the existing data of natural resources is greater than the natural resource requirements, the original national land space natural resource data is used. If the existing data of natural resources is less than the natural resource requirements, the simulated natural resource data is obtained according to the national land space planning indicators.

[0211] The scheme generation submodule generates a national land space planning simulation scheme based on simulated population distribution data, simulated land use data, simulated ecological environment data, simulated natural resources data, and basic geographic information data.

[0212] Specifically, by simulating population distribution data, simulation plans such as transportation planning, housing planning, and commercial facilities planning are generated; by simulating land use data, simulation plans such as cultivated land use planning, forest land use planning, and grassland use planning are generated; by simulating ecological environment data, simulation plans such as ecological environment protection planning, ecological rational utilization planning, and ecological sustainable development planning are generated; by simulating natural resource data, simulation plans such as natural resource use planning and natural resource exploitation planning are generated.

[0213] The model execution module 24 inputs the data information of the national land space analysis results into the national land space planning dynamic simulation model to obtain the national land space planning simulation plan.

[0214] The distribution map generation module 25 inputs the national land space planning simulation plan into the GIS system for analysis to obtain a dynamic simulation distribution map of the national land space.

[0215] Specifically, various information data are integrated, stored, updated, retrieved and scientifically analyzed through cloud computing to obtain a dynamic simulation distribution map of the national land space.

[0216] Furthermore, the distribution map generation module 25 includes the following submodules:

[0217] The data import submodule imports the data of the national land space planning simulation plan into the GIS system.

[0218] Specifically, it includes simulated population distribution data, simulated land use data, simulated ecological environment data and simulated natural resource data, etc. Based on the basic geographic information data, the regional administrative boundaries, regional location units and other differences are extracted to determine the regional planning scope and surrounding elements.

[0219] The scheme analysis submodule conducts spatial analysis based on the national land space planning simulation scheme and obtains the analysis results of the national land space planning simulation scheme.

[0220] Specifically, the national land space planning simulation plan is spatially expressed and analyzed to identify the type, scope and intensity of changes in data such as population distribution, land use, ecological environment and natural environment. Combined with spatial statistics and model simulation methods, future trends of change are predicted, and key planning areas such as ecologically sensitive areas, nature reserves and basic farmland are marked to ensure that planning activities will not cause irreversible impacts on these areas.

[0221] The simulation distribution map generation submodule generates a dynamic simulation distribution map of the national land space based on the analysis results of the national land space planning simulation plan.

[0222] Specifically, the dynamic simulation distribution map of national land space includes the overall layout of the map, such as: map name, location diagram, compass, legend, scale, compiling unit and other annotation information.

[0223] The data update submodule updates the dynamic simulation distribution map of national land space according to the continuously acquired national land space planning simulation plan.

[0224] Specifically, the data of the national land space is dynamically acquired through cloud computing and is updated in real time. Therefore, the real-time data transmission model execution module 24 of the information analysis module 22 is required to generate an updated national land space planning simulation plan, and then transmit the updated national land space planning simulation plan to the distribution map generation module 25, re-analyze the national land space planning simulation plan spatially, update the national land space dynamic simulation distribution map, and ensure the timeliness of the national land space dynamic simulation distribution map.

[0225] The evaluation map generation module 26 forms a national land space planning evaluation map according to the national land space planning requirements and the national land space dynamic simulation distribution map.

[0226] Specifically, the dynamic simulation plan of national land space will be evaluated according to the national land space planning evaluation map, and the rationality and feasibility of the planning plan will be explained to ensure the scientificity and feasibility of the planning plan.

[0227] Furthermore, the evaluation graph generation module 26 includes the following submodules:

[0228] The indicator system setting submodule sets the evaluation indicator system based on the dynamic simulation distribution map of the national land space and the requirements of the national land space planning.

[0229] Specifically, the evaluation index system includes ecological environment quality indicators, land use efficiency indicators and economic development level indicators.

[0230] The indicator weight determination submodule summarizes and assigns values ​​to the evaluation indicators through principal component analysis and cluster analysis to determine the weight of each indicator.

[0231] Specifically, different indicators are analyzed through principal component analysis and cluster analysis to determine their importance in the indicator system, and the factor analysis method is used to determine the weight of each indicator according to different importance.

[0232] The evaluation map generation sub-module uses the spatial overlay method to superimpose data of different indicators to form a national land space planning evaluation map.

[0233] Specifically, GIS is used for spatial analysis to ensure that the data of various indicators can be accurately superimposed in space to reflect the results of national land space evaluation. The national land space planning requirements and the national land space planning evaluation map are compared to check whether the national land space planning simulation plan meets the national land planning requirements. If it does not meet the requirements, the information collection and processing module 21 is executed to re-collect national land space information data.

[0234] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solution of the present invention should be included in the scope of protection of the present invention.

Claims

1. A dynamic simulation method for land space planning integrating GIS and cloud computing, characterized in that: include: Step S1, the cloud platform collects land and space information data through the GIS system, establishes a land and space information database and pre-processes the database data information; Step S2: The cloud platform performs spatial analysis on the land and space information data to obtain the land and space analysis results; Step S3: The cloud platform constructs a dynamic simulation model of national land space planning according to national land space planning requirements; Step S4: The cloud platform inputs the data information of the national land space analysis results into the national land space planning dynamic simulation model to obtain a national land space planning simulation plan; Step S5: The cloud platform inputs the national land space planning simulation plan into the GIS system for analysis to obtain a dynamic simulation distribution map of the national land space; Step S6: The cloud platform forms a national land space planning evaluation map based on the national land space planning requirements and the national land space dynamic simulation distribution map.

2. The method for dynamic simulation of land space planning integrating GIS and cloud computing as claimed in claim 1, characterized in that: The cloud platform performs spatial analysis on the national land space information data. The sub-steps for obtaining the national land space analysis results are as follows: Step S21: The cloud platform performs spatial analysis on the population distribution information data to obtain population distribution analysis data; Step S22: The cloud platform performs spatial analysis on the land use information data to obtain land use analysis data; Step S23: The cloud platform performs spatial analysis on the ecological environment information data to obtain ecological environment analysis data; Step S24: the cloud platform performs spatial analysis on the natural resource information data to obtain natural resource analysis data; Step S25: The cloud platform stores the land and space analysis result information data in the database to obtain the land and space analysis result information database.

3. The method for dynamic simulation of land space planning integrating GIS and cloud computing as claimed in claim 1, characterized in that: The sub-steps of the cloud platform to build a dynamic simulation model of national land space planning according to national land space planning requirements are as follows: Step S31, the cloud platform obtains national land space planning indicators according to national land space planning requirements; Step S32: The cloud platform optimizes the population distribution analysis data in the analysis results according to the national land space population distribution planning indicators to obtain simulated population distribution data; Step S33: the cloud platform optimizes the land use analysis data in the analysis results according to the national land use planning indicators to obtain simulated land use data; Step S34: the cloud platform optimizes the ecological environment analysis data in the analysis results according to the national land space ecological environment planning indicators to obtain simulated ecological environment data; Step S35: The cloud platform optimizes the natural resource analysis data in the analysis results according to the national land space natural resource planning indicators to obtain simulated natural resource data; Step S36: The cloud platform generates a national land space planning simulation plan based on simulated population distribution data, simulated land use data, simulated ecological environment data, simulated natural resource data, and basic geographic information data.

4. The method for dynamic simulation of land space planning integrating GIS and cloud computing as claimed in claim 1, characterized in that: The cloud platform inputs the national land space planning simulation plan into the GIS system for analysis. The sub-steps for obtaining the dynamic simulation distribution map of national land space are as follows: Step S51, the cloud platform imports the data of the national land space planning simulation program into the GIS system; Step S52: the cloud platform performs spatial analysis according to the national land space planning simulation scheme to obtain the analysis results of the national land space planning simulation scheme; Step S53: The cloud platform generates a dynamic simulation distribution map of the national land space according to the analysis results of the national land space planning simulation scheme; Step S54: The cloud platform updates the dynamic simulation distribution map of the national land space according to the continuously acquired national land space planning simulation plan.

5. The method for dynamic simulation of land space planning integrating GIS and cloud computing as claimed in claim 1, characterized in that: The cloud platform forms the following sub-steps for the evaluation map of national land space planning based on the national land space distribution map and the preset indicator data of national land space planning: Step S61: The cloud platform sets an evaluation index system according to the dynamic simulation distribution map of national land space and the national land space planning requirements; Step S62: The cloud platform summarizes and assigns values ​​to the evaluation indicators through principal component analysis and cluster analysis to determine the weight of each indicator; Step S63: The cloud platform uses the spatial overlay method to superimpose data of different indicators to form a national land space planning evaluation map.

6. A dynamic simulation system for national land space planning integrating GIS and cloud computing, characterized in that: include: The information collection and processing module collects land and space information data through the GIS system, establishes a land and space information database, and pre-processes the database data; The information analysis module performs spatial analysis on the land and space information data to obtain the land and space analysis results; Model building module, which builds a dynamic simulation model of national land space planning according to national land space planning requirements; The model execution module inputs the data information of the national land space analysis results into the national land space planning dynamic simulation model to obtain the national land space planning simulation plan; The distribution map generation module inputs the national land space planning simulation plan into the GIS system for analysis to obtain the dynamic simulation distribution map of the national land space; The evaluation map generation module forms a national land space planning evaluation map based on the national land space planning requirements and the national land space dynamic simulation distribution map.

7. The GIS and cloud computing integrated national land space planning dynamic simulation system as claimed in claim 6, characterized in that: Information analysis module, including: The population distribution analysis submodule performs spatial analysis on population distribution information data to obtain population distribution analysis data; The land use analysis submodule performs spatial analysis on land use information data to obtain land use analysis data; The ecological environment analysis submodule performs spatial analysis on ecological environment information data to obtain ecological environment analysis data; The natural resource analysis submodule performs spatial analysis on natural resource information data to obtain natural resource analysis data; The analysis result storage submodule stores the land and space analysis result information data into the database to obtain the land and space analysis result information database.

8. The GIS and cloud computing integrated national land space planning dynamic simulation system as claimed in claim 6, characterized in that: Model building modules, including: The planning indicator acquisition submodule obtains the national land space planning indicators according to the national land space planning requirements; The population distribution optimization submodule optimizes the population distribution analysis data in the analysis results according to the national land space population distribution planning indicators to obtain the simulated population distribution data; The land use optimization submodule optimizes the land use analysis data in the analysis results according to the national land use planning indicators to obtain simulated land use data; The ecological environment optimization submodule optimizes the ecological environment analysis data in the analysis results according to the national land space ecological environment planning indicators to obtain simulated ecological environment data; The natural resource optimization submodule optimizes the natural resource analysis data in the analysis results according to the national land space natural resource planning indicators to obtain simulated natural resource data; The scheme generation submodule generates a national land space planning simulation scheme based on simulated population distribution data, simulated land use data, simulated ecological environment data, simulated natural resources data, and basic geographic information data.

9. The GIS and cloud computing integrated national land space planning dynamic simulation system as claimed in claim 6, characterized in that: The distribution map generation module specifically includes: The data import submodule imports the data of the national land space planning simulation program into the GIS system; The scheme analysis submodule performs spatial analysis based on the national land space planning simulation scheme and obtains the analysis results of the national land space planning simulation scheme; The simulation distribution map generation submodule generates a dynamic simulation distribution map of national land space according to the analysis results of the national land space planning simulation scheme; The data update submodule updates the dynamic simulation distribution map of national land space according to the continuously acquired national land space planning simulation plan.

10. The GIS and cloud computing integrated national land space planning dynamic simulation system according to claim 6, characterized in that: Evaluation graph generation module, specifically including: The indicator system setting submodule sets the evaluation indicator system according to the dynamic simulation distribution map of national land space and the requirements of national land space planning; The indicator weight determination submodule summarizes and assigns values ​​to the evaluation indicators through principal component analysis and cluster analysis to determine the weight of each indicator; The evaluation map generation sub-module uses the spatial overlay method to superimpose data of different indicators to form a national land space planning evaluation map.

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