Geographic information system (GIS)-based territorial space planning method and system

Abstract

The invention discloses a land space planning method and system based on a GIS, belongs to the technical field of data processing, and can improve the calculation efficiency of resource environment bearing capacity. Comprising the steps of obtaining a land space model of a target area established through a GIS; performing identification processing on the land space model to obtain a plurality of blank area models in the land space model; obtaining a screening proportion threshold value; calculating the proportion of each blank area model to the land space model, comparing the proportion with a screening proportion threshold value, and marking the blank area models of which the proportions are greater than the screening proportion threshold value; performing grid unit segmentation on each marked blank area model to obtain a plurality of different unit space models; performing similarity matching on each unit space model and a standard unit model in a preset model database to obtain a bearing capacity value corresponding to the unit space model; carrying out summation calculation according to the bearing capacity values to obtain a total bearing capacity value; and generating a territorial space planning report according to the total bearing capacity value.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a land space planning method and system based on GIS. Background Art

[0002] National land space planning is the process by which the national and local governments, within a certain area, comprehensively consider various factors such as nature, economy, and society, and scientifically plan and rationally utilize land, resources, and the environment.

[0003] Traditional land space planning methods mainly rely on the experience and manual calculations of planners, which not only consumes a lot of time and human resources, but also makes it difficult to ensure the accuracy and scientificity of the results. Especially in the calculation of resource and environmental carrying capacity, traditional methods usually use manual estimation, which is inefficient and difficult to quantify, resulting in limited scientificity and enforceability of planning.

[0004] The disclosure of the above background technology content is only used to assist in understanding the concept and technical solution of the present invention. It does not necessarily belong to the prior art of this patent application. In the absence of clear evidence that the above content has been disclosed on the filing date of this patent application, the above background technology should not be used to evaluate the novelty and creativity of the present application. Summary of the invention

[0005] The present application provides a GIS-based national land space planning method and system, which can improve the calculation efficiency of resource and environmental carrying capacity.

[0006] To achieve the above objectives, the present application discloses the following technical solutions:

[0007] In a first aspect, the present application embodiment provides a GIS-based land space planning method, comprising the following steps:

[0008] Obtain a land spatial model of the target area established through GIS;

[0009] Performing blank area recognition processing on the land space model to obtain multiple blank area models in the land space model;

[0010] Get the screening ratio threshold;

[0011] Calculate the ratio of each blank area model to the land space model, compare it with the screening ratio threshold, and mark the blank area models whose ratio is greater than the screening ratio threshold;

[0012] Each marked blank area model is divided into grid units to obtain several different unit space models;

[0013] Perform similarity matching on each unit space model with a standard unit model in a preset model database to obtain a corresponding carrying capacity value;

[0014] The overall bearing capacity value is obtained by summing up the bearing capacity values;

[0015] Generate a national land space planning report based on the overall carrying capacity value.

[0016] In the embodiment of the present application, the model database contains multiple standard unit models and the preset and known resource carrying capacity corresponding to each standard unit model. By gridding the land space model, a large area can be divided into multiple small unit space models, so that the resource carrying capacity of each small unit in the large area can be analyzed separately to improve the precision of the matching, thereby effectively improving the scientificity and executability of the overall planning.

[0017] By matching the similarity of each unit space model with the standard unit model in the preset model database, the carrying capacity value is obtained, and the overall carrying capacity value is obtained by summing up the carrying capacity values, thus realizing the automatic quantitative calculation of the carrying capacity value. In this way, on the one hand, it can effectively avoid the human estimation errors in traditional methods, thereby improving the scientificity and accuracy of the calculation; on the other hand, it can improve the calculation efficiency of resource and environmental carrying capacity, and facilitate the generation of national land space planning reports.

[0018] In addition, by only performing grid unit segmentation on the blank area models whose proportion is greater than the screening ratio threshold to obtain several different unit space models, the blank areas with small areas and no planning significance can be effectively excluded. In this way, on the one hand, the noise and errors caused by the blank areas with small areas and no planning significance can be avoided, ensuring the effectiveness and scientificity of the calculation of resource and environmental carrying capacity; on the other hand, the amount of calculated data can be reduced, further improving the calculation efficiency of resource and environmental carrying capacity; on the other hand, it can avoid wasting time and money on small areas, allowing planners to focus on key areas that have a greater impact on the overall planning, and invest limited resources in areas with more value and potential, ensuring that the focus of planning is more prominent.

[0019] In addition, by gridding only the blank area models whose proportions are greater than the screening ratio threshold to obtain several different unit space models, it is also possible to effectively avoid excluding unit space models that contain both non-target areas (for example, areas containing buildings) and blank areas, thereby further ensuring the effectiveness and scientificity of the resource and environmental carrying capacity calculations.

[0020] In some possible implementations of the first aspect, the blank area model refers to a model corresponding to an area in the land space model where there are no building features or water features;

[0021] The steps of performing blank area recognition processing on the land space model to obtain multiple blank area models in the land space model include:

[0022] Obtaining initial data of the land space model, including topography, landforms, building features and water features in the target area;

[0023] Preprocess the initial data to extract building characteristic data and water area characteristic data;

[0024] Based on the extracted building feature data and water feature data, a feature layer including all buildings and water areas is generated;

[0025] Mask the feature layer to generate a blank area layer, which includes every area in the target area where there are no building features or water features.

[0026] The blank area layer is used as input data and compared with the land space model to identify and mark multiple blank area models in the land space model. Among them, limiting the blank area model to the model corresponding to the area without building features and water features in the land space model can help identify unused or underutilized land, thereby facilitating more efficient allocation and utilization of land resources. By comprehensively extracting terrain, landform, building and water feature data, a comprehensive data foundation can be provided, which is conducive to improving the accuracy of blank area identification.

[0027] In some possible implementations of the first aspect, the step of obtaining a screening ratio threshold includes:

[0028] Obtain the minimum spatial planning area of ​​the target area;

[0029] The ratio of the minimum space planning area to the area of ​​the target area is calculated to obtain the screening ratio threshold. In this way, the screening ratio threshold can be flexibly obtained according to the specific situation of the target area to meet the planning needs of different locations.

[0030] In some possible implementations of the first aspect, the steps of calculating the ratio of each blank area model to the land space model and comparing it with a screening ratio threshold, and marking the blank area model having a ratio greater than the screening ratio threshold include:

[0031] Calculate the projection area of ​​the land space model on the first plane, recorded as the first projection area;

[0032] The ratio of the projected area of ​​each blank area model on the first plane to the first projected area is calculated, and compared with the screening ratio threshold, and the blank area models whose ratio is greater than the screening ratio threshold are marked. In this way, no matter how complex or irregular the shape of the blank area model is, the area can be calculated by projecting it into a unified plane coordinate system, which can effectively eliminate the errors caused by the diversity and complexity of the regional shape, thereby improving the accuracy of the screening results, effectively excluding small areas that have no actual development value, and ensuring that planning resources are concentrated on the most potential areas.

[0033] In some possible implementations of the first aspect, the mark corresponding to each blank area model whose ratio is greater than the screening ratio threshold is unique. In this way, each marked blank area can be tracked and managed through a unique identifier. When a blank area has been planned, it can be directly located and deleted through its unique identifier without having to re-perform complex identification and screening steps.

[0034] In some possible implementations of the first aspect, the step of obtaining the minimum spatial planning area of ​​the target area includes:

[0035] Receive the minimum space planning area of ​​the target area input by the user;

[0036] Verify that the data entered by the user is in the correct format;

[0037] The verified minimum space planning area data is stored in a preset database for retrieval. In this way, on the one hand, it is convenient to adjust the minimum space planning area according to actual needs, making the planning more adaptable.

[0038] In a second aspect, the embodiment of the present application provides a GIS-based national land space planning system, including:

[0039] The first acquisition module is used to acquire a land space model of a target area established through GIS;

[0040] The first recognition module is used to perform blank area recognition processing on the land space model to obtain multiple blank area models in the land space model;

[0041] The second acquisition module is used to obtain a screening ratio threshold;

[0042] The first comparison module is used to calculate the ratio of each blank area model to the land space model, compare it with the screening ratio threshold, and mark the blank area model whose ratio is greater than the screening ratio threshold;

[0043] The first segmentation module is used to perform grid unit segmentation on each marked blank area model to obtain a number of different unit space models;

[0044] A first matching module is used to perform similarity matching between each unit space model and a standard unit model in a preset model database to obtain a corresponding carrying capacity value;

[0045] A first calculation module, used for performing summation calculation according to the bearing capacity values ​​to obtain an overall bearing capacity value;

[0046] The first generation module is used to generate a national land space planning report based on the overall carrying capacity value.

[0047] In some possible implementations of the second aspect, the blank area model refers to a model corresponding to an area in the land space model where there are no building features or water features;

[0048] The first identification module is specifically used to: obtain initial data of the land space model, the initial data including the terrain, landform, building features and water features in the target area; pre-process the initial data to extract building feature data and water feature data therefrom; generate a feature layer containing all buildings and waters based on the extracted building feature data and water feature data; mask the feature layer to generate a blank area layer, the blank area layer including every area in the target area where no building features and water features exist; use the blank area layer as input data, compare it with the land space model, and identify and mark multiple blank area models in the land space model.

[0049] In some possible implementations of the second aspect, the second acquisition module is specifically used to: obtain the minimum spatial planning area of ​​the target area; calculate the ratio of the minimum spatial planning area to the area of ​​the target area to obtain a screening ratio threshold.

[0050] In some possible implementations of the second aspect, the first comparison module is specifically used to: calculate the projection area of ​​the land space model on the first plane, recorded as the first projection area; calculate the ratio of the projection area of ​​each blank area model on the first plane to the first projection area, and compare it with the screening ratio threshold, and mark the blank area models whose ratio is greater than the screening ratio threshold.

[0051] In some possible implementations of the second aspect, the label corresponding to each blank area model whose ratio is greater than the screening ratio threshold is unique.

[0052] In some possible implementations of the second aspect, the second acquisition module is specifically used to: receive the minimum space planning area of ​​the target area input by the user; verify whether the format of the data input by the user is correct; and store the verified minimum space planning area data in a preset database for call.

[0053] In a third aspect, an embodiment of the present application provides an electronic device, comprising one or more processors; a storage device on which one or more programs are stored; when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any technical solution of the first aspect.

[0054] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described in any technical solution of the first aspect is implemented.

[0055] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method described in any technical solution of the first aspect.

[0056] Among them, the technical effects brought about by any design method in the second to fifth aspects can refer to the technical effects brought about by different design methods in the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0058] Figure 1 A schematic diagram of a process flow of a GIS-based land space planning method provided for some embodiments of the present application;

[0059] Figure 2 A schematic diagram of the structure of a GIS-based national land space planning system provided for some embodiments of the present application;

[0060] Figure 3 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present application. DETAILED DESCRIPTION

[0061] Specific embodiments of the present invention will now be mentioned in detail. Although the present invention is described in conjunction with these specific embodiments, it should be appreciated that it is not intended to limit the present invention to these specific embodiments. On the contrary, these embodiments are intended to cover substitutions, changes or equivalent embodiments that may be included in the spirit and scope of the invention defined by the claims. In the following description, a large number of specific details are set forth in order to provide a comprehensive understanding of the present invention. The present invention may be implemented without some or all of these specific details.

[0062] When used in conjunction with "including," "methods comprising," or similar language in this specification and the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0063] Application Overview: National land space planning is the process by which the national and local governments scientifically plan and rationally utilize land, resources, and the environment within a certain area, taking into account a variety of factors such as nature, economy, and society.

[0064] Traditional land space planning methods mainly rely on the experience and manual calculations of planners, which not only consumes a lot of time and human resources, but also makes it difficult to ensure the accuracy and scientificity of the results. Especially in the calculation of resource and environmental carrying capacity, traditional methods usually use manual estimation, which is inefficient and difficult to quantify, resulting in limited scientificity and enforceability of planning.

[0065] In response to the above technical problems, the overall idea of ​​the technical solution provided by this application is as follows: a GIS-based national land space planning method is provided, comprising the following steps: obtaining a land space model of a target area established through GIS; performing blank area identification processing on the land space model to obtain multiple blank area models in the land space model; obtaining a screening ratio threshold; calculating the ratio of each blank area model to the land space model, and comparing it with the screening ratio threshold, and marking the blank area models whose ratio is greater than the screening ratio threshold; grid-unitizing each marked blank area model to obtain a number of different unit space models; performing similarity matching on each unit space model with a standard unit model in a preset model database to obtain a corresponding carrying capacity value; summing up the carrying capacity values ​​to obtain an overall carrying capacity value; and generating a national land space planning report based on the overall carrying capacity value.

[0066] The model database contains multiple standard unit models and the preset and known resource carrying capacity corresponding to each standard unit model. By gridding the land space model, a large area can be divided into multiple small unit space models, so that the resource carrying capacity of each small unit in the large area can be analyzed separately to improve the precision of the matching, thereby effectively improving the scientificity and feasibility of the overall planning.

[0067] By matching the similarity of each unit space model with the standard unit model in the preset model database, the carrying capacity value is obtained, and the overall carrying capacity value is obtained by summing up the carrying capacity values, thus realizing the automatic quantitative calculation of the carrying capacity value. In this way, on the one hand, it can effectively avoid the human estimation errors in traditional methods, thereby improving the scientificity and accuracy of the calculation; on the other hand, it can improve the calculation efficiency of resource and environmental carrying capacity, and facilitate the generation of national land space planning reports.

[0068] In addition, by only performing grid unit segmentation on the blank area models whose proportion is greater than the screening ratio threshold to obtain several different unit space models, the blank areas with small areas and no planning significance can be effectively excluded. In this way, on the one hand, the noise and errors caused by the blank areas with small areas and no planning significance can be avoided, ensuring the effectiveness and scientificity of the calculation of resource and environmental carrying capacity; on the other hand, the amount of calculated data can be reduced, further improving the calculation efficiency of resource and environmental carrying capacity; on the other hand, it can avoid wasting time and money on small areas, allowing planners to focus on key areas that have a greater impact on the overall planning, and invest limited resources in areas with more value and potential, ensuring that the focus of planning is more prominent.

[0069] In addition, by gridding only the blank area models whose proportions are greater than the screening ratio threshold to obtain several different unit space models, it is also possible to effectively avoid excluding unit space models that contain both non-target areas (for example, areas containing buildings) and blank areas, thereby further ensuring the effectiveness and scientificity of the resource and environmental carrying capacity calculations.

[0070] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced in conjunction with the accompanying drawings. Figure 1 The present application embodiment provides a GIS-based land space planning method, comprising the following steps:

[0071] S101: Acquire a land space model of a target area established by GIS;

[0072] Specifically, in some embodiments, the execution subject (e.g., computer equipment) of the GIS-based land space planning method can obtain the land space model of the target area established by GIS through wired connection or wireless connection. It should be noted that GIS is a technical system that collects, stores, manages, calculates, analyzes, and displays relevant geographical distribution data in the entire or part of the earth's surface space with the support of computer hardware and software systems. There will be corresponding map models in the GIS system, and all aspects of these map models are known and determined.

[0073] S102: performing blank area recognition processing on the land space model to obtain multiple blank area models in the land space model;

[0074] Specifically, in some embodiments, the blank area model refers to a model corresponding to an area in the land space model where there are no building features and water features. In this way, it can help identify unused or underutilized land, thereby facilitating a more efficient allocation and utilization of land resources. Of course, the present application is not limited to this. In other embodiments, the blank area model can also be a model corresponding to an area in the land space model where only building features do not exist.

[0075] Based on the above embodiment, the above execution subject may perform blank area recognition processing on the land space model through the following steps to obtain multiple blank area models in the land space model:

[0076] The first step is to obtain the initial data of the land space model, which includes the terrain, landforms, building characteristics and water characteristics in the target area;

[0077] The second step is to preprocess the initial data to extract building characteristic data and water area characteristic data; specifically, the preprocessing includes but is not limited to processing missing values ​​and abnormal data.

[0078] The third step is to generate a feature layer containing all buildings and water areas based on the extracted building feature data and water area feature data;

[0079] Specifically, the above-mentioned execution entity can apply a segmentation algorithm (such as multi-scale segmentation, k-means clustering or deep learning segmentation network) to segment the image into several small areas. Based on spectral features, texture features and shape features, identify areas that may belong to buildings. For example: based on NDVI (normalized vegetation index) and NDBI (normalized building index) for discrimination. Use a supervised classification algorithm (such as random forest, support vector machine SVM or convolutional neural network CNN) to classify the segmented areas and distinguish between building and non-building areas.

[0080] Calculate the water index (such as NDWI, normalized difference water index) to identify water areas. The NDWI formula is: NDWI = (green band - near infrared band) / (green band + near infrared band). Similarly, apply the segmentation algorithm to segment the water area. Use the classification algorithm to classify the segmented area to distinguish between water and non-water areas.

[0081] The classification results are vectorized to generate vector layers of building feature data and water feature data, and the building feature data and water feature data are superimposed to generate feature layers.

[0082] The fourth step is to perform mask processing on the feature layer to generate a blank area layer, which includes every area in the target area where there are no building features and water features;

[0083] The fifth step is to use the blank area layer as input data, compare it with the land space model, and identify and mark multiple blank area models in the land space model. By comprehensively extracting terrain, landforms, buildings and water feature data, a comprehensive data foundation can be provided, which is conducive to improving the accuracy of blank area identification.

[0084] S103: Obtaining a screening ratio threshold;

[0085] Specifically, in some embodiments, the above execution entity may obtain the screening ratio threshold through the following steps:

[0086] The first step is to obtain the minimum spatial planning area of ​​the target area;

[0087] Specifically, the above execution entity can obtain the minimum spatial planning area of ​​the target area through the following steps:

[0088] The first sub-step is to receive the minimum space planning area of ​​the target area input by the user;

[0089] The second sub-step is to verify whether the format of the data entered by the user is correct;

[0090] The third sub-step is to store the verified minimum space planning area data in a preset database for retrieval. In this way, on the one hand, it is convenient to adjust the minimum space planning area according to actual needs, making the planning more adaptable.

[0091] In the second step, the ratio of the minimum spatial planning area to the area of ​​the target area is calculated to obtain a screening ratio threshold. In this way, the screening ratio threshold can be flexibly obtained according to the specific conditions of the target area to adapt to the planning requirements of different locations. Of course, the application is not limited to this. In other embodiments, the minimum spatial planning area can be automatically extracted from relevant policy documents through natural language processing technology. In some other embodiments, the screening ratio input by the user can also be directly obtained as the screening ratio threshold.

[0092] S104: Calculate the ratio of each blank area model to the land space model, compare it with the screening ratio threshold, and mark the blank area model whose ratio is greater than the screening ratio threshold;

[0093] Specifically, in some embodiments, the execution subject may calculate the ratio of each blank area model to the land space model through the following steps, and compare it with the screening ratio threshold, and mark the blank area model whose ratio is greater than the screening ratio threshold:

[0094] The first sub-step is to calculate the projection area of ​​the land space model on the first plane, which is recorded as the first projection area;

[0095] In the second sub-step, the ratio of the projected area of ​​each blank area model on the first plane to the first projected area is calculated, and compared with the screening ratio threshold, and the blank area models whose ratio is greater than the screening ratio threshold are marked. In this way, no matter how complex or irregular the shape of the blank area model is, the area can be calculated by projecting it into a unified plane coordinate system, thereby effectively eliminating the errors caused by the diversity and complexity of the regional shape, thereby improving the accuracy of the screening results, effectively excluding small areas that have no actual development value, and ensuring that planning resources are concentrated on the most potential areas.

[0096] Preferably, based on the above embodiment, the mark corresponding to each blank area model whose ratio is greater than the screening ratio threshold is unique. In this way, each marked blank area can be tracked and managed through a unique identifier. When a blank area has been planned, it can be directly located and deleted through its unique identifier without having to re-perform complex identification and screening steps.

[0097] S105: performing grid unit segmentation on each marked blank area model to obtain a plurality of different unit space models;

[0098] Specifically, in some embodiments, the execution subject may perform grid unit segmentation on each marked blank area model to obtain a plurality of different unit space models through the following steps:

[0099] The first step is to retrieve the land space model established by the GIS;

[0100] The second step is to set a grid segmentation line and apply it to the land space model to generate a grid segmentation model, wherein the size of each unit of the grid segmentation model is the same as that of the standard unit model;

[0101] The third step is to generate a plurality of different unit space models based on the grid segmentation model.

[0102] S106: performing similarity matching on each unit space model and a standard unit model in a preset model database to obtain a corresponding carrying capacity value;

[0103] Specifically, the execution subject may perform similarity matching between each unit space model and a standard unit model in a preset model database to obtain a corresponding carrying capacity value through the following steps:

[0104] The first step: selecting a unit model similar to the unit space model from a model database according to geographical features to obtain a candidate unit model, wherein the geographical features include vegetation area features and land area features;

[0105] Step 2: obtaining spatial features according to the unit space model, and selecting a designated unit model from candidate unit models based on the spatial features;

[0106] Specifically, the execution subject may obtain the spatial features according to the unit space model through the following steps, and select the designated unit model from the candidate unit models based on the spatial features:

[0107] The first sub-step is to retrieve standard spatial features corresponding to the candidate unit model from the model database, wherein the standard spatial features include terrain gradient features and altitude features;

[0108] The second sub-step is to match the spatial features of the unit space model according to the standard spatial features;

[0109] The third sub-step is to select the designated unit model according to the matching result.

[0110] The third step: based on the designated unit model, retrieve the corresponding bearing capacity value from the model database.

[0111] S107: Calculate and sum the bearing capacity values ​​to obtain an overall bearing capacity value;

[0112] S108: Generate a national land space planning report based on the overall carrying capacity value.

[0113] See also Figure 2 Based on the same inventive concept as the GIS-based land space planning method in the aforementioned embodiment, the embodiment of the present application provides a GIS-based land space planning system, including:

[0114] The first acquisition module 201 is used to acquire a land space model of a target area established by GIS;

[0115] The first recognition module 202 is used to perform blank area recognition processing on the land space model to obtain multiple blank area models in the land space model;

[0116] The second acquisition module 203 is used to obtain a screening ratio threshold;

[0117] The first comparison module 204 is used to calculate the ratio of each blank area model to the land space model, compare it with the screening ratio threshold, and mark the blank area model whose ratio is greater than the screening ratio threshold;

[0118] The first segmentation module 205 is used to perform grid unit segmentation on each marked blank area model to obtain a plurality of different unit space models;

[0119] A first matching module 206 is used to perform similarity matching between each unit space model and a standard unit model in a preset model database to obtain a corresponding carrying capacity value;

[0120] A first calculation module 207, configured to obtain an overall bearing capacity value by summing up the bearing capacity values;

[0121] The first generation module 208 is used to generate a national land space planning report according to the overall carrying capacity value.

[0122] In some embodiments, the blank area model refers to a model corresponding to an area in the land space model where there are no building features or water features;

[0123] The first identification module is specifically used to: obtain initial data of the land space model, the initial data including the terrain, landform, building features and water features in the target area; pre-process the initial data to extract building feature data and water feature data therefrom; generate a feature layer containing all buildings and waters based on the extracted building feature data and water feature data; mask the feature layer to generate a blank area layer, the blank area layer including every area in the target area where no building features and water features exist; use the blank area layer as input data, compare it with the land space model, and identify and mark multiple blank area models in the land space model.

[0124] In some embodiments, the second acquisition module 203 is specifically used to: acquire the minimum spatial planning area of ​​the target area; calculate the ratio of the minimum spatial planning area to the area of ​​the target area to obtain a screening ratio threshold.

[0125] In some embodiments, the first comparison module 204 is specifically used to: calculate the projection area of ​​the land space model on the first plane, recorded as the first projection area; calculate the ratio of the projection area of ​​each blank area model on the first plane to the first projection area, and compare it with the screening ratio threshold, and mark the blank area models whose ratio is greater than the screening ratio threshold.

[0126] In some embodiments, the label corresponding to each white space model having a ratio greater than a screening ratio threshold is unique.

[0127] In some embodiments, the second acquisition module 203 is specifically used to: receive the minimum space planning area of ​​the target area input by the user; verify whether the format of the data input by the user is correct; and store the verified minimum space planning area data in a preset database for retrieval.

[0128] It is understandable that the modules and references recorded in this GIS-based national land space planning system Figure 1 The steps in the GIS-based national land space planning method described above correspond to each other. Therefore, the operations, features and beneficial effects described above for the method are also applicable to the GIS-based national land space planning system and the modules contained therein, and will not be repeated here.

[0129] See also Figure 3 Based on the inventive concept of a GIS-based land space planning method in the aforementioned embodiment, an embodiment of the present application provides an electronic device. The electronic device may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), etc., and fixed terminals such as digital TVs, desktop computers, etc. The electronic device includes a processing device 301 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a ROM 302 (read-only memory) or a program loaded from a storage device 308 into a RAM 303 (random access memory). In RAM 303, various programs and data required for the operation of the electronic device are also stored. The processing device 301, ROM 302, and RAM 303 are connected to each other via a bus 304. The input / output interface (i.e., an I / O interface 305) is also connected to the bus 304.

[0130] Typically, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309. The communication device 309 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data.

[0131] In particular, according to some embodiments of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of some embodiments of the present application are executed.

[0132] It should be noted that the computer-readable medium recorded in some embodiments of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In some embodiments of the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0133] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperTextTransferProtocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an adhoc peer-to-peer network), as well as any currently known or future developed network.

[0134] The computer-readable medium may be included in the electronic device; or it may exist independently without being assembled into the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: obtains the land space model of the target area established by GIS; performs blank area identification processing on the land space model to obtain multiple blank area models in the land space model; obtains a screening ratio threshold; calculates the ratio of each blank area model to the land space model, and compares it with the screening ratio threshold, and marks the blank area models whose ratio is greater than the screening ratio threshold; divides each marked blank area model into grid units to obtain several different unit space models; performs similarity matching on each unit space model with the standard unit model in the preset model database to obtain the corresponding carrying capacity value; performs summation calculation based on the carrying capacity value to obtain the overall carrying capacity value; generates a national land space planning report based on the overall carrying capacity value.

[0135] Computer program code for performing the operations of some embodiments of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0136] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0137] The modules described in some embodiments of the present application may be implemented by software or hardware. The modules described may also be set in a processor: for example, they may be described as: a first acquisition module, a first identification module, a second acquisition module, a first comparison module, a first segmentation module, a first matching module, a first calculation module, and a first generation module. The names of these modules do not, in some cases, constitute limitations on the modules themselves. For example, the first acquisition module may also be described as a "land space model acquisition module."

[0138] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0139] Some embodiments of the present application also provide a computer program product, including a computer program, which implements any of the above-mentioned GIS-based national land space planning methods when executed by a processor.

[0140] Although the present invention has been described in detail above by general description and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements can be made on the basis of the present invention. Therefore, these modifications or improvements made on the basis of not departing from the spirit of the present invention all belong to the scope of protection claimed by the present invention.

Claims

1. A GIS-based national land space planning method, characterized in that: The following steps are involved: Obtain a land spatial model of the target area established through GIS; Performing blank area recognition processing on the land space model to obtain a plurality of blank area models in the land space model; Get the screening ratio threshold; Calculating the ratio of each blank area model to the land space model, comparing it with the screening ratio threshold, and marking the blank area model whose ratio is greater than the screening ratio threshold; Performing grid unit segmentation on the blank area model of each mark to obtain a plurality of different unit space models; Performing similarity matching on each of the unit space models and a standard unit model in a preset model database to obtain a corresponding bearing capacity value; The overall bearing capacity value is obtained by summing up the bearing capacity values; Generate a national land space planning report based on the overall carrying capacity value.

2. The GIS-based national land space planning method according to claim 1, characterized in that: The blank area model refers to a model corresponding to an area in the land space model where there are no building features or water features; The step of performing blank area recognition processing on the land space model to obtain a plurality of blank area models in the land space model comprises: Acquire initial data of the land space model, wherein the initial data includes topography, landforms, building features and water features in the target area; Preprocessing the initial data to extract building characteristic data and water area characteristic data; Based on the extracted building feature data and water feature data, a feature layer including all buildings and water areas is generated; Performing mask processing on the feature layer to generate a blank area layer, wherein the blank area layer includes each area in the target area where there is no building feature or water feature; The blank area layer is used as input data and compared with the land space model to identify and mark multiple blank area models in the land space model.

3. The GIS-based national land space planning method according to claim 2 is characterized in that: The steps for obtaining the screening ratio threshold include: Obtain the minimum spatial planning area of ​​the target area; The ratio of the minimum space planning area to the area of ​​the target area is calculated to obtain the screening ratio threshold.

4. The GIS-based national land space planning method according to claim 3 is characterized in that: The steps of calculating the ratio of each blank area model to the land space model and comparing it with the screening ratio threshold, and marking the blank area model having a ratio greater than the screening ratio threshold include: Calculate the projection area of ​​the land space model on the first plane, recorded as the first projection area; The ratio of the projection area of ​​each blank area model on the first plane to the first projection area is calculated, and compared with the screening ratio threshold, and the blank area models whose ratio is greater than the screening ratio threshold are marked.

5. The GIS-based national land space planning method according to any one of claims 1 to 4, characterized in that: The mark corresponding to each blank area model whose ratio is greater than the screening ratio threshold is unique.

6. The GIS-based national land space planning method according to claim 3 is characterized in that: The step of obtaining the minimum spatial planning area of ​​the target area comprises: Receive the minimum space planning area of ​​the target area input by the user; Verify that the data entered by the user is in the correct format; The verified minimum space planning area data is stored in a preset database for later use.

7. A GIS-based national land space planning system, characterized in that: include: The first acquisition module is used to acquire a land space model of a target area established through GIS; A first recognition module is used to perform blank area recognition processing on the land space model to obtain a plurality of blank area models in the land space model; The second acquisition module is used to obtain a screening ratio threshold; A first comparison module, used for calculating the ratio of each blank area model to the land space model, comparing it with the screening ratio threshold, and marking the blank area model whose ratio is greater than the screening ratio threshold; A first segmentation module is used to perform grid unit segmentation on each marked blank area model to obtain a plurality of different unit space models; A first matching module, used for performing similarity matching between each of the unit space models and a standard unit model in a preset model database to obtain a corresponding carrying capacity value; A first calculation module, configured to obtain an overall bearing capacity value by summing up the bearing capacity values; The first generation module is used to generate a national land space planning report based on the overall carrying capacity value.

8. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processing device, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processing device, the method according to any one of claims 1 to 6 is implemented.

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