Perspective analysis method and system based on multi-element space superposition

Abstract

The application discloses a perspective analysis method and system based on multi-element space superposition and belongs to the technical field of geographic information processing, which comprises the following steps: acquiring analysis range data input by a user, wherein the analysis range data is generated by map drawing or external vector file import; selecting at least two analysis object layers; performing space alignment, coordinate system conversion and attribute field standardization processing on the analysis range data and the analysis object layers; adopting parallel space index technology, superimposing all analysis object layers and analysis range data at one time to generate a fine achievement library; storing space unit ID and original layer attribute fields in the fine achievement library; calculating target field values according to the area proportion of space units based on preset adjustment rules and outputting the target field values to a space data file and a table file; generating a multi-dimensional statistical report according to user-defined dimensions and statistical indexes based on the fine achievement library through a perspective analysis engine; and outputting fine space data files and analysis reports according to filter conditions.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of geographic information processing, and in particular relates to a perspective analysis method and system based on multi-element spatial overlay. BACKGROUND

[0002] A geographic information system (GIS) is a computer system for collecting, storing, managing, analyzing and displaying geographic spatial data. The commonly used spatial overlay analysis method in existing geographic information systems (GIS) is to perform intersection, union and difference operations on different spatial layers to reveal the correlation between geographic elements (for example, the distribution rule of population density and land type), which has become a core spatial analysis method in the fields of urban planning and agricultural evaluation, and is a very important analysis method in geographic information technology. The basic process includes: preparing multiple layers with spatial relationship (input data), spatial alignment and attribute matching of the layers, selecting appropriate overlay operation, and executing overlay analysis to generate new layers (output data); the input data is usually multiple vector or polygon layers, or raster data sets; the output data is the new layer after overlay processing, which contains comprehensive spatial and attribute information, and is used to reveal the spatial relationship between elements or generate new geographic information.

[0003] However, existing GIS tools (for example, Arc GIS, Super Map) use a bottom-up logic of two-by-two layer iterative overlay when processing multi-layer overlay scenarios (for example, integrating dozens of layers such as soil type, precipitation distribution, and terrain slope). That is, first overlay layers A and B to generate intermediate results, then overlay the intermediate results with layer C, and so on until all layers are calculated. The above traditional mode has three inherent defects: first, the calculation efficiency is severely limited, and the redundant operation caused by multiple generation and storage of intermediate results causes the processing time to grow exponentially, especially for large-scale high-precision data; second, the business application is disconnected, and the actual scenario (for example, forest land occupation analysis needs to output land type area report according to administrative area) needs to rely on manual scripting or manual processing of Excel data, and cannot automatically generate customized analysis reports.

[0004] Therefore, with the deep application of GIS in cross-industry decision-making, there is an urgent need for a perspective analysis method and system based on multi-element spatial overlay that can complete the whole layer overlay at one time, preserve the original attribute data, and directly output multi-dimensional statistical reports, to solve the pain points of low efficiency and report generation disconnection of traditional methods. SUMMARY

[0005] The present application is aimed at the above-mentioned problems, makes up for the deficiencies of the prior art, and provides a perspective analysis method and system based on multi-element space superposition; the present application realizes perspective analysis of arbitrary element information of space data superposition, and achieves the purpose of being able to superimpose analysis results and generate self-defined report results.

[0006] To achieve the above-mentioned purpose, the present application adopts the following technical solutions.

[0007] In a first aspect, the present application provides a perspective analysis method based on multi-element space superposition, comprising the following steps:

[0008] S1. Obtain analysis range data input by a user, wherein the analysis range data is generated by map drawing or external vector file import;

[0009] S2. Select at least two analysis object layers, wherein the analysis object layers are vector layers;

[0010] S3. Perform space alignment, coordinate system conversion and attribute field standardization processing on the analysis range data and the analysis object layers;

[0011] S4. Use parallel space index technology to superimpose all analysis object layers and analysis range data at one time to generate a detailed result library; store space unit ID and original layer attribute fields in the detailed result library;

[0012] S5. Calculate target field values according to the area proportion of space units based on preset adjustment rules, and output to a space data file and a table file;

[0013] S6. Generate a multi-dimensional statistical report according to user-defined dimensions and statistical indicators based on the detailed result library through a perspective analysis engine;

[0014] S7. Output detailed space data files and analysis reports according to filter conditions.

[0015] Further, in step S1, the analysis range data is a vector graph drawn by a user on a map interface or shp / gdb format data imported from outside.

[0016] Further, in step S2, the analysis object layers include at least two kinds of space vector data layers.

[0017] Further, in step S4, the one-time superposition uses non-two-two iteration space intersection operation, space union operation or raster algebra operation; the data structure of the detailed result library includes unique space unit ID and attribute field set of each original layer.

[0018] Further, in step S5, the adjustment rule is: according to the area proportion of the spatial unit in the superimposed area, the target field value is weighted and calculated.

[0019] Further, in step S5, the spatial data file is an shp format spatial data file, and the table file is an excel format statistical table file.

[0020] Further, in step S6, the dimensions include administrative division, land type or user-defined classification field; and the statistical indicators include summation, average value, maximum value or minimum value.

[0021] Further, in step S7, the filtering conditions include spatial range threshold or attribute field threshold.

[0022] Further, the analysis report output in step S7 includes statistical charts and spatial distribution visualization results of multiple dimensions.

[0023] In a second aspect, the present application further provides a perspective analysis system based on multi-element spatial superposition, comprising an analysis range acquisition module, a layer selection module, a data preprocessing execution module, a parallel superposition calculation and storage module, an adjustment calculation module, a perspective analysis engine module and a report generation module.

[0024] The analysis range acquisition module is configured to receive analysis range data generated by a user through map drawing or external vector file import.

[0025] The layer selection module is configured to load at least two analysis object layers, wherein the analysis object layers are vector layers.

[0026] The data preprocessing execution module is configured to perform spatial alignment, coordinate system conversion and attribute field standardization processing on the analysis range data and analysis object layers.

[0027] The parallel superposition calculation and storage module is configured to use parallel spatial index technology to superimpose all analysis object layers and analysis range data at one time, generate a detailed achievement database, and store spatial unit ID and original layer attribute field in the detailed achievement database.

[0028] The adjustment calculation module is configured to calculate target field values according to the area proportion of the spatial unit, and output the target field values to a spatial data file and a table file.

[0029] The perspective analysis engine module is configured to generate multi-dimensional statistical reports according to user-defined dimensions and statistical indicators based on the detailed achievement database through a perspective analysis engine.

[0030] The report generation module is configured to output detailed spatial data files and analysis reports according to filtering conditions.

[0031] Advantages of the present application:

[0032] 1. The present application uses parallel spatial index technology, which can superimpose all layers at one time, that is, superimpose analysis range data and all analysis object layers at one time, without iteration. Compared with traditional GIS tools, the efficiency is greatly improved, and the generated detailed result library can completely retain all original attribute data, providing a data basis for subsequent analysis. Moreover, through adjustment calculation rules, field values can be automatically weighted according to the area proportion of spatial units, solving the problem of spatial distribution of attribute values. Through the perspective analysis engine, users can freely define dimensions and statistical indicators to directly generate multi-dimensional statistical reports, replacing manual data processing.

[0033] 2. The present application constructs a closed loop from superposition calculation to report output, which has the following advantages: (1) Self-service report generation: users can output detailed spatial data files and analysis reports by configuring filtering conditions, which can shorten the business analysis period from several days to hours; (2) Multi-industry universality: suitable for report generation in scenarios such as urban land use planning, agricultural suitability evaluation, and forest land occupation analysis, solving the pain points of low efficiency of traditional GIS tools and report generation fragmentation, and promoting the transformation of spatial analysis to intelligent decision-making. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0035] Figure 1 A flowchart of a perspective analysis method based on multi-element spatial superposition of the present application.

[0036] Figure 2 A structural schematic diagram of a perspective analysis system based on multi-element spatial superposition of the present application.

[0037] In the figure, 200 is an analysis range acquisition module, 201 is a layer selection module, 202 is a data preprocessing execution module, 203 is a parallel superposition calculation and storage module, 204 is an adjustment calculation module, 205 is a perspective analysis engine module, 206 is a report generation module, 207 is a perspective analysis system based on multi-element spatial superposition. DETAILED DESCRIPTION

[0038] In order to make the technical problems, technical solutions and beneficial effects solved by the present application clearer, the present application will be further described in detail below in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0039] As shown in Figure 1 The perspective analysis method based on multi-element space superposition provided by the embodiment of the present application comprises the following steps:

[0040] S1. Obtain the analysis range data input by a user, wherein the analysis range data is generated by map drawing or external vector file import;

[0041] Specifically, in step S1, the analysis range data is a vector graph drawn by the user on a map interface or shp / gdb format data imported from outside.

[0042] S2. Select at least two analysis object layers, wherein the analysis object layers are vector layers;

[0043] Specifically, in step S2, the analysis object layers comprise at least two or more spatial vector data layers.

[0044] S3. Perform spatial alignment, coordinate system conversion and attribute field standardization processing on the analysis range data and the analysis object layers.

[0045] S4. Use parallel spatial index technology to superimpose all analysis object layers and analysis range data at one time to generate a fine-grained result library; store spatial unit ID and original layer attribute fields in the fine-grained result library;

[0046] Specifically, in step S4, the one-time superposition uses non-two-by-two iteration spatial intersection operation, spatial union operation or raster algebra operation; the data structure of the fine-grained result library comprises: unique spatial unit ID, attribute field set of each original layer; wherein the original layer attribute fields comprise: land use type, population density value, soil type.

[0047] S5. Calculate target field values according to the area proportion of spatial units based on preset adjustment rules and output to spatial data files and table files;

[0048] Specifically, in step S5, the adjustment rules are: performing weighted calculation on the target field values according to the area proportion of spatial units in the superposition region; the spatial data file is a shp format spatial data file, and the table file is an excel format statistical table file.

[0049] Wherein, the logic of weighting the target is that after a graphic element is cut, the target field value = the original field value * (the proportion of the area after cutting / the original area).

[0050] S6. Based on the fine-grained result library, generating multi-dimensional statistical reports by the perspective analysis engine according to user-defined dimensions and statistical indicators;

[0051] Specifically, in step S6, the dimensions include administrative divisions, land types or user-defined classification fields; and the statistical indicators include summation, average value, maximum value or minimum value.

[0052] S7. Outputting the fine-grained spatial data file and the analysis report according to the filtering conditions;

[0053] Specifically, in step S7, the filtering conditions include spatial range thresholds or attribute field thresholds; and the analysis report outputted in step S7 contains statistical charts and spatial distribution visualization results of multiple dimensions.

[0054] As shown in Figure 2 The embodiment of the present application provides a perspective analysis system based on multi-element spatial superposition, which is used to realize the perspective analysis method based on multi-element spatial superposition; the perspective analysis system based on multi-element spatial superposition 207 includes an analysis range acquisition module 200, a layer selection module 201, a data preprocessing execution module 202, a parallel superposition calculation and storage module 203, a adjustment calculation module 204, a perspective analysis engine module 205 and a report generation module 206.

[0055] The analysis range acquisition module 200 is used to receive analysis range data generated by the user through map drawing or external vector file import;

[0056] The layer selection module 201 is used to load at least two analysis object layers, which are vector layers or raster layers;

[0057] The data preprocessing execution module 202 is used to perform spatial alignment, coordinate system conversion and attribute field standardization processing on the analysis range data and the analysis object layers;

[0058] The parallel superposition calculation and storage module 203 is used to perform one-time superposition of all analysis object layers and analysis range data by using parallel spatial index technology, to generate a fine-grained result library, and to store spatial unit IDs and original layer attribute fields in the fine-grained result library;

[0059] The adjustment calculation module 204 is used to calculate target field values according to the area proportions of spatial units, and to output the target field values into spatial data files and table files;

[0060] The perspective analysis engine module 205 is used for generating a multi-dimensional statistical report by a perspective analysis engine based on the fine-grained result library according to user-defined dimensions and statistical indexes.

[0061] The report generation module 206 is used for outputting the fine-grained spatial data file and the analysis report according to the filtering condition.

[0062] The advantages of the present application include the following points: (1) the present application provides a method for realizing mutual superimposed analysis of two or more analysis object layers, instead of traditional successive superimposition (i.e., non-two-by-two iteration) based on two-by-two superimposition, and forms a fine-grained result library through one-time superimposed analysis, thereby simplifying the method for superimposing multi-element spatial data; (2) the present application provides a method for perspective analysis based on the fine-grained result library formed by superimposed analysis, and can complete grouping statistics of specified dimensions and can form a report table through horizontal and vertical layout; (3) the present application provides a self-service superimposed analysis report generation technology based on the fine-grained result library and the perspective analysis engine technology, and can automatically generate an analysis report according to different statistical index definitions for the purpose of business analysis.

[0063] The present application is characterized in that: the superimposed analysis method is expanded, the multi-analysis object layer and the analysis range data of input data are realized for one-time full analysis and form a superimposed analysis result library, i.e., a fine-grained result library, the fine-grained result library retains the original attributes of elements participating in analysis of each category, and therefore is a most detailed spatial+factor library; on the basis of this, the present application can realize the commonly used perspective analysis method for quantitative statistical analysis of the data analysis industry through the perspective analysis engine technology of free statistics, and forms a perspective analysis result report through defining multiple dimensions of perspective analysis results for one business scenario, and realizes the process as on-demand self-defined interaction.

[0064] In summary, the present application realizes the dual breakthrough of technical efficiency and application value through the steps S1 to S7 of the above-mentioned perspective analysis method based on multi-element space superposition and the technical scheme of the perspective analysis system 207 based on multi-element space superposition: in the technical aspect, the parallel space index technology is adopted, all analysis object layers are superimposed at one time, that is, all input layers (instead of the traditional two-by-two iteration mode), which significantly improves the operation efficiency; the fine result library constructed synchronously takes the "space unit ID + original attribute field set" as the storage structure (such as: retaining all input factors such as soil pH value, population density, crop type), forming a traceable multi-source data basement, and realizing attribute value space adjustment automation (such as: automatically distributing the total population according to the area proportion of each spatial unit), solving the core problem of multi-layer attribute fusion; further integrating the perspective analysis engine, supporting users to freely define statistical dimensions (such as: administrative district + land type) and indicators (such as: sum / average value), directly generating Excel files containing cross-report forms, and completely replacing the manual data processing process. In the application aspect, the present application constructs a complete closed loop from spatial superposition calculation to business report output: users can one-key output integrated spatial distribution graph (i.e. spatial data file in shp format) and multi-dimensional graph-text report (such as: crop yield heat map under different soil types) by configuring filtering conditions and perspective rules, which compresses the business cycle of agricultural suitability evaluation, urban development potential analysis and other scenes from several days to hours, and promotes the transformation of spatial analysis from professional tools to intelligent decision-making systems.

[0065] In the description of the present specification, the description referring to the terms "one embodiment", "some embodiments", "illustrative embodiment", "preferred embodiment", "specific implementation", or "preferred implementation" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0066] It can be understood that the above specific description of the present application is only used to illustrate the present application and is not limited to the technical scheme described in the embodiments of the present application. Those skilled in the art should understand that the present application can still be modified or replaced equivalently to achieve the same technical effect; as long as the use needs are met, it is within the protection scope of the present application.

Claims

1. A perspective analysis method based on multi-element spatial overlay, characterized in that: Includes the following steps; S1. Obtain the analysis range data input by the user, which is generated through map drawing or importing external vector files; S2. Select at least two analysis object layers, wherein the analysis object layers are vector layers; S3. Perform spatial alignment, coordinate system transformation, and attribute field standardization on the analysis range data and analysis object layer; S4. Using parallel spatial indexing technology, all analysis object layers and analysis range data are overlaid at once to generate a fragmented results library; the spatial unit ID and original layer attribute fields are stored in the fragmented results library; the one-time overlay is performed using non-pairwise iterative spatial intersection operation, spatial union operation or raster algebra operation; The data structure of the fragmented results library includes: a unique spatial unit ID and a set of attribute fields for each original layer; S5. Based on the preset adjustment rules, calculate the target field value according to the area ratio of the spatial unit, and output it to the spatial data file and table file; the adjustment rules are: the target field value is weighted according to the area ratio of the spatial unit in the superimposed area; the logic of weighting the target is that after a graphic element is cut, its target field value = original field value * (the ratio of the area after cutting / the original area). S6. Based on the fragmented results library, generate multidimensional statistical reports according to user-defined dimensions and statistical indicators using the perspective analysis engine; S7. Output a file of fragmented spatial data and an analysis report based on the filtering conditions.

2. The perspective analysis method based on multi-element spatial overlay according to claim 1, characterized in that: In step S1, the analysis range data is either a vector graphic drawn by the user on the map interface or externally imported shp / gdb format data.

3. The perspective analysis method based on multi-element spatial overlay according to claim 1, characterized in that: In step S2, the analysis object layer includes at least two spatial vector data layers.

4. The perspective analysis method based on multi-element spatial overlay according to claim 1, characterized in that: In step S5, the spatial data file is a shp format spatial data file, and the table file is an excel format statistical table file.

5. The perspective analysis method based on multi-element spatial overlay according to claim 1, characterized in that: In step S6, the dimensions include administrative divisions, land types, or user-defined classification fields; the statistical indicators include summation, average, maximum, or minimum values.

6. The perspective analysis method based on multi-element spatial overlay according to claim 1, characterized in that: In step S7, the filtering conditions include spatial range thresholds or attribute field thresholds.

7. The perspective analysis method based on multi-element spatial overlay according to claim 1, characterized in that: The analysis report output in step S7 includes statistical charts and spatial distribution visualizations across multiple dimensions.

8. A perspective analysis system based on multi-element spatial overlay, characterized in that: It includes modules for obtaining the analysis range, selecting layers, performing data preprocessing, parallel overlay calculation and storage, adjusting calculation, perspective analysis engine, and generating reports. The analysis range acquisition module is used to receive analysis range data generated by the user through map drawing or importing external vector files; The layer selection module is used to load at least two analysis object layers, wherein the analysis object layers are vector layers. The data preprocessing execution module is used to perform spatial alignment, coordinate system transformation and attribute field standardization on the analysis range data and the analysis object layer. The parallel overlay calculation and storage module is used to overlay all analysis object layers and analysis range data at one time using parallel spatial indexing technology to generate a fragmented results library, in which spatial unit IDs and original layer attribute fields are stored; the one-time overlay uses non-pairwise iterative spatial intersection operation, spatial union operation or raster algebra operation. The data structure of the fragmented results library includes: a unique spatial unit ID and a set of attribute fields for each original layer; The adjustment calculation module is used to calculate the target field value according to the area ratio of the spatial unit and output it to the spatial data file and table file. The adjustment rule is: the target field value is weighted according to the area ratio of the spatial unit in the superimposed area. The logic of weighting the target is that after a graphic element is cut, its target field value = original field value * (the ratio of the area after cutting to the original area). The perspective analysis engine module is used to generate multidimensional statistical reports based on the fragmented results library, according to user-defined dimensions and statistical indicators. The report generation module is used to output fragmented spatial data files and analysis reports based on filtering conditions.

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