CN114385627A - A data analysis method, device and storage medium based on GIS map - Google Patents

Abstract

The invention discloses a data analysis method, device and storage medium based on GIS map. The method includes: configuring thematic indicators, defining core analysis indicators, assigning index codes and display names, constructing the relationship between thematic indicators and the multi-dimensional analysis scheme, constructing a data source identifier corresponding to the map topic data, and setting the topic corresponding data source to generate Thematic index information configuration table; configure multi-dimensional analysis data, generate multi-dimensional analysis data indicator table based on thematic index information configuration table, and prepare map thematic area indicator data; Objects related to the location establish massive points and generate massive point data tables; based on the user's initiation, the display area is dynamically constructed. The bottom layer of the display area is the GIS map of the geographic information system, the suspension condition area on the left, and the analysis icon area on the right.

Description

A data analysis method, device and storage medium based on GIS map

technical field

The invention relates to the field of data analysis, in particular to a data analysis method, device and storage medium based on a GIS map.

Background technique

Traditional data analysis often relies on data analysis tools, each of which has its own advantages and disadvantages. Geographic information system (geography information system or geo-information system, GIS) maps are mature in the fields of navigation and other fields, but in the field of analysis, GIS maps can intuitively display areas or massive points, but interactive analysis is difficult; one-house display effect is good, However, the sense of space for listing data is insufficient; the interactive analysis function of multi-dimensional analysis is strong, but it is cumbersome for operators to operate.

As more and more data resources are accumulated in the data center, traditional data analysis often limits the user's analysis path and exploration imagination, and there are disadvantages that are not very useful.

Existing data analysis based on GIS maps is more focused on the data analysis effect based on geographic location. Even if combined with charts such as heat map, pie chart, column chart, etc., it focuses on geographic location and reflects its intuitive situation. . For analysis tools that focus on analyzing the nature of data and tracing its causes, such as multi-dimensional analysis, one-house analysis, etc., the operation requirements of operators are relatively high or the displayed data is not intuitive.

In the regional positioning of the GIS map, the location of the positioning region is drilled based on the defined map level, but the provincial regions in my country are different. However, in vast areas such as Xinjiang and Tibet, if you drill down to one level, you cannot intuitively see the area corresponding to the next-level area. You need to drill down to multiple levels to see the specific urban area.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a data analysis method, device and storage medium based on GIS map. The method integrates GIS map, multi-dimensional analysis and one-household three types of tools, which can support penetration from macro-regional index analysis to one-household analysis of massive onlookers. It integrates the relevant advantages of GIS maps and expands a set of algorithms based on the relevant advantages. Combined with this algorithm, it can better highlight the advantages of hierarchical regional positioning of data maps, and can better serve operators.

In view of this, the first aspect of the present invention provides a data analysis method based on a GIS map, characterized in that, the method includes: Step 110: configure thematic indicators, define core analysis indicators, assign indicator codes and display names, construct The relationship between the thematic indicators and the multi-dimensional analysis scheme, construct the data corresponding to the data source identifier of the map topic, and set the data source corresponding to the topic to generate the topic indicator information configuration table; Step 120: configure the multi-dimensional analysis data, based on the topic indicator The information configuration table generates a multi-dimensional analysis data index table, and prepares the map thematic area index data; Step 130: Based on the pre-preset massive point categories, through the data preparation method, establish massive points for all location-related objects in the data center, and generate massive point data table; Step 140: Based on the user's initiation, dynamically construct a display area, wherein the bottom layer of the display area is a geographic information system GIS map, the left suspension condition area, the right suspension analysis icon area, and the left suspension condition The area is related to the multi-dimensional analysis data indicator table, and the right-side floating analysis icon area is related to the massive point data table.

Optionally, in combination with the first aspect, in a possible implementation manner, the method further includes: Step 150: when receiving the user's first opening instruction, the displayed focus area is the area preset by the system parameters, and the display The level is the best display level for positioning the preset area in combination with the recommended focus algorithm; when receiving at least one operation from the user by dragging the map, zooming the level or clicking on the map drawing surface, the recommended focus area algorithm is recalculated. The best display area and repositioned to the best display tier.

Optionally, in combination with the first aspect, in a possible implementation manner, in the step 110, the data source may be a data table or a view.

Optionally, in combination with the first aspect, in a possible implementation manner, in step 120, the multi-dimensional analysis data indicator table is used for fast multi-dimensional analysis, and the multi-dimensional analysis data indicator table is a three-dimensional cube, wherein The dimensions of the three-dimensional cube include: topic, time, and area; in step 140, the user can select topic, time and area conditions from the left floating condition area, and the user can select from the right floating analysis icon area Conditional dynamic construction of map area display and multi-dimensional analysis.

Optionally, in combination with the first aspect, in a possible implementation manner, the algorithm for recommending the focus area in step 150 specifically includes: Step 151: Obtain basic page parameters, where the basic page parameters include: longitude The maximum and minimum values are C_GL and C_TL respectively, the maximum and minimum latitude values are C_GS and C_TS respectively, the center point of the screen is C, and the original map level F before the interactive page is changed and the current map after the interactive page is changed. Level R; Step 152: Obtain the area code list of the area to be selected, the area code list of the area to be selected is related to the preset area level table, and determine whether the area corresponding to the area code list of the area to be selected is recommended according to the basic parameters of the page Division; Step 153: Calculate the score of the recommended administrative division of the to-be-selected area according to the to-be-selected area division code list.

Optionally, in combination with the first aspect, in a possible implementation manner, the step 152 specifically includes: when the to-be-selected area division coding list satisfies both conditions, determining the corresponding to-be-selected area division coding list. The division is a recommended division, and the recommended division is added to the area to be selected. The two conditions include: Condition 1: If the current map level R ≥ the original map level F, the range of the division level value is the current The range of the map level plus or minus 1; or, if the current map level R < the original map level F, the range of the division level value is the range from the current map level to the current level minus 2; Condition 2: the preset level The maximum and minimum values of the longitude and longitude of the pre-set division level sub-table are respectively aL and aS, the maximum and minimum values of the division longitude and latitude of the pre-set division level sub-table are bL and bS respectively, and the preset division level The maximum and minimum longitude values of the sub-table divisions are displayed on the screen, and the maximum and minimum latitude values are displayed on the display screen.

Optionally, in combination with the first aspect, in a possible implementation manner, the step 153 specifically includes: taking the difference between the maximum value C_GL of the longitude and the minimum value C_TL as the length, and taking the maximum value C_GS and the minimum value C_TS of the latitude as the length. As the width, the area of the screen display area is obtained; the score of the recommended administrative division of the candidate area is calculated according to the area of the screen display area.

Optionally, in combination with the first aspect, in a possible implementation manner,

The calculation of the score of the recommended administrative division of the candidate area according to the area of the screen display area specifically includes: judging whether the coordinate longitude of the center point of the screen is within the range of the maximum longitude and the minimum longitude of the area, and the coordinate latitude of the center point of the screen is within the maximum latitude and the minimum longitude of the area. Within the minimum latitude range, if it is satisfied, the value of a is recorded as the set score; the area of the area to be selected in the display area ÷ the area of the display area × 10, the result is b, and it is judged whether the value of b is greater than the set threshold, if If the b value is greater than the set threshold, the result obtained by subtracting the set gradient score from the b value is assigned to b; the distance from the center point of all the areas to be selected to the center point of the screen is obtained, and the ranking score is calculated. Sort from small to large, and the value of the zone with the smallest distance from the center point is assigned in descending order, and the obtained value is recorded as c; the obtained weight score is recorded as a+b+c.

A second aspect of the present invention provides a data analysis device based on a GIS map, characterized in that the device includes: a memory and a processor, the memory stores codes, and the processor is configured to execute the codes , when the code is executed, the terminal executes the GIS map-based data analysis method described in any one of the possible implementation manners of the first aspect to the first aspect.

A third aspect of the present application provides a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by one or more When executed by the multiple processors, the one or more processors can be caused to execute any possible GIS map-based data analysis method according to the first aspect to the first aspect of the present application.

The invention discloses a data analysis method, device and storage medium based on GIS map. The method includes: Step 110: configure thematic indicators, define core analysis indicators, assign index codes and display names, construct the relationship between the thematic indicators and the multi-dimensional analysis scheme, construct data corresponding to data source identifiers for map topics, and set thematic correspondence data source to generate a thematic index information configuration table; Step 120: configure multi-dimensional analysis data, generate a multi-dimensional analysis data indicator table based on the thematic index information configuration table, and prepare map thematic area indicator data; Step 130: based on pre-set Mass point category Through the method of data preparation, all location-related objects in the data center are set up to create mass points, and a mass point data table is generated; Step 140: Based on the user's initiation, dynamically construct a display area, wherein the bottom layer of the display area is geographic Information system GIS map, left suspension condition area, right suspension analysis icon area, the left suspension condition area is related to the multi-dimensional analysis data indicator table, and the right suspension analysis icon area is related to the massive point data table related.

Provides an integrated experience data analysis method based on GIS maps, combining GIS maps, multi-dimensional analysis and one-stop tools, from macro-area index analysis to micro-mass point one-stop analysis, taking multi-dimensional analysis The interactive operation of the GIS map, the drag-and-zoom of the GIS map, the detailed and intuitive features of the one-house model, users can complete the exploration and analysis of the data center by themselves by clicking and dragging. The combination of maps and multi-dimensional analysis expands spatial thinking for users. The map is combined with the one-household style, from a more abstract and concrete object viewing method of one-household style to a method of guiding and exploring with the massive points of the map, tracing back to the specific one-household information. This method is mainly to meet the penetrating monitoring of "one pole in the bottom" in business, starting from macro thematic indicators, and realizes the level-by-level penetration of provinces, cities and counties to detailed and massive points.

The area size and boundaries of traditional maps are too different. In view of the weakness of traditional GIS map area analysis, which is difficult to penetrate layer by layer, in the positioning of the map area, an algorithm is used to comprehensively score items, weight ratios, ranking scores and other methods. , intelligently acquires the focus area. It solves the problem that the traditional map can only penetrate through and find the weaknesses of the region according to the defined level in the interactive operation of the map.

Description of drawings

The present invention will be further described below in conjunction with the accompanying drawings and embodiments, in which:

Fig. 1 is a kind of data analysis method flow chart based on GIS map provided by the present invention;

2 is a schematic diagram of a dynamic construction area layout provided by the present invention;

3 is a flowchart of a recommended focus area algorithm provided by the present invention;

FIG. 4 is a schematic diagram of calculation of a zone display range provided by the present invention;

Fig. 5 is the display effect diagram of a kind of massive point provided by the present invention;

FIG. 6 is a schematic diagram showing an administrative division provided by the present invention;

7 is a schematic diagram showing an administrative division provided by the present invention;

FIG. 8 is a schematic structural diagram of a data analysis device based on a GIS map provided by the present invention.

Detailed ways

The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application. In this application, "at least one" means one or more, and "plurality" means two or more. "And/or", which describes the association relationship of the associated objects, indicates that there can be three kinds of relationships, for example, A and/or B, which can indicate: the existence of A alone, the existence of A and B at the same time, and the existence of B alone, where A, B can be singular or plural. The character "/" generally indicates that the associated objects are an "or" relationship. "At least one item(s) below" or similar expressions thereof refer to any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (a) of a, b or c, can represent: a, b, c, a and b, a and c, b and c or a and b and c, where a, b and c can be It can be single or multiple. It is worth noting that "at least one item(s)" can also be interpreted as "one item(s) or more(s)".

It should be noted that, in this application, words such as "exemplary" or "for example" are used to represent examples, illustrations or illustrations. Any embodiment or design described in this application as "exemplary" or "such as" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present the related concepts in a specific manner.

The descriptions of the first, second, etc. appearing in the embodiments of the present application are only used for illustration and distinguishing the description objects, and have no order. any limitations of the examples.

First, make a brief introduction to the technical terms involved in this application:

GIS: Geographic Information System (Geographic Information System or Geo-Informationsystem, GIS), which is a specific and very important spatial information system. It is a technical system that collects, stores, manages, calculates, analyzes, displays and describes the relevant geographical distribution data in the whole or part of the earth's surface (including the atmosphere) space with the support of computer hardware and software systems.

Massive points: also known as coordinate points, a kind of geographically marked points on the map, which are used to specifically locate the specific spatial level of a certain unit of an enterprise.

Mass point type: It is a classification method tailored for mass points in order to distinguish between different attributes and mass points of different natures. Such as: massive poverty alleviation points.

Thematic indicators: also known as thematic statistical indicators, thematic statistical indicators are statistical indicators formulated for a certain economic or social issue, which are used to describe the overall basic situation and the comprehensive quantity of the distribution characteristics of each variable. For example, the basic situation of financial investment of poverty alleviation funds can be used as a thematic indicator of the number of regional poverty alleviation funds.

Multi-dimensional analysis: It is one of the advanced statistical analysis methods, which is to analyze a product or a market phenomenon on a space coordinate of more than two dimensions. The present invention includes three dimensions: thematic index dimension, division dimension and time dimension.

One-House Type: It is a data presentation report component that can combine and display related elements of enterprises, units, departments and other similar institutions, and can also classify and count data according to different attributes.

The purpose of the present invention is to establish a data analysis method based on a GIS map to provide an integrated experience. First, define a map, multi-dimensional analysis, and one-house shared thematic index analysis system. By combining the index system, configure the GIS map thematic index, prepare Massive point data; secondly, when the user is roaming the map, the algorithm constructs a thematic analysis of the current area based on parameters such as the user's area and the coordinates of the center point of the screen; finally, after the interaction parameter combination meets the preset conditions, it switches to dynamic construction of massive point analysis .

The contents of the present invention are as follows: First, three types of analysis tools, GIS map, multi-dimensional analysis and one-house analysis, are combined through a series of configuration methods to provide users with an analysis method based on GIS maps. Second, in this analysis method, the algorithm automatically recommends the optimal display level in the focus area, thereby improving the user's operating experience.

Specifically, referring to FIG. 1, the present invention provides a data analysis method based on a GIS map, and the method includes:

S110 , configuring thematic indicators, defining core analysis indicators, assigning index codes and display names, constructing the relationship between the thematic indicators and the multi-dimensional analysis scheme, constructing a data source identifier corresponding to the data of the map topic, and setting a data source corresponding to the topic to generate Thematic indicator information configuration table.

Configure thematic indicators. Define core analysis indicators, assign indicator codes and display names, construct the relationship between thematic indicators and multi-dimensional analysis solutions, construct the data corresponding to the data source identifier of the map topic, and set the corresponding data source for the topic. The data source can be a data table or view, storage In Table 1 thematic indicator information configuration table.

field name field description ZBGUID Indicator coding ZBNAME Indicator name IS_BGT Whether multi-dimensional analysis indicators TABLE_NAME The area data corresponds to the data table or view name SHOW_TEXT Data query display field

Table 1 Thematic indicator information configuration table

S120. Configure multi-dimensional analysis data, generate a multi-dimensional analysis data indicator table based on the topic indicator information configuration table, and prepare map topic area indicator data.

To prepare the map thematic area indicator data, it can be divided into the following two steps:

Step 2.1 Configure multi-dimensional analysis data, which is to generate multi-dimensional analysis data indicator table based on thematic indicator information configuration table, which is used for fast multi-dimensional analysis. The indicator data table is a three-dimensional cube with dimensions: topic, time, area, measure: indicator value, basis The prepared corresponding data associated with multi-dimensional analysis and indicators is stored in the indicator table of dimensional analysis data in Table 2. The ZBGUID field in the table and the ZBGUID field in Table 1 are associated fields.

field name field description DQ area code RQ datetime ZBGUID Indicator coding ZBVALUE Index value

Table 2 Multidimensional analysis data indicators table

Step 2.2 Prepare the data table or view corresponding to the thematic data source. The structure of the table or view corresponding to the data must contain the requirements of Table 3. After preparation, add the corresponding data table name and data query display fields to Table 1.

Table 3 Data source structure template corresponding to the theme

By agreeing on the structure of the data source, it is convenient to quickly add or adjust topics. After the configuration is completed, the thematic identifiers in Table 3 can be maintained in the corresponding fields in Table 1.

S130 , establishing mass points for all location-related objects in the data center through a data preparation method based on the preset mass point categories, and generating a mass point data table.

Prepare indicator massive point data. Based on the method of data preparation based on the pre-set mass point categories, establish mass points for all location-related objects in the data center (such as poverty alleviation points, budget units, etc.), and generate a mass point data table. See Table 4 for the structure of the mass point data table .

field name field description AD_CODE zoning code ZBGUID Indicator coding MC Mass Point Names LAT latitude LNG longitude MSXX Descriptive information, massive point display information URL One-House Analysis Link

Table 4 Mass Point Data Table Structure

S140. Dynamically construct a display area based on the user's initiation, wherein the bottom layer of the display area is a geographic information system GIS map, a left suspension condition area, a right suspension analysis icon area, the left suspension condition area and the multi-dimensional The analysis data indicator table is related, and the right-side floating analysis icon area is related to the massive point data table.

Dynamically build display areas. After completing the above three steps, after the user opens the map, the area layout will be displayed, see Figure 2. The bottom layer is a GIS map, and the condition area is suspended on the left, where you can select thematic indicators, selection area, selection time and other conditions; the right side is suspended in the analysis chart area. Dynamically build map area representations and multidimensional analysis based on selection criteria. Among them, the region selection can obtain the recommended focus region according to the algorithm through interactive operation on the map. For details, please refer to FIG. 2 for an understanding of the dynamic construction area layout, which will not be repeated here.

Recommended focus area. After the user drags the map, zooms the level, clicks through, etc., the user's focus area under the area level is automatically identified through a special algorithm.

The algorithm is divided into the following steps:

1. Get the basic parameters of the page. According to the coordinates of the four extreme values of the current screen, obtain the maximum and minimum longitude C_GL, C_TL, the maximum and minimum latitude C_GS, C_TS, obtain the center point of the screen as C, and obtain the original map level F before the interactive page change and the interactive page change After the current map level R.

2. Obtain a list of district codes for the area to be selected. This step depends on the prefabricated zoning level table of the system, see Table 5.

field name field description QH_CODE standard zoning code QH_NAME Standard zoning name MAP_LVL Default map level aL Regional latitude maximum aS Minimum area latitude bL The maximum longitude of the region bS Minimum area longitude QH_C Regional center point coordinates

Table 5 Prefabricated division level table

When the corresponding zone in the table satisfies both of the following conditions:

Condition 1:

The current map level R≥original map level F, then the value range of the division level is the range of plus or minus 1 for the current map level. or,

The current map level R<original map level F, then the value range of the division level is the range from the current map level to the current level minus 2.

The formula is as follows:

IF(R≥F){(MAP_LVL IN(R-1～R+1)}ELSE IF(R<F){(MAP_LVL IN(R-2～R)}.

It should be noted that the condition 1 is a result obtained based on the user's operation behavior. When R is greater than F, it is a reduction operation, and when R is less than F, it is an expansion operation. The two value ranges are defined according to the user's specific operation behavior. Ability to optimize selection based on user behavior.

Condition 2:

The system prefabricated zoning level sub-table divides the maximum and minimum values of longitude aL, aS, and the maximum and minimum values of latitude bL, bS. Satisfy the maximum value of longitude or the minimum value of longitude in the display screen, and the maximum value and minimum value of latitude in the display screen, the formula is as follows:

(C_GL>aL>C_GS||C_GL>aS>C_GS)&&(C_TL>bL>C_TS||C_TL>bS>C_TS).

Then this area is recommended and added to the area to be selected.

3. Algorithm calculation area. Calculate the score of the recommended administrative division of the candidate area.

Please refer to Figure 3, the specific calculation process is as follows:

First, obtain the area of the screen display area, use the difference between the maximum and minimum longitudes of the extreme coordinates of the display area as the length, and the difference between the maximum and minimum latitudes as the width to obtain the display area area C_MJ, the formula is as follows: C_MJ=(C_GL-C_GS)*(C_TL -C_TS).

Score calculation indicators:

3.1) Scoring method: whether the center point of the screen is within the current and calculated area to be selected. That is, the area to be selected needs to satisfy: the coordinate longitude of the screen center point is within the maximum and minimum longitude of the region, and the coordinate latitude of the screen center point is within the maximum and minimum latitude of the region, if it is satisfied, the value of a is recorded as the set score, otherwise the value of a Recorded as 0 points. Exemplarily, the set score may be 3 points. The set score can be valued according to actual needs, and the value of 3 points is only used as an example of this application, and this example cannot be used as a limitation of this application.

The formula is: a=IF(bL>C>bS&&aL>C>aS){3}ELSE{0}

3.2) Weighting method: the area of the area to be selected in the display area ÷ the area of the display area × 10, if the result is greater than the set threshold, the fixed gradient score will be subtracted from the result.

Exemplarily, the set threshold may be 7, and the fixed gradient score may be 4. The set threshold and the fixed gradient value can be set according to actual requirements. This application only uses the set threshold value of 7 and the fixed gradient score of 4 as an example, which cannot be used as a limitation of the application.

Area to be selected in the display area = length x width.

Among them, the long value method includes:

1.1) Calculate the result of [(If the maximum longitude of the region is greater than C_GL, use C_GL, otherwise use bL) minus (if the minimum longitude of the region is less than C_GS, use C_GS, otherwise use bS);

1.2) If the calculation result is a non-negative number, the result is taken as a long value;

1.3) If the result is negative, the long value is 0.

Wide value methods include:

2.1) Calculate the result of [(If the maximum regional latitude is greater than C_TL, use C_TL, otherwise use aL) minus (if the regional minimum latitude is less than C_TS, use C_TS, otherwise use aS);

2.2) If the calculation result is a non-negative number, the result is taken as the value of width;

2.3) If the calculation result is a negative number, the value of width is 0.

After calculating the area to be selected in the display area, calculate the value of b:

3.1), b = the area of the area to be selected in the display area ÷ the area of the display area × 10;

3.2) Determine whether the value of b is greater than 7. If the value of b is greater than 7, assign the result obtained by subtracting 4 from the value of b to b.

The specific calculation formula of the above calculation steps is as follows:

long = (IF(bL>C_GL){C_GL}ELSE{bL}-IF(bS<C_GS){C_GS}ELSE{bS})

Width = (IF(aL>C_TL){C_TL}ELSE{aL}-IF(aS<C_TS){C_TS}ELSE{aS})

b=IF(length<0){0}ELSE{length}*IF(width<0){0}ELSE{width}/C_MJ*10

b=IF(b>7){b-4}

3.3) Ranking method: Find the distance from the center point of all the districts to be selected to the center point of the screen and calculate the ranking score. Sort by distance according to the order from small to large, and the value of the zone with the smallest distance from the center point is assigned and decreased, and the obtained value is recorded as c.

Exemplarily, if the value (5) of the area with the smallest distance from the center point is assigned to the lower area in sequence, it is decremented by 5÷the number of areas to be selected and multiplied by 2, and the obtained result is c. The value of the zone with the smallest distance from the center point is 5, which is only an example, and is not a limitation of the present application, and may be other natural numbers. The specific formula is:

Set the number of lists to be divided into lists as list.length;

得值从小到大排序，list[0]得c＝5、list[1]得c＝5–(5/list.length*1)、list[2]得c＝5–(5/list.length*2)、list[n]得c＝5–(5/list.length*n)。其中，QH_C经度为地区中心点的经度的，QH_C纬度为地区中心点的纬度；C经度为屏幕中心点的经度，C纬度为屏幕中心点的纬度。Sort the list internally, according to

The values are sorted from small to large, list[0] has c=5, list[1] has c=5–(5/list.length*1), and list[2] has c=5–(5/list.length *2), list[n] obtains c=5-(5/list.length*n). Among them, the longitude of QH_C is the longitude of the center point of the area, and the latitude of QH_C is the latitude of the center point of the area; the longitude of C is the longitude of the center point of the screen, and the latitude of C is the latitude of the center point of the screen.

3.4) The weight score is equal to a+b+c.

4. Data return. The administrative division with the highest score is the recommended administrative division, and the administrative division code of the area is returned to the foreground.

The calculation process is shown in Figure 3, and the screen area and the candidate area are shown in Figure 4. The simplest example, the algorithm calculation process is: first, for the regions of about 3,000 provinces, cities and counties in the country, preset the latitude and longitude coordinates of the center point of each region, the best Map level; secondly, obtain the map level of each area, which satisfies that the level is within the range of the map display level of the screen, and the latitude and longitude of the center point of each area is within the coordinates of the four vertices of the screen. The zone in the area is filtered and the central zone is located, and after the zone is obtained, the corresponding appropriate display level set in the table is combined and returned.

S150. When receiving the user's first opening instruction, the displayed focus area is the area preset by the system parameters, and the display level is the best display level to locate the preset area in combination with the recommended focus algorithm; When dragging the map, zooming the level, or clicking at least one of the map drawing surfaces, the optimal display area is recalculated through the recommended focus area algorithm, and repositioned to the optimal display level.

Smart switch. Turn on the device for the first time, the focus area is the area set by the system parameters, and combine the algorithm to locate the area and the best display level; in the case of initialization, the device will use the regional theme display as the entrance to display the regional theme and Multi-dimensional analysis data, the content of the map drawing surface in the figure is based on the relevant configuration in step 1 as the data basis, and the content of the multi-dimensional analysis part on the right is based on the relevant configuration in step 2.1 as the display basis, the linkage between the two can be through the indicators on the left map List to switch between different indicator data.

Secondly, when the user is operating, by dragging the map, zooming the level, clicking on the map drawing surface, etc., the device will recalculate and locate the best display area under the level according to the algorithm content of step 4, and Relocate to the optimal display level of the best division. For example, when the user operates a new area, the device will call the algorithm to obtain the current area and the best level, draw the area information, and then adjust the area to the best display level.

Once again, when the user's operation calls the algorithm to obtain the last-level division, and the current level is greater than the optimal display level by 2 or more, for example, in a specific township and county and you want to zoom in, the device will Switch the display mode by yourself according to the current region, the current indicator and the data in step 3, so that the user can see the massive point data under the region and indicator, and when the user selects a specific massive point, the one-stop link of the point is displayed (URL), as shown in Figure 5.

Finally, when the user operates again and calls the algorithm to obtain that the division is not the last-level division or is less than the last-level division display level plus 2, the device will also automatically switch to the corresponding thematic display module, and can dynamically switch between the two .

The invention provides a data analysis method, device and storage medium based on GIS map. The method includes: Step 110: configure thematic indicators, define core analysis indicators, assign index codes and display names, construct the relationship between the thematic indicators and the multi-dimensional analysis scheme, construct a data source identifier corresponding to the map topic data, and set the topic correspondence data source to generate a thematic index information configuration table; Step 120: configure multi-dimensional analysis data, generate a multi-dimensional analysis data indicator table based on the thematic index information configuration table, and prepare map thematic area indicator data; Step 130: based on pre-set Mass point category Through the method of data preparation, all location-related objects in the data center are set up to create mass points, and a mass point data table is generated; Step 140: Based on the user's initiation, dynamically construct a display area, wherein the bottom layer of the display area is geographic Information system GIS map, left suspension condition area, right suspension analysis icon area, the left suspension condition area is related to the multi-dimensional analysis data indicator table, and the right suspension analysis icon area is related to the massive point data table related.

Further, the present application provides a specific example taking the analysis of poverty alleviation in the financial field as an example. The method may specifically include:

Step 1 Configure thematic indicators, map codes, assign unique identifiers, indicator codes and display names, and establish the indicator as a multi-dimensional analysis plan indicator, as shown in Table 6.

Table 6

Step 2 Prepare the map thematic area indicator data.

Step 2.1 Configure multidimensional analysis data, as shown in Table 7.

area code datetime Indicator coding Index value 4201 2020 101 1000 4202 2020 101 2000 4203 2020 101 3000 ... ... ... ...

Table 7

Step 2.2 Prepare the data table corresponding to the thematic data source, prepare the corresponding data table Bda_t_map_ztt_fp and meet the data table field requirements as shown in Table 8.

zoning code datetime Division level field 1 field 2 42 2020 2 1000 1000 4202 2020 3 2000 2000 420201 2020 4 3000 3000 ... ... ... ... ...

Table 8

Step 3: Prepare the indicator mass point data, as shown in Table 9.

zoning code Indicator coding Mass Point Names longitude latitude Descriptive information, massive point display information 4201 101 Enterprise one 136.00000 27.12300 Company name: 123; Poverty alleviation amount: 456 4201 101 unit two 136.12300 27.00000 Unit name: 456; Poverty alleviation amount: 123 ... ... ... ... ... ...

Table 9

Step 4 Dynamically construct the display area. After completing the configuration steps in steps 1-3, open the operation interface of the device, the device will use the user login authority as the initialization area location, and start to dynamically construct the area display.

When the user performs a roaming operation, the algorithm starts to calculate the next step.

1. Get the basic parameters of the page. Obtain the coordinates of the four extreme values: maximum and minimum latitude 45.5, 42.5, maximum and minimum longitude 132.333, 129.667, screen center point [44.000, 131.000], level 6 before the change, level 7 after the change

2. Obtain a list of district codes for the area to be selected. Query the data content of the prefabricated table that meets the following Where conditions

MAP_LVL IN(6,7,8)AND(45.5>aL>42.5 OR 45.5>aS>42.5)AND(132.333>bL>129.667 OR 132.333>bS>129.667)

Suppose that the list of all the districts to be selected that meets the conditions is obtained and contains 3 elements as follows:

3. Algorithm calculation area. Calculate the score of the recommended administrative division of the candidate area. Take the calculation process of BJ city when the level is 7 after the change as an example:

Calculate and obtain the screen display area C_MJ=(45.5-42.5)*(132.333-129.667)=7.998

Score calculation indicators:

3.1) Scoring method: whether the center point of the screen is within the area to be selected.

a=IF(43.111>44.000>43.100&&130.111>131.000>130.100){3}ELSE{0}=0

3.2) Weighting method: the proportion of the area to be selected in the display area:

long = [(IF(43.111>45.5){45.5}ELSE{43.111})-(IF(41.000<42.5){42.5}ELSE{43.100})]=0.611

wide = [(IF(130.111>132.333){132.333}ELSE{130.111})-

(IF(130.100<129.667){129.667}ELSE{130.100})]=0.011

b=IF(0.611<0){0}ELSE{0.611}*IF(0.011<0){0}ELSE{0.011}/7.998*10≈0.008

b=IF(b>7){b–4}=0.008

3.3) Ranking method: Find the distance from the center point of all the districts to be selected to the center point of the screen and calculate the ranking score.

Take the first element in the list to find the distance between the center points of the element as:

Calculate the distance between the center points of all three elements by analogy, and sort the list from small to large according to the value. Taking Figure 6 as an example, the following ranking and weight score list are obtained.

ranking area rank score 1 BJ City 5 2 TJ City 5–(5/3*1)=3.333 3 HB Province 5–(5/3*2)=1.666

4. Data return. Finally, count the sum of the scores between 3.1 and 3.3, take the administrative division with the highest score as the recommended administrative division, and return the administrative division code and best display level of the area to the front desk.

Assume that BJ City and HB Province are used as examples in Figure 6 and Figure 7. In the case shown in Figure 6, the map level is 8. Although the center point of BJ city is closer to the center point of the screen, this algorithm combines the position, area and distance of the center point to calculate the score with multiple weights, and finally HB province is the most important If the user clicks and drills down to trigger the algorithm, the device will automatically locate the best display layer in the province, otherwise the display area has to be switched.

The scene area scores are as follows:

ranking area total score 3.1 Step Score 3.2 Step Score 3.3 Step Score 1 HB Province 9.83 3 3.5 3.33 2 BJ City 9.3 3 1.3 5 3 TJ City 2.36 0 0.7 1.66

In the case shown in Figure 7, the map level is 9, and contrary to Figure 6, BJ City will be the best display area, and the default display level will be returned.

The scene area scores are as follows:

ranking area total score 3.1 Step Score 3.2 Step Score 3.3 Step Score 1 HB Province 12.33 3 6 3.33 2 BJ City 12.5 3 4.5 5 3 TJ City 5.26 0 3.6 1.66

Step 5: Device smart display switching. Based on the above configuration in combination with the device algorithm, the user can use the system parameter preset area combination algorithm to locate the current area location and the best display area during initialization, and view the summary data content of poverty alleviation topics in the current area. Switch between thematic display and massive point display by yourself, if you do not manually switch.

When the user drags the map, zooms the level, clicks on the map drawing surface, etc., the device will recalculate and locate the best display area under the level according to the content of the algorithm in step 4, and relocate to the best display area. The optimal display level of the division. For example, when the user operates to a new area, the device will call the algorithm to obtain the current area and the best level, draw the area information, and then adjust the area to the best display level.

When the user's operation calls the algorithm to obtain the last-level division, and the current level is more than 2 levels higher than the optimal display level, such as a specific township and county and wants to zoom in, the device will The region, the current indicator, and the data in step 3 can automatically switch the display mode, so that the user can see the massive point data under the region and indicator, and when the user selects a specific massive point, the one-stop link (URL) of the point is displayed. ).

The effect of the invention is that: an analysis framework is established, which integrates three types of analysis tools: GIS map, multi-dimensional analysis and one-house report, so as to realize the step-by-step penetration analysis from macro to micro, and only need to configure the data source of thematic indicators , no code development is required, work efficiency is improved, and penetrating monitoring of "one pole in the bottom" in business is satisfied.

And in the regional positioning of the map, through an algorithm, comprehensive scoring items, weight ratio, ranking score and other methods, intelligently obtain the focus area. It solves the problem that the traditional map can only penetrate through and find the weaknesses of the region according to the defined level in the interactive operation of the map.

The data analysis method based on GIS map provided by this application has the following advantages:

1. Integration. Multi-dimensional analysis and chart analysis are integrated on the GIS map, and the method and content of map analysis have been greatly improved, making it possible to analyze "one stick to the bottom".

2. Configurability. The new thematic indicators can be realized only through configuration to meet the needs of business expansion.

3. Efficiency. When operating the map to find the area, an algorithm is used to automatically obtain the focus area, thereby improving the user's operating experience.

8 is a schematic structural diagram of a GIS map-based data analysis device provided by an embodiment of the present application. The GIS map-based data analysis device 200 may have relatively large differences due to different configurations or performances, and may include one or more than one A processor (central processing unit, CPU) 210 (eg, one or more processors) and a memory 220, one or more storage media 230 (eg, one or more mass storage devices) storing application programs 233 or data 232. Wherein, the memory 220 and the storage medium 230 may be short-term storage or persistent storage. The program stored in the storage medium 230 may include one or more modules (not shown in the figure), and each module may include a series of instructions to operate on the GIS map-based data analysis apparatus 200 . Furthermore, the processor 210 may be configured to communicate with the storage medium 230 to execute a series of instruction operations in the storage medium 230 on the local government debt risk assessment apparatus 200 .

The GIS map-based data analysis device 200 may also include one or more power supplies 240, one or more wired or wireless network interfaces 230, one or more input and output interfaces 260, and/or, one or more operating systems 231, For example Windows Serve, Mac OS X, Unix, Linux, FreeBSD and many more. Those skilled in the art can understand that the data analysis apparatus based on the GIS map shown in FIG. 8 does not constitute a limitation on the data processing equipment, and may include more or less components than those shown in the figure, or combine some components, or different component layout.

The present application also provides a computer-readable storage medium. The computer-readable storage medium may be a non-volatile computer-readable storage medium. The computer-readable storage medium may also be a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to execute the steps of the GIS map-based data analysis method.

Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and unit described above may refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

The integrated unit, if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application can be embodied in the form of software products in essence, or the parts that contribute to the prior art, or all or part of the technical solutions, and the computer software products are stored in a storage medium , including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: U disk, removable hard disk, read-only memory (RON), random access memory (RAM), magnetic disk or optical disk and other media that can store program codes .

In the embodiments provided in the present application, it should be understood that the disclosed methods may be implemented in other manners without exceeding the spirit and scope of the present application. The present embodiment is only an exemplary example and should not be taken as a limitation, and the specific content given should not limit the purpose of this application. For example, some features can be ignored, or not implemented.

The technical means disclosed in the solution of the present application are not limited to the technical means disclosed in the above embodiments, but also include technical solutions composed of any combination of the above technical features. It should be pointed out that for those skilled in the art, without departing from the principles of the present application, several improvements and modifications can also be made, and these improvements and modifications are also regarded as the protection scope of the present application.

A GIS map-based data analysis method, device, and storage medium provided by the embodiments of the present application have been described above in detail. The principles and implementations of the present application are described with specific examples in this article. It is only used to help understand the method of the present application and its core idea; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific embodiments and application scope. In summary, The contents of this specification should not be construed as limiting the application. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it is still possible to modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements to some of the technical features; and these Modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims (10)

1. A GIS map-based data analysis method, characterized in that the method comprises:

step 110: configuring thematic indexes, defining core analysis indexes, distributing index codes and display names, constructing the relation between the thematic indexes and a multi-dimensional analysis scheme, constructing data source identifications corresponding to data of map thematic, and setting data sources corresponding to the thematic to generate a thematic index information configuration table;

step 120: configuring multidimensional analysis data, generating a multidimensional analysis data index table based on the thematic index information configuration table, and preparing map thematic area index data;

step 130: establishing mass points for all position-related objects of a data center by a data preparation method based on mass point categories preset in advance to generate a mass point data table;

step 140: based on the starting of a user, dynamically constructing a display area, wherein the bottom layer of the display area is a Geographic Information System (GIS) map, a left suspension condition area and a right suspension analysis icon area, the left suspension condition area is related to the multi-dimensional analysis data index table, and the right suspension analysis icon area is related to the mass point data table.

2. The GIS map-based data analysis method of claim 1, further comprising:

step 150: when a user first opening instruction is received, the displayed focus area is an area preset by system parameters, and the display level is an optimal display level for positioning the preset area by combining a recommended focus algorithm; when receiving at least one operation of dragging the map, zooming the level or clicking the map drawing surface by the user, recalculating the optimal display area through the recommended focus area algorithm, and repositioning to the optimal display level.

3. The GIS map-based data analysis method of claim 1, wherein, in the step 110,

the data source may be a data table or view.

4. The GIS map based data analysis method of claim 1, wherein in step 120,

the multi-dimensional analysis data index table is used for rapid multi-dimensional analysis, and the multi-dimensional analysis data index table is a three-dimensional cube, wherein the dimensions of the three-dimensional cube comprise: topic, time, area;

in the step 140, the process is carried out,

the user can select special subjects, time and area conditions from the left side floating condition area, and the user can dynamically construct map area display and multidimensional analysis from the right side floating analysis icon area selection conditions.

5. The GIS map-based data analysis method of claim 2, wherein the recommended focus area algorithm in step 150 specifically comprises:

step 151: acquiring page basic parameters, wherein the page basic parameters comprise: the maximum value and the minimum value of the longitude are respectively C _ GL and C _ TL, the maximum value and the minimum value of the latitude are respectively C _ GS and C _ TS, the central point of a screen is obtained as C, and an original map level F before the interactive page changes and a current map level R after the interactive page changes are obtained;

step 152: acquiring a partition coding list of a to-be-selected partition, wherein the partition coding list of the to-be-selected partition is related to a preset partition level list, and determining whether a partition corresponding to the partition coding list of the to-be-selected partition is a recommended partition according to the page basic parameters;

step 153: and calculating the score of the recommended administrative division of the area to be selected according to the area to be selected division coding list.

6. The GIS map-based data analysis method of claim 5, wherein said step 152 specifically comprises:

when the to-be-selected area partition coding list simultaneously meets two conditions, determining that a partition corresponding to the to-be-selected area partition coding list is a recommended partition, and adding the recommended partition into the to-be-selected area, wherein the two conditions comprise:

condition 1: if the current map level R is larger than or equal to the original map level F, the partition level numeric area is the area of plus or minus 1 of the current map level; or if the current map level R is smaller than the original map level F, the partition level sub-value range is the range from the current map level to the current level minus 2;

condition 2: the maximum value and the minimum value of the division longitude of the preset division level list are aL and aS respectively, the maximum value and the minimum value of the division longitude latitude of the preset division level list are bL and bS respectively, the maximum value and the minimum value of the division longitude of the preset division level list are displayed on a screen, and the maximum value and the minimum value of the latitude are displayed on the display screen.

7. The GIS map-based data analysis method according to claim 6, wherein the step 153 specifically comprises:

taking the difference between the maximum value C _ GL and the minimum value C _ TL of the longitude as the length, and taking the maximum value C _ GS and the minimum value C _ TS of the latitude as the width to obtain the area of the screen display area;

and calculating the score of the recommended administrative division of the area to be selected according to the area of the screen display area.

8. The GIS map-based data analysis method according to claim 7, wherein the calculating the score of the recommended administrative division of the area to be selected according to the area of the screen display area specifically comprises:

judging whether the coordinate longitude of the central point of the screen is within the range of the maximum longitude and the minimum longitude of the region or not, and the coordinate latitude of the central point of the screen is within the range of the maximum latitude and the minimum latitude of the region, if so, recording the value a as a set score;

the area of the to-be-selected region in the display region is divided by the area of the display region multiplied by 10, the result is b, whether the value b is larger than a set threshold value or not is judged, and if the value b is larger than the set threshold value, the result obtained by subtracting the set gradient score from the value b is assigned to b;

obtaining the distances from the center points of all compartments to be selected to the center point of the screen, calculating ranking scores, sorting the compartments according to the sequence from small to large according to the distance sorting, assigning the value of the compartment with the smallest distance from the center point downwards, and gradually reducing the value, wherein the obtained value is marked as c;

the resulting weight score was designated as a + b + c.

9. A GIS map-based data analysis apparatus, the apparatus comprising: a memory having code stored therein, and a processor configured to execute the code, the terminal performing the GIS map-based data analysis method of any one of claims 1 to 8 when the code is executed.

10. A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform the GIS map-based data analysis method of any one of claims 1 to 8.

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