CN115186074B - Method for simulating soil pH value spatial distribution pattern based on Meta analysis - Google Patents
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Abstract
The invention discloses a method for simulating a soil pH value spatial distribution pattern based on Meta analysis, which belongs to the premise of keeping the soil pH value spatial variation in local areas and gives consideration to the global spatial variation characteristic. Firstly, searching and screening soil data according to keywords; screening relevant data and information of the pH value of the soil from the soil data; generating a geometric center point of a corresponding four-level administrative region according to the face data of the four-level administrative regions of China provinces, cities, counties and towns; adding a pH attribute value to geometric center points of each administrative area by using the pH value of the soil obtained from the literature; and interpolating the obtained space discrete point data, and converting the space discrete point data into space continuous data to obtain a space distribution map of the soil pH. The invention collects data of different types and different scales based on Meta analysis, and creates a set of method for integrating spatial distribution patterns of different types and different scale data acquisition area scale research objects.
Description
Technical Field
The invention belongs to the technical field of space geographic information, and particularly relates to a method for simulating a soil pH value spatial distribution pattern based on Meta analysis.
Background
Meta analysis is commonly used for quantitative pooled analysis of system reviews. By integrating all relevant studies, it is advantageous to explore the consistency of evidence for each study and the variability between studies, as compared to a single study. And when a plurality of research results are inconsistent or have no statistical significance, the statistical analysis result close to the real situation can be obtained by adopting Meta analysis. However, when Meta analysis is used to integrate different research results, the idea is to trend to the same true value; however, the spatial distribution pattern discusses its spatial heterogeneity, so that the existing Meta analysis method cannot be applied to the simulation of the spatial distribution pattern of the regional scale.
Aiming at the research of a certain regional scale, such as the simulation of the heterogeneity of the spatial distribution pattern of the soil pH value of the national scale, if the soil pH value is obtained by simply adopting the modes of sample point arrangement, sampling, physicochemical analysis and interpolation, the time and the labor are very consumed. A large number of published documents report the observation data of the soil pH value in each region of China, but the data are different in measurement scale and number presentation mode according to the own research purpose, and the spatial distribution pattern of the soil pH value in the whole country is difficult to obtain by directly adopting an interpolation method, so that the data are collected, classified and distributed, and the spatial distribution pattern of the soil pH value in the whole country is obtained by adopting the interpolation method.
Disclosure of Invention
In view of the above problems, the method provided by the present patent makes the best use of the collected data, and gives consideration to the spatial variation characteristics of the soil pH values of the local area and the whole area, so as to obtain the spatial-temporal distribution pattern of the soil pH values of the chinese area.
The invention adopts the technical scheme that:
a method for simulating a soil pH spatial distribution pattern based on Meta analysis, comprising the steps of:
step 1: retrieving and screening soil data according to the keywords;
step 2: screening relevant data and information of the pH value of the soil from the soil data;
step 3: generating a geometric center point of a corresponding four-level administrative region according to the face data of the four-level administrative regions of China provinces, cities, counties and towns;
step 4: adding a pH attribute value to geometric center points of each administrative area by using the pH value of the soil obtained from the literature;
step 5: and (3) interpolating the space discrete point data obtained in the step (4), and converting the space discrete point data into space continuous data to obtain a space distribution map of the soil pH.
Further, in step 1, the screening criteria of the soil data include: the method comprises the steps of containing study area position information and sample number information; the pH analysis and test method is required to adopt industry standard; the pH value of the soil can be extracted from the characters, the tables and the images.
Further, in step 2, the article title, publication year, publication, and recorded study site name, study site type, study site coordinates, number of samples, and detected soil pH value of the test soil pH experiment are extracted from the screened document.
Further, after extracting data, performing data heterogeneity test, selecting I 2 The formula for checking the data heterogeneity is as follows:
wherein: q is the sum of the weighted mean squares of the effects, df is the degree of freedom, I 2 The value of (2) reflects the degree of data heterogeneity, the larger the value is, the larger the heterogeneity is, the I 2 Less than 50% indicates homogeneity of the study, and a fixed model can be selected as the calculation model in the analysis, I 2 Above 50%, further sensitivity analysis is required to screen off outliers.
Further, in step 4, generating corresponding four-level geometric center point data by using face data of four-level administrative division of province, city, county and village, adding a field representing the pH value of soil in an attribute table of each level geometric center point data, recording the pH value of the soil at each location by using the field, wherein the initial attribute value defaults to 100; the specific implementation method of the step 4 is as follows:
step 41: firstly, calculating a weighted average value of sampling data of the soil pH value of the region at the level according to the zone name of the statistical data;
step 42: this weighted average is assigned to the geometric center point of the next-level administrative district that it is subordinate to.
Further, in step 41, the average concentration of soil pH in each zone is obtained by taking the number of samples of the soil pH detection experiment in each document as a weight, and the formula is as follows:
in the pH value i，a Is the average pH of the soil in the i region of administrative class a; pH value i，n Is the n-th recorded pH of the soil in zone i; m is m i，n Is the number of samples recorded by the nth of the soil in the i zone; n is the total number of all records of the i area in administrative level a.
Further, in step 42, the calculated pH average concentration of each area in each administrative level is assigned to the geometric center of the area of the next administrative level subordinate thereto, the first-level soil pH average value is assigned to the city geometric center point subordinate thereto, and the first-level soil pH average value is assigned to the county first-level geometric center point subordinate thereto; the average value of the pH of the soil of the county level is assigned to the geometric center point of the level of the villages and towns subordinate to the average value, and the data of the level below the villages and towns are used as point source data.
Further, in step 5, four types of soil pH values are combined into a point data file, and the discrete point pH data is converted into spatially continuous data by using a spatial interpolation method.
The beneficial effects are that: compared with the prior art, the invention has the following advantages:
according to the method for simulating the spatial distribution pattern of the soil pH value based on the Meta analysis, based on collected data of different types and different scales, the data are converted into data of point types, and then the spatial distribution pattern of the soil pH value of the regional scale is obtained through interpolation. The prior art is often a method for carrying out in-situ sampling measurement on a local area to obtain point data containing soil pH, and the method is time-consuming and labor-consuming and can only be implemented on the local area. Therefore, compared with the method based on the field monitoring information, the method for realizing the spatialization of the research elements based on the method of collecting the data by the Meta analysis, provided by the invention, can greatly save funds and time cost. Compared with the traditional Meta analysis (the Meta analysis is a statistical method for quantitatively and comprehensively evaluating a plurality of similar independent research results based on literature data), the invention creates a set of data preprocessing method, integrates spatial data with different scales, further performs the spatial analysis, and is an important supplement for the Meta analysis.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a graph of the results of the present invention for extracting a portion of data from a large number of documents;
FIG. 3 is a schematic diagram of the geometric center points of provincial, municipal, county, and village-town levels of the present invention;
FIG. 4 is a schematic representation of the spatial distribution of pH in the soil between various levels of administrative divisions according to the present invention.
Detailed Description
The invention will be further illustrated with reference to specific examples, which are carried out on the basis of the technical solutions of the invention, it being understood that these examples are only intended to illustrate the invention and are not intended to limit the scope thereof.
As shown in fig. 1, the method for simulating the spatial distribution pattern of the pH value of the soil based on Meta analysis of the present invention comprises the following specific steps:
step 1: retrieving and screening soil data according to the keywords;
searching documents in mainstream document databases such as a China knowledge network (CNKI) AND the Web of Science (WOS), AND performing document screening work according to a definite standard, wherein Soil AND pH is used as a Chinese document searching keyword AND oil AND pH is used as an English document searching keyword in the searching process; and (3) carrying out document screening on the corresponding standard after document retrieval, wherein the screening standard comprises the following steps: (1) the literature needs to contain study area position information and sample number information; (2) the pH analysis and test method used in the literature needs to adopt industry standards; (3) the pH value of the soil can be extracted from the characters, tables and images of the literature.
Step 2: screening relevant data and information of the pH value of the soil from the soil data;
and extracting relevant data and information of the soil pH value of each zone from soil experimental data published in the literature, and carrying out pretreatment such as abnormal value screening on the data. The article title, publication year, publication and recorded research location name, research location type, research location coordinate, experiment sample number and detected soil pH value of the experiment of detecting soil pH are extracted from the screened literature, wherein the research location type comprises 5 types in total, namely, the type of the surface source data is province, the city, county and the point source data, namely, the villages and towns and below villages and towns, the type of the surface source data needs to record the accurate names of specific research areas of corresponding administrative levels, the data of the point source type needs to use the specific village names or geographical location names, the detailed longitude and latitude coordinates of the research areas are obtained based on a pick-up coordinate system provided by a hundred-degree map, and the statistical result of the data is shown in figure 2.
Counting the number of samples in the soil pH detection experiments recorded in each document and the pH value of each sample detected by the experiments; the statistical data were then checked for data heterogeneity using the Meta analysis kit in R Studio, option I 2 The formula for checking the data heterogeneity is as follows:
where Q is the sum of the weighted mean squares of the effects, df is the degree of freedom, I 2 The value of (2) reflects the degree of data heterogeneity, the larger the value is, the larger the heterogeneity is, the I 2 Less than 50% indicates homogeneity of the study, and a fixed model can be selected as the calculation model in the analysis, I 2 Above 50% further sensitivity analysis is required.
Step 3: and generating corresponding four-level geometric center point data according to the face data of the four-level administrative regions of provinces, cities, counties and towns.
Firstly, the ArcGIS is utilized to respectively obtain the midpoint value of the face element of each administrative grade in the X-axis direction and the midpoint value of the face element of each administrative grade in the Y-axis direction, and the coordinate combination of the midpoint values in the two directions is the geometric center point of the face element of each administrative grade, as shown in figure 3, so that the province geometric center point file, the city geometric center point file, the county geometric center point file and the village and town geometric center point file are respectively obtained. Adding fields in an attribute table of each level of geometric center point data: the initial value of the "soil_ph" field defaults to 100, and the soil pH value of each region is recorded using this field value.
Step 4: and adding the pH attribute value to the geometric center points of each administrative district by using the pH value of the soil obtained from the literature.
Generating corresponding four-level geometric center point data by using the face data of four-level administrative division of provinces, cities, counties and towns, adding a field representing the pH value of soil in an attribute table of each level of geometric center point data, recording the pH value of the soil at each location by using the field, and defaulting to 100 as an initial attribute value. The method specifically comprises the following steps:
(1) Data collected from the same region at a certain level is obtained from a plurality of documents, and firstly, a weighted average value of sampling data of soil pH value of the region at the certain level is calculated according to the zone name of the statistical data;
since the average pH value is selected as the data representative of a certain research result when the literature data is extracted, and the number of research samples of each literature is different, so that the information carried by each data is different, the average pH concentration of soil in each region is obtained by taking the sample number of soil pH detection experiments in each literature as a weight, and the formula is as follows:
in the pH value i，a Is the average pH of the soil in the i region of administrative class a; pH value i，n Is the n-th recorded pH of the soil in zone i; m is m i，n Is the number of samples recorded by the nth of the soil in the i zone; n is the total number of all records of the i area in administrative level a.
(2) This weighted average is assigned to the geometric center point of the next-level administrative district that it is subordinate to.
The calculated pH average concentration of each area in each administrative level is assigned to the geometric center of the area of the subordinate next-level administrative level, the first-level soil pH average value is assigned to the subordinate city geometric center point, and the first-level soil pH average value is assigned to the subordinate county first-level geometric center point; the county level soil pH average is assigned to the geometric center point of the subordinate village level, the village level and the data of the level below the village as point source data, as shown in figure 4. The five types of data finally collected are displayed in the form of point data in the geographic space, and then a point data file is synthesized, and the specific implementation mode is as follows:
the presentation party in the form of point data in the geographic space is: generating point data in ArcGIS according to recorded longitude and latitude coordinates by combining the obtained point data with the geometric center point data of the city, county and village recorded with the pH value of the soil into a point data file, thereby obtaining discrete point data recorded with the pH value of the soil.
Step 5: embodiments utilize common interpolation methods: and (3) performing difference value on the soil pH discrete point data of each zone by an inverse distance weight interpolation method (IDW), and converting the difference value into space continuous data to obtain a simulated space distribution diagram of the soil pH.
In ArcGIS, an IDW method is selected, discrete point data recorded with the pH value of the soil obtained in the step 4 is used as input data, and the soil pH value is interpolated in the whole Chinese area, so that a spatial distribution map of the soil pH value is obtained, and the specific implementation mode is as follows:
four types of soil pH values are combined into a point data file. Discrete point pH data is converted to spatially continuous data using the IDW method. The IDW assumes that the value of the point to be interpolated is more influenced by the near known point than the far known point, and the calculation formula is:
wherein Z is j Is the pH estimated value of the point j to be interpolated, Z i Is the pH value of the known point i, d i Is the distance between the known point i and the point j to be interpolated, S is the number of known points used in estimating the pH value of the interpolation point, k is a definite power, the power k controls the degree of local influence, defaulting to 2, as the power increases, the pH value of the point to be interpolated will gradually approach the pH value of the nearest known point, the surface will become more detailed (less smooth), the pH of the known point will be given a smaller power valuePoints farther away have a greater impact, resulting in smoother planes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (6)
1. A method for simulating a soil pH value spatial distribution pattern based on Meta analysis is characterized by comprising the following steps of: the method comprises the following steps:
step 1: retrieving and screening soil data according to the keywords;
step 2: screening relevant data and information of the pH value of the soil from the soil data;
step 3: generating a geometric center point of a corresponding four-level administrative region according to the face data of the four-level administrative regions of China provinces, cities, counties and towns; step 4: adding a pH attribute value to geometric center points of each administrative area by using the pH value of the soil obtained from the literature; the specific implementation mode is as follows:
generating corresponding four-level geometric center point data by using the face data of four-level administrative division of provinces, cities, counties and towns, adding a field representing the pH value of soil in an attribute table of each level of geometric center point data, recording the pH value of the soil at each location by using the field, and defaulting the initial attribute value to be 100;
step 41: firstly, calculating a weighted average value of sampling data of the soil pH value of the region at the level according to the zone name of the statistical data;
step 42: assigning the weighted average value to the geometric center point of the next-level administrative district subordinate to the weighted average value;
the calculated pH average concentration of each area in each administrative level is assigned to the geometric center of the area of the subordinate next-level administrative level, the pH average value of the provincial first-level soil is assigned to the subordinate city geometric center point, and the pH average value of the municipal first-level soil is assigned to the subordinate county first-level geometric center point; the average value of the pH of the soil of the county level is assigned to the geometric center point of the level of the villages and towns subordinate to the average value, and the data of the level below the villages and towns are used as point source data;
step 5: and (3) interpolating the space discrete point data obtained in the step (4), and converting the space discrete point data into space continuous data to obtain a space distribution map of the soil pH.
2. The method for simulating a spatial distribution pattern of soil pH values based on Meta analysis of claim 1, wherein: in step 1, the screening criteria of the soil data include: the method comprises the steps of containing study area position information and sample number information; the pH analysis and test method is required to adopt industry standard; the pH value of the soil can be extracted from the characters, the tables and the images.
3. The method for simulating a spatial distribution pattern of soil pH values based on Meta analysis of claim 1, wherein: in step 2, the article title, publication year, publication and recorded study location name, study location type, study location coordinates, number of samples and detected soil pH value of the experiment for detecting soil pH are extracted from the screened document.
4. A method of modeling soil pH spatial distribution pattern based on Meta analysis according to claim 3, wherein: after extracting data, checking data heterogeneity, selecting I 2 The formula for checking the data heterogeneity is as follows:
wherein: q is the sum of the weighted mean squares of the effects, df is the degree of freedom, I 2 The value of (2) reflects the degree of data heterogeneity, the larger the value is, the larger the heterogeneity is, the I 2 Less than 50% indicates homogeneity of the study, and a fixed model is selected as a calculation model in the analysis, I 2 Above 50%, further sensitivity analysis was performed to screen off outliers.
5. The method for simulating a spatial distribution pattern of soil pH values based on Meta analysis of claim 1, wherein: in step 41, the average concentration of soil pH in each zone is obtained by weighting the number of samples of the soil pH detection experiment in each document, and the formula is as follows:
in the pH value i，a Is the average pH of the soil in the i region of administrative class a; pH value i，n Is the n-th recorded pH of the soil in zone i; m is m i，n Is the number of samples recorded by the nth of the soil in the i zone; n is the total number of all records of the i area in administrative level a.
6. The method for simulating a spatial distribution pattern of soil pH values based on Meta analysis of claim 1, wherein: in step 5, the four types of soil pH values are synthesized into a point data file, and the discrete point pH data are converted into space continuous data by using a space interpolation method.
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