CN112486963A - Multi-source data gridding cleaning method and system - Google Patents

Multi-source data gridding cleaning method and system Download PDF

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CN112486963A
CN112486963A CN202011346406.7A CN202011346406A CN112486963A CN 112486963 A CN112486963 A CN 112486963A CN 202011346406 A CN202011346406 A CN 202011346406A CN 112486963 A CN112486963 A CN 112486963A
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代佳佳
潘耀忠
王金云
郑学昌
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Beijing Normal University
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Abstract

The invention relates to a multi-source data gridding cleaning method and a system, wherein the county-level statistical standing population information is obtained from a statistical yearbook and is matched with administrative division information of a county, the population quantity of a to-be-distributed county is distributed according to county-level census data and population kilometer grid data, complete county-level standing population information is obtained, and the county-level standing population information is subjected to spatial correlation; the method comprises the steps of obtaining multi-source spatial data in each village and town boundary range in village and town level standing population information after spatial correlation, splicing the multi-source spatial data according to the village and town boundary, converting the multi-source spatial data into the same projection coordinate system, meshing the administrative boundary spatial region of the village and town, determining the multi-source spatial data, the village and town population number of each grid through spatial analysis and calculation, enabling population data, navigation data, land coverage data and night light data to be spliced in a seamless mode in space, and achieving meshing packaging of the population and spatial multi-source data.

Description

Multi-source data gridding cleaning method and system
Technical Field
The invention relates to the technical field of data processing, in particular to a multi-source data gridding cleaning method and system.
Background
At present, according to the yearbook of statistics, census data and the like, only population data of administrative units such as provinces, cities and counties in administrative regions can be obtained, population distribution data corresponding to spatial regions cannot be obtained, multi-source spatial data related to population distribution in the spatial regions cannot be obtained, and the obtained population data and the multi-source spatial data have the problems of loss, non-uniform data standards and the like, so that a reliable data basis cannot be provided for earthquake insurance loss evaluation, national economic development planning and the like.
Disclosure of Invention
The invention aims to provide a gridding cleaning method and a gridding cleaning system for multi-source data so as to realize gridding packaging of population and space multi-source data.
In order to achieve the purpose, the invention provides the following scheme:
a multi-source data gridding cleaning method, the method comprising:
acquiring county level statistical permanent population information of the year to be cleaned from a statistical yearbook; the village-town level statistics standing population information comprises a village-town code, a village-town name and a population number;
according to the village and town codes of the village and town level statistics standing population information, matching and associating the village and town statistical standing population information with the village and town administrative division information of the year to be cleaned, acquiring the village and town codes which are not matched with the village and town statistical standing population information in the village and town administrative division information and corresponding village and town names, and determining the village and town to be allocated; the town administrative division information comprises a town code, a town name and a town boundary;
distributing population quantity to the towns to be distributed according to township population census data and population kilometer grid data to obtain township distributed constant population information;
the township level statistical standing population information and the township level distribution standing population information form township level standing population information of the year to be cleaned;
according to the village and town code of the village and town level standing population information, performing spatial association on the village and town administrative division information of the year to be cleaned and the village and town standing population information by adopting a spatial association function of acgis software to obtain the village and town level standing population information after the spatial association;
acquiring multi-source spatial data within each village and town boundary range in the village and town level standing population information after spatial correlation; the multi-source space data comprises navigation data, land cover data and night light data;
splicing the multi-source space data according to the boundaries of the villages and the towns, and converting the spliced multi-source space data into the same projection coordinate system by using the projection conversion function of acgis software to obtain the projected multi-source space data;
gridding is carried out in a projection coordinate system by taking a village and town administrative boundary as a spatial region to obtain hectometer grid data;
determining projected multi-source spatial data contained in each grid in the hectometer grid data according to the projected multi-source spatial data;
and performing space intersection operation on the hectometer grid data and the village-level permanent population information after the space association, and determining the name of the village and the town where each grid is located in the hectometer grid data and the population quantity corresponding to the name of the village and the town where each grid is located.
Optionally, according to the country-level census data and the population kilometer grid data, it is right to wait to distribute the population quantity in the country, obtain the information of the country-level distribution population living in general, specifically include:
judging whether the towns to be distributed are successfully matched with towns codes in towns-level population census data or not, and obtaining a judgment result;
if the judgment result shows that the county and town occupation population proportion is larger than the preset county and town population proportion, acquiring population proportion of the county and town to be distributed occupying the county and city according to county and town population general survey data;
acquiring the population number of the county city of the towns to be distributed from the township level statistical standing population information;
determining the population number of the villages and towns to be distributed in the year to be cleaned according to the population number of the county and the city where the villages and towns to be distributed occupy and the population proportion of the county and the city where the villages and towns to be distributed occupy;
if the judgment result shows that the country boundary range to be distributed is not the statistical range, acquiring the population sum of the country in the statistical range and the population sum of the province where the country to be distributed is located from the population kilometer grid data by adopting a spatial statistical analysis method;
according to the population sum in the statistical range and the population sum of the province where the towns to be distributed are located, a formula is utilized
Figure BDA0002799949190000031
Determining the population number of towns to be distributed of the years to be cleaned;
the method comprises the following steps of acquiring statistics of the years to be cleaned, wherein y is the population number of towns to be distributed of the years to be cleaned, k is the population proportion of the towns to be distributed occupying the county and city, P is the population number of the county and city, the S is the population sum of the provinces, where the towns to be distributed are published by the statistics yearbook of the years to be cleaned, a is the population sum of the towns within the statistics range, and A is the population sum of the provinces, where the towns to be distributed are within the statistics range.
Optionally, the township level statistics lives population information with the township level distribution lives population information constitutes township level lives population information of the year of waiting to wash, and then still includes:
acquiring the population sum of each province according to the information of the county level standing population;
obtaining the ratio of the population of each province to the population of each province in the statistical yearbook, and determining the province with the ratio out of the preset ratio range as an error province;
obtaining the number of the permanent population of each county and city of the error province according to the statistical yearbook;
according to the number of the ith county and city standing population of the error province, utilizing a formula
Figure BDA0002799949190000032
Determining an error index of the ith county and city of the error province;
according to the error index of ith county and city of the error province, using a formula Yj＝Ki×yjDetermining the corrected population number of the jth village and town of the ith county and city of the error province;
wherein, KiError index of ith county and city as error province, MiThe population quantity of the ith county and city of error provinces in the constant population information, N, is counted for the townshipjThe population quantity y of the j village and town of the ith county and town of error provinces in the constant population information is counted for the village and townjNumber of assigned population, Y, for jth county and town of ith county and city of error provincejCorrected population number for jth township in ith county and city of error province.
Optionally, the navigation data includes: the area and length of each road;
the land cover data comprises: land type and area of each land type; the land types include impervious surfaces, cultivated land, woodland, grassland, water, wetlands, bare land, lichen, shrubs and ice and snow;
the night light data includes: the radiation signal produced by night lights and fires.
Optionally, the multi-source spatial data are spliced according to the boundaries of the towns, and the spliced multi-source spatial data are converted into the same projection coordinate system by using the projection conversion function of the acgis software to obtain the projected multi-source spatial data, and then the method further includes:
removing discontinuous roads in the navigation data of the projected multi-source spatial data by using a spatial continuity analysis method;
smoothing night light data of the projected multi-source space data by utilizing Gaussian low-pass filtering to eliminate noise data;
extracting impervious surface, cultivated land, forest land, grassland and water body land types in the land coverage data of the projected multi-source space data by utilizing the reclassification function of acgis software;
and obtaining the area of the impervious surface, the cultivated land, the forest land, the grassland and the water body by utilizing the area calculation function of the acgis software.
A multi-source data gridding cleaning system, the system comprising:
the township statistical standing population information acquisition unit is used for acquiring township statistical standing population information of the year to be cleaned from a statistical yearbook; the village-town level statistics standing population information comprises a village-town code, a village-town name and a population number;
a to-be-allocated village and town determining unit, configured to match and associate the village-level statistics standing population information with the village and town administrative division information of the year to be cleaned according to the village and town code of the village-level statistics standing population information, obtain a village and town code which is not matched with the village and town administrative division information in the village and town administrative division information and a corresponding village and town name, and determine that the to-be-allocated village and town exist; the town administrative division information comprises a town code, a town name and a town boundary;
the township level distribution standing population information obtaining unit is used for distributing population quantity to the township to be distributed according to township level census data and population kilometer grid data to obtain township level distribution standing population information;
the township level standing population information forming unit is used for forming township level standing population information of the year to be cleaned by the township level statistical standing population information and the township level distribution standing population information;
the spatial association village-township standing population information obtaining unit is used for performing spatial association on the village administrative division information of the year to be cleaned and the village-township standing population information by adopting a spatial association function of acgis software according to the village code of the village-township standing population information to obtain the village-township standing population information after the spatial association;
the multi-source spatial data acquisition unit is used for acquiring multi-source spatial data in each village and town boundary range in the village and town level permanent population information after spatial correlation; the multi-source space data comprises navigation data, land cover data and night light data;
the projected multi-source spatial data obtaining unit is used for splicing the multi-source spatial data according to the boundaries of the villages and the towns, converting the spliced multi-source spatial data into the same projection coordinate system by using the projection conversion function of acgis software, and obtaining the projected multi-source spatial data;
a hectometer grid data obtaining unit, configured to perform meshing in the projection coordinate system with the village and town administrative boundary as a spatial region, so as to obtain hectometer grid data;
the grid projected multi-source spatial data determining unit is used for determining projected multi-source spatial data contained in each grid in the hectometer grid data according to the projected multi-source spatial data;
and the grid population number determining unit is used for performing space intersection operation on the hectometer grid data and the village-level permanent population information after the space association to determine the name of the village and the town where each grid is located in the hectometer grid data and the population number corresponding to the name of the village and the town where each grid is located.
Optionally, the township level distribution standing population information obtaining unit specifically includes:
a judgment result obtaining subunit, configured to judge whether the township to be allocated is successfully matched with the township code in the township-level census data, and obtain a judgment result;
the population proportion obtaining subunit is configured to, if the determination result indicates yes, obtain, according to country-level census data, a population proportion of the county and city occupied by the to-be-distributed villages and towns;
a county and city population number obtaining subunit, configured to obtain, from the township level statistics standing population information, a population number of a county and city where the township to be allocated is located;
the first village and town population number determining subunit is used for determining the population number of the village and town to be distributed of the year to be cleaned according to the population number of the county and city where the village and town to be distributed are located and the population proportion of the county and city where the village and town to be distributed occupy;
a population sum of towns obtaining subunit, configured to, if the determination result indicates no, obtain, by using the boundary range of the towns to be allocated as a statistical range, a population sum of the towns within the statistical range and a population sum of provinces where the towns to be allocated are located from the population kilometer grid data by using a spatial statistical analysis method;
a second village and town population number determining subunit, configured to use a formula according to the population number sum in the statistical range and the population number sum of the province where the village and town to be allocated are located
Figure BDA0002799949190000061
Determining the population number of the towns to be distributed of the years to be cleaned;
the method comprises the following steps of acquiring a statistic yearbook of a year to be cleaned, acquiring a statistic yearbook of the year to be cleaned, and acquiring the statistic yearbook of the year to be cleaned, wherein y is the population number of the villages to be distributed of the year to be cleaned, k is the population proportion of the counties and cities occupied by the villages and cities to be distributed, P is the population number of the counties and cities to be distributed, S is the population number sum of the provinces where the villages and cities to be distributed are published by the statistic yearbook of the year to be cleaned, a is the population sum of the villages and cities in a statistic.
Optionally, the system further includes:
the provincial population total acquiring unit is used for acquiring the population total of each province according to the information of the county-level permanent population;
an error province determining and acquiring unit, configured to acquire a ratio of the total population of each province to the total population of each province in the statistical yearbook, and determine a province for which the ratio is not within a preset range of the ratio as an error province;
the county and city frequent population number obtaining unit is used for obtaining the number of the frequent population of each county and city of the error province according to the statistical yearbook;
an error index obtaining unit, configured to utilize a formula according to the number of the ith county and city regular population of the error province
Figure BDA0002799949190000062
Determining an error index of the ith county and city of the error province;
a corrected population number obtaining unit for utilizing the formula Y according to the error index of the ith county and city of the error provincej＝Ki×yjDetermining the corrected population number of the jth village and town of the ith county and city of the error province;
wherein, KiError index of ith county and city as error province, MiThe population quantity of the ith county and city of error provinces in the constant population information, N, is counted for the townshipjThe population quantity y of the j village and town of the ith county and town of error provinces in the constant population information is counted for the village and townjNumber of assigned population, Y, for jth county and town of ith county and city of error provincejCorrected population number for jth township in ith county and city of error province.
Optionally, the navigation data includes: the area and length of each road;
the land cover data comprises: land type and area of each land type; the land types include impervious surfaces, cultivated land, woodland, grassland, water, wetlands, bare land, lichen, shrubs and ice and snow;
the night light data includes: the radiation signal produced by night lights and fires.
Optionally, the system further includes:
a discontinuous road removing unit, configured to remove discontinuous roads from the projected navigation data of the multi-source spatial data by using a spatial continuity analysis method;
the noise data eliminating unit is used for smoothing night light data of the projected multi-source space data by Gaussian low-pass filtering to eliminate noise data;
the land cover data extraction unit is used for extracting the types of impervious surfaces, cultivated land, forest land, grassland and water body land in the land cover data of the projected multi-source space data by utilizing the reclassification function of acgis software;
and the area extraction unit is used for obtaining the area of the impervious surface, the area of cultivated land, the area of forest land, the area of grassland and the area of water body by utilizing the area calculation function of acgis software.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a multi-source data gridding cleaning method and a multi-source data gridding cleaning system, wherein township statistical standing population information of a year to be cleaned is obtained from a statistical yearbook and is matched and associated with township administrative division information, the quantity of population to be distributed to townships in the township administrative division information is distributed according to township census data and kilometer grid data of population, complete township standing population information is obtained, and the complete township standing population information is spatially associated; and then multi-source spatial data in each village and town boundary range in the village and town level resident population information after spatial correlation are obtained, the multi-source spatial data are spliced according to the village and town boundaries, the spliced multi-source spatial data are converted into the same projection coordinate system by using the projection conversion function of the acgis software, the village and town administrative boundaries are used as spatial regions in the projection coordinate system for gridding, the number of the multi-source spatial data, the village and the village of each grid is further determined, the population data, the navigation data, the land coverage data and the night light data are spliced on the space in a seamless mode, and the gridding packaging of the population and the spatial multi-source data is realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flowchart of a multi-source data gridding cleaning method provided by the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a gridding cleaning method and a gridding cleaning system for multi-source data so as to realize gridding packaging of population and space multi-source data.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The invention provides a multi-source data gridding cleaning method, as shown in figure 1, the method comprises the following steps:
s101, acquiring the county level statistical permanent population information of the year to be cleaned from the statistical yearbook; the township level statistical resident population information comprises a township code, a township name and population quantity.
S102, matching and associating the village-level statistical standing population information with the village-level administrative division information of the year to be cleaned according to the village-town code of the village-level statistical standing population information, acquiring the village-town code which is not matched with the village-level statistical standing population information in the village-town administrative division information and a corresponding village-town name, and determining the village to be allocated; the town administrative division information includes a town code, a town name, and a town boundary.
And S103, distributing the population quantity to the towns to be distributed according to the township population census data and the population kilometer grid data, and obtaining township-level distribution permanent population information.
And S104, the county level statistical standing population information and the county level distribution standing population information form the county level standing population information of the year to be cleaned.
And S105, according to the village and town code of the village and town level standing population information, performing spatial association on the village and town administrative division information of the year to be cleaned and the village and town standing population information by adopting a spatial association function of acgis software, and obtaining the village and town level standing population information after the spatial association.
S106, obtaining multi-source spatial data in each village and town boundary range in the village and town level frequent population information after spatial correlation; the multi-source spatial data includes navigation data, land cover data, and night light data.
And S107, splicing the multi-source spatial data according to the boundaries of the villages and towns, converting the spliced multi-source spatial data into the same projection coordinate system by using the projection conversion function of acgis software, and obtaining the projected multi-source spatial data.
And S108, gridding by taking the administrative boundary of the village and the town as a spatial region in the projection coordinate system to obtain hectometer grid data.
And S109, determining the projected multi-source spatial data contained in each grid in the hectometer grid data according to the projected multi-source spatial data.
And S110, performing space intersection operation on the hectometer grid data and the village-level permanent population information after space association, and determining the name of the village and the town where each grid is located in the hectometer grid data and the population number corresponding to the name of the village and the town where each grid is located.
The method comprises the following specific processes:
step S103, distributing population quantity to the towns to be distributed according to township population census data, and obtaining township distributed constant population information, wherein the step S specifically comprises the following steps:
judging whether the towns to be distributed are successfully matched with towns codes in towns-level population census data or not, and obtaining a judgment result;
if the judgment result shows that the country is the urban area, acquiring the population proportion of the county and the city occupied by the towns to be distributed according to the township-level census data;
acquiring the population number of the county and city of the towns to be distributed from the county-level statistical frequent population information;
determining the population number of the county and town to be distributed of the year to be cleaned according to the population number of the county and city to which the county and town to be distributed is located and the population proportion of the county and city to which the county and town to be distributed occupies;
if the judgment result shows that the country boundary range to be distributed is not the statistical range, acquiring the population sum of the villages and towns in the statistical range and the population sum of the provinces where the villages and towns to be distributed are located from the population kilometer grid data by adopting a spatial statistical analysis method;
according to the population sum in the statistical range and the population sum of the province where the towns to be distributed are located, the formula is utilized
Figure BDA0002799949190000101
The population number of towns to be allocated for the year to be cleaned is determined.
The method comprises the following steps of acquiring a statistic yearbook of a year to be cleaned, acquiring a statistic yearbook of the year to be cleaned, and acquiring the statistic yearbook of the year to be cleaned, wherein y is the population number of the villages to be distributed of the year to be cleaned, k is the population proportion of the counties and cities occupied by the villages and cities to be distributed, P is the population number of the counties and cities to be distributed, S is the population number sum of the provinces where the villages and cities to be distributed are published by the statistic yearbook of the year to be cleaned, a is the population sum of the villages and cities in a statistic.
Step S104, the county level statistical standing population information and the county level distribution standing population information form the county level standing population information of the year to be cleaned, and then the method further comprises the following steps:
acquiring the population total of each province according to the information of the county-level steady population;
obtaining the ratio of the population of each province to the population of each province in the statistical yearbook, and determining the province with the ratio out of the preset ratio range as an error province; the preset range of the ratio is 0.9-1.1.
Obtaining the number of the permanent population of each county and city of the error province according to the statistical yearbook;
according to the number of the ith county and city standing population of the error province, using a formula
Figure BDA0002799949190000102
Determining an error index of the ith county and city of the error province;
according to the error index of ith county and city of error province, using formula Yj＝Ki×yjDetermining the error provinceCorrected population number for jth township in ith county.
Wherein, KiError index of ith county and city as error province, MiThe population quantity of the ith county and city of error provinces in the constant population information, N, is counted for the townshipjThe population quantity y of the j village and town of the ith county and town of error provinces in the constant population information is counted for the village and townjNumber of assigned population, Y, for jth county and town of ith county and city of error provincejCorrected population number for jth township in ith county and city of error province.
Step S106, the navigation data includes: the area and length of each road. The land cover data includes: land type and area of each land type; types of land include impervious surfaces, arable land, woodland, grassland, water, wetlands, bare land, jungle, shrubs, and ice and snow. The night light data includes: the radiation signal produced by night lights and fires.
Step S107, splicing the multi-source spatial data according to the boundaries of the villages and towns, converting the spliced multi-source spatial data into the same projection coordinate system by using the projection conversion function of acgis software, obtaining the projected multi-source spatial data, and then further comprising:
removing discontinuous roads in the navigation data of the projected multi-source spatial data by using a spatial continuity analysis method;
smoothing night light data of the projected multi-source space data by utilizing Gaussian low-pass filtering to eliminate noise data;
extracting impervious surface, cultivated land, forest land, grassland and water body land types in land coverage data of the projected multi-source space data by utilizing the reclassification function of acgis software;
and obtaining the area of the impervious surface, the cultivated land, the forest land, the grassland and the water body by utilizing the area calculation function of the acgis software.
And step S109, calculating the corresponding impervious surface, cultivated land, forest land, grassland, water body land type area, navigation road area, length and night light data value in each grid by using acgis software according to the projected multi-source space data. The calculation process is mainly divided into three steps: the first step is as follows: and (3) performing space intersection operation, and a second step: area calculation, and the third step: and (4) spatial correlation.
The method provided by the invention can be used for correcting, repairing and merging the data, solving the problems of unified format and measurement unit, error data repair and noise and redundant data elimination, realizing seamless splicing of multi-source data, ensuring the precision of exposure parameter fine inversion products and grid space products from the source of input data, and providing a reliable data base for final evaluation of earthquake insurance loss.
The invention provides a specific embodiment for determining the exposure degree of county-level permanent population information in a hectometer grid in 2016 years in China by a multi-source data gridding cleaning method.
The multi-source data includes demographic data and multi-source spatial data.
Step 1: cleansing of demographic data
(1)2016 population match for perennial
2016 country-level permanent population data including a country name, a country code and population information are obtained from a statistical yearbook, and the population data and 2016 country-country and country administrative division data (including a country boundary and a country code) are subjected to one-to-one matching association according to the country code. Due to the lack of the collected statistical yearbook data, only 2016 years of population in part of the counties and towns of the country can be obtained.
(2)2016 population proportion assignment
In order to complement the missing data in the step (1), the population proportion of each county and city occupied by each village and town is calculated according to the 2010-country-level census data, the villages and towns without population data are screened out on the basis of the step (1) to be allocated, and the population quantity of each county and town to be allocated in 2016 is calculated according to the 2016 county-level household registration population quantity and the 2010-year population proportion. The calculation method comprises the following steps: the population of the township to be distributed is the proportion of the population of the township, and the number of the family members in 2016 county level in the county where the township is located.
(3)2010 population kilometer grid supplement
Since there is a change in part of the country code, which causes inconsistency between the country codes in 2016 and 2010, the distribution of the country code changed in (2) is not allowed, and (2) all missing data cannot be completed. And (3) screening a village and a town without population data on the basis of the step (2) to serve as a village and a town to be distributed, taking the space boundary of the village and the town to be distributed as a statistical range, adopting a space statistical analysis method to count the population sum in a 2010-year population kilometer grid in the range, performing stretch on the counted population sum to serve as the population number of the village and the town to be distributed, and finally completing all township population. The specific stretching method comprises the following steps: firstly, the total population of the 2010-year population kilometer grid of the province where the village and the town are to be distributed is counted by using the space boundary of the province where the village and the town are to be distributed to obtain A, and the population of the village and the town to be distributed is the total population (A) of the 2010-year population kilometer grid of the province where the village and the town are located and published by the county number sum of the village and the town statistics yearbook.
(4) Screening of the different provinces
A set of complete population numbers of villages and towns is completed through the steps (1), (2) and (3), and then the population numbers of the villages and towns with errors are subjected to error correction. The first step of correction is to screen the provinces with big differences, and the specific method comprises the following steps: according to the supplemented township population, the population total of each province is added and calculated, the population total of each province is compared with the population total of each province in 2016 published in the statistical yearbook, the ratio of the population total of each province is calculated, the provinces with large differences are screened out, and the step (5) is executed on the provinces with large differences, and the screening rule is as follows: ratio >1.1 or ratio < 0.9.
(5) Calculating the error index of each county/city of the provinces with large differences
To eliminate the error assigned according to the kilometer grid and the household data, an error index is first obtained, which is 2016 county/city-level persistent population (from the yearbook), of different provinces, and the error index is 2016 county/city-level persistent population (from the yearbook) -the number of township population of 2016 persistent population (matching result from step (1))/(county is assigned according to 2016 county-level population (assignment result from step (2)) /) the township is assigned according to 2010 spatial distribution population (assignment result from step (3)).
(6) Distribution result of correction difference province
The correction method comprises the following steps: the error index of the county/city of the township to be corrected x the distributed population of the township (from 2 and 3), and 2016 township population is obtained by correction.
(7) Verification
And (3) counting the population data of the national level and the provincial level, comparing the population data with the population data of the 2016 perpetual living, calculating the relative error, wherein the relative error of the national population is 0.028% and the population error of each province is within 5% through statistical calculation, so that the requirements are met.
(8) Information association
And (3) associating 2016 administrative district boundary data with 2016 washed township population data (the result of the step (6)) according to a township code field by adopting a spatial association function of acgis professional software.
Step 2: cleaning of multi-source spatial data
Selecting multi-source spatial data related to population distribution, wherein the multi-source spatial data mainly comprises the following steps: navigation data, land cover data, night light data.
Navigation data: mainly refers to road data of various levels, and each road has area and length information.
Land coverage data: including 10 types of cultivated land, forest, grassland, wetland, bare land, water body, impervious surface, lichen, shrub and ice and snow.
Night light data: the collected signals are radiation signals generated by night lamplight, fire light and the like. The DMSP/OLS sensor works at night and can detect urban light and even low-intensity light emitted by small-scale residential areas, traffic flows and the like.
(1) Data pre-processing
And (4) carrying out data preprocessing aiming at the three data. Including data stitching and projection conversion. Data splicing is the basis for data integrity. And splicing the framing multi-source spatial data according to the national boundary to form a national multi-source spatial data. The complete data was transformed into a unified projection coordinate system (WGS84-Albers) using a projection transformation function based on the arcgis professional tool.
(2) Outlier rejection
For the preprocessed navigation data, removing roads which cannot be continuous in the navigation data through common spatial continuity analysis in the prior art;
and smoothing the preprocessed night light data through Gaussian low-pass filtering to eliminate image noise generated by sporadic weak light.
(3) Available type extraction
Aiming at the preprocessed land coverage data, an impervious layer is extracted based on the reclassification function of arcgis software, the types of cultivated land, forest land, grassland and water body land are extracted, and other types are abandoned.
And step 3: spatial computation
(1) Hectometer standard grid formulation
From the national administrative boundary space range, 100 x 100 meters of grid data are constructed, and the coordinate system requirement is unified as WGS 84-Albers.
(2) Spatial analysis and valuation
According to the result of the grid data (step 1) of the preset unified reference, calculating the corresponding impervious surface, the types and areas of cultivated land, woodland, grassland and water body land, the area and length of a navigation road and the night light data value in the range of hundred meters by using arcgis software, determining the number of population of a village and a town where each grid is located and each village and town through the space intersection operation of the grid data and the population data, and finally unifying various spatial information and demographic information into a hundred-meter grid frame.
The multi-source data gridding cleaning method provided by the invention has the following advantages:
1. complete refined population data
Through the cleaning process of this patent, 2016 country-wide township data of year has been obtained, compares other national province level data, some provinces county level data that can obtain, and this data is not only meticulous but also complete.
2. Unified, seamless splice
The original basic geographic data, the navigation map data, the light index data, the socioeconomic data or the population data are different from one another in data space units, coordinate systems, data sources, time and the like, and after cleaning, the original basic geographic data, the navigation map data, the light index data, the socioeconomic data or the population data have the same space coordinate system (WGS84-Albers) and the same time attribute (2016), show the same data form (hectometer grids), and are a set of complete data set after cleaning. And grid units with the scale of hundred meters are constructed nationwide, are in a continuous state spatially and are not divided due to administrative affiliation.
3. Supporting flexible applications
And large-range multi-source data information is packaged in a hectometer refinement unit, and a model can be flexibly scheduled and used according to actual data requirements.
The invention also provides a multi-source data gridding cleaning system, which comprises:
the township statistical standing population information acquisition unit is used for acquiring township statistical standing population information of the year to be cleaned from a statistical yearbook; the village-town level statistics standing population information comprises a village-town code, a village-town name and a population number;
the to-be-distributed village and town determining unit is used for matching and associating the village-level statistical standing population information with the village and town administrative division information of the year to be cleaned according to the village and town code of the village-level statistical standing population information, acquiring the village and town code which is not matched with the village-level statistical standing population information in the village and town administrative division information and the corresponding village and town name, and determining the to-be-distributed village and town; the town administrative division information comprises a town code, a town name and a town boundary;
the device comprises a township level distribution standing population information obtaining unit, a population distribution unit and a population distribution unit, wherein the township level distribution standing population information obtaining unit is used for distributing population quantity to a township to be distributed according to township level population census data and population kilometer grid data to obtain township level distribution standing population information;
the township level standing population information forming unit is used for forming township level standing population information of the year to be cleaned by township level statistical standing population information and township level distribution standing population information;
the spatial association village-township standing population information obtaining unit is used for performing spatial association on the village administrative division information of the year to be cleaned and the village-township standing population information by adopting a spatial association function of acgis software according to a village code of the village-township standing population information to obtain the village-township standing population information after the spatial association;
the multi-source spatial data acquisition unit is used for acquiring multi-source spatial data in each village and town boundary range in the village and town level permanent population information after spatial correlation; the multi-source space data comprises navigation data, land cover data and night light data;
the projected multi-source spatial data obtaining unit is used for splicing the multi-source spatial data according to the boundaries of the villages and towns, converting the spliced multi-source spatial data into the same projection coordinate system by using the projection conversion function of acgis software, and obtaining the projected multi-source spatial data;
a hectometer grid data obtaining unit, configured to perform meshing in the projection coordinate system with the village and town administrative boundary as a spatial region, so as to obtain hectometer grid data;
the grid projected multi-source spatial data determining unit is used for determining projected multi-source spatial data contained in each grid in the hectometer grid data according to the projected multi-source spatial data;
and the grid population number determining unit is used for performing space intersection operation on the hectometer grid data and the village-level permanent population information after space association to determine the name of the village and the town where each grid is located in the hectometer grid data and the population number corresponding to the name of the village and the town where each grid is located.
The township level distribution standing population information obtaining unit specifically comprises:
the judging result obtaining subunit is used for judging whether the towns to be distributed are successfully matched with the towns codes in the towns-level census data or not and obtaining a judging result;
the population proportion obtaining subunit is used for obtaining the population proportion of the county and city occupied by the towns to be distributed according to the township population census data if the judgment result shows that the county and city are occupied by the township population census data;
the county and city population number obtaining subunit is used for obtaining the population number of the county and city where the villages and towns to be distributed are located from the county and town level statistics standing population information;
the first village and town population number determining subunit is used for determining the population number of the village and town to be distributed of the year to be cleaned according to the population number of the county and city where the village and town to be distributed occupy and the population proportion of the county and city where the village and town to be distributed occupy;
a village and town population sum obtaining subunit, configured to, if the determination result indicates no, obtain, by using the boundary range of the village and town to be allocated as a statistical range, a village and town population sum in the statistical range and a population sum of a province in which the village and town to be allocated are located from the population kilometer grid data by using a spatial statistical analysis method;
a second village and town population number determining subunit, configured to use a formula according to the population number sum in the statistical range and the population number sum of the province where the village and town to be allocated are located
Figure BDA0002799949190000161
Determining the population number of towns to be distributed of the years to be cleaned;
the method comprises the following steps of acquiring a statistic yearbook of a year to be cleaned, acquiring a statistic yearbook of the year to be cleaned, and acquiring the statistic yearbook of the year to be cleaned, wherein y is the population number of the villages to be distributed of the year to be cleaned, k is the population proportion of the counties and cities occupied by the villages and cities to be distributed, P is the population number of the counties and cities to be distributed, S is the population number sum of the provinces where the villages and cities to be distributed are published by the statistic yearbook of the year to be cleaned, a is the population sum of the villages and cities in a statistic.
The system further comprises:
the provincial population total acquiring unit is used for acquiring the population total of each province according to the information of the county-level permanent population;
an error province determining and acquiring unit, configured to acquire a ratio of the total population of each province to the total population of each province in the statistical yearbook, and determine a province for which the ratio is not within a preset range of the ratio as an error province;
the county and city frequent population number obtaining unit is used for obtaining the frequent population number of each county and city of the error provinces according to the statistical yearbook;
an error index obtaining unit for obtaining error scoreThe number of the daily population of the ith county and city of shares by using a formula
Figure BDA0002799949190000171
Determining an error index of the ith county and city of the error province;
a corrected population number obtaining unit for obtaining the error index of the ith county and city according to the error province by using the formula Yj＝Ki×yjDetermining the corrected population number of the jth village and town of the ith county and city of the error province;
wherein, KiError index of ith county and city as error province, MiThe population quantity of the ith county and city of error provinces in the constant population information, N, is counted for the townshipjThe population quantity y of the j village and town of the ith county and town of error provinces in the constant population information is counted for the village and townjNumber of assigned population, Y, for jth county and town of ith county and city of error provincejCorrected population number for jth township in ith county and city of error province.
The navigation data includes: the area and length of each road;
the land cover data includes: land type and area of each land type; land types include impervious surfaces, arable land, woodland, grassland, water, wetlands, bare land, jungle, shrubs, and ice and snow;
the night light data includes: the radiation signal produced by night lights and fires.
The system further comprises:
the discontinuous road removing unit is used for removing discontinuous roads in the projected navigation data of the multi-source space data by using a space continuity analysis method;
the noise data eliminating unit is used for smoothing night light data of the projected multi-source space data by utilizing Gaussian low-pass filtering to eliminate noise data;
the land cover data extraction unit is used for extracting the types of impervious surfaces, cultivated land, forest land, grassland and water body land in the land cover data of the projected multi-source space data by utilizing the reclassification function of the acgis software;
and the area extraction unit is used for obtaining the area of the impervious surface, the area of cultivated land, the area of forest land, the area of grassland and the area of water body by utilizing the calculation function of the acgis software area.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. A multi-source data gridding cleaning method is characterized by comprising the following steps:
acquiring county level statistical permanent population information of the year to be cleaned from a statistical yearbook; the village-town level statistics standing population information comprises a village-town code, a village-town name and a population number;
according to the village and town codes of the village and town level statistics standing population information, matching and associating the village and town statistical standing population information with the village and town administrative division information of the year to be cleaned, acquiring the village and town codes which are not matched with the village and town statistical standing population information in the village and town administrative division information and corresponding village and town names, and determining the village and town to be allocated; the town administrative division information comprises a town code, a town name and a town boundary;
distributing population quantity to the towns to be distributed according to township population census data and population kilometer grid data to obtain township distributed constant population information;
the township level statistical standing population information and the township level distribution standing population information form township level standing population information of the year to be cleaned;
according to the village and town code of the village and town level standing population information, performing spatial association on the village and town administrative division information of the year to be cleaned and the village and town standing population information by adopting a spatial association function of acgis software to obtain the village and town level standing population information after the spatial association;
acquiring multi-source spatial data within each village and town boundary range in the village and town level standing population information after spatial correlation; the multi-source space data comprises navigation data, land cover data and night light data;
splicing the multi-source space data according to the boundaries of the villages and the towns, and converting the spliced multi-source space data into the same projection coordinate system by using the projection conversion function of acgis software to obtain the projected multi-source space data;
gridding is carried out in a projection coordinate system by taking a village and town administrative boundary as a spatial region to obtain hectometer grid data;
determining projected multi-source spatial data contained in each grid in the hectometer grid data according to the projected multi-source spatial data;
and performing space intersection operation on the hectometer grid data and the village-level permanent population information after the space association, and determining the name of the village and the town where each grid is located in the hectometer grid data and the population quantity corresponding to the name of the village and the town where each grid is located.
2. The multi-source data gridding cleaning method according to claim 1, wherein the step of distributing the population quantity to the township to be distributed according to township-level census data and population kilometer grid data to obtain township-level distribution standing population information specifically comprises the steps of:
judging whether the towns to be distributed are successfully matched with towns codes in towns-level population census data or not, and obtaining a judgment result;
if the judgment result shows that the county and town occupation population proportion is larger than the preset county and town population proportion, acquiring population proportion of the county and town to be distributed occupying the county and city according to county and town population general survey data;
acquiring the population number of the county city of the towns to be distributed from the township level statistical standing population information;
determining the population number of the villages and towns to be distributed in the year to be cleaned according to the population number of the county and the city where the villages and towns to be distributed occupy and the population proportion of the county and the city where the villages and towns to be distributed occupy;
if the judgment result shows that the country boundary range to be distributed is not the statistical range, acquiring the population sum of the country in the statistical range and the population sum of the province where the country to be distributed is located from the population kilometer grid data by adopting a spatial statistical analysis method;
according to the population sum in the statistical range and the population sum of the province where the towns to be distributed are located, a formula is utilized
Figure FDA0002799949180000021
Determining the population number of towns to be distributed of the years to be cleaned;
the method comprises the following steps of acquiring statistics of the years to be cleaned, wherein y is the population number of towns to be distributed of the years to be cleaned, k is the population proportion of the towns to be distributed occupying the county and city, P is the population number of the county and city, the S is the population sum of the provinces, where the towns to be distributed are published by the statistics yearbook of the years to be cleaned, a is the population sum of the towns within the statistics range, and A is the population sum of the provinces, where the towns to be distributed are within the statistics range.
3. The multi-source data gridding cleaning method according to claim 1, wherein the township statistical standing population information and the township distribution standing population information form township standing population information of a year to be cleaned, and then further comprising:
acquiring the population sum of each province according to the information of the county level standing population;
obtaining the ratio of the population of each province to the population of each province in the statistical yearbook, and determining the province with the ratio out of the preset ratio range as an error province;
obtaining the number of the permanent population of each county and city of the error province according to the statistical yearbook;
according to the number of the ith county and city standing population of the error province, utilizing a formula
Figure FDA0002799949180000031
Determining an error index of the ith county and city of the error province;
according to the error index of ith county and city of the error province, using a formula Yj＝Ki×yjDetermining the corrected population number of the jth village and town of the ith county and city of the error province;
wherein, KiError index of ith county and city as error province, MiThe population quantity of the ith county and city of error provinces in the constant population information, N, is counted for the townshipjThe population quantity y of the j village and town of the ith county and town of error provinces in the constant population information is counted for the village and townjNumber of assigned population, Y, for jth county and town of ith county and city of error provincejCorrected population number for jth township in ith county and city of error province.
4. The multi-source data gridding cleaning method according to claim 1,
the navigation data includes: the area and length of each road;
the land cover data comprises: land type and area of each land type; the land types include impervious surfaces, cultivated land, woodland, grassland, water, wetlands, bare land, lichen, shrubs and ice and snow;
the night light data includes: the radiation signal produced by night lights and fires.
5. The multi-source data gridding cleaning method according to claim 4, wherein the multi-source spatial data is spliced according to a village and town boundary, and the spliced multi-source spatial data is converted into the same projection coordinate system by using a projection conversion function of acgis software to obtain the projected multi-source spatial data, and then the method further comprises:
removing discontinuous roads in the navigation data of the projected multi-source spatial data by using a spatial continuity analysis method;
smoothing night light data of the projected multi-source space data by utilizing Gaussian low-pass filtering to eliminate noise data;
extracting impervious surface, cultivated land, forest land, grassland and water body land types in the land coverage data of the projected multi-source space data by utilizing the reclassification function of acgis software;
and obtaining the area of the impervious surface, the cultivated land, the forest land, the grassland and the water body by utilizing the area calculation function of the acgis software.
6. A multi-source data gridding cleaning system, the system comprising:
the township statistical standing population information acquisition unit is used for acquiring township statistical standing population information of the year to be cleaned from a statistical yearbook; the village-town level statistics standing population information comprises a village-town code, a village-town name and a population number;
a to-be-allocated village and town determining unit, configured to match and associate the village-level statistics standing population information with the village and town administrative division information of the year to be cleaned according to the village and town code of the village-level statistics standing population information, obtain a village and town code which is not matched with the village and town administrative division information in the village and town administrative division information and a corresponding village and town name, and determine that the to-be-allocated village and town exist; the town administrative division information comprises a town code, a town name and a town boundary;
the township level distribution standing population information obtaining unit is used for distributing population quantity to the township to be distributed according to township level census data and population kilometer grid data to obtain township level distribution standing population information;
the township level standing population information forming unit is used for forming township level standing population information of the year to be cleaned by the township level statistical standing population information and the township level distribution standing population information;
the spatial association village-township standing population information obtaining unit is used for performing spatial association on the village administrative division information of the year to be cleaned and the village-township standing population information by adopting a spatial association function of acgis software according to the village code of the village-township standing population information to obtain the village-township standing population information after the spatial association;
the multi-source spatial data acquisition unit is used for acquiring multi-source spatial data in each village and town boundary range in the village and town level permanent population information after spatial correlation; the multi-source space data comprises navigation data, land cover data and night light data;
the projected multi-source spatial data obtaining unit is used for splicing the multi-source spatial data according to the boundaries of the villages and the towns, converting the spliced multi-source spatial data into the same projection coordinate system by using the projection conversion function of acgis software, and obtaining the projected multi-source spatial data;
a hectometer grid data obtaining unit, configured to perform meshing in the projection coordinate system with the village and town administrative boundary as a spatial region, so as to obtain hectometer grid data;
the grid projected multi-source spatial data determining unit is used for determining projected multi-source spatial data contained in each grid in the hectometer grid data according to the projected multi-source spatial data;
and the grid population number determining unit is used for performing space intersection operation on the hectometer grid data and the village-level permanent population information after the space association to determine the name of the village and the town where each grid is located in the hectometer grid data and the population number corresponding to the name of the village and the town where each grid is located.
7. The multi-source data gridding cleaning system according to claim 6, wherein the township level distribution standing population information obtaining unit specifically comprises:
a judgment result obtaining subunit, configured to judge whether the township to be allocated is successfully matched with the township code in the township-level census data, and obtain a judgment result;
the population proportion obtaining subunit is configured to, if the determination result indicates yes, obtain, according to country-level census data, a population proportion of the county and city occupied by the to-be-distributed villages and towns;
a county and city population number obtaining subunit, configured to obtain, from the township level statistics standing population information, a population number of a county and city where the township to be allocated is located;
the first village and town population number determining subunit is used for determining the population number of the village and town to be distributed of the year to be cleaned according to the population number of the county and city where the village and town to be distributed are located and the population proportion of the county and city where the village and town to be distributed occupy;
a population sum of towns obtaining subunit, configured to, if the determination result indicates no, obtain, by using the boundary range of the towns to be allocated as a statistical range, a population sum of the towns within the statistical range and a population sum of provinces where the towns to be allocated are located from the population kilometer grid data by using a spatial statistical analysis method;
a second village and town population number determining subunit, configured to use a formula according to the population number sum in the statistical range and the population number sum of the province where the village and town to be allocated are located
Figure FDA0002799949180000051
Determining the population number of the towns to be distributed of the years to be cleaned;
the method comprises the following steps of acquiring a statistic yearbook of a year to be cleaned, acquiring a statistic yearbook of the year to be cleaned, and acquiring the statistic yearbook of the year to be cleaned, wherein y is the population number of the villages to be distributed of the year to be cleaned, k is the population proportion of the counties and cities occupied by the villages and cities to be distributed, P is the population number of the counties and cities to be distributed, S is the population number sum of the provinces where the villages and cities to be distributed are published by the statistic yearbook of the year to be cleaned, a is the population sum of the villages and cities in a statistic.
8. The multi-source data gridding cleaning system according to claim 6, further comprising:
the provincial population total acquiring unit is used for acquiring the population total of each province according to the information of the county-level permanent population;
an error province determining and acquiring unit, configured to acquire a ratio of the total population of each province to the total population of each province in the statistical yearbook, and determine a province for which the ratio is not within a preset range of the ratio as an error province;
the county and city frequent population number obtaining unit is used for obtaining the number of the frequent population of each county and city of the error province according to the statistical yearbook;
an error index obtaining unit, configured to utilize a formula according to the number of the ith county and city regular population of the error province
Figure FDA0002799949180000061
Determining an error index of the ith county and city of the error province;
a corrected population number obtaining unit for utilizing the formula Y according to the error index of the ith county and city of the error provincej＝Ki×yjDetermining the corrected population number of the jth village and town of the ith county and city of the error province;
wherein, KiError index of ith county and city as error province, MiThe population quantity of the ith county and city of error provinces in the constant population information, N, is counted for the townshipjThe population quantity y of the j village and town of the ith county and town of error provinces in the constant population information is counted for the village and townjNumber of assigned population, Y, for jth county and town of ith county and city of error provincejCorrected population number for jth township in ith county and city of error province.
9. The multi-source data gridding cleaning system according to claim 6,
the navigation data includes: the area and length of each road;
the land cover data comprises: land type and area of each land type; the land types include impervious surfaces, cultivated land, woodland, grassland, water, wetlands, bare land, lichen, shrubs and ice and snow;
the night light data includes: the radiation signal produced by night lights and fires.
10. The multi-source data gridding cleaning system according to claim 9, further comprising:
a discontinuous road removing unit, configured to remove discontinuous roads from the projected navigation data of the multi-source spatial data by using a spatial continuity analysis method;
the noise data eliminating unit is used for smoothing night light data of the projected multi-source space data by Gaussian low-pass filtering to eliminate noise data;
the land cover data extraction unit is used for extracting the types of impervious surfaces, cultivated land, forest land, grassland and water body land in the land cover data of the projected multi-source space data by utilizing the reclassification function of acgis software;
and the area extraction unit is used for obtaining the area of the impervious surface, the area of cultivated land, the area of forest land, the area of grassland and the area of water body by utilizing the area calculation function of acgis software.
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090158185A1 (en) * 2007-12-17 2009-06-18 Socialexplorer, Inc. Adaptive map layer visibility control
CN101894121A (en) * 2010-03-22 2010-11-24 中国地震局地震研究所 Method for administrative area data gridding
US20120001915A1 (en) * 2003-08-01 2012-01-05 Pyxis Innovation Inc. Close-packed, uniformly adjacent multiresolutional, overlapping spatial data ordering
CN103218517A (en) * 2013-03-22 2013-07-24 南京信息工程大学 GIS (Geographic Information System)-based region-meshed spatial population density computing method
CN106844642A (en) * 2017-01-20 2017-06-13 杭州电子科技大学 A kind of method that the density of population in road network grid is calculated based on GIS
CN110704565A (en) * 2019-09-27 2020-01-17 泉州师范学院 Demographic data gridding modeling method based on remote sensing and GIS
CN111833224A (en) * 2020-05-26 2020-10-27 东南大学 Urban main and auxiliary center boundary identification method based on population grid data

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120001915A1 (en) * 2003-08-01 2012-01-05 Pyxis Innovation Inc. Close-packed, uniformly adjacent multiresolutional, overlapping spatial data ordering
US20090158185A1 (en) * 2007-12-17 2009-06-18 Socialexplorer, Inc. Adaptive map layer visibility control
CN101894121A (en) * 2010-03-22 2010-11-24 中国地震局地震研究所 Method for administrative area data gridding
CN103218517A (en) * 2013-03-22 2013-07-24 南京信息工程大学 GIS (Geographic Information System)-based region-meshed spatial population density computing method
CN106844642A (en) * 2017-01-20 2017-06-13 杭州电子科技大学 A kind of method that the density of population in road network grid is calculated based on GIS
CN110704565A (en) * 2019-09-27 2020-01-17 泉州师范学院 Demographic data gridding modeling method based on remote sensing and GIS
CN111833224A (en) * 2020-05-26 2020-10-27 东南大学 Urban main and auxiliary center boundary identification method based on population grid data

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
DIMITRIOS MENTIS 等: "A GIS-based approach for electrification planning—A case study on Nigeria" *
HAIPING XIAO 等: "The population development functional zoning in Yunnan Province using the multi-factor superposition model based on GIS" *
何浩 等: "统计遥感空间基础框架的研究与应用" *
唐奇: "基于GIS的人口空间离散化方法及其应用——以北方地区为例" *
潘顺: "长三角人口数据格网化及其人口空间分布特征分析" *

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