CN112486963B - Multi-source data gridding cleaning method and system - Google Patents
Multi-source data gridding cleaning method and system Download PDFInfo
- Publication number
- CN112486963B CN112486963B CN202011346406.7A CN202011346406A CN112486963B CN 112486963 B CN112486963 B CN 112486963B CN 202011346406 A CN202011346406 A CN 202011346406A CN 112486963 B CN112486963 B CN 112486963B
- Authority
- CN
- China
- Prior art keywords
- village
- population
- data
- town
- level
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Abstract
The invention relates to a multi-source data gridding cleaning method and a system, which are used for acquiring village-level statistical resident population information from a statistical annual survey, matching the statistical resident population information with village-level administrative division information, distributing population quantity to villages to be distributed according to village-level population census data and population kilometer grid data, acquiring complete village-level resident population information, and carrying out spatial correlation on the village-level resident population information; the method comprises the steps of acquiring multi-source space data in each village boundary range in village-town level resident population information after spatial association, splicing the multi-source space data according to the village boundaries, converting the multi-source space data into the same projection coordinate system, gridding the space area of the village-town administrative boundaries, determining the multi-source space data of each grid, villages and towns and population quantity of the villages through spatial analysis and calculation, and realizing seamless splicing of the population data, navigation data, land coverage data and night light data in space so as to realize gridding packaging of the population and space multi-source data.
Description
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 statistical annual-check, census data and the like, only the population data of administrative units such as provinces, cities and counties in administrative regions can be known, but the population distribution data corresponding to space regions cannot be known, multi-source space data related to population distribution in space regions cannot be known, and the problems of lack, non-uniform data standard and the like of the available population data and multi-source space data exist, so that a reliable data basis cannot be provided for seismic insurance loss evaluation, national economic development planning and the like.
Disclosure of Invention
The invention aims to provide a multi-source data meshing cleaning method and system so as to realize meshing packaging of population and space multi-source data.
In order to achieve the above object, the present invention provides the following solutions:
a multi-source data meshing cleaning method, the method comprising:
acquiring village and town level statistical resident population information of the year to be cleaned from the statistical year authentication; the village-level statistical resident population information comprises village codes, village names and population numbers;
according to the village codes of the village-level statistical resident population information, carrying out matching association on the village-level statistical resident population information and village administrative division information of the year to be cleaned, and acquiring the village codes and corresponding village names, which are not matched with the village-level statistical resident population information, of the village administrative division information of the villages and towns, so as to determine the villages to be allocated; the village and town administrative division information comprises a village and town code, a village and town name and a village and town boundary;
Distributing population quantity to the villages to be distributed according to village-level population census data and population kilometer grid data to obtain village-level distribution resident population information;
the village-level statistical resident population information and the village-level distribution resident population information form village-level resident population information of the year to be cleaned;
according to the village code of the village-level resident population information, adopting the space association function of acgis software to carry out space association on village administrative division information of the year to be cleaned and the village-level resident population information, and obtaining the village-level resident population information after the space association;
acquiring multi-source space data in each village-town boundary range in the village-town level resident population information after the space association; the multi-source space data comprises navigation data, land coverage data and night light data;
splicing the multi-source space data according to village and town boundaries, and converting the spliced multi-source space data into the same projection coordinate system by utilizing the projection conversion function of the acgis software to obtain projected multi-source space data;
gridding is carried out in a projection coordinate system by taking a village and town administrative boundary as a space region, so as to obtain hundred-meter grid data;
Determining projected multi-source spatial data contained in each grid in the hundred-meter grid data according to the projected multi-source spatial data;
and carrying out space intersection operation on the hundred-meter grid data and the village-level resident population information after space association, and determining the village name of each grid in the hundred-meter grid data and the population number corresponding to the village name.
Optionally, the distributing population quantity to the villages to be distributed according to the village-level population census data and the population kilometer grid data to obtain village-level distribution resident population information, which specifically includes:
judging whether the villages to be distributed are successfully matched with village codes in village-town level population census data or not, and obtaining a judging result;
if the judgment result shows that the current value is positive, obtaining the population proportion of the county and the city occupied by the villages to be distributed according to the village and town level population census data;
acquiring population numbers of counties and cities of the villages to be distributed from the village-level statistical resident population information;
determining the population number of the villages to be distributed in the year to be cleaned according to the population number of the counties to be distributed and the population proportion of the counties to be distributed to occupy the counties to be distributed by using a formula y=k×P;
If the judgment result shows that the rural area network distribution method is not used, taking the rural area boundary range to be distributed as a statistical range, and adopting a space statistical analysis method to obtain 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;
according to the population quantity sum in the statistical range and the population quantity sum of the provinces where the villages and towns to be distributed are located, utilizing a formula
Determining the population number of villages to be distributed in the year to be cleaned;
wherein y is the population number of towns to be allocated in the year to be cleaned, k is the population proportion of towns to be allocated occupying the county and the city, P is the population number of towns to be allocated in the county and the city, S is the population sum of towns to be allocated in the province published by the statistical annual survey of the year to be cleaned, a is the population sum of towns in the statistical range, and A is the population sum of towns to be allocated in the statistical range.
Optionally, the village-level statistical resident population information and the village-level distribution resident population information form village-level resident population information of the year to be cleaned, and further includes:
acquiring population total of each province according to the village and town level resident population information;
Obtaining the ratio of the population total number of each province to the population total number of each province in the statistical annual survey, and determining the province with the ratio not in the ratio preset range as an error province;
obtaining the number of resident population in each county and city of the error province according to the statistical annual survey;
according to the number of the i county resident population of the error province, the formula is utilized
The ith county and city of determining the error provinceError index of (2);
according to the error index of the ith county and city of the error province, using the formula Y j ＝K i ×y j Determining a corrected population quantity for a j-th village and town of an i-th county and city of the error province;
wherein K is i Error index of ith county and city as error province, M i Counting the population number of the ith county and city of error province in resident population information for village and town level, N j Counting the population number of the jth village and town of the ith county and city of the error province in the resident population information for the village and town level, y j Assigning population numbers for the jth village and town of the ith county and city of the error province, Y j The corrected population number for the jth village and town of the ith county and city of the error province.
Optionally, the navigation data includes: the area and length of each road;
the land cover data includes: land type and area of each land type; the land types include water impermeable surfaces, cultivated lands, woodlands, grasslands, bodies of water, wetlands, bare lands, moss, shrubs, and ice and snow;
The night light data includes: radiation signals generated by night lights and fire lights.
Optionally, the splicing the multi-source space data according to the village and town boundaries, converting the spliced multi-source space data into the same projection coordinate system by using a projection conversion function of the acgis software, and obtaining projected multi-source space data, and then further including:
removing discontinuous roads in navigation data of the projected multi-source spatial data by using a spatial continuity analysis method;
smoothing the night lamplight data of the projected multi-source space data by using Gaussian low-pass filtering to eliminate noise data;
extracting the types of the water-impermeable surfaces, cultivated lands, woodlands, grasslands and water lands in the land coverage data of the projected multi-source space data by utilizing the reclassification function of the acgis software;
the area calculation function of the acgis software is utilized to obtain the area of the watertight surface, the area of the cultivated land, the area of the woodland, the area of the grassland and the area of the water body.
A multi-source data gridding cleaning system, the system comprising:
the village-town statistical resident population information acquisition unit is used for acquiring village-town statistical resident population information of the year to be cleaned from the statistical year authentication; the village-level statistical resident population information comprises village codes, village names and population numbers;
The village and town to be allocated determining unit is used for carrying out matching association on the village and town level statistical resident population information and village and town administrative division information of the year to be cleaned according to the village and town codes of the village and town level statistical resident population information, acquiring the village and town codes and corresponding village names, which are not matched with the village and town level statistical resident population information, in the village and town administrative division information, and determining the village and town to be allocated; the village and town administrative division information comprises a village and town code, a village and town name and a village and town boundary;
the village-level distribution resident population information obtaining unit is used for obtaining village-level distribution resident population information for the villages and towns to be distributed according to the village-level population census data and the population kilometer grid data;
the village-level resident population information forming unit is used for forming village-level resident population information of the year to be cleaned by the village-level statistical resident population information and the village-level distribution resident population information;
the space-related village-level resident population information obtaining unit is used for carrying out space-related on village-level administrative division information of the year to be cleaned and the village-level resident population information by adopting the space-related function of acgis software according to the village code of the village-level resident population information to obtain the village-level resident population information after the space-related;
The multi-source space data acquisition unit is used for acquiring multi-source space data in each village and town boundary range in the village and town level resident population information after the space association; the multi-source space data comprises navigation data, land coverage data and night light data;
the projected multi-source space data acquisition unit is used for splicing the multi-source space data according to village and town boundaries, converting the spliced multi-source space data into the same projection coordinate system by utilizing the projection conversion function of the acgis software, and acquiring the projected multi-source space data;
the system comprises a hundred-meter grid data obtaining unit, a three-dimensional grid data obtaining unit and a three-dimensional grid data obtaining unit, wherein the hundred-meter grid data obtaining unit is used for gridding a rural administrative boundary serving as a space region in a projection coordinate system;
a multi-source space data determining unit after grid projection, configured to determine, according to the multi-source space data after projection, multi-source space data after projection included in each grid in the hundred-meter grid data;
and the grid population number determining unit is used for carrying out space intersection operation on the hundred-meter grid data and the village-level resident population information after the space association to determine the village name where each grid in the hundred-meter grid data is located and the population number corresponding to the village name where each grid is located.
Optionally, the village and town level distribution resident population information obtaining unit specifically includes:
the judging result obtaining subunit is used for judging whether the villages to be distributed are successfully matched with the village codes in the village-town level population 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 the city occupied by the villages to be distributed according to the village and town level population census data if the judgment result shows that the judgment result is yes;
the county and city population quantity acquisition subunit is used for acquiring the population quantity of the county and city where the villages and towns to be distributed are located from the village and towns level statistical resident population information;
the first village population quantity determining subunit is used for determining the population quantity of the villages to be distributed in the year to be cleaned according to the population quantity of the counties to be distributed and the population proportion of the counties to be distributed in the counties to be distributed, and the formula y=k×P is utilized;
the village and town population sum obtaining subunit is configured to obtain, if the judging result indicates no, a village and town population sum in the statistical range and a village and town population sum in a province where the villages and towns to be distributed are located from the population kilometer grid data by using the space statistical analysis method with the village and town boundary range to be distributed as the statistical range;
A second village population quantity determining subunit, configured to utilize the formula according to the population quantity sum in the statistical range and the population quantity sum in the province where the villages and towns to be allocated
Determining the population number of villages to be distributed in the year to be cleaned;
wherein y is the population number of towns to be allocated in the year to be cleaned, k is the population proportion of towns to be allocated occupying the county and the city, P is the population number of towns to be allocated in the county and the city, S is the population sum of towns to be allocated in the province published by the statistical annual survey of the year to be cleaned, a is the population sum of towns in the statistical range, and A is the population sum of towns to be allocated in the statistical range.
Optionally, the system further comprises:
the province population total number acquisition unit is used for acquiring population total numbers of each province according to the village and town level resident population information;
the error province determining and acquiring unit is used for acquiring the ratio of the population total number of each province to the population total number of each province in the statistical annual survey, and determining the province with the ratio not in the ratio preset range as the error province;
the county and city resident population quantity acquisition unit is used for acquiring the county and city resident population quantity of each county and city of the error province according to the statistical annual survey;
An error index obtaining unit for obtaining the number of the i-th county and city resident population of the error province by using the formula
Determining an error index of the ith county and city of the error province;
a correction population number acquisition unit for using the formula Y according to the error index of the ith county and city of the error province j ＝K i ×y j Determining a corrected population quantity for a j-th village and town of an i-th county and city of the error province;
wherein K is i Error index of ith county and city as error province, M i Counting the population number of the ith county and city of error province in resident population information for village and town level, N j Counting the population number of the jth village and town of the ith county and city of the error province in the resident population information for the village and town level, y j Assigning population numbers for the jth village and town of the ith county and city of the error province, Y j The corrected population number for the jth village and town of the ith county and city of the error province.
Optionally, the navigation data includes: the area and length of each road;
the land cover data includes: land type and area of each land type; the land types include water impermeable surfaces, cultivated lands, woodlands, grasslands, bodies of water, wetlands, bare lands, moss, shrubs, and ice and snow;
The night light data includes: radiation signals generated by night lights and fire lights.
Optionally, the system further comprises:
the discontinuous road removing unit is used for removing discontinuous roads in the navigation data of the projected multi-source space data by using a space continuity analysis method;
the noise data eliminating unit is used for carrying out smoothing processing on night light data of the multi-source space data after projection by utilizing Gaussian low-pass filtering, and eliminating noise data;
the land coverage data extraction unit is used for extracting the types of the water-impermeable surfaces, cultivated lands, woodlands, grasslands and water lands in the land coverage data of the projected multi-source space data by utilizing the reclassification function of the acgis software;
the area extraction unit is used for obtaining the area of the watertight surface, the area of the cultivated land, the area of the forest land, the area of the grassland and the area of the water body by utilizing the area calculation function of the 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 system, which are used for acquiring village-level statistical resident population information of a year to be cleaned from a statistical year discriminator, carrying out matching association with village-level population census data and population kilometer grid data, distributing population quantity to be distributed in the village-level population census data to obtain complete village-level resident population information, and carrying out spatial association on the complete village-level resident population information; and then acquiring multi-source space data in each village boundary range in the village-town level resident population information after spatial association, splicing the multi-source space data according to the village boundaries, converting the spliced multi-source space data into the same projection coordinate system by utilizing the projection conversion function of acgis software, gridding the projection coordinate system by taking the village administrative boundaries as space areas, further determining the multi-source space data of each grid, the villages and towns and the population number of the villages and towns, and realizing seamless spatial splicing of the population data, the navigation data, the land coverage data and the night lamplight data and gridding packaging of the population and the space multi-source data.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a multi-source data gridding cleaning method provided by the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a multi-source data meshing cleaning method and system so as to realize meshing packaging of population and space multi-source data.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
The invention provides a multi-source data meshing cleaning method, which is shown in figure 1 and comprises the following steps:
s101, acquiring village and town level statistical resident population information of the year to be cleaned from a statistical year discriminator; the village-level statistical resident population information includes village codes, village names and population numbers.
S102, according to the village codes of the village-level statistical resident population information, matching and associating the village-level statistical resident population information with village administrative division information of the year to be cleaned, and acquiring the village codes and corresponding village names of the village administrative division information which are not matched with the village-level statistical resident population information, and determining the village codes and the corresponding village names as the villages to be allocated; the town administrative division information includes a town code, a town name, and a town boundary.
And S103, distributing population quantity to the villages to be distributed according to the village-level census data and the kilometer population grid data, and obtaining village-level distribution resident population information.
S104, the village-level statistical resident population information and the village-level distribution resident population information form village-level resident population information of the year to be cleaned.
S105, according to the village code of the village-level resident population information, space association function of acgis software is adopted to carry out space association on village administrative division information of the year to be cleaned and the village-level resident population information, and the village-level resident population information after space association is obtained.
S106, acquiring multi-source space data in each village and town boundary range in the village and town level resident population information after space association; the multi-source spatial data includes navigation data, land cover data, and night light data.
And S107, splicing the multi-source space data according to village and town boundaries, and converting the spliced multi-source space data into the same projection coordinate system by utilizing the projection conversion function of the acgis software to obtain the projected multi-source space data.
S108, gridding is carried out in a projection coordinate system by taking the administrative boundaries of villages and towns as space areas, and hundred-meter grid data are obtained.
S109, determining the projected multi-source space data contained in each grid in the hundred-meter grid data according to the projected multi-source space data.
S110, performing space intersection operation on the hundred-meter grid data and the village-level resident population information after space association, and determining the village name of each grid in the hundred-meter grid data and the population number corresponding to the village name.
The method comprises the following specific processes:
step S103, distributing population quantity to be distributed towns according to township level population census data to obtain township level distribution resident population information, which specifically comprises the following steps:
Judging whether the villages to be distributed are successfully matched with village codes in village-town level population census data or not, and obtaining a judging result;
if the judgment result shows that the urban population census data are yes, obtaining population proportion of the county and the city occupied by the villages to be distributed according to the village and town level census data;
acquiring population numbers of counties and cities where villages and towns to be distributed are located from village and towns level statistical resident population information;
according to the population quantity of the county and the city of the villages to be allocated and the population proportion of the county and the city of the villages to be allocated, determining the population quantity of the villages to be allocated in the year to be cleaned by utilizing a formula y=k×P;
if the judgment result shows that the urban area boundary range to be allocated is not the statistical range, a space statistical analysis method is adopted to obtain 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 allocated are located from the population kilometer grid data;
according to the population quantity sum in the statistical range and the population quantity sum of the provinces of the villages and towns to be distributed, the formula is utilized
And determining the population number of the villages to be distributed for the year to be cleaned.
Wherein y is the population number of towns to be allocated in the year to be cleaned, k is the population proportion of towns to be allocated occupying the county and the city, P is the population number of towns to be allocated in the county and the city, S is the population sum of towns to be allocated in the province published by the statistical annual survey of the year to be cleaned, a is the population sum of towns in the statistical range, and A is the population sum of towns to be allocated in the statistical range.
Step S104, the village-level statistical resident population information and the village-level distribution resident population information form village-level resident population information of the year to be cleaned, and then further comprises:
acquiring population total of each province according to village and town level resident population information;
obtaining the ratio of the population total number of each province to the population total number of each province in the statistical annual survey, and determining the province with the ratio not in the ratio preset range as an error province; the preset ratio range is 0.9-1.1.
Obtaining the number of resident population in each county and city of the error province according to the statistical annual survey;
according to the number of the i county resident population of the error province, the formula is utilized
Determining an error index of an ith county and a city of the error province;
according to the error index of the ith county and city of the error province, using the formula Y j ＝K i ×y j The corrected population number of the jth village and town of the ith county and city of the error province is determined.
Wherein K is i Error index of ith county and city as error province, M i Counting the population number of the ith county and city of error province in resident population information for village and town level, N j Counting the population number of the jth village and town of the ith county and city of the error province in the resident population information for the village and town level, y j Assigning population numbers for the jth village and town of the ith county and city of the error province, Y j The corrected population number for the jth village and town of the ith county and city of the 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; land types include water impermeable surfaces, cultivated land, woodland, grasslands, water bodies, wetlands, bare land, moss, shrubs, and ice and snow. Night light data includes: radiation signals generated by night lights and fire lights.
Step S107, splicing the multi-source space data according to village and town boundaries, converting the spliced multi-source space data into the same projection coordinate system by utilizing the projection conversion function of the acgis software to obtain projected multi-source space data, and then further comprising:
removing discontinuous roads in navigation data of projected multi-source space data by using a space continuity analysis method;
smoothing night lamplight data of the projected multi-source space data by using Gaussian low-pass filtering to eliminate noise data;
extracting the types of the water-impermeable surfaces, cultivated lands, woodlands, grasslands and water lands in the land coverage data of the projected multi-source space data by utilizing the reclassification function of the acgis software;
The area calculation function of the acgis software is utilized to obtain the area of the watertight surface, the area of the cultivated land, the area of the woodland, the area of the grassland and the area of the water body.
Step S109, according to the projected multi-source space data, calculating corresponding impermeable surfaces, cultivated lands, forest lands, grasslands, water land type areas, navigation road areas, navigation length and night light data values in each grid by using acgis software. The calculation process mainly comprises three steps: the first step: space intersection operation, the second step: calculating the area, and thirdly: and (5) spatial correlation.
The method and the system for correcting, repairing and merging the data solve the problems of unified format and measuring unit, error data repair, noise and redundant data elimination, realize seamless splicing of multi-source data, ensure the precision of the exposure parameter fine inversion product and grid space product from the source of input data, and can provide a reliable data base for final seismic insurance loss evaluation.
The invention provides a specific embodiment for determining the exposure of the rural resident population information of 2016-year village and town in China to the hundred-meter grid population by using a multi-source data grid cleaning method.
The multi-source data includes demographic data and multi-source spatial data.
Step 1: cleaning of demographic data
(1) Resident population matching in 2016
And obtaining 2016-year village-town level resident population data from the statistical annual-number, wherein the resident population data comprises village-town names, village-town codes and population information, and carrying out one-to-one matching association on the population data and 2016-year national village-town administrative division data (comprising village-town boundaries and village-town codes) according to the village-town codes. Because of the lack of statistical annual-discrimination data collected, only the urban population of the part of the country in 2016 can be obtained.
(2) Proportion distribution of 2016-year household registration population
To complement the missing data in the step (1), the population proportion of each village and town occupying the county and the city is calculated according to the village and town level population census data in 2010, the villages and towns without population data are screened out on the basis of the step (1) to be distributed as villages and towns, and the population quantity of each village and towns to be distributed in 2016 is calculated according to the population quantity of the county and the population proportion in 2010. The calculation method comprises the following steps: township population to be allocated = ratio of township population × number of county-level household demographics of 2016 year in county where the township is located.
(3) Population kilometer grid supplement in 2010
Since some town codes are changed, which causes inconsistency between the town codes in 2016 and 2010, when (2) the town codes are changed, they are not allocated, (2) all missing data cannot be completed. And (3) screening villages and towns which still have no population data on the basis of the step (2) as villages and towns to be distributed, taking the space boundary of the villages and towns to be distributed as a statistical range, adopting a space statistical analysis method to count the population quantity sum in the 2010-year population kilometer grid in the range, and carrying out Lashen on the counted population quantity sum as the population quantity of the villages and towns to be distributed, and finally completing all village and township population. The specific stretching method comprises the following steps: firstly, using space boundary of the province where the villages and towns are to be distributed to count the total population of the 2010-year population kilometer grid, obtaining A, wherein the population of the villages and towns to be distributed = the sum of the population numbers of the villages and towns counted by 2016-year statistics and yearly authentication to publish the total population of the province where the villages and towns are located/the total population (A) of the 2010-year population kilometer grid of the province where the villages and towns are located.
(4) Great province of screening difference
A complete set of village and town population is completed through the steps (1), (2) and (3), and then error correction is carried out on the village and town population with errors. The first step of correction is to screen out great differences, and the specific method is as follows: according to the population of the village and town after being completed, the population total number of each province is added and calculated, the population total number is compared with the population total number of each province in 2016 years published in the statistical annual survey, the ratio of the population total number and the population total number is calculated, the provinces with larger differences are screened out, and the step (5) is executed for the provinces with larger differences, so that the screening rule is adopted: ratio >1.1 or ratio <0.9.
(5) Calculating error index of each county/city with great difference
To eliminate errors in distribution of data of kilometers mesh and household, an error index is constructed by first obtaining 2016 county/city level resident population (from statistical annual survey) of widely different provinces, error index=2016 county/city level resident population (from statistical annual survey) -town population of 2016 year resident population (matching result from step (1))/(distribution of villages according to 2016 county population (distribution result from step (2) +distribution of villages according to 2010 space distribution population (distribution result from step (3)).
(6) Correcting the dispensing result of widely differing provinces
The correction method comprises the following steps: to-be-corrected township population = error index of county/city of the township x the township allocated population (from 2 and 3), the 2016 year township level population is obtained by correction.
(7) Verification of
And (3) comparing the national population data and provincial population data with 2016-year resident population data, calculating relative errors, and calculating the national population relative errors by statistics to 0.028%, wherein the population errors of all provincials are within 5%, so that the requirements are met.
(8) Information association
And (3) adopting a space association function of acgis professional software to associate 2016-year administrative division boundary data with 2016-year village-town population data (the result of the step (6)) after cleaning according to a village-town code field.
Step 2: cleaning of multisource spatial data
Selecting multi-source spatial data related to population distribution, wherein the multi-source spatial data mainly comprises: navigation data, land cover data, night light data.
Navigation data: the road data mainly refer to road data of various levels, and each road has area and length information.
Land cover data: including farmland, forests, grasslands, wetlands, bare lands, bodies of water, watertight surfaces, moss, shrubs, ice and snow.
Night light data: the radiation signals generated by night lamplight, fire light and the like are collected. The DMSP/OLS sensor works at night and can detect low-intensity light emitted by urban lights, even small-scale residents, traffic flows and the like.
(1) Data preprocessing
And carrying out data preprocessing on the three data. Including data stitching and projective transformation. Data stitching is the basis for data integrity. And splicing the framing multi-source space data according to the national boundary to form a frame of nationwide multi-source space data. The complete data is transformed into a unified projection coordinate system (WGS 84-Albers) using a projection transformation function based on arcgis specialized tools.
(2) Outlier rejection
Aiming at the preprocessed navigation data, removing roads which cannot be continuous in the navigation data through the common spatial continuity analysis in the prior art;
and smoothing the preprocessed night lamplight data through Gaussian low-pass filtering to eliminate image noise generated by scattered weak lamplight.
(3) Available type extraction
And extracting a watertight layer based on arcgis software reclassifying function aiming at the preprocessed land coverage data, and discarding other types of cultivated land, woodland, grassland and water land types.
Step 3: space computation
(1) Hundred meter standard grid formulation
According to the national administrative boundary space range, 100 x 100 meters of grid data are constructed, and the coordinate system is required to be unified as WGS84-Albers.
(2) Spatial analysis and assignment
According to the result of the preset unified standard grid data (step 1), arcgis software is utilized to calculate the corresponding impermeable surface, farmland, woodland, grassland, water land type area, navigation road area, length and night light data values in the hundred-meter range, the villages and towns where each grid is located and the population number of each village and towns are determined through the space intersection operation of the grid data and the population data, and finally various spatial information and demographic information are unified into a hundred-meter grid frame.
The multi-source data gridding cleaning method provided by the invention has the following advantages:
1. complete refined demographic data
Through the cleaning process of this patent, the data of the rural class of 2016 nationwide range has been obtained, compares other acquirable nationwide province level data, and partial province county level data, and this data is both meticulous and complete.
2. Unified standard, seamless splice
The original basic geographic data, navigation map data, light index data, socioeconomic data or population data are different in data space units, coordinate systems, data sources, time and the like, and after cleaning, the data have the same space coordinate system (WGS 84-Albers), the same time attribute (2016 years) and the same data form (hundred-meter grid), so that the data are a complete set of data after cleaning. Moreover, the grid cells with the hundred-meter scale are constructed nationwide and are in a continuous state in space, and are not divided by administrative attribution.
3. Supporting flexible applications
The large-scale multi-source data information is packaged in a hundred-meter refining unit, and flexible scheduling and use of the model according to actual data requirements can be supported.
The invention also provides a multi-source data gridding cleaning system, which comprises:
the village-town statistical resident population information acquisition unit is used for acquiring village-town statistical resident population information of the year to be cleaned from the statistical year authentication; the village-level statistical resident population information comprises village codes, village names and population numbers;
the village and town to be allocated determining unit is used for carrying out matching association on the village and town level statistical resident population information and the village and town administrative division information of the year to be cleaned according to the village and town codes of the village and town level statistical resident population information, and obtaining the village and town codes and corresponding village names which are not matched with the village and town level statistical resident population information in the village and town administrative division information, and determining the village and town to be allocated; the village and town administrative division information comprises a village and town code, a village and town name and a village and town boundary;
the village-level distribution resident population information obtaining unit is used for obtaining village-level distribution resident population information according to village-level population census data and population kilometer grid data and the number of villages to be distributed;
The village-level resident population information forming unit is used for forming village-level resident population information of the year to be cleaned by village-level statistical resident population information and village-level distribution resident population information;
the space-related village-level resident population information obtaining unit is used for carrying out space-related on village-level administrative division information of the year to be cleaned and village-level resident population information by adopting a space-related function of acgis software according to village codes of the village-level resident population information to obtain the village-level resident population information after the space-related;
the multi-source space data acquisition unit is used for acquiring multi-source space data in each village and town boundary range in the village and town level resident population information after spatial association; the multi-source spatial data includes navigation data, land cover data and night light data;
the projected multi-source space data acquisition unit is used for splicing the multi-source space data according to the village and town boundaries, converting the spliced multi-source space data into the same projection coordinate system by utilizing the projection conversion function of the acgis software, and acquiring the projected multi-source space data;
the system comprises a hundred-meter grid data obtaining unit, a three-dimensional grid data obtaining unit and a three-dimensional grid data obtaining unit, wherein the hundred-meter grid data obtaining unit is used for gridding a rural administrative boundary serving as a space region in a projection coordinate system;
A multi-source space data determining unit after grid projection, configured to determine, according to the multi-source space data after projection, multi-source space data after projection contained in each grid in the hundred-meter grid data;
and the grid population number determining unit is used for carrying out space intersection operation on the hundred-meter grid data and the village-level resident population information after space association to determine the village name where each grid in the hundred-meter grid data is located and the population number corresponding to the village name where each grid is located.
The village and town level distribution resident population information obtaining unit specifically comprises:
the judging result obtaining subunit is used for judging whether the villages to be distributed are successfully matched with the village codes in the village-town level population 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 the city occupied by the villages to be distributed according to the village and town level population census data if the judgment result shows that the judgment result is yes;
the county and city population quantity acquisition subunit is used for acquiring the population quantity of county and city of the villages and towns to be distributed from the village and towns level statistical resident population information;
the first village population quantity determining subunit is used for determining the population quantity of the villages to be distributed in the year to be cleaned according to the population quantity of the counties to be distributed and the population proportion of the counties to be distributed to occupy the counties to be distributed by utilizing the formula y=k×P;
The village and town population sum obtaining subunit is used for obtaining the village and town population sum in the statistical range and the population sum of the province where the villages and towns to be distributed are located from the population kilometer grid data by adopting a space statistical analysis method with the village and towns boundary range to be distributed as the statistical range if the judging result indicates no;
a second village population quantity determining subunit, configured to utilize the formula according to the population quantity sum in the statistical range and the population quantity sum of the provinces where the villages and towns to be allocated are located
Determining the population number of villages to be distributed in the year to be cleaned;
wherein y is the population number of towns to be allocated in the year to be cleaned, k is the population proportion of towns to be allocated occupying the county and the city, P is the population number of towns to be allocated in the county and the city, S is the population sum of towns to be allocated in the province published by the statistical annual survey of the year to be cleaned, a is the population sum of towns in the statistical range, and A is the population sum of towns to be allocated in the statistical range.
The system further comprises:
the province population total number acquisition unit is used for acquiring population total number of each province according to village and town level resident population information;
the error province determining and acquiring unit is used for acquiring the ratio of the population total number of each province to the population total number of each province in the statistical annual survey, and determining the province with the ratio not in the ratio preset range as the error province;
The county and city resident population quantity acquisition unit is used for acquiring the resident population quantity of each county and city of the error province according to the statistical annual survey;
an error index obtaining unit for obtaining the number of the i county and city resident population according to the error province by using the formula
Determining an error index of an ith county and a city of the error province;
a correction population number acquisition unit for using the formula Y according to the error index of the ith county and city of the error province j ＝K i ×y j Determining the correction population number of the jth village and town of the ith county and city of the error province;
wherein K is i Error index of ith county and city as error province, M i Counting the population number of the ith county and city of error province in resident population information for village and town level, N j Counting the population number of the jth village and town of the ith county and city of the error province in the resident population information for the village and town level, y j Assigning population numbers for the jth village and town of the ith county and city of the error province, Y j The corrected population number for the jth village and town of the ith county and city of the 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 water impermeable surfaces, cultivated lands, woodlands, grasslands, bodies of water, wetlands, bare lands, moss, shrubs, and ice and snow;
Night light data includes: radiation signals generated by night lights and fire lights.
The system further comprises:
the discontinuous road removing unit is used for removing discontinuous roads in the navigation data of the projected 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 and eliminating noise data;
the land coverage data extraction unit is used for extracting the types of the water-impermeable surfaces, cultivated lands, woodlands, grasslands and water lands in the land coverage data of the projected multi-source space data by utilizing the reclassification function of the acgis software;
the area extraction unit is used for obtaining the area of the watertight surface, the area of the cultivated land, the area of the forest land, the area of the grassland and the area of the water body by utilizing the calculation function of the acgis software area.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. A method for multi-source data meshing cleaning, the method comprising:
acquiring village and town level statistical resident population information of the year to be cleaned from the statistical year authentication; the village-level statistical resident population information comprises village codes, village names and population numbers;
according to the village codes of the village-level statistical resident population information, carrying out matching association on the village-level statistical resident population information and village administrative division information of the year to be cleaned, and acquiring the village codes and corresponding village names, which are not matched with the village-level statistical resident population information, of the village administrative division information of the villages and towns, so as to determine the villages to be allocated; the village and town administrative division information comprises a village and town code, a village and town name and a village and town boundary;
Distributing population quantity to the villages to be distributed according to village-level population census data and population kilometer grid data to obtain village-level distribution resident population information;
the village-level statistical resident population information and the village-level distribution resident population information form village-level resident population information of the year to be cleaned;
according to the village code of the village-level resident population information, adopting the space association function of acgis software to carry out space association on village administrative division information of the year to be cleaned and the village-level resident population information, and obtaining the village-level resident population information after the space association;
acquiring multi-source space data in each village-town boundary range in the village-town level resident population information after the space association; the multi-source space data comprises navigation data, land coverage data and night light data;
splicing the multi-source space data according to village and town boundaries, and converting the spliced multi-source space data into the same projection coordinate system by utilizing the projection conversion function of the acgis software to obtain projected multi-source space data;
gridding is carried out in a projection coordinate system by taking a village and town administrative boundary as a space region, so as to obtain hundred-meter grid data;
Determining projected multi-source spatial data contained in each grid in the hundred-meter grid data according to the projected multi-source spatial data;
and carrying out space intersection operation on the hundred-meter grid data and the village-level resident population information after space association, and determining the village name of each grid in the hundred-meter grid data and the population number corresponding to the village name.
2. The multi-source data gridding cleaning method according to claim 1, wherein the step of distributing population numbers to the towns to be distributed according to township population census data and population kilometer grid data to obtain township distribution resident population information comprises the following steps:
judging whether the villages to be distributed are successfully matched with village codes in village-town level population census data or not, and obtaining a judging result;
if the judgment result shows that the current value is positive, obtaining the population proportion of the county and the city occupied by the villages to be distributed according to the village and town level population census data;
acquiring population numbers of counties and cities of the villages to be distributed from the village-level statistical resident population information;
determining the population number of the villages to be distributed in the year to be cleaned according to the population number of the counties to be distributed and the population proportion of the counties to be distributed to occupy the counties to be distributed by using a formula y=k×P;
If the judgment result shows that the rural area network distribution method is not used, taking the rural area boundary range to be distributed as a statistical range, and adopting a space statistical analysis method to obtain 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;
according to the population quantity sum in the statistical range and the population quantity sum of the provinces where the villages and towns to be distributed are located, utilizing a formula
Determining the population number of villages to be distributed in the year to be cleaned; />
Wherein y is the population number of towns to be allocated in the year to be cleaned, k is the population proportion of towns to be allocated occupying the county and the city, P is the population number of towns to be allocated in the county and the city, S is the population sum of towns to be allocated in the province published by the statistical annual survey of the year to be cleaned, a is the population sum of towns in the statistical range, and A is the population sum of towns to be allocated in the statistical range.
3. The multi-source data meshing cleansing method of claim 1 wherein the village-level statistical resident population information and the village-level assignment resident population information constitute village-level resident population information for the year to be cleansed, and further comprising thereafter:
Acquiring population total of each province according to the village and town level resident population information;
obtaining the ratio of the population total number of each province to the population total number of each province in the statistical annual survey, and determining the province with the ratio not in the ratio preset range as an error province;
obtaining the number of resident population in each county and city of the error province according to the statistical annual survey;
according to the number of the i county resident population of the error province, the formula is utilized
Determining an error index of the ith county and city of the error province;
according to the error index of the ith county and city of the error province, using the formula Y j ＝K i ×y j Determining a corrected population quantity for a j-th village and town of an i-th county and city of the error province;
wherein K is i Error index of ith county and city as error province, M i Counting the population number of the ith county and city of error province in resident population information for village and town level, N j Counting the population number of the jth village and town of the ith county and city of the error province in the resident population information for the village and town level, y j Assigning population numbers for the jth village and town of the ith county and city of the error province, Y j The corrected population number for the jth village and town of the ith county and city of the error province.
4. The method of multi-source data meshing cleansing as defined in claim 1, wherein,
The navigation data includes: the area and length of each road;
the land cover data includes: land type and area of each land type; the land types include water impermeable surfaces, cultivated lands, woodlands, grasslands, bodies of water, wetlands, bare lands, moss, shrubs, and ice and snow;
the night light data includes: radiation signals generated by night lights and fire lights.
5. The method for meshing and cleaning multi-source data according to claim 4, wherein the steps of splicing the multi-source spatial data according to village and town boundaries, converting the spliced multi-source spatial data into the same projection coordinate system by using a projection conversion function of acgis software to obtain projected multi-source spatial data, and further comprising:
removing discontinuous roads in navigation data of the projected multi-source spatial data by using a spatial continuity analysis method;
smoothing the night lamplight data of the projected multi-source space data by using Gaussian low-pass filtering to eliminate noise data;
extracting the types of the water-impermeable surfaces, cultivated lands, woodlands, grasslands and water lands in the land coverage data of the projected multi-source space data by utilizing the reclassification function of the acgis software;
The area calculation function of the acgis software is utilized to obtain the area of the watertight surface, the area of the cultivated land, the area of the woodland, the area of the grassland and the area of the water body.
6. A multi-source data meshing cleaning system, the system comprising:
the village-town statistical resident population information acquisition unit is used for acquiring village-town statistical resident population information of the year to be cleaned from the statistical year authentication; the village-level statistical resident population information comprises village codes, village names and population numbers;
the village and town to be allocated determining unit is used for carrying out matching association on the village and town level statistical resident population information and village and town administrative division information of the year to be cleaned according to the village and town codes of the village and town level statistical resident population information, acquiring the village and town codes and corresponding village names, which are not matched with the village and town level statistical resident population information, in the village and town administrative division information, and determining the village and town to be allocated; the village and town administrative division information comprises a village and town code, a village and town name and a village and town boundary;
the village-level distribution resident population information obtaining unit is used for obtaining village-level distribution resident population information for the villages and towns to be distributed according to the village-level population census data and the population kilometer grid data;
The village-level resident population information forming unit is used for forming village-level resident population information of the year to be cleaned by the village-level statistical resident population information and the village-level distribution resident population information;
the space-related village-level resident population information obtaining unit is used for carrying out space-related on village-level administrative division information of the year to be cleaned and the village-level resident population information by adopting the space-related function of acgis software according to the village code of the village-level resident population information to obtain the village-level resident population information after the space-related;
the multi-source space data acquisition unit is used for acquiring multi-source space data in each village and town boundary range in the village and town level resident population information after the space association; the multi-source space data comprises navigation data, land coverage data and night light data;
the projected multi-source space data acquisition unit is used for splicing the multi-source space data according to village and town boundaries, converting the spliced multi-source space data into the same projection coordinate system by utilizing the projection conversion function of the acgis software, and acquiring the projected multi-source space data;
the system comprises a hundred-meter grid data obtaining unit, a three-dimensional grid data obtaining unit and a three-dimensional grid data obtaining unit, wherein the hundred-meter grid data obtaining unit is used for gridding a rural administrative boundary serving as a space region in a projection coordinate system;
A multi-source space data determining unit after grid projection, configured to determine, according to the multi-source space data after projection, multi-source space data after projection included in each grid in the hundred-meter grid data;
and the grid population number determining unit is used for carrying out space intersection operation on the hundred-meter grid data and the village-level resident population information after the space association to determine the village name where each grid in the hundred-meter grid data is located and the population number corresponding to the village name where each grid is located.
7. The multi-source data meshing cleansing system of claim 6 wherein said village-level distribution resident demographic information obtaining unit comprises in particular:
the judging result obtaining subunit is used for judging whether the villages to be distributed are successfully matched with the village codes in the village-town level population 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 the city occupied by the villages to be distributed according to the village and town level population census data if the judgment result shows that the judgment result is yes;
the county and city population quantity acquisition subunit is used for acquiring the population quantity of the county and city where the villages and towns to be distributed are located from the village and towns level statistical resident population information;
The first village population quantity determining subunit is used for determining the population quantity of the villages to be distributed in the year to be cleaned according to the population quantity of the counties to be distributed and the population proportion of the counties to be distributed in the counties to be distributed, and the formula y=k×P is utilized;
the village and town population sum obtaining subunit is configured to obtain, if the judging result indicates no, a village and town population sum in the statistical range and a village and town population sum in a province where the villages and towns to be distributed are located from the population kilometer grid data by using the space statistical analysis method with the village and town boundary range to be distributed as the statistical range;
a second village population quantity determining subunit, configured to utilize the formula according to the population quantity sum in the statistical range and the population quantity sum in the province where the villages and towns to be allocated
Determining the population number of villages to be distributed in the year to be cleaned;
wherein y is the population number of towns to be allocated in the year to be cleaned, k is the population proportion of towns to be allocated occupying the county and the city, P is the population number of towns to be allocated in the county and the city, S is the population sum of towns to be allocated in the province published by the statistical annual survey of the year to be cleaned, a is the population sum of towns in the statistical range, and A is the population sum of towns to be allocated in the statistical range.
8. The multi-source data meshing cleansing system of claim 6, further comprising:
the province population total number acquisition unit is used for acquiring population total numbers of each province according to the village and town level resident population information;
the error province determining and acquiring unit is used for acquiring the ratio of the population total number of each province to the population total number of each province in the statistical annual survey, and determining the province with the ratio not in the ratio preset range as the error province;
the county and city resident population quantity acquisition unit is used for acquiring the county and city resident population quantity of each county and city of the error province according to the statistical annual survey;
an error index obtaining unit for obtaining the number of the i-th county and city resident population of the error province by using the formula
Determining an error index of the ith county and city of the error province;
a correction population number acquisition unit for using the formula Y according to the error index of the ith county and city of the error province j ＝K i ×y j Determining a corrected population quantity for a j-th village and town of an i-th county and city of the error province;
wherein K is i Error index of ith county and city as error province, M i Counting the population number of the ith county and city of error province in resident population information for village and town level, N j Counting the population number of the jth village and town of the ith county and city of the error province in the resident population information for the village and town level, y j Assigning population numbers for the jth village and town of the ith county and city of the error province, Y j The corrected population number for the jth village and town of the ith county and city of the error province.
9. The multi-source data grid cleaning system of claim 6 wherein,
the navigation data includes: the area and length of each road;
the land cover data includes: land type and area of each land type; the land types include water impermeable surfaces, cultivated lands, woodlands, grasslands, bodies of water, wetlands, bare lands, moss, shrubs, and ice and snow;
the night light data includes: radiation signals generated by night lights and fire lights.
10. The multi-source data meshing cleaning system of claim 9, further comprising:
the discontinuous road removing unit is used for removing discontinuous roads in the navigation data of the projected multi-source space data by using a space continuity analysis method;
the noise data eliminating unit is used for carrying out smoothing processing on night light data of the multi-source space data after projection by utilizing Gaussian low-pass filtering, and eliminating noise data;
The land coverage data extraction unit is used for extracting the types of the water-impermeable surfaces, cultivated lands, woodlands, grasslands and water lands in the land coverage data of the projected multi-source space data by utilizing the reclassification function of the acgis software;
the area extraction unit is used for obtaining the area of the watertight surface, the area of the cultivated land, the area of the forest land, the area of the grassland and the area of the water body by utilizing the area calculation function of the acgis software.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011346406.7A CN112486963B (en) | 2020-11-26 | 2020-11-26 | Multi-source data gridding cleaning method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011346406.7A CN112486963B (en) | 2020-11-26 | 2020-11-26 | Multi-source data gridding cleaning method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112486963A CN112486963A (en) | 2021-03-12 |
| CN112486963B true CN112486963B (en) | 2023-05-26 |
Family
ID=74934836
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011346406.7A Active CN112486963B (en) | 2020-11-26 | 2020-11-26 | Multi-source data gridding cleaning method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112486963B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2436312C (en) * | 2003-08-01 | 2011-04-05 | Perry Peterson | Close-packed, uniformly adjacent, multiresolutional, overlapping spatial data ordering |
| US20090158185A1 (en) * | 2007-12-17 | 2009-06-18 | Socialexplorer, Inc. | Adaptive map layer visibility control |
-
2020
- 2020-11-26 CN CN202011346406.7A patent/CN112486963B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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)
| Title |
|---|
| Dimitrios Mentis 等.A GIS-based approach for electrification planning—A case study on Nigeria.《Energy for Sustainable Development》.2015,142-150. * |
| Haiping Xiao 等.The population development functional zoning in Yunnan Province using the multi-factor superposition model based on GIS.《2011 19th International Conference on Geoinformatics》.2011,1-5. * |
| 何浩 等.统计遥感空间基础框架的研究与应用.《测绘科学》.2011,第36卷(第06期),253-256. * |
| 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.《北京师范大学学报(自然科学版)》.2012,第48卷(第06期),654-658+584. * |
| 潘顺.长三角人口数据格网化及其人口空间分布特征分析.《中国优秀硕士学位论文全文数据库 社会科学Ⅱ辑》.2017,H125-23. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112486963A (en) | 2021-03-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhu et al. | The effect of urban morphology on the solar capacity of three-dimensional cities | |
| CN106909692B (en) | Method for calculating urban public facility coverage radiation index | |
| Li et al. | Explore the recreational service of large urban parks and its influential factors in city clusters–Experiments from 11 cities in the Beijing-Tianjin-Hebei region | |
| Liu et al. | Characterizing three dimensional (3-D) morphology of residential buildings by landscape metrics | |
| Wang et al. | Spatiotemporal variability in long-term population exposure to PM2. 5 and lung cancer mortality attributable to PM2. 5 across the Yangtze River Delta (YRD) region over 2010–2016: A multistage approach | |
| CN114881550B (en) | Resource equalization allocation method and system based on spatial information | |
| CN112288311A (en) | Convenient and fast residential area supporting facility metering method based on POI data | |
| CN114881466A (en) | Multi-source data-based population space partition fitting method | |
| CN105844031A (en) | Mobile phone positioning data based urban traffic corridor identification method | |
| CN112486963B (en) | Multi-source data gridding cleaning method and system | |
| Yu et al. | A simple but actionable metric for assessing inequity in resident greenspace exposure | |
| CN106980942A (en) | Calculate method of the bicycle free way to the coverage of public bicycles lease point | |
| CN109190940B (en) | Method for laying common road traffic condition survey stations by considering regional boundary control | |
| Chen et al. | Which green is more equitable? A study of urban green space equity based on morphological spatial patterns | |
| CN104794164B (en) | Method based on the social parking demand of data identification settlement parking stall matching of increasing income | |
| Wang et al. | Past land use decisions and socioeconomic factors influence urban greenbelt development: a case study of Shanghai, China | |
| Crols et al. | Downdating high-resolution population density maps using sealed surface cover time series | |
| Georgati et al. | Spatially explicit population projections: The case of Copenhagen, Denmark | |
| CN112926029B (en) | Residential area identification and division method for rural domestic sewage treatment | |
| CN115271332A (en) | Drought monitoring method | |
| Ahmed et al. | How accurate are locations in Malaysian accident data? Development of a rectification procedure based on nested filtered search technique | |
| Goodman | Environmental Justice and GIS: A Comparison of Three GIS Methods for Estimating Vulnerable Population Exposed to Brownfield Pollution in Portland, Oregon | |
| CN112802191A (en) | Real-time simulation display system for city planning | |
| CN103247224B (en) | Drawing method of galloping distribution map and device thereof based on galloping days | |
| CN116403112B (en) | Method and device for demarcating rural black and odorous water body investigation range |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |