CN106708962A - Urban population distribution method based on building properties - Google Patents
Urban population distribution method based on building properties Download PDFInfo
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- CN106708962A CN106708962A CN201611086311.XA CN201611086311A CN106708962A CN 106708962 A CN106708962 A CN 106708962A CN 201611086311 A CN201611086311 A CN 201611086311A CN 106708962 A CN106708962 A CN 106708962A
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- building
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- 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
- G06F16/29—Geographical information databases
Abstract
The invention discloses an urban population distribution method based on building properties. The method comprises the specific steps that all building information and building periphery interest point information in an electronic map are obtained according to an urban longitude and latitude coordinate range; the electronic map is queried targeting a certain population statistic region, coordinates of the population statistic region are determined, and the gross population in the region is queried; all buildings in the population statistic region are screened out according to building locations and boundary angle point coordinates of the population statistic region; social activity properties of the buildings are inferred; population attraction coefficients, at different time unit areas, of the buildings of different social activity property types are set, and the population in the population statistic region is distributed into each building in the region to obtain building-grade population distribution; and all population statistic regions in a city are traversed to obtain urban population distribution. The method is applied to building-grade urban population distribution, the problem of rough urban population distribution scale can be effectively solved, and population distribution timing difference is reflected.
Description
Technical field
The present invention relates to the technical field that population distribution is estimated, more particularly, to a kind of city based on building attribute
City's population distribution method.
Background technology
Urban population spatial distribution is research human behavior, assessment urban environment and mankind's interaction under Effects of Urbanization
Basic work.Government aspect, multiple census data from macroscopically presenting Urban Population Distribution feature, and for smaller
The Urban Population Distribution research of yardstick provides partial data basis.Technological layer, the magnanimity interest that network electronic map is provided
Point provides another approach for human behavior research, meanwhile, the attribute of point of interest reflects building very to a certain extent
To the social activities attribute of this area, this makes it possible to be based on the Urban Population Distribution method of building attribute.
At present, Urban Population Distribution is remained in some problems.
First, Urban Population Distribution regional scale is coarse.In view of census data Duo Yi streets are base unit, cause
Population distribution based on census data is mostly with block as smallest dimension, it is impossible to reflect the population of building rank
Spatial distribution characteristic and difference.Secondly, even different periods population distribution is special round the clock for the building of different society activity attributes
Property is significantly different, and conventional method can not embody population distribution timing difference.
The content of the invention
Present invention aim to overcome that the shortcoming of prior art and deficiency, there is provided a kind of computational efficiency is high, processing method is simple
Single Urban Population Distribution method based on building attribute, for the urban population spatial and temporal distributions of class of buildings.
In order to solve the above technical problems, the technical solution adopted by the present invention is：
A kind of Urban Population Distribution method based on building attribute, comprises the steps of：
A () obtains all buildings in electronic map according to city latitude and longitude coordinates scope, the mode inquired about using building
Thing information and building periphery interest point information；
B () is directed to a certain geographical area, electronic map query is carried out with the entitled keyword in region, determines demographics
Area coordinate, and the query region population from urban population generaI investigation yearbook；
C () filters out the institute of the geographical area according to building object location and geographical area border angular coordinate
There is building；
D () pushes away according to the type of several points of interest nearest around building, weighing factor and with a distance from building
The social activities attribute of the building different time sections of breaking；
E () sets different society activity attributes type building unit area population attraction coefficient, by geographical area
During interior population is assigned in region per solitary building, the population distribution of class of buildings is obtained；
F () is directed to urban area, repeat step (b), (c), (d) and (e) obtain Urban Population Distribution.
The present invention takes full advantage of the building and interest point data of electronic map magnanimity, anti-by interest point data attribute
The type of social activities attribute in building is reflected, and the population distribution in city is calculated with this, obtain more fine city
Population distribution.The population distribution that the present invention is obtained can not only reflect population variation tendency spatially, also embody population point
Cloth otherness in time.Meanwhile, also evade part population partitioning model region has been divided using rectangular block, and lead
Cause the problem of the destruction of regional space similitude.
The present invention is obtained using building and interest point data, building social activities attribute determines and building population point
Sound transmission computational problem is solved with three technological means.
Further, the information of the building include building name, each angular coordinate in bottom surface, center point coordinate,
Story height, place administrative region.
Further, the point of interest refers to be abstracted into data object in electronic map, all kinds of in map for representing
The atural object of service.
Further, the interest point information includes interest point name, coordinate of interest points, interest vertex type, point of interest
The distance of weighing factor and point of interest apart from building.
Further, the building social activities attribute includes residential area, Office Area, shopping centre and style area four
Class.
Further, in the step (d), the deduction of building social activities attribute is comprised the following steps：
(1) determine that the certain distance BM interior BN points of interest nearest from building central point in building periphery is built as influence
Build the interest point set of thing social activities attribute；
(2) building periphery each point of interest P is determinediContribution to a certain type in building social activities attribute, its
Influence and the distance dependent of point of interest weighing factor, point of interest and building；
(3) contribution of comprehensive each point of interest to the type of building social activities attribute four, determines the society of the building
Can activity attributes.
Further, in the step (e), different society activity attributes different periods building unit area population is inhaled
Draw coefficient different.
Further, in the step (e), per solitary building population distribution by geographical area total number of people
Ratio according to building attraction coefficient is allocated.
Further, all geographical areas are traveled through in the step (f), and repeat step (b), (c),
D () and (e), obtains the population distribution of urban area building rank.
Compared with prior art, present invention has the advantages that：Urban population is carried out under conditions of based on building attribute
Distribution, so as to get population distribution can reach building rank, while can by set relevant parameter embody population distribution
Otherness in time.It is embodied in：
(1) it is determined that during building social activities attribute, make use of the interest point data of magnanimity, belonged to by interest point data
Property, the function or purposes of building are pointing directly at, the type of accurate fine sign building social activities attribute reaches building
The population distribution that becomes more meticulous of thing rank；
(2) it is determined that being different society Activity Type according to the different periods during building unit area attraction coefficient
Building sets different attraction coefficients, while building rank population distribution is considered, it is also considered that reality servant
The timing difference of mouth distribution, such as population distribution round the clock with different periods are simulated.
(3) population distribution of building form can realize the region customization of population distribution feature evaluation, evade part
Population partitioning model is divided using rectangular block to region, and causes the problem of the destruction of regional space similitude.
Brief description of the drawings
Fig. 1 is the Urban Population Distribution method flow diagram based on building attribute.
Specific embodiment
The present invention will be further described below in conjunction with the accompanying drawings, but embodiments of the present invention are not limited to this.
As shown in figure 1, the present invention provides a kind of Urban Population Distribution method based on building attribute.By following steps
Realize：
Step 1：Latitude and longitude coordinates scope according to city, city is obtained using building querying method from electronic map
Owned building information in region, and it is stored in database.The information of building includes that each angle point of building name, bottom surface is sat
Mark, center point coordinate, story height, place administrative region.
Step 2：For each building, according to its center point coordinate, looked into from electronic map using automatic search algorithm
Ask and limit nearest from building central point BN point of interest in BM around building, using interest point information as building
Attribute is stored in database.In further data processing and data are calculated, the related letter of building is directly obtained from database
Breath.Interest point information includes interest point name, coordinate of interest points, interest vertex type, point of interest weighing factor and point of interest distance
The distance of building.
Step 3：To each geographical area D in geographical area set DSi, from urban population generaI investigation yearbook
The population of query region.And with the entitled keyword in geographical area, using automatic search algorithm, in Internet map
The coordinate of middle acquisition geographical area, database is stored in by the area information of acquisition.
Step 4：The pin point coordinate of center position and geographical area according to building, by geographical area
Owned building screen.
Step 5：Determine the certain distance BM interior BN points of interest nearest from building central point in building periphery as shadow
Ring the interest point set of building social activities attribute.
Step 6：Determine building periphery each point of interest PiContribution to building social activities attributeIts influence
With the distance dependent of point of interest weighing factor, point of interest and building：
Wherein,Weighing factor of the point of interest to building is represented, it is related to interest vertex type；Represent emerging
Interest point apart from building distance, point of interest from building more away from, its impact effect will be smaller, and n is distance attenuation exponent.
Step 7：According to the type of each point of interest, determine that point of interest is a certain to building social activities attribute in all set
The contribution of item：
Wherein,Represent a certain building classification BTS of buildingjRatio；Represent point of interest PiIt is corresponding
Building type, N is the number of point of interest around building.
Step 8：Contribution of comprehensive each point of interest to the type of building social activities attribute four, determines the building
Social activities attribute.
Step 9：Setting different society activity attributes different periods building unit area population attraction coefficient.
Step 10：The total number of people of geographical area is allocated according to the ratio of building attraction coefficient, is obtained
Population distribution per solitary building.
Step 11：The traversal all geographical areas in city, and repeat step 4-10, obtain urban area building
The population distribution of rank.
The implementation method of invention described above, is not intended to limit the scope of the present invention..It is any in this hair
Done modification, equivalent and improvement etc. within bright spiritual principles, should be included in claim protection of the invention
Within the scope of.
Claims (9)
1. a kind of Urban Population Distribution method based on building attribute, it is characterised in that comprise the steps of：
A (), according to city latitude and longitude coordinates scope, owned building is believed during the mode inquired about using building obtains electronic map
Breath and building periphery interest point information；
B () is directed to a certain geographical area, electronic map query is carried out with the entitled keyword in region, determines geographical area
Coordinate, and the query region population from urban population generaI investigation yearbook；
C () filters out all of the geographical area and builds according to building object location and geographical area border angular coordinate
Build thing；
D (), according to the type of several points of interest nearest around building, weighing factor and with a distance from building, inferring should
The social activities attribute of building different time sections；
E () sets different society activity attributes type building unit area population attraction coefficient, by geographical area
During population is assigned in region per solitary building, the population distribution of class of buildings is obtained；
F () is directed to each geographical area, repeat step (b), (c), (d) and (e) obtain Urban Population Distribution.
2. the Urban Population Distribution method based on building attribute according to claim 1, it is characterised in that the building
The information of thing includes building name, each angular coordinate in bottom surface, center point coordinate, story height, place administrative region.
3. the Urban Population Distribution method based on building attribute according to claim 1, it is characterised in that the interest
Point refers to be abstracted into data object in electronic map, for representing the atural object of all kinds of services in map.
4. the Urban Population Distribution method based on building attribute according to claim 1, it is characterised in that the interest
Point information includes interest point name, coordinate of interest points, and interest vertex type, point of interest weighing factor and point of interest are apart from building
Distance.
5. the Urban Population Distribution method based on building attribute according to claim 1, it is characterised in that the building
Thing social activities attribute includes residential area, Office Area, shopping centre and the class of style area four.
6. the Urban Population Distribution method based on building attribute according to claim 1, it is characterised in that the step
D in (), the deduction of building social activities attribute is comprised the following steps：
(d1) determine the interior BN points of interest nearest from building central point of building peripheral distance BM as influence building society
The interest point set of meeting activity attributes；
(d2) building periphery each point of interest P is determinediContribution to a certain type in building social activities attribute, its influence
With the distance dependent of point of interest weighing factor, point of interest and building；
(d3) contribution of comprehensive each point of interest to the type of building social activities attribute four, determines that the society of the building is living
Dynamic attribute.
7. the Urban Population Distribution method based on building attribute according to claim 1, it is characterised in that the step
E in (), different society activity attributes different periods building unit area population attraction coefficient is different.
8. the Urban Population Distribution method based on building attribute according to claim 1, it is characterised in that the step
E in (), the population distribution per solitary building is entered by the total number of people of geographical area according to the ratio of building attraction coefficient
Row distribution.
9. the Urban Population Distribution method based on building attribute according to claim 1, it is characterised in that the step
In (f), all geographical areas are traveled through, and repeat step (b), (c), (d) and (e), obtain urban area building
The population distribution of rank.
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108600340A (en) * | 2018-04-08 | 2018-09-28 | 深圳市和讯华谷信息技术有限公司 | It is a kind of that total method and device is pushed away based on the history crowd size for moving big-sample data |
| CN108871286A (en) * | 2018-04-25 | 2018-11-23 | 中国科学院遥感与数字地球研究所 | The completed region of the city density of population evaluation method and system of space big data collaboration |
| CN109947887A (en) * | 2019-03-20 | 2019-06-28 | 智慧足迹数据科技有限公司 | Population distribution statistical method and device |
| CN110019626A (en) * | 2017-12-21 | 2019-07-16 | 腾讯科技（深圳）有限公司 | A kind of the determination method and relevant apparatus of population distribution information |
| CN110263109A (en) * | 2019-05-22 | 2019-09-20 | 中国科学院地理科学与资源研究所 | A kind of family's amount evaluation method merging internet information and GIS technology |
| CN110298253A (en) * | 2019-05-30 | 2019-10-01 | 特斯联（北京）科技有限公司 | A kind of physically weak quasi- display methods of urban architecture based on population big data and system |
| CN110704789A (en) * | 2019-08-16 | 2020-01-17 | 重庆特斯联智慧科技股份有限公司 | Population dynamic measurement and calculation method and system based on 'urban superconcephalon' computing platform |
| CN112668752A (en) * | 2020-11-27 | 2021-04-16 | 合肥泽众城市智能科技有限公司 | Safe evacuation method and system for gas pipeline leakage emergency |
| CN113191553A (en) * | 2021-05-06 | 2021-07-30 | 深圳市数字城市工程研究中心 | Population space distribution estimation method and system based on building scale |
| CN114363823A (en) * | 2021-05-26 | 2022-04-15 | 科大国创云网科技有限公司 | Population density monitoring method and system based on MR (magnetic resonance) permanent station and building outline |
| CN115186009A (en) * | 2022-07-13 | 2022-10-14 | 中国科学院地理科学与资源研究所 | Urban population daily change spatialization method and system based on interest point data |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101673304A (en) * | 2008-10-23 | 2010-03-17 | 中国科学院地理科学与资源研究所 | Spatial visualization system of statistical population information and method thereof |
| KR20130011179A (en) * | 2011-07-20 | 2013-01-30 | (주)헤르메시스 | Identifying the population with zoning on smartphone |
| CN104156898A (en) * | 2014-07-18 | 2014-11-19 | 广东建邦计算机软件有限公司 | Management method for population information, rental room information and business operation site information |
-
2016
- 2016-11-30 CN CN201611086311.XA patent/CN106708962A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101673304A (en) * | 2008-10-23 | 2010-03-17 | 中国科学院地理科学与资源研究所 | Spatial visualization system of statistical population information and method thereof |
| KR20130011179A (en) * | 2011-07-20 | 2013-01-30 | (주)헤르메시스 | Identifying the population with zoning on smartphone |
| CN104156898A (en) * | 2014-07-18 | 2014-11-19 | 广东建邦计算机软件有限公司 | Management method for population information, rental room information and business operation site information |
Non-Patent Citations (3)
| Title |
|---|
| TAIYANGZHONG 等: "Impact of land revenue on the urban land growth toward decreasing population density in Jiangsu Province, China", 《HABITAT INTERNATIONAL》 * |
| 李淑娟 等: "城市建筑物人口时空分布模型与实验分析", 《地球信息科学学报》 * |
| 林飞娜 等: "基于GIS的城市人口空间分布模型与应用-以长春市为例", 《测绘科学》 * |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110019626B (en) * | 2017-12-21 | 2022-04-08 | 腾讯科技（深圳）有限公司 | Method for determining population distribution information and related device |
| CN110019626A (en) * | 2017-12-21 | 2019-07-16 | 腾讯科技（深圳）有限公司 | A kind of the determination method and relevant apparatus of population distribution information |
| CN108600340A (en) * | 2018-04-08 | 2018-09-28 | 深圳市和讯华谷信息技术有限公司 | It is a kind of that total method and device is pushed away based on the history crowd size for moving big-sample data |
| CN108871286A (en) * | 2018-04-25 | 2018-11-23 | 中国科学院遥感与数字地球研究所 | The completed region of the city density of population evaluation method and system of space big data collaboration |
| CN109947887A (en) * | 2019-03-20 | 2019-06-28 | 智慧足迹数据科技有限公司 | Population distribution statistical method and device |
| CN110263109A (en) * | 2019-05-22 | 2019-09-20 | 中国科学院地理科学与资源研究所 | A kind of family's amount evaluation method merging internet information and GIS technology |
| CN110263109B (en) * | 2019-05-22 | 2021-03-23 | 中国科学院地理科学与资源研究所 | Household number estimation method integrating internet information and GIS technology |
| CN110298253A (en) * | 2019-05-30 | 2019-10-01 | 特斯联（北京）科技有限公司 | A kind of physically weak quasi- display methods of urban architecture based on population big data and system |
| CN110704789A (en) * | 2019-08-16 | 2020-01-17 | 重庆特斯联智慧科技股份有限公司 | Population dynamic measurement and calculation method and system based on 'urban superconcephalon' computing platform |
| CN110704789B (en) * | 2019-08-16 | 2021-04-13 | 重庆特斯联智慧科技股份有限公司 | Population dynamic measurement and calculation method and system based on 'urban superconcephalon' computing platform |
| CN112668752A (en) * | 2020-11-27 | 2021-04-16 | 合肥泽众城市智能科技有限公司 | Safe evacuation method and system for gas pipeline leakage emergency |
| CN113191553A (en) * | 2021-05-06 | 2021-07-30 | 深圳市数字城市工程研究中心 | Population space distribution estimation method and system based on building scale |
| CN114363823A (en) * | 2021-05-26 | 2022-04-15 | 科大国创云网科技有限公司 | Population density monitoring method and system based on MR (magnetic resonance) permanent station and building outline |
| CN114363823B (en) * | 2021-05-26 | 2023-09-19 | 科大国创云网科技有限公司 | Population density monitoring method and system based on MR (magnetic resonance) resident places and building outlines |
| CN115186009A (en) * | 2022-07-13 | 2022-10-14 | 中国科学院地理科学与资源研究所 | Urban population daily change spatialization method and system based on interest point data |
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