CN104408094B - A kind of thematic picture rapid generation of real time environment monitoring based on user location - Google Patents
A kind of thematic picture rapid generation of real time environment monitoring based on user location Download PDFInfo
- Publication number
- CN104408094B CN104408094B CN201410648109.6A CN201410648109A CN104408094B CN 104408094 B CN104408094 B CN 104408094B CN 201410648109 A CN201410648109 A CN 201410648109A CN 104408094 B CN104408094 B CN 104408094B
- Authority
- CN
- China
- Prior art keywords
- grid
- picture
- server
- data
- monitoring
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/5866—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Library & Information Science (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Processing Or Creating Images (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a kind of, and the real time environment based on user location monitors thematic picture rapid generation.This method is：1) server carries out space interpolation to environmental monitoring data and obtains raster map layer, then generates PNG grid pictures according to raster map layer；2) user terminal sends environment inquiry request, and server requests to generate the rectangular coordinates range in request region according to this；3) server is inquired from grid picture database according to temporal information, thematic graph type and rectangular coordinates range in request and obtains all PNG grid pictures in request region；Then it carries out splicing and is cut out to obtain an environmental monitoring special topic picture with rectangular extent to be shown back to user terminal.The invention enables users can be quickly and easily from the ambient conditions around the understanding on space-time position.
Description
Technical field
The present invention is to provide real time environment monitoring data special topic picture Rapid Generation Techniques based on customer position information, specifically
It is related to a kind of location information according to customer mobile terminal, is provided a user in a manner of visualizing picture around its current location
The method of environmental quality monitoring thematic map information in certain area coverage.
Background technology
Air pollution in environmental problem getting worse, especially city, noise pollution become the environmental problem of most serious
One of, it is directly related to people's health.So that the public is obtained context dependant information, not only facilitates the public and recognize lived ring
Border situation also advantageously improves its environmental consciousness.And since people has inherent spatial vision ability, so map becomes public affairs
Many visual principal modes of science data.On the basis of gradient map, thematic data is added, intuitively shows the special topic
The map of the distribution situation of one attribute spatially is thematic map.Environment thematic map can be with the real-time of show surroundings monitoring data
It is geographical visualized that there is visual attraction as a result, being not only easy to public understanding, it is also effective that people is helped to cope with information overabundance,
The pollution situation for intuitively efficiently obtaining living environment, has great application value.
It is to determine to use first by location technology based on location-based service (location based service, abbreviation LBS)
Then the geographical location for the mobile terminal that family is held utilizes wireless communication technique and GIS technology will be with the relevant information in the position
Service is supplied to the mobile terminal of user.Location based service can be divided into two classes：One kind provides clothes based on the inquiry of user
Business；Another kind of is to the direct Push Service of user, such as marketing message.LBS includes location technology, development of Mobile Internet technology and geography
Information technology.Existing mobile positioning technique has very much, most popular to have GPS positioning, network positions and alignment by union skill
Art.Mobile transmission technology has GPRS, CDMA, WCDMA, TDS-CDMA, WIFI, WIMAX, communication technology of satellite etc..Geography letter
Breath technology is then to be analyzed, handled for spatial data, making the functions such as thematic map and publication.With Android and IOS
The fast development of Mobile operating system, LBS are also more and more extensive in the application of all trades and professions.
Under the conditions of the prior art, location-based real time environment quality-monitoring service, such as air pollution regulations, temperature,
Precipitation etc. only provides a user monitoring actual value at space coordinate point or the analogue value or the ensemble average value in the region, this
It is presented to user in the form of numerical value and family not easy to use understands true environment quality around current geographic position.
Invention content
In view of the problems of the existing technology, present invention aims at propose a kind of time based on customer mobile terminal and
Location information realizes within the scope of the arbitrary geographic band of position that real time environment monitoring data thematic map quickly generates picture and returns to use
Family provides a user the real time environment quality-monitoring information based on space time information so that user can be quickly and easily from space-time
The method of ambient conditions around understanding on position.
The present invention step include：
1) data prediction environment timing acquisition real time environment monitoring data protect environmental monitoring data and its space time information
Real time environment monitor database is stored to be stored；
2) Cokriging spatial interpolation methods are used, the various real-time monitorings with space time information that step 1) is obtained
The backgrounds raster data such as data and landform, temperature, the magnitude of traffic flow carries out space interpolation and obtains raster map layer, is saved in space-time grid
Database；
3) raster map layer for obtaining step 2) interpolation, be arranged Color scheme, then according to a certain percentage ruler in GIS software
The middle PNG grid pictures for generating 256x256 pixels, grid picture database is saved in by space time information and grid picture together；
4) user is positioned in request using mobile terminal device, and coordinate position, distance range, time are believed
Breath and thematic graph type etc. upload to WEB server as request input parameter；
5) after WEB server receives request, centered on coordinate points, the distance range that user specifies is that unit is counted
It calculates, generates the rectangular coordinates range in request region；
6) the rectangular coordinates model that temporal information, thematic graph type and the step 5) that server is submitted according to step 4) generate
It encloses, carrying out space-time intersection inquiry with the grid image data information that step 3) generates obtains all PNG lattice that user asks region
Net picture；
7) it asks the PNG grid pictures in region to splice the user that step 6) obtains, the rectangle model of step 5) is used in combination
The environmental monitoring special topic picture for being cut out to obtain needed for user's request is enclosed, after marking legend and temporal information etc. on picture,
It is shown back to subscription client with http protocol.
Compared with prior art, the positive effect of the present invention is：
The present invention proposes a kind of time based on customer mobile terminal and location information, realizes arbitrary geographic band of position model
It encloses interior real time environment monitoring data thematic map to quickly generate picture and return to user, provides a user the reality based on space time information
When environmental quality monitoring information.
It in realization technology, is detached using WEB service environment and data prediction environment, real time environment is monitored into number
It is held asynchronous from the background according to the complexity such as acquisition, space-time grid data interpolation, the generation of space-time grid grid picture, time-consuming calculating task
Row.WEB service program only carries out space-time grid picture query and task is cut out in picture splicing, reduces the computational load of server
Amount, request of the quick response user to real time environment monitoring data special topic picture so that user can be quickly and easily from space-time
The ambient conditions around understanding on position.
Description of the drawings
Attached drawing quickly generates flow chart for the thematic picture of real time environment monitoring based on user location.
Specific implementation mode
To 2 data service environments involved in the present invention：Data prediction environment and WEB service environment, wherein data are pre-
Processing environment is realized：Real-time Monitoring Data timing acquisition and storage, Real-time Monitoring Data space interpolation, monitor raster data in real time
Grid picture generates, the storage of Real-time Monitoring Data grid picture space-time and etc.；WEB service environment is responsible for receiving client service
Request, analysis request parameter carry out rectangular extent calculating, the intersection retrieval of Real-time Monitoring Data grid picture space-time, and picture splicing is cut
The functions such as sanction.
Present invention is further described in detail with atmosphere pollution data instance below in conjunction with the accompanying drawings：
Data prediction environment
The first step, Real-time Monitoring Data timing acquisition and storage：Data, which are write, using Python crawls service routine,
Every timing in 20 minutes crawls protoatmosphere pollutant monitoring data from internet atmosphere environment supervision website, just using Python
Then expression formula re modules are parsed, extraction monitoring time information (dateh), monitoring point latitude and longitude coordinates (x, y), and monitoring is called the roll
Claim (city), (name) is numbered in monitoring point, monitoring index value (SO2, O3, NOx, CO, PM2.5, PM10) etc., data are combined into
Json formatted datas are stored in mongodb databases.
Json data formats are：
{
"_id":ObjectId("52cb6af9af56137081000000"),
"co":"2.3",
"no2":"74",
"so2":"59",
"o3":"7",
"pm10":"101",
"pm25":"147",
"x":"116.417",
"y":"39.929",
"dateh":"2014010710",
"city":"beijing",
"city0":" Beijing ",
"name":" east four "
}
Second step, Real-time Monitoring Data space interpolation：After the completion of the data of all monitoring sites in the first step crawl, from
All Real-time Monitoring Datas being newly inserted, such as monitoring time dateh=" 2014010710 " are extracted in mongodb databases
All data, remove the exception record without numerical value.
Since the coordinate of Real-time Monitoring Data is longitude and latitude geographical coordinate, need geographic coordinate system being converted to plane projection
Coordinate system, regional use Albers coordinate systems.Coordinate projection conversion is carried out using Python+OGR software packages.Projection
After converting, using geoR modules and constrainedKriging modules in the R statistical softwares that increase income, using Cokriging
Spatial interpolation methods, respectively to each single item monitoring index value (SO2, O3, NOx, CO, PM2.5, PM10) and landform, temperature, traffic
The backgrounds raster data such as flow carries out space interpolation, and the resolution ratio of raster data depends on actual range, interpolation after interpolation
With monitoring point distribution situation etc., be adjusted according to actual conditions, we using 90m resolution ratio to each single item monitoring index value into
Row interpolation obtains raster data.
Third step, monitoring raster data grid picture generates in real time：
We carry out grid picture generation to raster data after the interpolation of step 2), and the engineer's scale of grid picture is according to grid
The resolution ratio of data, coverage area etc. are selected；We select 1：250000 engineer's scales are carried out using Python+GDAL software packages
PNG grid pictures generate.Grid picture calculating process is as follows：
In existing GIS-Geographic Information System environment, 1 inch is equal to 0.254 meter, is equal to 96 pixels；
1：Practical raster resolution corresponding to 250000 engineer's scales is 250000* (0.254/96)=66.15 meter；
Total latice piece quantity computation method of entire interpolation raster data is as follows, wherein right, left, top,
Bottom is the spatial dimension of raster data, and unit is rice：
X-axis pixel number is：X=round (abs (right-left)/66.15)
Y-axis pixel number is：Y=round (abs (top-bottom)/66.15)
1：The total quantity of the grid picture of entire interpolation raster data is under 250000 engineer's scales：
T=round (X/256) * round (Y/256)
Arbitrary grid picture Ti,j(X>i>=0, Y>j>=0) the spatial dimension minX of corresponding raster datai,minYj,
maxXi,maxYjCalculation formula be：
minXi=left+ (256*66.15) * i, wherein X>i>=0
maxXi=left+ (256*66.15) * (i+1), wherein X>i>=0
minYj=bottom+ (256*66.15) * j, wherein Y>j>=0
maxYj=bottom+ (256*66.15) * (j+1), wherein Y>j>=0
After the completion of grid picture generates, picture and metadata information are stored to grid picture database, wherein picture
Metadata information includes：Monitoring data type and acquisition time, range right, left, top, bottom of raster data, lattice
The width and height of net offset index i and j and grid.
WEB server environment
4th step, client parameter collection are submitted：On the mobile terminal device, warp GPS automatic positioning modules obtained
Latitude format coordinate position, current time, the request distance (m) of user setting, thematic graph type (such as PM2.5, O3Deng) etc. requests
Information coding is that XML format parameter is submitted to server by HTTP request.
5th step, client Parameter analysis of electrochemical calculate：
After server receives the XML parameters of client submission, XML data is parsed first, relevant parameter is obtained, by longitude and latitude
The coordinate position for spending format carries out the coordinate Px that coordinate projection is converted to Albers coordinate systems using Python+OGR software packages,
y.The distance range W (unit rice) that the coordinate points and user are specified calculate and forms rectangular extent minX, a minY,
MaxX, maxY, calculation formula are：
MinX=Px–W
MaxX=Px+W
MinY=Py–W
MaxY=Py+W
Then rectangular extent minX, minY, maxX, maxY (unit rice) are converted into grid offset index range, specifically
Calculation formula is：
tileXmin=round ((minX-left)/256)
tileXmax=round ((maxX-left)/256)
tileYmin=round ((minY-left)/256)
tileYmax=round ((maxY-left)/256)
6th step, slice time-space attribute intersection inquiry：
The grid offset index range (tileX corresponding to rectangular extent is asked using the user that step 5) is calculatedmin,
tileYmin, tileXmax, tileYmax), time, thematic graph type and the grid picture database of step 3) storage carry out space-time
Intersection inquiry.The offset index of grid, which is located at user, asks within the scope of the grid offset index of range, then meets space intersection item
Part.
7th step, thematic map slice splicing are cut out；
Obtained grid image data is inquired using step 6), it is viscous to carry out image using the PIL image procossings library of Python
After patch is spliced and cut out, the image data of PNG format is saved as, by WEB server, client is returned to http response request
End is shown.
Claims (5)
1. a kind of thematic picture rapid generation of real time environment monitoring based on user location, step are：
1) environmental monitoring data and its space time information are saved in real time environment by server timing acquisition real time environment monitoring data
Monitor database；
2) space interpolation is carried out to environmental monitoring data and obtains raster map layer, be saved in space-time grid data library；
3) Color scheme is arranged to the raster map layer, then ruler generates PNG latices in GIS software according to a certain percentage
Space time information and grid picture are saved in grid picture database by piece together；Wherein, the generation PNG grid pictures, by when
The method that empty information and grid picture are saved in grid picture database together is：According to the spatial dimension of the raster data of setting
And engineer's scale, calculate the grid picture total quantity of entire interpolation raster data；Calculate each grid picture Ti,jCorresponding raster data
Spatial dimension, raster data is cut；After the completion of grid picture generates, picture and metadata information are stored to lattice
Net picture database, wherein picture metadata information include：Monitoring data type and acquisition time, the range of raster data, lattice
Net offset index i and j, the width and height of grid；
4) subscription client sends environment inquiry request to server, and the environment inquiry request includes the coordinate of subscription client
Position, distance range, time and thematic graph type；
5) after server receives the environment inquiry request, centered on coordinate position, specified distance range is that unit is counted
It calculates, generates the rectangular coordinates range in request region；
6) server is according to temporal information, thematic graph type and the rectangular coordinates range in environment inquiry request, from described
Inquiry obtains all PNG grid pictures in request region in grid picture database；Wherein, the server is according to request region
Corresponding grid offset index range, time, thematic graph type carry out space-time intersection inquiry to the grid picture database,
Obtain all PNG grid pictures in request region；
7) server is used in combination the rectangular extent to be cut out to obtain a ring to asking the PNG grid pictures in region to splice
Monitoring thematic picture in border is shown back to subscription client.
2. the method as described in claim 1, which is characterized in that the server uses Cokriging spatial interpolation methods,
Space interpolation is carried out to environmental monitoring data and obtains raster map layer.
3. the method as described in claim 1, which is characterized in that environmental monitoring thematic map piece subscript of the server in return
Remember legend and temporal information, is then shown back to subscription client with http protocol.
4. the method as described in claim 1, which is characterized in that the server is periodically from internet atmosphere environment supervision website
On crawl protoatmosphere pollutant monitoring data, parsed using Python regular expression re modules, extract monitoring time
Then data are combined by information, monitoring point latitude and longitude coordinates, monitoring point title, monitoring point number, various monitoring index values
Json formatted datas are stored in mongodb databases.
5. the method as described in claim 1, which is characterized in that environment inquiry request information coding is by the subscription client
XML format parameter is submitted to server by HTTP request.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410648109.6A CN104408094B (en) | 2014-11-15 | 2014-11-15 | A kind of thematic picture rapid generation of real time environment monitoring based on user location |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410648109.6A CN104408094B (en) | 2014-11-15 | 2014-11-15 | A kind of thematic picture rapid generation of real time environment monitoring based on user location |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104408094A CN104408094A (en) | 2015-03-11 |
| CN104408094B true CN104408094B (en) | 2018-08-14 |
Family
ID=52645725
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410648109.6A Active CN104408094B (en) | 2014-11-15 | 2014-11-15 | A kind of thematic picture rapid generation of real time environment monitoring based on user location |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104408094B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105092784B (en) * | 2015-05-08 | 2017-10-31 | 中国科学院遥感与数字地球研究所 | A kind of air monitoring, querying method and equipment |
| CN113436296A (en) * | 2017-09-28 | 2021-09-24 | 天津市生态环境监测中心 | Method for generating contour map in real time based on monitoring data |
| CN108182717B (en) * | 2017-12-15 | 2021-10-29 | 北京金风科创风电设备有限公司 | Geographic information image generation method and device |
| CN110302672A (en) * | 2019-06-06 | 2019-10-08 | 重庆工商大学融智学院 | A kind of distribution tuning method of Urban eco-space |
| CN110910480A (en) * | 2019-09-29 | 2020-03-24 | 谢国宇 | Environment monitoring image rendering method based on color mode mapping relation |
| CN111324825B (en) * | 2020-01-20 | 2024-04-30 | 北京百度网讯科技有限公司 | Method and device for searching target personnel |
| CN115599880A (en) * | 2022-11-29 | 2023-01-13 | 福建慧政通信息科技有限公司（Cn） | Map legend configuration management method and terminal |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000194742A (en) * | 1998-12-28 | 2000-07-14 | Hitachi Eng Co Ltd | Ambient air quality simulation system |
| CN101388043A (en) * | 2008-09-26 | 2009-03-18 | 北京航空航天大学 | OGC high performance remote sensing image map service method based on small picture |
| CN102254330A (en) * | 2010-07-29 | 2011-11-23 | 山东大学 | Image processing-based method for visualization of air pollution data |
| CN102842103A (en) * | 2012-07-17 | 2012-12-26 | 北京交通大学 | Two-dimensional holographic visualization system and method of high-speed comprehensive detecting train |
| CN103336093A (en) * | 2013-06-26 | 2013-10-02 | 中山大学 | Regional spatial quality analysis method |
| CN104102845A (en) * | 2014-07-24 | 2014-10-15 | 北京坤成科技有限公司 | Scale adaptation interpolation method and scale adaptation interpolation system |
-
2014
- 2014-11-15 CN CN201410648109.6A patent/CN104408094B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000194742A (en) * | 1998-12-28 | 2000-07-14 | Hitachi Eng Co Ltd | Ambient air quality simulation system |
| CN101388043A (en) * | 2008-09-26 | 2009-03-18 | 北京航空航天大学 | OGC high performance remote sensing image map service method based on small picture |
| CN102254330A (en) * | 2010-07-29 | 2011-11-23 | 山东大学 | Image processing-based method for visualization of air pollution data |
| CN102842103A (en) * | 2012-07-17 | 2012-12-26 | 北京交通大学 | Two-dimensional holographic visualization system and method of high-speed comprehensive detecting train |
| CN103336093A (en) * | 2013-06-26 | 2013-10-02 | 中山大学 | Regional spatial quality analysis method |
| CN104102845A (en) * | 2014-07-24 | 2014-10-15 | 北京坤成科技有限公司 | Scale adaptation interpolation method and scale adaptation interpolation system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104408094A (en) | 2015-03-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104408094B (en) | A kind of thematic picture rapid generation of real time environment monitoring based on user location | |
| US11107025B2 (en) | System and method for producing and distributing information relevant to water events | |
| US10192289B2 (en) | System, method, and apparatus for data processing and display | |
| Yi | FragMAP: a tool for long-term and cooperative monitoring and analysis of small-scale habitat fragmentation using an unmanned aerial vehicle | |
| Dembski et al. | Digital twin, virtual reality and space syntax: Civic engagement and decision support for smart, sustainable cities | |
| CN107451150B (en) | Geographic data presentation method and device | |
| DE202012013463U1 (en) | Creating and observing notifications for a geographic area | |
| Pokric et al. | Augmented Reality Enabled IoT Services for Environmental Monitoring Utilising Serious Gaming Concept. | |
| Corcoran et al. | Characterising the metric and topological evolution of OpenStreetMap network representations | |
| CN103440344A (en) | Electronic map displaying method and electronic map displaying device | |
| JP2014203191A (en) | Information providing system, information request terminal, information processing system, control method, and program | |
| CN110389981B (en) | Data display method, device, electronic equipment and computer readable storage medium | |
| CN103886773A (en) | Method for monitoring taxi on GIS map in real time under B/S environment | |
| Sagl et al. | Near real-time geo-analyses for emergency support: A radiation safety exercise | |
| CN110992501A (en) | Data monitoring method, device, equipment and computer readable storage medium | |
| Liu et al. | Location-based instant satellite image service: concept and system design | |
| Harbola et al. | Geo-visualisation and visual analytics for smart cities: a survey | |
| CN113342916B (en) | Geographic tag image file format data processing method and device and electronic equipment | |
| CN114443787A (en) | Atmospheric pollution feature identification method and device | |
| CN110717087B (en) | Method and system for acquiring normalized vegetation index NDVI of designated position point | |
| CN106529841A (en) | Handheld GIS modern agricultural park management system based on Android platform | |
| Wiemann et al. | Classification-driven air pollution mapping as for environment and health analysis | |
| CN104063755A (en) | Information System To Obtain An Exposition Rating Of A Geographical Area | |
| Xie et al. | Research on intelligent supervision method and system developing of soil remediation project based on 3D mobile GIS | |
| Pachoulas et al. | An adaptable Web GIS platform for monitoring Port air quality |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |