CN104408094A - Method for rapidly generating real-time environment monitoring special topic picture based on user location - Google Patents
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Abstract
本发明公开了一种基于用户位置的实时环境监测专题图片快速生成方法。本方法为:1)服务器对环境监测数据进行空间插值得到栅格图层,然后根据栅格图层生成PNG格网图片;2)用户端发送环境查询请求,服务器根据该请求生成请求区域的矩形坐标范围;3)服务器根据请求中的时间信息、专题图类型和矩形坐标范围,从格网图片数据库中查询得到请求区域的所有PNG格网图片;然后进行拼接并用矩形范围进行剪裁得到一环境监测专题图片返回到用户端进行展示。本发明使得用户可以方便快速地从时空位置上的理解周围的环境情况。
The invention discloses a method for quickly generating special pictures for real-time environment monitoring based on user positions. This method is as follows: 1) The server performs spatial interpolation on the environmental monitoring data to obtain a grid layer, and then generates a PNG grid image according to the grid layer; 2) The client sends an environment query request, and the server generates a rectangle of the requested area according to the request Coordinate range; 3) The server queries the grid image database to obtain all PNG grid images in the requested area according to the time information, thematic map type, and rectangular coordinate range in the request; then splicing and clipping with the rectangular range to obtain an environmental monitoring Thematic pictures are returned to the client for display. The invention enables the user to quickly and conveniently understand the surrounding environment from the space-time position.
Description
技术领域technical field
本发明是基于用户位置信息提供实时环境监测数据专题图片快速生成技术,具体涉及一种根据用户移动终端的位置信息,以可视化图片的方式向用户提供其当前位置周围一定区域范围内的环境质量监测专题图信息的方法。The present invention provides real-time environmental monitoring data thematic picture rapid generation technology based on user location information, and specifically relates to a method of providing users with environmental quality monitoring within a certain area around their current location in the form of visualized pictures based on the location information of the user's mobile terminal Method for thematic map information.
背景技术Background technique
环境问题日益严重,尤其是城市中的空气污染,噪声污染,成为最严重的环境问题之一,直接关系到人们的健康。使公众获得环境相关信息,不仅有助于公众认识所生活的环境状况,还有利于提高其环保意识。而由于人有与生俱来的空间视觉能力,所以地图成为公众科学数据可视化的主要形式。在基础底图的基础上,加入专题数据,直观的展现该专题某一属性在空间上的分布情况的地图即为专题图。环境专题图可以展示环境监测数据的实时地理可视化结果,不仅易于大众理解,具有视觉吸引力,还有效的帮助人们应对信息过剩,直观快捷的获取生活环境的污染状况,具有极大的应用价值。Environmental problems are becoming more and more serious, especially air pollution and noise pollution in cities, which have become one of the most serious environmental problems and are directly related to people's health. Making the public obtain environment-related information will not only help the public understand the environmental conditions they live in, but also help improve their environmental awareness. And because people have innate spatial vision capabilities, maps have become the main form of public scientific data visualization. On the basis of the basic base map, adding thematic data, the map that intuitively shows the spatial distribution of a certain attribute of the theme is the thematic map. The environmental thematic map can display the real-time geographic visualization results of environmental monitoring data. It is not only easy for the public to understand, but also has visual appeal. It can also effectively help people deal with information overload and obtain the pollution status of the living environment intuitively and quickly, which has great application value.
基于位置服务(location based service,简称LBS)是首先通过定位技术确定用户所持的移动终端的地理位置,然后利用无线通讯技术和GIS技术将与该位置相关的信息服务提供给用户的移动终端。基于位置的服务可分为两类:一类基于用户的查询而提供服务;另一类是向用户直接推送服务,如营销信息。LBS包括定位技术、移动互联网技术和地理信息技术。现有的移动定位技术有很多,使用最广泛的有GPS定位、网络定位和联合定位技术。移动传输技术有GPRS,CDMA,WCDMA,TDS-CDMA,WIFI,WIMAX,卫星通信技术等等。地理信息技术则是针对空间数据进行分析、处理、制作专题图以及发布等功能。随着Android和IOS移动操作系统的快速发展,LBS在各行各业的应用也越来越广泛。Location based service (LBS for short) is to first determine the geographical location of the mobile terminal held by the user through positioning technology, and then use wireless communication technology and GIS technology to provide information services related to the location to the mobile terminal of the user. Location-based services can be divided into two categories: one type provides services based on user queries; the other type directly pushes services to users, such as marketing information. LBS includes positioning technology, mobile Internet technology and geographic information technology. There are many existing mobile positioning technologies, the most widely used are GPS positioning, network positioning and joint positioning technology. Mobile transmission technologies include GPRS, CDMA, WCDMA, TDS-CDMA, WIFI, WIMAX, satellite communication technology and so on. Geographic information technology is to analyze, process, make thematic maps and release spatial data. With the rapid development of Android and IOS mobile operating systems, LBS has become more and more widely used in various industries.
现有技术条件下,基于位置的实时环境质量监测服务,例如空气污染指标、温度、降水等,只向用户提供空间坐标点处的监测实际值或模拟值,或该区域的整体平均值,这种以数值的形式展现给用户并不易使用户理解当前地理位置周围的真实环境质量。Under existing technical conditions, location-based real-time environmental quality monitoring services, such as air pollution indicators, temperature, precipitation, etc., only provide users with the actual or simulated values monitored at spatial coordinate points, or the overall average value of the area. It is not easy for the user to understand the real environmental quality around the current geographical location if it is presented to the user in the form of a numerical value.
发明内容Contents of the invention
针对现有技术存在的问题,本发明目的在于提出一种基于用户移动终端的时间和位置信息,实现任意地理位置区域范围内实时环境监测数据专题图快速生成图片返回给用户,向用户提供基于时空信息的实时环境质量监测信息,使得用户可以方便快速地从时空位置上理解周围的环境情况的方法。In view of the problems existing in the prior art, the purpose of the present invention is to propose a method based on the time and location information of the user's mobile terminal, to realize the real-time environmental monitoring data thematic map within the range of any geographical location to quickly generate pictures and return them to the user, and to provide the user with time-space-based The real-time environmental quality monitoring information of the information enables users to quickly and conveniently understand the surrounding environmental conditions from the spatial and temporal position.
本发明的步骤包括:The steps of the present invention include:
1)数据预处理环境定时获取实时环境监测数据,将环境监测数据及其时空信息保存到实时环境监测数据库进行存储;1) The data preprocessing environment regularly acquires real-time environmental monitoring data, and saves the environmental monitoring data and its spatio-temporal information to the real-time environmental monitoring database for storage;
2)采用协同克里格空间插值方法,将步骤1)获取的带有时空信息的各种实时监测数据和地形、温度、交通流量等背景栅格数据进行空间插值得到栅格图层,保存到时空栅格数据库;2) Using the collaborative kriging spatial interpolation method, the various real-time monitoring data with space-time information obtained in step 1) and the background grid data such as terrain, temperature, and traffic flow are subjected to spatial interpolation to obtain a grid layer, and saved to Spatio-temporal raster database;
3)将步骤2)插值得到的栅格图层,设置颜色方案,然后按照一定比例尺在GIS软件中生成256x256像素的PNG格网图片,将时空信息和格网图片一起保存到格网图片数据库;3) step 2) the raster layer obtained by interpolation, set the color scheme, then generate a PNG grid picture of 256x256 pixels in GIS software according to a certain scale, and save the spatio-temporal information and the grid picture together to the grid picture database;
4)用户在请求时候,使用移动终端设备进行定位,将坐标位置、距离范围、时间信息和专题图类型等作为请求输入参数上传到WEB服务器;4) When the user requests, use the mobile terminal device to locate, and upload the coordinate position, distance range, time information and thematic map type as request input parameters to the WEB server;
5)WEB服务器接收请求后,以坐标点为中心,用户指定的距离范围为单位进行计算,生成请求区域的矩形坐标范围;5) After the WEB server receives the request, it calculates with the coordinate point as the center and the distance range specified by the user as the unit, and generates a rectangular coordinate range of the request area;
6)服务器根据步骤4)提交的时间信息、专题图类型和步骤5)生成的矩形坐标范围,跟步骤3)生成的格网图片数据信息进行时空相交查询得到用户请求区域的所有PNG格网图片;6) According to the time information submitted in step 4), the type of thematic map and the rectangular coordinate range generated in step 5), the server performs a space-time intersection query with the grid image data information generated in step 3) to obtain all PNG grid images in the area requested by the user ;
7)将步骤6)得到的用户请求区域的PNG格网图片进行拼接,并用步骤5)的矩形范围进行剪裁得到用户请求所需的环境监测专题图片,在图片上标记图例和时间信息等后,以HTTP协议返回到用户客户端进行展示。7) splicing the PNG grid picture of the user request area obtained in step 6), and clipping with the rectangular range of step 5) to obtain the environmental monitoring thematic picture required by the user request, after marking the legend and time information, etc. on the picture, It is returned to the user client through HTTP protocol for display.
与现有技术相比,本发明的积极效果为:Compared with prior art, positive effect of the present invention is:
本发明提出一种基于用户移动终端的时间和位置信息,实现任意地理位置区域范围内实时环境监测数据专题图快速生成图片并返回给用户,向用户提供基于时空信息的实时环境质量监测信息。The invention proposes a method based on the time and location information of the user's mobile terminal to realize the real-time environmental monitoring data thematic map in any geographic location to quickly generate pictures and return them to the user, and provide the user with real-time environmental quality monitoring information based on spatio-temporal information.
在实现技术上,使用WEB服务环境和数据预处理环境进行分离,将实时环境监测数据获取、时空栅格数据插值、时空栅格格网图片生成等复杂、耗时的计算任务在后台异步执行。WEB服务程序只执行时空格网图片查询和图片拼接剪裁任务,降低服务器的计算负载量,快速响应用户对实时环境监测数据专题图片的请求,使得用户可以方便快速地从时空位置上的理解周围的环境情况。In terms of implementation technology, the WEB service environment and data preprocessing environment are used to separate, and complex and time-consuming computing tasks such as real-time environmental monitoring data acquisition, spatiotemporal grid data interpolation, and spatiotemporal grid image generation are executed asynchronously in the background. The WEB service program only performs spatio-temporal network image query and image splicing and cutting tasks, reducing the computing load of the server, and quickly responding to user requests for real-time environmental monitoring data thematic images, so that users can easily and quickly understand the surrounding environment from the spatial-temporal position environmental conditions.
附图说明Description of drawings
附图为基于用户位置的实时环境监测专题图片的快速生成流程图。The attached figure is a flow chart of the rapid generation of the real-time environmental monitoring thematic pictures based on the user's location.
具体实施方式Detailed ways
本发明中涉及到2个数据服务环境:数据预处理环境和WEB服务环境,其中数据预处理环境实现:实时监测数据定时获取和存储,实时监测数据空间插值,实时监测栅格数据格网图片生成,实时监测数据格网图片时空存储等步骤;WEB服务环境负责接收客户端服务请求,解析请求参数进行矩形范围计算,实时监测数据格网图片时空相交检索,图片拼接剪裁等功能。The present invention involves two data service environments: a data preprocessing environment and a WEB service environment, wherein the data preprocessing environment realizes: real-time monitoring data timing acquisition and storage, real-time monitoring data space interpolation, real-time monitoring grid data grid image generation , real-time monitoring of steps such as space-time storage of data grid pictures; WEB service environment is responsible for receiving client service requests, parsing request parameters for rectangular range calculation, real-time monitoring of data grid picture space-time intersecting retrieval, picture splicing and clipping and other functions.
下面结合附图和大气污染物数据为例对本发明作进一步详细描述:Below in conjunction with accompanying drawing and air pollutant data, the present invention is described in further detail as an example:
数据预处理环境Data Preprocessing Environment
第一步、实时监测数据定时获取和存储:使用Python语言编写数据爬取服务程序,每20分钟定时从互联网大气环境监测网站上爬取原始大气污染物监测数据,使用Python正则表达式re模块进行解析,提取监测时间信息(dateh),监测点经纬度坐标(x,y),监测点名称(city),监测点编号(name),监测指标值(SO2,O3,NOx,,CO,PM2.5,PM10)等,将数据组合成json格式数据,存储在mongodb数据库。The first step, real-time monitoring data timing acquisition and storage: use Python language to write a data crawling service program, crawl the original air pollutant monitoring data from the Internet atmospheric environment monitoring website every 20 minutes, and use Python regular expression re module Parsing, extracting monitoring time information (dateh), monitoring point latitude and longitude coordinates (x, y), monitoring point name (city), monitoring point number (name), monitoring index value (SO 2 , O 3 , NO x , CO, PM2.5, PM10), etc., combine the data into json format data and store it in the mongodb database.
Json数据格式为:Json data format is:
{{
"_id":ObjectId("52cb6af9af56137081000000"),"_id":ObjectId("52cb6af9af56137081000000"),
"co":"2.3","co": "2.3",
"no2":"74","no2": "74",
"so2":"59","so2": "59",
"o3":"7","o3": "7",
"pm10":"101","pm10": "101",
"pm25":"147","pm25": "147",
"x":"116.417","x": "116.417",
"y":"39.929","y": "39.929",
"dateh":"2014010710","dateh": "2014010710",
"city":"beijing","city": "beijing",
"city0":"北京市","city0": "Beijing",
"name":"东四""name": "East Fourth"
}}
第二步、实时监测数据空间插值:当第一步中所有监测网站的数据爬取完成后,从mongodb数据库中抽取最新插入的所有实时监测数据,例如监测时间dateh="2014010710"的所有数据,去除无数值的异常记录。The second step, real-time monitoring data spatial interpolation: When the data crawling of all monitoring websites in the first step is completed, all the latest inserted real-time monitoring data are extracted from the mongodb database, for example, all data of monitoring time dateh="2014010710", Remove abnormal records with no value.
由于实时监测数据的坐标为经纬度地理坐标,需要将地理坐标系转换为平面投影坐标系统,中国区域采用Albers坐标系统。利用Python+OGR软件包进行坐标投影转换。投影转换完成后,利用开源R统计软件中geoR模块和constrainedKriging模块,采用协同克里格空间插值方法,分别对每一项监测指标值(SO2,O3,NOx,,CO,PM2.5,PM10)和地形、温度、交通流量等背景栅格数据进行空间插值,插值后栅格数据的分辨率取决于实际范围、插值效果和监测点分布情况等,根据实际情况进行调整,我们采用90m分辨率对每一项监测指标值进行插值得到栅格数据。Since the coordinates of the real-time monitoring data are longitude and latitude geographic coordinates, it is necessary to convert the geographic coordinate system into a planar projection coordinate system, and the Albers coordinate system is adopted in China. Coordinate projection transformation was carried out using the Python+OGR package. After the projection conversion is completed, use the geoR module and constrainedKriging module in the open source R statistical software, and use the collaborative Kriging space interpolation method to calculate the values of each monitoring indicator (SO 2 , O 3 , NO x , CO, PM2.5 , PM10) and terrain, temperature, traffic flow and other background raster data for spatial interpolation, the resolution of the interpolated raster data depends on the actual range, interpolation effect and distribution of monitoring points, etc., adjust according to the actual situation, we use 90m The resolution interpolates the value of each monitoring indicator to obtain raster data.
第三步、实时监测栅格数据格网图片生成:The third step, real-time monitoring raster data grid image generation:
我们对步骤2)的插值后栅格数据进行格网图片生成,格网图片的比例尺根据栅格数据的分辨率,覆盖范围等进行选择;我们选择1:25万比例尺利用Python+GDAL软件包进行PNG格网图片生成。格网图片计算过程如下:We generate a grid image for the interpolated raster data in step 2), and the scale of the grid image is selected according to the resolution and coverage of the raster data; we choose a scale of 1:250,000 and use the Python+GDAL software package PNG grid image generation. The grid image calculation process is as follows:
现有地理信息系统环境中,1英寸等于0.254米,等于96像素;In the existing geographic information system environment, 1 inch is equal to 0.254 meters, which is equal to 96 pixels;
1:25万比例尺所对应的实际栅格分辨率为250000*(0.254/96)=66.15米;1: The actual grid resolution corresponding to the 250,000 scale is 250,000*(0.254/96)=66.15 meters;
整个插值栅格数据的总格网图片数量计算方法如下,其中right,left,top,bottom为栅格数据的空间范围,单位为米:The calculation method of the total number of grid images of the entire interpolated raster data is as follows, where right, left, top, and bottom are the spatial range of the raster data, and the unit is meter:
X轴像素数为:X=round(abs(right–left)/66.15)The number of pixels on the X axis is: X=round(abs(right–left)/66.15)
Y轴像素数为:Y=round(abs(top–bottom)/66.15)The number of pixels on the Y axis is: Y=round(abs(top–bottom)/66.15)
1:25万比例尺下整个插值栅格数据的格网图片的总数量为:The total number of grid images of the entire interpolated raster data at a scale of 1:250,000 is:
T=round(X/256)*round(Y/256)T=round(X/256)*round(Y/256)
任意格网图片Ti,j(X>i>=0,Y>j>=0)对应栅格数据的空间范围minXi,minYj,maxXi,maxYj的计算公式为:The calculation formula of any grid image T i,j (X>i>=0, Y>j>=0) corresponding to the spatial range of raster data minX i , minY j , maxX i , maxY j is:
minXi=left+(256*66.15)*i,其中X>i>=0minX i =left+(256*66.15)*i, where X>i>=0
maxXi=left+(256*66.15)*(i+1),其中X>i>=0maxX i =left+(256*66.15)*(i+1), where X>i>=0
minYj=bottom+(256*66.15)*j,其中Y>j>=0minY j = bottom+(256*66.15)*j, where Y>j>=0
maxYj=bottom+(256*66.15)*(j+1),其中Y>j>=0maxY j = bottom+(256*66.15)*(j+1), where Y>j>=0
格网图片生成完成后,将图片以及元数据信息存储到格网图片数据库,其中图片元数据信息包括:监测数据类型和采集时间,栅格数据的范围right、left、top、bottom,格网偏移索引i和j,以及格网的width和height。After the grid image is generated, store the image and metadata information in the grid image database, where the image metadata information includes: monitoring data type and collection time, grid data range right, left, top, bottom, grid offset Shift indices i and j, and grid width and height.
WEB服务器环境WEB server environment
第四步、客户端参数收集提交:在移动终端设备上,将GPS自动定位模块获取的经纬度格式坐标位置、当前时间、用户设置的请求距离(m)、专题图类型(如PM2.5,O3等)等请求信息编码为XML格式参数通过HTTP请求提交到服务器。The fourth step, client parameter collection and submission: on the mobile terminal device, the longitude-latitude format coordinate position obtained by the GPS automatic positioning module, the current time, the request distance (m) set by the user, the thematic map type (such as PM 2.5 , O 3 etc.) and other request information are encoded into XML format parameters and submitted to the server through HTTP requests.
第五步、客户端参数解析计算:The fifth step, client parameter analysis and calculation:
服务器接收到客户端提交的XML参数后,首先解析XML数据,获取相关参数,将经纬度格式的坐标位置利用Python+OGR软件包进行坐标投影转换为Albers坐标系统的坐标Px,y。将该坐标点与用户指定的距离范围W(单位米)进行计算形成一个矩形范围minX,minY,maxX,maxY,其计算公式为:After the server receives the XML parameters submitted by the client, it first parses the XML data, obtains relevant parameters, and uses the Python+OGR software package to perform coordinate projection conversion of the coordinate position in the latitude and longitude format into the coordinates Px, y of the Albers coordinate system. Calculate the coordinate point and the distance range W (in meters) specified by the user to form a rectangular range minX, minY, maxX, maxY, and the calculation formula is:
minX=Px–WminX= Px -W
maxX=Px+WmaxX= Px +W
minY=Py–WminY=P y –W
maxY=Py+WmaxY=P y +W
然后将矩形范围minX,minY,maxX,maxY(单位米)转换为格网偏移索引范围,具体计算公式为:Then convert the rectangular range minX, minY, maxX, maxY (in meters) into the grid offset index range, the specific calculation formula is:
tileXmin=round((minX-left)/256)tileX min = round((minX-left)/256)
tileXmax=round((maxX-left)/256)tileX max = round((maxX-left)/256)
tileYmin=round((minY-left)/256)tileY min = round((minY-left)/256)
tileYmax=round((maxY-left)/256)tileY max = round((maxY-left)/256)
第六步、切片时空属性相交查询:Step 6. Slice spatiotemporal attribute intersection query:
利用步骤5)计算得到的用户请求矩形范围所对应的格网偏移索引范围(tileXmin,tileYmin,tileXmax,tileYmax)、时间、专题图类型与步骤3)存储的格网图片数据库进行时空相交查询。格网的偏移索引位于用户请求范围的格网偏移索引范围内,则符合空间相交条件。Use the grid offset index range (tileX min , tileY min , tileX max , tileY max ) corresponding to the rectangular range requested by the user calculated in step 5), time, thematic map type and the grid image database stored in step 3). Space-time intersection query. If the offset index of the grid is within the grid offset index range of the user requested range, the spatial intersection condition is met.
第七步、专题图切片拼接剪裁;The seventh step, thematic map slice splicing and cutting;
利用步骤6)查询得到的格网图片数据,利用Python的PIL图像处理库进行图像粘贴拼接和剪裁后,保存为PNG格式的图片数据,通过WEB服务器,以HTTP响应请求返回给客户端进行显示。Use the grid image data obtained in step 6) to query, use the PIL image processing library of Python to paste, stitch and crop the image, save it as image data in PNG format, and return it to the client with an HTTP response request through the WEB server for display.
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