CN101900662B - Method for visualizing regional pollutant concentration based on particle system - Google Patents

Abstract

The invention discloses a method for visualizing regional pollutant concentration based on a particle system. The method comprises the following steps of: (1) inputting an image and pollutant concentration forecast data; (2) carrying out delamination and item division on the pollutant forecast data to obtain data to be displayed; (3) confirming corresponding particle attribute according to the selected data; (4) carrying out fuzzy smooth processing between adjacent particles; (5) confirming a corresponding atmospheric scattering model according to attribute values of the particles; and (6) fusing the particles and the image. The invention can show the distributing condition of a pollutant concentration value in a region and be fused with the image and overcomes the defect of no inclusion of pollutant concentration information of the common image.

Description

Regional pollution substrate concentration method for visualizing based on particIe system

Technical field

The present invention relates to regional pollution substrate concentration method for visualizing based on particIe system.

Background technology

In order to understand and the air pollution that controls environment, a lot of scholars study concentration distribution of pollutants, diffusion way and display form etc. in the atmosphere.Document [1] has proposed a kind of parsing Gauss model; Can predict atmospheric pollution level after the instantaneous pollutant emission; This model is widely used in prediction local pollution intensity; Can dope pollutant pollution range and CONCENTRATION DISTRIBUTION situation over time, and the result is showed in GIS.Demonstration major part in GIS all is based on two dimension now, can't show its characteristic in area of space.Because pollutant all has opaque characteristic usually, can make sky seem muddy.For the CONCENTRATION DISTRIBUTION and the diffusion effect of more vivo simulating pollutant in the atmosphere, we utilize the model of fuzzy (opaque) object are described.

Fuzzy objective such as flame, cloud, mist, smog etc. because of it does not have fixed shape, can't use traditional method for drafting to draw.Document [2] has proposed the method for using particIe system to come these fuzzy objectives of modeling.ParticIe system is made up of particle assembly; Each particle in the particle assembly all has the attribute of oneself; Comprise position, speed (comprising speed and direction), size, color, transparency, life-span etc., these attributes constantly changed along with the time, formed object complicated and changeable.Document [3] has proposed on the basis of particIe system, uses the method for texture spilling that particle is carried out texture, forms the changeable cloud of shape, and the travel path of illumination in particle uses forward scattering model and Rayleigh phase function.Harris improves particIe system in modeling, introduced texture and made the figure of drafting truer, but on local detail because particle property is provided with improperly, cause the effect distortion.

Summary of the invention

The present invention has proposed based on particIe system regional pollution substrate concentration method for visualizing for more vivo simulating the CONCENTRATION DISTRIBUTION and the diffusion effect of pollutant in the atmosphere.

For realizing above-mentioned purpose, the present invention adopts following technical scheme:

Based on the regional pollution substrate concentration method for visualizing of particIe system, this method comprises the steps:

Step1: obtain the pollutant levels forecast data;

Step2: the pollutant levels forecast data is carried out layering, obtain the pollutant levels value of designated layer;

Step3: the pollutant levels value to designated layer is played up, and obtains the property value of particle;

Step4: to bluring smoothing processing between the adjacent particles after playing up;

Step5:, confirm that corresponding atmospheric scattering model obtains the particle picture of designated layer simultaneously according to the property value of the particle after the fuzzy smoothing processing;

Step6: particle picture and satellite image image are merged, obtain comprising the image of pollutant levels information.

The pollutant levels forecast data is among said step1 or the step2: the concentration forecast data of pellet PM10, sulphuric dioxide SO2, nitrogen monoxide NO, nitrogen dioxide NO2, carbon monoxide CO, ozone O3.

The gatherer process of said pollutant levels forecast data is following:

A: at first gather air pollutants through the automatic checkout equipment of some environmental monitoring websites;

B: data acquisition transmission appearance carries out the A/D conversion with the air pollutants data of automatic checkout equipment collection, and the data after the conversion adopt HJ/T212-2005 State Environmental Protection Administration data transmission standard communications protocol to be transferred to the service end of Surveillance center;

C: Surveillance center's service end with the data processing that receives after, send into prediction of air quality computation model system;

D: through prediction of air quality computation model system the air pollutants data of gathering are handled, obtained the pollutant levels data.

Among the said step3 from particle position, the size of particle, the color value of particle and opacity value come pollutant levels are played up, and be specific as follows:

A. particle position: the spacing between adjacent particles equates, is expressed as d;

B. particle size

Use two kinds of methods to form the particle size of mist: rule and method and random device.

(1) rule and method: be about to all corresponding fixing particle size of each concentration; Particle size is defined in

scope, carries out linear interpolation according to the size of concentration value;

(2) random device: at first, the maximal value of calculating concentration and minimum value, the corresponding particle size of maximal value are five times of minimum value; Other particle sizes obtain from linear interpolation between the two;

C. particle color and opacity

Concentration value size according to pollutant; Utilize mapping function

to obtain the corresponding color value size of each concentration value, the color value of particle and opacity equate with concentration value; Wherein, x representes the pollutant levels value, and f (x) is corresponding color value size.

The process of fuzzy smoothing processing is following among the said step4:

First: mark frontier point, known particle position promptly (x, y z), find out x, y, the maximal value of position and minimum value are labeled as frontier point with it on the z direction, wherein, x, y, z are the three-dimensional coordinate of particle;

Second: the z value is fixing, find out the frontier point respective x, the y value, (x, y is when z) having 8 adjoint points, then when interior point

$\mathrm{color}(x,y,z)=$

$\frac{1}{16}\×(4\mathrm{color}(x,y,z)+2\mathrm{color}(x-1,y,z)+2\mathrm{color}(x+1,y,z)$

$+2\mathrm{color}(x,y-1,z)+2\mathrm{color}(x,y+1,z)+\mathrm{color}(x-1,y-1,z)$

$+\mathrm{color}(x-1,y+1,z)+\mathrm{color}(x+1,y-1,z)+\mathrm{color}(x+1,y+1,z))$

When in interior point is put for neighbours, putting,

$\mathrm{color}(x,y,z)=\frac{1}{6}\×(2\mathrm{color}(x,y,z)+\mathrm{color}(x-1,y,z)$

$+\mathrm{color}(x+1,y,z)+\mathrm{color}(x,y-1,z)+\mathrm{color}(x,y+1,z));$

Wherein, (x, y are at coordinate points (x, y, the color value of z) locating, color (x-1, y z) to color; Z) be coordinate points (x-1, y, the color value of z) locating, (x+1, y z) are coordinate points (x+1, y, the color value of z) locating to color; Color (x, y-1, z) be coordinate points (x, y-1, the color value of z) locating, (x, y+1 are at coordinate points (x z) to color; Y+1, the color value of z) locating, (x-1, y-1 are at coordinate points (x-1, y-1, the color value of z) locating, color (x-1 z) to color; Y+1, z) be coordinate points (x-1, y+1, the color value of z) locating, (x+1, y-1 are at coordinate points (x+1 z) to color; Y-1, the color value of z) locating, (x+1, y+1 are at coordinate points (x+1, y+1, the color value of z) locating z) to color.

The atmospheric scattering model of said step5 comprises:

The Rayleigh scattering:

$P\left(\mathrm{\θ}\right)=\frac{3}{4}(1+{\cos }^2\mathrm{\θ})$

The Mie scattering model:

$P(\mathrm{\θ},g)=\frac{3(1-g^2)}{2(2+g^2)}\frac{(1+{\cos }^2\mathrm{\θ})}{{(1+g^2-2g\cos \mathrm{\θ})}^{\frac{3}{2}}}$

Wherein, θ is the angle between incident direction and the scattering direction, and P (θ) is to be the phase function of parameter with θ; G ∈ (1,1) describes material scattering strength forward or backward, and (θ is with g g) to P, and θ is the phase function of parameter.

The invention has the beneficial effects as follows: the present invention gathers air pollutants through the automatic checkout equipment of some environmental monitoring websites; Through prediction of air quality computation model system the air pollutants data of gathering are handled; Obtain the pollutant levels data; After the pollutant levels data are played up smoothing processing, can show the distribution situation of pollutant levels value in a certain zone, particle picture that obtains and imaged image are merged; Overcome the shortcoming that general imaged image does not comprise the concentration information of pollutant, can observe the distribution situation of a certain local pollution control substrate concentration intuitively.

Description of drawings

Fig. 1 air pollution data acquisition flow figure;

Fig. 2 is an algorithm flow chart of the present invention;

Fig. 3 is the imaged image when not containing concentration data;

Fig. 4 is the concentration value display image that adds two layer data, and wherein particle size is big or small at random, and the visual angle is identical;

Fig. 5 is the concentration value display image that adds two layer data, wherein particle size and concentration value linear dependence;

Fig. 6 is the concentration value display image that contains the Floor 12 data; Comprise two parts image (a) and (b), the image that obtains from different view respectively, particle size and concentration value linear dependence; The concentration critical value of selecting is 0.1; What show is all particles greater than this concentration value, Albedo=02 wherein, γ=0.09;

Fig. 7 is the concentration value display image that contains the Floor 12 data, comprises two parts image (a) and (b), the image that obtains from different view respectively; Particle size and concentration value linear dependence, the concentration critical value is identical with Fig. 5, Albedo=02; Compare with Fig. 5 far in γ=0.09, viewpoint;

Fig. 8 is the concentration value display image that contains the Floor 12 data, comprises two parts image (a) and (b), the image that obtains from different view respectively, and particle size is size at random, the identical Albedo=02 with Fig. 5 of concentration critical value, γ=0.09.

Embodiment

Below in conjunction with accompanying drawing and embodiment the utility model is described further:

The present invention adopts and inserts telecommunications broadband networks and GPRS/CDMA wireless data transmission network, realizes the real-time Transmission of Monitoring Data.The telecommunications wide bandwidth is nominally 10M, and its transfer rate can reach the requirement of real-time Transmission image.The bandwidth of GPRS net is K more than 200, can reach the requirement of real-time transmission data information.Each atmospheric surveillance substation of inserting the telecommunications broadband networks also need dispose a data acquisition transmission appearance except that data collecting device and ESC8800 analog to digital conversion equipment, be transferred to the output of ESC8800 analog to digital conversion equipment through data broadband networks and GPRS/CDMA wireless data transmission network the server of Monitoring and Controlling central machine room through data acquisition transmission appearance.Utilize the high speed of broadband networks and GPRS/CDMA wireless data transmission network, stable transmission channel, guarantee that each node and monitoring center control effective connection of machine room data acquisition server, satisfy the requirement of data in real time transmission.

The network requirement of native system monitoring station covers the urban district, Jinan City, serves as main the explanation with the communication modes of automatic monitoring network for air quality.The monitoring network scope mainly comprises N atmospheric surveillance website.Ambient air quality Surveillance center carries out wired or wireless being connected through automatic monitoring network for air quality with air quality monitoring station, citywide point.The ambient air quality monitoring station of Jinan City has 7, and they are: seed stations warehouse (full good fortune bridge east), (3) chemical plant, Jinan (Ji Luolu), (4) national defence section cadre's sanitarium (near the heavy vapour technique center), near (5) lathe two factories (fleet), (6) development area (in the sub-district, Ya Ju garden-engine plant area of light cavalry in), (7) institute of agricultural sciences (Duan Dian nursery) are economized by (1) city environmental monitoring station, (2).Gather the data processing centre (DPC) that the atmosphere quality raw data is transferred to central station then by 7 substations and carry out various processing.The network of present each monitoring station and Surveillance center is connected various network such as all having adopted broadband and GPRS/CDMA and inserts.It is as shown in Figure 1 that network connects synoptic diagram.

It is mean effective value of per minute that the frequency is gathered in surrounding air and exhaust emission source; Forecast data is for per hour once.The collecting flowchart of air pollution data is following:

1. at first through import automatic checkout equipment in the environment measuring site configuration; Analyze the content of airborne pollutant, the pollutant of detection mainly comprises pellet (PM10), sulphuric dioxide (SO2), nitrogen monoxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) etc.Automatic checkout equipment is the 100-E of U.S. API company, comprises PM10, SO2, NO, NO2, CO, air quality monitoring appearance such as O3.

2. data acquisition transmission appearance through A/D (mould/number) conversion, converts the air pollutants data of automatic checkout equipment collection the data of transmission over networks to, and this data acquisition transmission appearance is a high-performance embedded system.CPU has adopted 32 high-performance embedded microprocessors of the ColdFire MCF5272 of Motorola; In save as 32MB; System flash FLASH is 4M; Operating system adopts the LINUX platform of technical grade, has high system reliability and security and deposits the monitoring historical data with sufficient storage space.

3. the signal that appearance is transmitted in data acquisition is transferred to the service end of Surveillance center through network (GPRS, wired unlimited internet).

4. Surveillance center's service end data layout of becoming the air forecasting model to handle the data-switching that receives.

5. the air pollution data of using the prediction of air quality models treated to gather, the prediction of air quality model adopts the prediction of air quality model of the Chinese Academy of Sciences.

6. the data of utilizing the air forecasting model to handle, the air that produces the 69*79*12 of Jinan City forecasts grid data.

Between automatic checkout equipment and data acquisition transmission appearance, adopt the MODBUS communications protocol of standard in the industry, serial data mouth (RS232 or RS485) is adopted in the communication of the data acquisition at station transmission appearance and monitoring instrument automatically, or port (TCP/IP).

Data acquisition transmission appearance adopts IEC 60870-5-104 or HJ/T212-2005 data transmission standard communication protocol to transmit with Surveillance center, and these stipulations can transmitting real-time data and historical data, support to the time and terminal fitting equipment control.Also support the HJ/T212-2005 of Environmental Protection Administration data transmission standard communications protocol, support " the automatic monitor message transmission of environomental pollution source, switching technology standard " that State Environmental Protection Administration formulates.

Automatically the data transport network of the data acquisition at station transmission appearance and control centers at different levels adopts the communication modes based on TCP/IP, as: GPRS (Gerneral Packer Radio Service abbreviation GPRS or EGPRS); ADSL (Asymmetrical Digital Subscriber Loop abridge ADSL); CDMA (Code Division Multiple Access abridge CDMA).

A kind of regional pollution substrate concentration method for visualizing based on particIe system.Steps of the method are: 1) input imaged image and pollutant levels forecast data; 2), obtain data to display with pollution prediction data hierarchy, sub-item; 3), confirm corresponding particle property according to selected data; 4) the fuzzy smoothing processing between the adjacent particles; 5), confirm corresponding atmospheric scattering model according to the property value of particle; 6) particle and imaged image are merged.

Said step 2) in, forecast data comprises that six kinds of pollutant levels data are: SO2, NO2, NO, CO, PM10, O3.Jinan City's ground region is divided into the grid of 69*79, and its resolution is 1km*1km, through prediction of air quality computation model system area of space is divided into 12 layers.The storage format of data is: each hour, according to project order, to each project item successively with the horizontal x of ground region, vertical y direction; Spatial altitude level direction travels through, and can obtain at this time point place, and project item is (x in the position; Y, the concentration prediction value of level) locating.

In the step 3),, at first must set up the corresponding relation between this pollutant levels value and the color value for the pollutant in the designated space zone is played up by its concentration value.The pollutant of supposing in space lattice, to exist exists with the form of particle, and each particle has corresponding property like particle position, particle size, particle color value and opacity.Concentration value size according to contaminant particles; Utilize mapping function

to set up the corresponding size of each concentration value, the color value of particle and opacity all equal this value.

A. particle position

Spacing between adjacent particles equates, is expressed as d.

B. particle size

Use two kinds of methods to form the particle size of mist: random device and rule and method

(1) rule and method: all corresponding fixing particle size of this each concentration of expression.Particle size is defined in

scope; Size according to concentration value is carried out linear interpolation; Suppose that the concentration value maximal value is MaxCon; Corresponding particle size is d; Minimum value is MinCon; The corresponding particle size particle size that then concentration value Con is corresponding for

is:

can find out from this: at first, the minimal size of particle is so particle is continuous; Secondly, the size variation of particle makes the cigarette surface seem uneven, and is truer.But less if the concentration value between the particle changes, then particIe system can become smooth, and the sense of reality reduces

(2) random device: the radius of particle is by deciding with concentration value two aspects at random.At first; The maximal value MaxCon of calculating concentration and minimum M inCon; Suppose that the corresponding particle size of minimum value is: 2.054*rand ()/(RAND_MAX+1), wherein rand () is the function in the C language, returns one from 0 arbitrary integer to the largest random number; It is a big integer of fixing that largest random is counted RAND_MAX; Rand ()/(RAND_MAX+1) is the random value between (0,1), and the corresponding particle size of maximal value is five times of minimum value; The particle size that then concentration value Con is corresponding be the linear interpolation acquisition between the two, and the interpolation method formula is:

This method has overcome the defective that goes up a kind of method, even the concentration value of two particles equates that their size equates not necessarily that also still, the relation between particle size and the concentration value is not obvious.

The present invention compares these two kinds of methods, and when the result was illustrated in whole region subdivision shown, it was better, as shown in Figure 4 to use random device to calculate the particle size effect, and the effect fluctuations of using random device to obtain is obvious, and sense of reality effect is better; And during the visualization display in a certain threshold range of Floor 12 data, the rule and method effect is better, from the comparison of Fig. 7 and Fig. 8, can find out; In the design sketch that the particle size of using random device to obtain obtains some little particles are arranged; Influence visual effect, but using particle size and particle concentration value linear correlative method, when promptly using rule and method to obtain the method for particle size; Can address this problem, and the visual effect that obtains is better.

C. particle color and opacity

Use the concentration value size at net point place to represent the color of particle and the size of opacity value, through to the pollutant levels value analysis can know, lot of data all be distributed in (0,1] between, partial data is greater than 1 less.Because the span of color and opacity is defined between [0,1],, the concentration value of particle is mapped between [0,1] so need the use mapping function.In order to guarantee that size order remains unchanged between the concentration value, mapping function must have following character: (1) localization (0 ,+∞), codomain (0,1]; (2) function f (x) monotone increasing.The mapping function that uses does

$f\left(x\right)=x\ln \frac{x+1}{x}---\left(3\right)$

In the step 4), the pollutant levels value distributes and rough in the atmosphere, if but the concentration value between the adjacent particles differs greatly, and can cause between particle change color violent, influence visual effect, so we will carry out the fuzzy smoothing processing between the color value.

Arthmetic statement is following:

At first, the mark frontier point, known particle position, promptly (x, y z), find out x, y, and the maximal value of position and minimum value are labeled as frontier point with it on the z direction;

The second, the z value is fixing, find out the frontier point respective x, the y value, we do not process frontier point; Other point is called interior point.According to the number of the abutment points of interior point, interior point is divided in two types-8 abutment points point in the point and 4 abutment points.Because each point has 4 abutment points at least, only handle abutment points at the diagonal line place.

Dot cycle in all is handled, and (x, y is when z) having 8 adjoint points, then when interior point

$\mathrm{color}(x,y,z)=$

$\frac{1}{16}\×(4\mathrm{color}(x,y,z)+2\mathrm{color}(x-1,y,z)+2\mathrm{color}(x+1,y,z)---\left(4\right)$

$+2\mathrm{color}(x,y-1,z)+2\mathrm{color}(x,y+1,z)+\mathrm{color}(x-1,y-1,z)$

$+\mathrm{color}(x-1,y+1,z)+\mathrm{color}(x+1,y-1,z)+\mathrm{color}(x+1,y+1,z))$

When in interior point is put for neighbours, putting,

$\mathrm{color}(x,y,z)=\frac{1}{6}\×(2\mathrm{color}(x,y,z)+\mathrm{color}(x-1,y,z)$

$+\mathrm{color}(x+1,y,z)+\mathrm{color}(x,y-1,z)+\mathrm{color}(x,y+1,z))---\left(5\right)$

Wherein, (x, y are at coordinate points (x, y, the color value of z) locating, color (x-1, y z) to color; Z) be coordinate points (x-1, y, the color value of z) locating, (x+1, y z) are coordinate points (x+1, y, the color value of z) locating to color; Color (x, y-1, z) be coordinate points (x, y-1, the color value of z) locating, (x, y+1 are at coordinate points (x z) to color; Y+1, the color value of z) locating, (x-1, y-1 are at coordinate points (x-1, y-1, the color value of z) locating, color (x-1 z) to color; Y+1, z) be coordinate points (x-1, y+1, the color value of z) locating, (x+1, y-1 are at coordinate points (x+1 z) to color; Y-1, the color value of z) locating, (x+1, y+1 are at coordinate points (x+1, y+1, the color value of z) locating z) to color.

In the step 5), system uses the atmospheric scattering model, and we are based on following hypothesis: in order to simplify calculating, the number of particles that our hypothesis comprises in each unit cube grid is identical, and the different concentration value is corresponding to different particle radii sizes.And in the low place of concentration value, particle is little, the place that concentration value is high, and particle radii are big.

Through the pollutant levels value that comprises in the atmosphere is analyzed, pollutant levels are bigger in 6,7,8 layers.Then we use Mie scattering model simulation atmospheric scattering at these three layers, and use the Rayleigh scattering at other layers.

Simplified model is used in the Rayleigh scattering

$P\left(\mathrm{\θ}\right)=\frac{3}{4}(1+{\cos }^2\mathrm{\θ})---\left(1\right)$

The Mie scattering model uses: the improved Mie scattering model of Henyey_Greenstein

$P(\mathrm{\θ},g)=\frac{3(1-g^2)}{2(2+g^2)}\frac{(1+{\cos }^2\mathrm{\θ})}{{(1+g^2-2g\cos \mathrm{\θ})}^{\frac{3}{2}}}---\left(2\right)$

Wherein, θ is the angle between incident direction and the scattering direction, and P (θ) is to be the phase function of parameter with θ;

G ∈ (1,1) describes material scattering strength forward or backward, and (θ is with g g) to P, and θ is the phase function of parameter.

Use scattering model can obtain particle light scattering size under illumination condition,, can confirm the color value that KPT Scatter comes out according to what of which color value scattering in the solar spectrum.

In the step 6), the method that particle picture and imaged image merge is: as base map, the opacity that then particle picture itself is had according to each particle is added in the image data with image data.The purpose that merges is: original image data is not comprise contaminant information, after the fusion, just can on imaged image, find out the distribution situation of pollutant.

Analyze in the face of the image result that generates down, undressed original satellite image is as shown in Figure 3.

Fig. 4 is identical with the data that Fig. 5 representes, has all represented two-layer visualization of data effect.In Fig. 4, the radii size of particle is big or small at random, among Fig. 5, and particle size and particle concentration value linear dependence.From Fig. 4, can find out some fluctuations of fogmeter face, surface ratio is more true to nature, but in Fig. 5, the fluctuating of mist is less, surperficial smoother, thus can know when the overall situation is represented that the particle radii size is for big or small effect is better at random.

What Fig. 6 described to Fig. 8 is the concentration value display image that contains the Floor 12 data, and the concentration critical value of selection is 0.1, demonstration be all particles greater than this concentration value; In Fig. 7 and Fig. 8; The mist of black ellipse the inside has provided the contrast of two kinds of methods, as can be seen from the figure, in the design sketch that the particle size of using random device to obtain obtains some little particles is arranged; Influence visual effect; But when using particle size and particle concentration value linear correlative method, can address this problem, and the visual effect that obtains is better.

List of references in the foregoing comprises:

[1]N.kh.Arystanbekova.Application?of?Gaussian?plume?models?for?air?pollution?simulation?at?instantaneous?emissions.2004?IMACS.Published?by?Elsevier?B.V.451-458.

[2]William?T.Reeves.Particle?Systems-A?Technique?for?Modeling?a?class?of?Fuzzy?Objects.ACM?Transactions?on?Graphics，Vol.2，No.2，April?1983.91-108.

[3]M.Harris，A.Lastra.Real-time?cloud?rendering.Computer?Graphics?Forum(Eurographics′01Proc.)，20(3)：C.76.C.84，2001.76-84.

Claims (3)

1. based on the regional pollution substrate concentration method for visualizing of particIe system, it is characterized in that this method comprises the steps:

Step1: obtain the pollutant levels forecast data;

Step2: the pollutant levels forecast data is carried out layering, obtain the pollutant levels value of designated layer;

Step3: the pollutant levels value to designated layer is played up, and obtains the property value of particle;

Step4: to bluring smoothing processing between the adjacent particles after playing up;

Step5:, confirm that corresponding atmospheric scattering model obtains the particle picture of designated layer simultaneously according to the property value of the particle after the fuzzy smoothing processing;

Step6: particle picture and satellite image image are merged, obtain comprising the image of pollutant levels information;

Among the said step3 from particle position, the size of particle, the color value of particle and opacity value come pollutant levels are played up, and be specific as follows:

A. particle position: the spacing between adjacent particles equates, is expressed as d;

B. particle size

Use two kinds of methods to form the particle size of mist: rule and method and random device;

(1) rule and method: be about to all corresponding fixing particle size of each concentration; Particle size is defined in

scope, carries out linear interpolation according to the size of concentration value;

(2) random device: at first, the maximal value of calculating concentration and minimum value, the corresponding particle size of maximal value are five times of minimum value; Other particle sizes obtain from linear interpolation between the two;

C. particle color and opacity

Concentration value size according to pollutant; Utilize mapping function

to obtain the corresponding color value size of each concentration value, the color value of particle and opacity equate with concentration value; Wherein, x representes the pollutant levels value, and f (x) is corresponding color value size;

The process of fuzzy smoothing processing is following among the said step4:

First: mark frontier point, known particle position promptly (x, y z), find out x, y, the maximal value of position and minimum value are labeled as frontier point with it on the z direction, wherein, x, y, z are the three-dimensional coordinate of particle;

Second: the z value is fixing, find out the frontier point respective x, the y value,

(x, y is when z) having 8 adjoint points, then when interior point

$\mathrm{color}(x,y,z)=$

$\frac{1}{16}\×(4\mathrm{color}(x,y,z)+2\mathrm{color}(x-1,y,z)+2\mathrm{color}(x+1,y,z)$

$+2\mathrm{color}(x,y-1,z)+2\mathrm{color}(x,y+1,z)+\mathrm{color}(x-1,y-1,z)$

$+\mathrm{color}(x-1,y+1,z)+\mathrm{color}(x+1,y-1,z)+\mathrm{color}(x+1,y+1,z))$

When in interior point is put for neighbours, putting,

$\mathrm{color}(x,y,z)=\frac{1}{6}\×(2\mathrm{color}(x,y,z)+\mathrm{color}(x-1,y,z)$

$+\mathrm{color}(x+1,y,z)+\mathrm{color}(x,y-1,z)+\mathrm{color}(x,y+1,z));$

Wherein, (x, y are at coordinate points (x, y, the color value of z) locating, color (x-1, y z) to color; Z) be coordinate points (x-1, y, the color value of z) locating, (x+1, y z) are coordinate points (x+1, y, the color value of z) locating to color; Color (x, y-1, z) be coordinate points (x, y-1, the color value of z) locating, (x, y+1 are at coordinate points (x z) to color; Y+1, the color value of z) locating, (x-1, y-1 are at coordinate points (x-1, y-1, the color value of z) locating, color (x-1 z) to color; Y+1, z) be coordinate points (x-1, y+1, the color value of z) locating, (x+1, y-1 are at coordinate points (x+1 z) to color; Y-1, the color value of z) locating, (x+1, y+1 are at coordinate points (x+1, y+1, the color value of z) locating z) to color;

The atmospheric scattering model of said step5 comprises:

The Rayleigh scattering model: $P\left(\mathrm{\θ}\right)=\frac{3}{4}(1+{\mathrm{Cos}}^2\mathrm{\θ})$

The Mie scattering model:

$P(\mathrm{\θ},g)=\frac{3(1-g^2)}{2(2+g^2)}\frac{(1+{\cos }^2\mathrm{\θ})}{{(1+g^2-2g\cos \mathrm{\θ})}^{\frac{3}{2}}}$

Wherein, θ is the angle between incident direction and the scattering direction, and P (θ) is to be the phase function of parameter with θ; G ∈ (1,1) describes material scattering strength forward or backward, and (θ is with g g) to P, and θ is the phase function of parameter;

The method that particle picture and imaged image merge among the said step6 is: as base map, the opacity that then particle picture itself is had according to each particle is added in the image data with image data.

2. the regional pollution substrate concentration method for visualizing based on particIe system as claimed in claim 1 is characterized in that the pollutant levels forecast data is among said step1 or the step2: pellet PM10, sulphuric dioxide SO ₂, nitrogen monoxide NO, nitrogen dioxide NO ₂, carbon monoxide CO and ozone O ₃The concentration forecast data.

3. the regional pollution substrate concentration method for visualizing based on particIe system as claimed in claim 1 is characterized in that the gatherer process of said pollutant levels forecast data is following:

A: at first gather air pollutants through the automatic checkout equipment of some environmental monitoring websites;

B: data acquisition transmission appearance carries out the A/D conversion with the air pollutants data of automatic checkout equipment collection, and the data after the conversion adopt HJ/T212-2005 State Environmental Protection Administration data transmission standard communications protocol to be transferred to the service end of Surveillance center;

C: Surveillance center's service end with the data processing that receives after, send into prediction of air quality computation model system;

D: through prediction of air quality computation model system the air pollutants data of gathering are handled, obtained the pollutant levels data.

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