CN102176073A - Ambient air quality comprehensive monitoring method based on first ambient satellite - Google Patents
Ambient air quality comprehensive monitoring method based on first ambient satellite Download PDFInfo
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Abstract
The invention discloses an ambient air quality comprehensive monitoring method based on a first ambient satellite, and the method comprises the following steps: S1, inverting an ambient air quality monitoring remote sensing parameter by using a remote sensing model according to the remote sensing data of a first ambient A satellite and/or satellite B; S2, analyzing the remote analyzing parameter according to the basic geographic information data to obtain an ambient air quality monitoring result. By using a satellite remote sensing technology, an air quality space distribution result facing to the field of ambient protection is obtained while the rapid, large-scale and facet monitoring is satisfied, thereby realizing powerful complementation with a ground monitoring station.
Description
Technical field
The present invention relates to the applications of atmospheric remote sensing techniques field, relate in particular to a kind of ambient air quality integrated monitoring based on a satellite of environment based on the observation satellite remotely-sensed data.
Background technology
The aerocolloidal research of satellite remote sensing starts from the middle nineteen seventies in last century.France has promoted polarization multi-angle (POLDER) camera from 1996 and has surveyed aerocolloidal research, in the Moderate Imaging Spectroradiomete (MODIS) that 1999 and the U.S. Terra that launched in 2002 and Aqua carry the aerocolloidal distribution on global product of 10 kms has been issued in the whole world.Also formed system on the satellite remote sensing gasoloid inversion algorithm, satellite remote sensing land aerosol method mainly contains dark goal method, structure function method, multi-angle polarization method etc.
The load that China is used for aerosol monitoring mainly is wind and cloud FY series, and FY-2 FY2 has had the sand and dust detectivity; No. three FY3 of wind and cloud are loaded with sensors such as visible light infrared scanning radiometer, Moderate Imaging Spectroradiomete, can carry out gasoloid and survey.Environment of China and the disaster monitoring forecast small satellite satellite seat ring satellite in border (HJ-1A/B) have higher spatial, temporal resolution and wide covering characteristics, will provide new remote-sensing flatform for China's ambient air quality remote sensing monitoring.
Estimate that based on satellite remote sensing particle contamination substrate concentration near the ground and monitored area pollute, main thinking all is to set up correlation model between aerosol optical depth (AOT or AOD) and particle concentration near the ground by other parameters directly or indirectly.Be broadly divided into three classes:
1) the directly related model of AOT and particle concentration near the ground.
AOT and the subaerial PM of scholar with ground based observa tion arranged
10(usually the aerodynamics equivalent diameter is called PM10 at the particle below 10 microns, be called pellet or floating dust again) and PM
2.5(PM2.5 is meant that diameter is less than or equal to 2.5 microns particle in the atmosphere, is also referred to as and can goes into the lung particle) concentration has been carried out correlation analysis (Chu etc., 2003; Slater etc., 2004), have also directly that the AOT of satellite remote sensing and particle concentration near the ground are carried out relevance ratio is right.(Wang and Christopher, 2003; Koelemeijer etc., 2006; Engle-Cox etc., 2004).
2) consider the correlation model that aerosol vertical distribution and relative humidity influence.
Koelemeijer etc. (2006) utilize atmospheric boundary layer height with the relative humidity data MODIS AOT to be carried out vertical correcting with humidity and correct, and have estimated the particle near the ground of European Region; Wang etc. (2010) carry out vertical correcting with humidity in the relative humidity of atmospheric boundary layer height that utilizes laser radar to survey and actual measurement to the AOT of ground inverting and correct; Liu etc. (2004) take the lead in using the Atmospheric Chemistry transmission mode to simulate the correlationship of whole layer AOT of each graticule mesh place and particle concentration near the ground.
3) correlation model of the multiple environment weather factor of consideration.
Gupta (2006) initial analysis AOT and particle concentration correlationship near the ground susceptibility to meteorologic factors such as cloud coverage, wind speed and mixolimnion height, relative humidity; Pelletier etc. (2007) have taken all factors into consideration wind speed, pressure, relative humidity, atmosphere precipitable water etc., have set up the experience correlation model of particle concentration near the ground and AOT; Liu etc. (2005a) have used a PM
2.5The general linear regression model (LRM) of concentration is introduced some geography, environmental factor as accessory factor.
Dust and sand weather is meant that high wind rolls a large amount of dirt sand from ground, makes stuffyly, and a kind of weather phenomenon that horizontal visibility obviously descends is by a kind of spontaneous phenomenon due to special geographical environment and the meteorological condition.At present the remote sensing monitoring of sand and dust mainly utilizes geostationary meteorological satellite (GMS) and GMS/VISSR, polar orbiting meteorological satellite NOAA/AVHRR (AVHRR is the main detection instrument of NOAA series satellite, and it is a kind of scanning radiometer of five spectrum channels), FY21C/MVISR and Terra, Aqua/MODIS data.MVISR and AVHRR data, spatial resolution is 1.1km, (1.25～4km), sweep length 2300～2800km is as appropriately then being used to extract sand and dust information preferably opportunity to be higher than geostationary meteorological satellite (GMS).
Utilize satellite remote sensing to carry out sand and dust monitorings, existing both at home and abroad many people carried out studying (model one is big etc., 2003; Goudie et al, 1992; Li Qing etc., 2006), mainly adopt the monitoring of the method realization sand and dust of multiband combination.
General stalk combustion temperature is between 500K-1000K, so its emittance should mainly concentrate between 2.8 microns-5.7 microns.The radiation of high-temp combustion fire mainly concentrates on two discrete zones, and strong band is between the 4-5 micron, and weak band is (Justice et al., 2006) between the 2-3 micron, then relatively little many of the radiation of other spectral coverages.This shows that high-temp combustion belongs to selective radiator.During biological burning, background pixel around the radiation value of middle-infrared band will be higher than it far away, its spoke brightness is very obvious.
Utilize remote sensing technology to carry out large-scale crop straw burning fire point position and the monitoring of burning flue dust, domestic existing many people have carried out studying (He Liming etc., 2007; Zou Chunhui etc., 2005; Fang Meng etc., 2006)." slow fire point probe algorithm up and down " (Giglio et al., 2003 based on sensing datas such as NOAA/AVHRR and Terra/MODIS; Flasse et al, 1996) be most widely used aspect the monitoring of fire point.At present, the sensor that is mainly used in the monitoring of fire point is MODIS (Giglio et al., 2003), and AVHRR (Flasse et al., 1996) etc., the infrared camera of HJ-1B star also have the ability that the fire point is surveyed.
In existing satellite remote sensing control of quality monitoring method,, air quality indexs such as particle, crop straw burning, sand and dust to be monitored respectively, monitoring efficient is low.
Summary of the invention
(1) technical matters that will solve
The technical problem to be solved in the present invention is: provide a kind of based on A star of environment and B star ambient air quality integrated monitoring; can utilize satellite remote sensing technology; satisfy fast, on a large scale, in the planar monitoring; obtain air quality spatial distribution result, realized strong complementation with the ground monitoring station towards field of environment protection.
(2) technical scheme
For addressing the above problem, the invention provides a kind of ambient air quality integrated monitoring based on a satellite of environment, the method comprising the steps of:
S1. according to the remotely-sensed data of A star of environment and/or B star, utilize Remote Sensing Model, inverting ambient air quality monitoring remote sensing parameter;
S2. according to basic geographic information data, analyze described remote sensing parameter, obtain the ambient air quality monitoring result.
Wherein, described Remote Sensing Model comprises: dark target algorithm, slow fire point detection and multiband thresholding algorithm up and down.
Wherein, step S1 further comprises:
S1.1 utilizes dark target algorithm, the inverting aerosol optical depth according to A star of environment and/or B star CCD camera data;
S1.2 utilizes slow fire point probe algorithm up and down, inverting thermal anomaly point according to A star of environment and/or B star infrared camera data;
S1.3 utilizes the multiband thresholding algorithm according to A star of environment and/or B star CCD camera data, and the inverting sand and dust distribute and grade.
Wherein, step S2 further comprises:
S2.1 utilizes the particle inversion algorithm, according to basic geographic information data and described aerosol optical depth, obtains particle pollution monitoring and analysis result;
S2.2 utilizes the crop straw burning inversion algorithm, according to basic geographic information data and described thermal anomaly point, obtains crop straw burning monitoring and analysis result;
S2.3 distributes and grade according to basic geographic information data and described sand and dust, obtains distant monitoring of sand and dust and analysis result.
Wherein, comprise that also step is vertically corrected described aerosol optical depth and humidity is corrected before the step S2.1.
Wherein, described basic geographic information data is according to the vector data of the administrative division of different stage and the face of land grouped data of preset proportion chi.
Wherein, it is characterized in that described preset proportion chi is 1: 100 ten thousand.
(3) beneficial effect
Method of the present invention is based on satellite remote sensing technology, based on the CCD camera and the infrared camera data of HJ-1A/B star, satisfying fast, on a large scale, in the planar monitoring, obtained the air quality spatial distribution result towards field of environment protection.
Description of drawings
Fig. 1 is the ambient air quality integrated monitoring process flow diagram based on a satellite of environment according to one embodiment of the present invention.
Embodiment
The ambient air quality integrated monitoring based on a satellite of environment (HJ-1A/B) that the present invention proposes reaches embodiment in conjunction with the accompanying drawings and is described in detail as follows.
As shown in Figure 1, the ambient air quality integrated monitoring based on a satellite of environment according to one embodiment of the present invention comprises step:
S1. according to the remote sensing raw data of HJ-1A and/or B star, utilization comprises dark target algorithm, the Remote Sensing Model of the algorithm of slow fire point probe algorithm and multiband threshold method up and down, carry out remote-sensing inversion and calculate, obtain the inversion result of ambient air quality monitoring remote sensing parameters such as gasoloid, sand and dust, thermal anomaly;
S2. according to basic geographic information data, each remote sensing parameter that analysis obtains above obtains the ambient air quality monitoring result towards aspects such as particle, sand and dust and crop straw burnings.
Wherein, step S1 further comprises:
S1.1 utilizes dark target algorithm, the inverting aerosol optical depth according to A star of environment and/or B star CCD camera data;
S1.2 utilizes slow fire point probe algorithm up and down, inverting thermal anomaly point according to A star of environment and/or B star infrared camera data;
S1.3 utilizes the multiband thresholding algorithm according to A star of environment and/or B star CCD camera data, and the inverting sand and dust distribute and grade.
Step S2 further comprises:
S2.1 utilizes the particle inversion algorithm, according to basic geographic information data and through the aerosol optical depth of vertically correcting and humidity is corrected, obtains particle pollution monitoring and analysis result;
S2.2 utilizes the crop straw burning inversion algorithm, according to basic geographic information data and described thermal anomaly point, obtains crop straw burning monitoring and analysis result;
S2.3 distributes and grade according to basic geographic information data and described sand and dust, obtains distant monitoring of sand and dust and analysis result.
The basic geographical information packet that present embodiment is mentioned is drawn together the vector data of province, city, the three grades of administrative divisions in county, and 1: 100 ten thousand face of land grouped data etc.
Above embodiment only is used to illustrate the present invention; and be not limitation of the present invention; the those of ordinary skill in relevant technologies field; under the situation that does not break away from the spirit and scope of the present invention; can also make various variations and modification; therefore all technical schemes that are equal to also belong to category of the present invention, and scope of patent protection of the present invention should be defined by the claims.
Claims (7)
1. ambient air quality integrated monitoring based on a satellite of environment is characterized in that the method comprising the steps of:
S1. according to the remotely-sensed data of A star of environment and/or B star, utilize Remote Sensing Model, inverting ambient air quality monitoring remote sensing parameter;
S2. according to basic geographic information data, analyze described remote sensing parameter, obtain the ambient air quality monitoring result.
2. the ambient air quality integrated monitoring based on a satellite of environment as claimed in claim 1 is characterized in that described Remote Sensing Model comprises: dark target algorithm, slow fire point detection and multiband thresholding algorithm up and down.
3. the ambient air quality integrated monitoring based on a satellite of environment as claimed in claim 2 is characterized in that step S1 further comprises:
S1.1 utilizes dark target algorithm, the inverting aerosol optical depth according to A star of environment and/or B star CCD camera data;
S1.2 utilizes slow fire point probe algorithm up and down, inverting thermal anomaly point according to A star of environment and/or B star infrared camera data;
S1.3 utilizes the multiband thresholding algorithm according to A star of environment and/or B star CCD camera data, and the inverting sand and dust distribute and grade.
4. the ambient air quality integrated monitoring based on a satellite of environment as claimed in claim 3 is characterized in that step S2 further comprises:
S2.1 utilizes the particle inversion algorithm, according to basic geographic information data and described aerosol optical depth, obtains particle pollution monitoring and analysis result;
S2.2 utilizes the crop straw burning inversion algorithm, according to basic geographic information data and described thermal anomaly point, obtains crop straw burning monitoring and analysis result;
S2.3 distributes and grade according to basic geographic information data and described sand and dust, obtains distant monitoring of sand and dust and analysis result.
5. the ambient air quality integrated monitoring based on a satellite of environment as claimed in claim 4 is characterized in that, comprises that also step is vertically corrected described aerosol optical depth and humidity is corrected before the step S2.1.
6. as each described ambient air quality integrated monitoring of claim 1-5 based on a satellite of environment, it is characterized in that described basic geographic information data is the face of land grouped data according to the vector data and the preset proportion chi of the administrative division of different stage.
7. the ambient air quality integrated monitoring based on a satellite of environment as claimed in claim 6 is characterized in that described preset proportion chi is 1: 100 ten thousand.
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| CN102521681A (en) * | 2011-11-18 | 2012-06-27 | 中国科学院对地观测与数字地球科学中心 | Remote sensing data quality monitoring system with extensible function and performance |
| CN102565294A (en) * | 2011-02-01 | 2012-07-11 | 环境保护部卫星环境应用中心 | Water source area monitoring and evaluation method |
| CN104007486A (en) * | 2014-06-05 | 2014-08-27 | 中国气象局气象探测中心 | Atmospheric temperature and humidity profile processing method and system with active and passive remote sensing combined |
| CN104021276A (en) * | 2014-05-14 | 2014-09-03 | 中国农业科学院农业资源与农业区划研究所 | Global and regional air quality monitoring method |
| CN104635242A (en) * | 2015-02-16 | 2015-05-20 | 罗敬宁 | Sand storm monitoring method based on multi-source satellite remote sensing data |
| CN105092784A (en) * | 2015-05-08 | 2015-11-25 | 中国科学院遥感与数字地球研究所 | Atmosphere pollution monitoring and query method and device |
| CN106446307A (en) * | 2015-08-05 | 2017-02-22 | 中国科学院遥感与数字地球研究所 | Aerosol foundation data-based AOD vertical correction effect evaluation method and system |
| CN106950574A (en) * | 2017-04-14 | 2017-07-14 | 北京市环境保护监测中心 | The remote sensing measuring method and device of gray haze total amount in a kind of air |
| CN108225572A (en) * | 2018-01-19 | 2018-06-29 | 北京师范大学 | City high temperature heat anomaly detection method based on IRMSS thermal band |
| CN110595960A (en) * | 2019-08-02 | 2019-12-20 | 中国科学院遥感与数字地球研究所 | PM2.5 concentration remote sensing estimation method based on machine learning |
| CN111579504A (en) * | 2020-06-29 | 2020-08-25 | 中国科学技术大学 | Atmospheric pollution component vertical distribution inversion method based on optical remote sensing |
| CN111696074A (en) * | 2020-04-30 | 2020-09-22 | 中国资源卫星应用中心 | Fire point monitoring system based on high score four and application |
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- 2011-01-24 CN CN 201110025814 patent/CN102176073A/en active Pending
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| 《Remote Sensing of Environment》 20031231 Louis Giglio and et al "An Enhanced Contextual Fire Detection Algorithm for MODIS" 273-282 , 第87期 2 * |
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| CN102565294A (en) * | 2011-02-01 | 2012-07-11 | 环境保护部卫星环境应用中心 | Water source area monitoring and evaluation method |
| CN102565294B (en) * | 2011-02-01 | 2014-10-29 | 环境保护部卫星环境应用中心 | Water source area monitoring and evaluation method |
| CN102521681A (en) * | 2011-11-18 | 2012-06-27 | 中国科学院对地观测与数字地球科学中心 | Remote sensing data quality monitoring system with extensible function and performance |
| CN104021276A (en) * | 2014-05-14 | 2014-09-03 | 中国农业科学院农业资源与农业区划研究所 | Global and regional air quality monitoring method |
| CN104021276B (en) * | 2014-05-14 | 2017-07-04 | 中国农业科学院农业资源与农业区划研究所 | A kind of whole world and regional air quality monitoring method |
| CN104007486A (en) * | 2014-06-05 | 2014-08-27 | 中国气象局气象探测中心 | Atmospheric temperature and humidity profile processing method and system with active and passive remote sensing combined |
| CN104635242B (en) * | 2015-02-16 | 2017-04-12 | 罗敬宁 | Sand storm monitoring method based on multi-source satellite remote sensing data |
| CN104635242A (en) * | 2015-02-16 | 2015-05-20 | 罗敬宁 | Sand storm monitoring method based on multi-source satellite remote sensing data |
| CN105092784A (en) * | 2015-05-08 | 2015-11-25 | 中国科学院遥感与数字地球研究所 | Atmosphere pollution monitoring and query method and device |
| CN106446307A (en) * | 2015-08-05 | 2017-02-22 | 中国科学院遥感与数字地球研究所 | Aerosol foundation data-based AOD vertical correction effect evaluation method and system |
| CN106446307B (en) * | 2015-08-05 | 2020-01-14 | 中国科学院遥感与数字地球研究所 | Aerosol foundation data-based AOD (automated optical inspection) vertical correction effect evaluation method and system |
| CN106950574A (en) * | 2017-04-14 | 2017-07-14 | 北京市环境保护监测中心 | The remote sensing measuring method and device of gray haze total amount in a kind of air |
| CN106950574B (en) * | 2017-04-14 | 2019-11-08 | 北京市环境保护监测中心 | The remote sensing measuring method and device of gray haze total amount in a kind of atmosphere |
| CN108225572A (en) * | 2018-01-19 | 2018-06-29 | 北京师范大学 | City high temperature heat anomaly detection method based on IRMSS thermal band |
| CN110595960A (en) * | 2019-08-02 | 2019-12-20 | 中国科学院遥感与数字地球研究所 | PM2.5 concentration remote sensing estimation method based on machine learning |
| CN111696074A (en) * | 2020-04-30 | 2020-09-22 | 中国资源卫星应用中心 | Fire point monitoring system based on high score four and application |
| CN111696074B (en) * | 2020-04-30 | 2024-04-05 | 中国资源卫星应用中心 | Fire monitoring system based on high-resolution fourth-order and application |
| CN111579504A (en) * | 2020-06-29 | 2020-08-25 | 中国科学技术大学 | Atmospheric pollution component vertical distribution inversion method based on optical remote sensing |
| CN115016036A (en) * | 2022-06-28 | 2022-09-06 | 中科三清科技有限公司 | Agricultural weather monitoring method, device, equipment and storage medium |
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Application publication date: 20110907 |