CN114324074A - Atmosphere monitoring sailing method based on backward trajectory model and remote sensing image - Google Patents
Atmosphere monitoring sailing method based on backward trajectory model and remote sensing image Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 39
- 238000000034 method Methods 0.000 title claims abstract description 22
- 239000003344 environmental pollutant Substances 0.000 claims abstract description 12
- 231100000719 pollutant Toxicity 0.000 claims abstract description 12
- 238000007781 pre-processing Methods 0.000 claims abstract description 8
- 238000012937 correction Methods 0.000 claims description 21
- 238000011160 research Methods 0.000 claims description 14
- 239000000443 aerosol Substances 0.000 claims description 13
- 230000005855 radiation Effects 0.000 claims description 10
- 238000004458 analytical method Methods 0.000 claims description 7
- 230000004927 fusion Effects 0.000 claims description 3
- 239000000779 smoke Substances 0.000 claims description 3
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- 239000012855 volatile organic compound Substances 0.000 description 8
- 238000002310 reflectometry Methods 0.000 description 5
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- 238000004364 calculation method Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000003912 environmental pollution Methods 0.000 description 2
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Abstract
The invention provides an atmospheric monitoring sailing method based on a backward track model and remote sensing images, which comprises the steps of preprocessing data, calling recent data of field real-time monitoring equipment in a monitoring area, calling digital model data of the monitoring area by a backward track model module, and optimizing sailing data. The remote sensing image data preprocessing and analyzing system carries out preliminary preprocessing and analyzing according to the remote sensing image data, provides daily GIS base maps and pollutant space difference maps of different time nodes by combining a map provided by on-site real-time monitoring equipment and images, carries out preliminary investigation and evaluation on the area, reports the report to a driver and other workers, and can reduce the cost of navigation monitoring by reasonably matching with the remote sensing data.
Description
Technical Field
The invention relates to the technical field of big data analysis application, in particular to an atmospheric monitoring sailing method based on a backward trajectory model and a remote sensing image.
Background
On the premise that the current atmospheric environmental pollution status is gradually improved, atmospheric pollution control is from particulate matter (PM2.5) prevention and control to PM2.5 and ozone (O3) cooperative control, and prevention and control pollution sources are also transferred from large industrial point sources to small and medium industrial sources, unorganized emission and various emission surface sources. Volatile Organic Compounds (VOCs), one of the important precursors for PM2.5 and O3, are also of course one of the pollutant species that are important for monitoring and abatement.
In order to reduce the influence of volatile organic compounds on environmental pollution, in addition to perfecting the emission list and the total amount of VOCs, standardizing and establishing a detection technical means of various VOCs is also one of key works, and the VOCs are observed by expanding new or strengthening the existing fixed stations and detection networks or equipping instruments into movable devices to obtain more dense and systematic emission and pollution distribution information, so that the method is a commonly used VOCs navigation monitoring means.
The sailing monitoring technology adds real-time monitoring geographical position information on three factors of time, species and concentration which are normally output by fixed-point monitoring, and provides a plurality of layers of possibility for data use and interpretation. The monitoring of navigating has the characteristics that mobility is strong, can master VOCs's dynamic spatial distribution and pollution characteristics fast, is prior art, traces to the important technological means of source to the ambient air influence of pollution emission source, but changes the shortcoming that technological means exists and do: (1) depending on a large amount of labor cost, the wages of matched technicians are high; (2) the driving route is not targeted well and takes a long time.
Disclosure of Invention
In view of the problems described in the background art, the invention aims to provide an atmospheric monitoring sailing method based on a backward trajectory model and remote sensing images, which can be reasonably matched with remote sensing data and has stable performance.
In order to achieve the purpose, the invention provides the following technical scheme:
an atmosphere monitoring sailing method based on a backward track model and a remote sensing image comprises the following steps:
q1, preprocessing data, automatically extracting aerosol wave bands of a monitoring area according to remote sensing image data, independently performing radiation correction on the aerosol wave bands, independently extracting after atmospheric correction, starting a preprocessing program, independently performing research and analysis on a pollution area, and providing data of a pollution research range if pollutants in the pollution area are obviously improved compared with the previous day in the research and analysis result, and sending a report to a backward trajectory model module to generate a corresponding log file for auditing;
q2, retrieving recent data of the field real-time monitoring equipment in the monitoring area, drawing a recent pollution research range according to a Krigin algorithm, sending the report to a backward trajectory model module and copying a driver and background workers after drawing is finished;
q3, calling digital model data, digital model data DEM (digital elevation model) data and DSM (digital surface model) data of a monitoring area by the backward track model module, analyzing the influence degree among pollutants, terrain, smoke and buildings by the backward track model module according to the digital model data, making a preliminary estimation report of the pollution condition of a monitoring area, and sending the preliminary estimation report to a mobile phone APP of a driver and simultaneously copying the driver and background workers;
q4, optimizing the navigation data, after the track model is ended, immediately alarming by a driver mobile phone APP to prompt to go for navigation immediately and provide optimized route navigation.
In the above technical solution, the report in Q2 includes: real-time pollution level, pollution change trend within 3 hours in the future, potential pollution sources, main pollutants, and key areas needing navigation.
In the technical scheme, the aerosol wave band is from a multispectral and hyperspectral remote sensing satellite with the aerosol wave band.
In the technical scheme, the remote sensing image data is a remote sensing image obtained by geographic registration, radiation correction, FLAASH atmospheric correction, ortho-correction and fusion by using a GIS base map product above L2.
The remote sensing image data preprocessing and analyzing system carries out preliminary preprocessing and analyzing according to the remote sensing image data, provides daily GIS base maps and pollutant space difference maps of different time nodes by combining a map provided by on-site real-time monitoring equipment and images, carries out preliminary investigation and evaluation on the area, reports the report to a driver and other workers, and can reduce the cost of navigation monitoring by reasonably matching with the remote sensing data.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments of the present invention, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention discloses an atmosphere monitoring sailing method based on a backward track model and a remote sensing image by an embodiment, and has the innovation points that the idea of an airbus pixel factory is absorbed, the remote sensing image is automatically subjected to primary processing, and a large amount of labor is saved. The full automation of the operations of geographic registration, radiation correction, FLAASH atmospheric correction, orthographic correction, sharpening and the like is realized. Meanwhile, the system can also automatically extract various indexes and automatically draw polluted areas. The remote sensing image comprises but is not limited to a high-resolution satellite series developed independently in China, a high-view/Beijing satellite series, a hyperspectral (such as high resolution 5/Oldhatt and the like) satellite series, a resource satellite series, a wind and cloud satellite series, a foreign Landsat satellite series and radar satellites in various countries, and the data of the satellites are used for calculating indexes such as surface temperature, surface humidity, leaf area index, vegetation coverage, net primary productivity and the like of local areas. These indices provide precision support for the following backward trajectory module.
The method comprises the following steps:
q1, preprocessing data, automatically extracting aerosol wave bands in a monitoring area according to remote sensing image data, independently performing radiation correction on the aerosol wave bands, independently extracting after atmospheric correction, starting a preprocessing program, and independently performing research and analysis on a pollution area (for example, a system finds that the aerosol thickness in a certain area has an obvious rising trend or reaches an alarm critical line, and automatically buffers and masks the area, and the masked area is determined as a research area. the traditional method adopts manual intervention and needs a large amount of background personnel. the method refers to the idea of airbus pixel factory, completely breaks away from manual work, although the parameters such as color and hue of an effect picture are not beautiful, but are completely enough when a computer reads the result), and in the research and analysis result, if pollutants in the pollution area are found to be obviously improved compared with the previous date, the pollution research range data is provided, sending the report to a backward track model module to generate a corresponding (. txt format) log file for auditing; the aerosol wave band comes from a multispectral and hyperspectral remote sensing satellite with the aerosol wave band, and remote sensing image data are remote sensing images after geographic registration, radiation correction, FLAASH atmospheric correction, orthographic correction and fusion by using GIS base map products above L2.
The radiometric calibration may calibrate the values of the telemetry data to radiometric and reflectivity. This option can be used if the image has gain and offset for each band. The calculation formula of the radiation is as follows:
Lλ＝Gain*Pixel value+Offset
if the gain and offset are in W/(m2 sr μm), the radiation dose is also in W/(m2 sr μm)
Atmospheric Top (TOA) reflectance (0 to 1.0). This option may be used if the image has gain, offset, solar irradiance, solar altitude, and acquisition time defined in the metadata.
If the input file contains metadata about the reflectivity gain and offset, the algorithm will use these values to calibrate the data to TOA reflectivity. The algorithm measures the reflection gain and offset from the sine of the solar altitude, for example using the Landsat-8 file. If the input file does not contain metadata about the reflectivity gain and offset, the algorithm will calculate the TOA reflectivity using the following formula:
wherein:
Lλradiance in units of W/(m2 sr μm)
d is the earth-sun distance in astronomical units.
ESUNλSolar irradiance, in units of W/(m2 ×)μm)
Theta is the sun altitude angle
Radiance this option is only applicable to terrestrial satellite-8, ETM + and TM thermography. The luminance temperature (kelvin) is calculated as follows:
wherein:
k1 and K2 ═ calibration constants (kelvin). The algorithm reads these values from the metadata of Landsat.
Atmospheric correction: spectral hypercube fast line-of-sight atmospheric analysis (FLAASH) is an atmospheric correction module developed by the Spectral Sciences institute (Spectral Sciences Inc.) with the support of the united states air Force Research Laboratory.
FLAASH is an atmospheric correction method that retrieves spectral reflectance from hyperspectral radiometric images. FLAASH employs a modern radiation transfer model to compensate for atmospheric effects. The method has the advantages of high precision and long calculation time compared with other algorithms (such as QUAC). FLAASH is integrated into my algorithm.
Q2, retrieving recent data (data are PM2.5, PM10, TSP, O3 and the like) of the on-site real-time monitoring equipment of the monitoring area, drawing a recent pollution research range according to a Kriging algorithm, sending the report to a backward trajectory model module and copying a driver and background workers after drawing is finished; the report includes: real-time pollution level, pollution change trend within 3 hours in the future, potential pollution sources, main pollutants, and key areas needing navigation.
Kriging algorithm: in statistics, the kriging method, also known as gaussian process regression, is an interpolation method based on a gaussian process controlled by a pre-covariance, which, under the appropriate assumptions, gives the Best Linear Unbiased Prediction (BLUP) at the non-sampled position, the speed at which the algorithm is performed depending on the number of points in the input data set and the size of the region of interest.
Q3, calling digital model data, digital model data DEM (digital elevation model) data and DSM (digital surface model) data of a monitoring area by the backward track model module, analyzing the influence degree among pollutants, terrain, smoke and building washing by the backward track model module according to the digital model data, making a preliminary estimation report of the pollution condition of the monitoring area, and sending the preliminary estimation report to a mobile phone APP of a driver and simultaneously copying the driver and background workers;
the backward trajectory model module is provided by NOAA, USAF, and integrates the UI of AERMOD/AERSCREEN.
Q4, optimizing the data of navigating, after the back orbit model stops, driver's cell-phone APP reports to the police immediately, and the suggestion is started immediately and is walked the navigation to provide the optimization route navigation.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (4)
1. An atmosphere monitoring sailing method based on a backward track model and a remote sensing image is characterized in that: the method comprises the following steps:
q1, preprocessing data, automatically extracting aerosol wave bands of a monitoring area according to remote sensing image data, independently performing radiation correction on the aerosol wave bands, independently extracting after atmospheric correction, starting a preprocessing program, independently performing research and analysis on a pollution area, and providing data of a pollution research range if pollutants in the pollution area are obviously improved compared with the previous day in the research and analysis result, and sending a report to a backward trajectory model module to generate a corresponding log file for auditing;
q2, retrieving recent data of the field real-time monitoring equipment in the monitoring area, drawing a recent pollution research range according to a Krigin algorithm, sending the report to a backward trajectory model module and copying a driver and background workers after drawing is finished;
q3, calling digital model data, digital model data DEM (digital elevation model) data and DSM (digital surface model) data of a monitoring area by the backward track model module, analyzing the influence degree among pollutants, terrain, smoke and buildings by the backward track model module according to the digital model data, making a preliminary estimation report of the pollution condition of a monitoring area, and sending the preliminary estimation report to a mobile phone APP of a driver and simultaneously copying the driver and background workers;
q4, optimizing the data of navigating, after the back orbit model stops, driver's cell-phone APP reports to the police immediately, and the suggestion is started immediately and is walked the navigation to provide the optimization route navigation.
2. The atmospheric monitoring sailing method based on the backward trajectory model and the remote sensing image as claimed in claim 1, characterized in that: the report in Q2 includes: real-time pollution level, pollution change trend within 3 hours in the future, potential pollution sources, main pollutants, and key areas needing navigation.
3. The atmospheric monitoring sailing method based on the backward trajectory model and the remote sensing image as claimed in claim 1, characterized in that: the aerosol wave band is from a multispectral and hyperspectral remote sensing satellite with the aerosol wave band.
4. The atmospheric monitoring sailing method based on the backward trajectory model and the remote sensing image as claimed in claim 1, characterized in that: the remote sensing image data is a remote sensing image obtained by geographic registration, radiation correction, FLAASH atmospheric correction, orthographic correction and fusion by using a GIS base map product more than L2.
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