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HJ 1008-2018: Technical specification for straw burning monitoring based on satellite remote sensing
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Technical specification for straw burning monitoring based on satellite remote sensing
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Standard similar to HJ 1008-2018 HJ 91.1 HJ 212 HJ 644 HJ 164 HJ 839 Basic data | Standard ID | HJ 1008-2018 (HJ1008-2018) | | Description (Translated English) | Technical specification for straw burning monitoring based on satellite remote sensing | | Sector / Industry | Environmental Protection Industry Standard | | Classification of Chinese Standard | Z10 | | Word Count Estimation | 13,187 | | Date of Issue | 2018-12-26 | | Date of Implementation | 2019-06-01 | | Regulation (derived from) | Ministry of Ecology and Environment Announcement No. 71 of 2018 | | Issuing agency(ies) | Ministry of Ecology and Environment | HJ 1008-2018: Technical specification for straw burning monitoring based on satellite remote sensing
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Technical specification for brewing monitoring based on satellite remote sensing
National Environmental Protection Standard of the People's Republic
Satellite remote sensing straw incineration monitoring technical specification
Technical specification for brew burning monitoring
Based on satellite remote sensing
Published on.2018-12-26
2019-06-01 Implementation
Ministry of Ecology and Environment released
i directory
Foreword...ii
1 Scope...1
2 Normative references...1
3 Terms and Definitions...1
4 General...1
5 Monitoring methods... 2
6 Monitoring product production...8
7 Quality Control...8
Appendix A (informative) Common data sources for satellite straw monitoring...9
Foreword
To implement the "Environmental Protection Law of the People's Republic of China" and the "Air Pollution Control Law of the People's Republic of China"
To guide satellite remote sensing monitoring of straw burning, to prevent air pollution, improve air quality, and develop this standard.
This standard specifies the method of satellite remote sensing monitoring of straw burning, product production, quality control and so on.
Appendix A of this standard is an informative annex.
This standard is the first release.
This standard is formulated by the Department of Eco-Environmental Monitoring, the Department of Regulations and Standards of the Ministry of Ecology and Environment.
This standard was drafted. Satellite Environment Application Center of the Ministry of Environmental Protection.
This standard is verified by. Jiangsu Environmental Monitoring Center, Beijing Environmental Monitoring Center, Heilongjiang Province Environmental Science Research
hospital.
This standard is approved by the Ministry of Ecology and Environment on December 26,.2018.
This standard has been implemented since June 1,.2019.
This standard is explained by the Ministry of Ecology and Environment.
1 Satellite remote sensing straw incineration monitoring technical specification
1 Scope of application
This standard stipulates the use of polar-orbiting satellites for remote sensing monitoring of straw burning, product production, quality control and other content.
This standard is applicable to satellite remote sensing monitoring of straw burning.
2 Normative references
The contents of this standard refer to the terms in the following documents.
GB/T 32453-2015 Satellite Earth observation data product classification and classification rules.
3 Terms and definitions
The following terms and definitions apply to this standard.
3.1
Brightness temperature
The black body temperature equal to the radiation output of the observed object, which is numerically equivalent to the radiant temperature, quoted from GB/T
32453-2015.
3.2
Apparent reflectance
Refers to the ratio of the reflected energy at the top of the atmosphere to the incident energy of the sun.
3.3
Suspected fire point of burning
Refers to the straw burning point to be verified by the technical methods of this standard.
3.4
Suspected fire point confidence of straw burning
Refers to the probability that the suspected fire point of straw burning is the actual fire point monitored by the technical methods of this standard.
4 General
4.1 Monitoring principle
Differences in brightness temperature between mid-infrared and thermal infrared based on suspected fire point pixels and background normal temperature pixels in straw burning
Do not heat abnormal points, combined with land classification data, extract suspected fire points from straw burning.
4.2 Monitoring means
Straw incineration monitoring is carried out using optical and infrared sensors of polar-orbiting satellites. The sensor should have a range of 0.65μm
2 visible light red band, near-infrared band near 0.8μm, mid-infrared band near 4μm, near 11μm and 12μm
Refer to Appendix A for the thermal infrared band and band settings.
4.3 Monitoring content
The location, quantity, and reliability of suspected fire spots in straw burning.
4.4 Monitoring process
The satellite remote sensing monitoring process for straw burning is shown in Figure 1.
Satellite remote sensing data
Remote sensing data preprocessing
Straw burning suspected fire point extraction
Estimation of reliability of suspected fire point in straw burning
Land use data
Monitoring products to produce geographic information data
Thermal anomaly extraction
Figure 1 Straw burning satellite remote sensing monitoring process
5 Monitoring methods
5.1 Remote sensing data preprocessing
First, the satellite remote sensing data is subjected to quality inspection, radiation correction and geometric correction, and then the visible light and near infrared waves are calculated.
The apparent reflectance of the segment and the brightness temperature of the mid-infrared and thermal infrared bands.
The apparent reflectance is calculated as follows.
Cos
LD
ESUN
= (1)
In the formula.
ρ -- apparent reflectance;
--constant, sr;
- radiance, W/(m2 · sr · μm);
-- the distance between the sun and the earth, the astronomical unit;
ESUN - the average solar spectrum irradiance at the top of the atmosphere, W/(m2 · μm);
θ -- solar zenith angle, °.
The brightness temperature is calculated as follows.
Ln 1
Hc
Hc
⎛ ⎞
⎜ ⎟
⎝ ⎠
(2)
In the formula.
3T
-- apparent brightness temperature, K;
-- speed of light, m/s;
Λ--center wavelength, μm;
- radiance, W/(m2 · sr · μm);
h--Planck constant, taking 6.626×10-34J·s;
k - Boltzmann constant, taking 1.38 × 10-23 J/K.
5.2 Cloud and water body pixel recognition and rejection
Identify and eliminate cloud and water pixels that meet the following conditions.
The discriminating conditions of the cloud pixel are.
Ρ1 12 t1 ρ2 12 t 2
12 t1
Rn( )rn Th T Th Th T Th
T Th
ρ ρ ρ ρ ) > ∨ ( < ) ∨ (( ) > ∧ < ⎧
⎪ < ⎩
Daytime
at night
(3)
The criteria for determining the water body pixel are.
n ρ3 ( ) ( 0)Th NDVIρ < ∧ < where, ( )
Nrnr
NDVI ρ ρ ρ ρ= − )/ ( (4)
In the formula.
Rρ - the apparent reflectivity of the pixel in the red band;
Nρ - the apparent reflectivity of the pixel in the near infrared;
12T - the brightness temperature of the pixel in the thermal infrared band (around 12μm), K;
ρ1Th
- discriminate the threshold, the reference value can take 0.9;
ρ2Th
- discriminate the threshold, the reference value may take 0.7;
t1Th -- discriminating threshold, the reference value can be 265K;
t 2Th -- discriminating threshold, the reference value can be 285K;
ρ3Th
- discriminate the threshold, the reference value can be taken as 0.15;
NDVI - normalized vegetation index;
Daytime - the solar zenith angle is less than 85° (the same below);
At night - the solar zenith angle is greater than or equal to 85° (the same below).
5.3 Thermal anomaly extraction
5.3.1 Extraction Process
The hot anomaly extraction process is as follows.
4The initial threshold of the initial fixed fire point is determined by determining the background threshold of the initial fixed fire point
Initial fixed fire point discrimination
Daytime
False fire point removal
Non-fire point
at night
Cloudless land image
Tentative fire point
Thermal anomaly
Figure 2 Hot abnormal point extraction process
5.3.2 Initial fixed fire point discrimination
First of all, the remote sensing pixels should be initially classified to distinguish the initial fire point pixels from the non-fire point pixels.
The initial fire point determination conditions are.
4 t3 t1 ρ4
4 t4 t1
( ) ( ) (
( ) ( )
T Th T Th Th
T Th T Th
> ∧ ∆ > ∧ < ) ⎧
⎪ > ∧ ∆ > ⎩
Daytime
at night
(5)
In the formula.
4T - the brightness temperature of the pixel in the mid-infrared band (around 4μm), K;
T∆ - the difference between the brightness temperature of the pixel in the mid-infrared band (around 4 μm) and the thermal infrared band (near 11 μm),
K;
ρ4Th
- discriminate the threshold, the reference value may take 0.3;
t3Th -- discriminating threshold, the reference value can be taken as 300K;
t4Th -- discriminating threshold, the reference value can be 305K;
t1Th∆ -- The threshold is determined, and the reference value can be taken as 10K.
5.3.3 Initial fixed fire point absolute threshold test
If the initial fire point is in the daytime, the formula (6) is satisfied and it can be judged as a tentative fire point. In the nighttime situation, satisfied
Equation (7) can be identified as a thermal anomaly point. Other initial fire points that do not meet the conditions need to enter the background threshold test process.
Determine it in one step.
4 t5T Th > (6)
4 t6T Th > (7)
In the formula.
t5Th -- discriminating threshold, the reference value can be taken as 360K;
t6Th -- discriminates the threshold, and the reference value can be 320K.
5.3.4 Initial fixed fire point background threshold test
Centering on the initial fire point, create a background window of size N×N, classify and count the background pixels in the window.
5 its brightness temperature characteristics. Background pixels include both background fire point pixels and valid background pixels.
Among them, the background fire point pixels meet the following conditions during daytime and nighttime respectively.
昼. 4 t7 t2( ) ( )T Th T Th∆ > ∧ ∆ > (8)
Night. 4 t8 t3( ) ( )T Th T Th∆ > ∧ ∆ > (9)
In the formula.
t7Th -- discriminating threshold, the reference value can be 325K;
t2Th∆ - discriminating threshold, the reference value can be taken as 20K;
t8Th -- discriminating threshold, the reference value can be taken as 310K;
t3Th∆ -- The threshold value can be taken as 10K.
The cloudless land background pixels outside the background fire point pixel in the window are valid background pixels. If the number of valid background pixels
Satisfy 25% of the total number of cells in the window, and more than 8, then the background pixel temperature characteristics of the statistics window, the window start size
It is 3×3. If the effective background pixels are not enough, increase the window (eg. 5×5, 7×721×21) and continue the above
Classify and count until there are enough valid background pixels in the window. If N=21 is still not enough effective background
For the pixel, the initial fire point is identified as a non-fire point.
If the above background fire point pixel and effective background pixel temperature characteristics are successfully extracted, then the temperature of the initial fire point is
The characteristics (4T, 11T, and T∆) are used to determine multiple threshold conditions as follows.
E1 TT T Th δ∆∆ > ∆ × (10)
t4T T Th∆∆ > ∆ (11)
4 4 e2 4T T Th δ > × (12)
11 11 11 t9TT Thδ > − (13)
4 t10Thδ ′ > (14)
In the formula.
T∆ -- the brightness of the effective background pixels in the mid-infrared (near 4 μm) and thermal infrared (near 11 μm)
The mean value of the difference, K;
4T
- the mean value of the luminance temperature of the effective background pixel in the mid-infrared band (around 4 μm), K;
11T - the brightness temperature of the pixel in the thermal infrared band (near 11μm), K;
11T -- the average of the luminance temperature of the effective background pixel in the thermal infrared band (near 11 μm), K;
4δ - the average absolute deviation of the luminance temperature of the effective background pixel in the mid-infrared band (around 4 μm);
11δ - the average absolute deviation of the luminance temperature of the effective background pixel in the thermal infrared band (near 11 μm);
δ ∆ -- Brightness of effective background pixels in the mid-infrared (near 4 μm) and thermal infrared (near 11 μm)
The average absolute deviation of the temperature difference;
4δ ′ -- the average absolute deviation of the brightness temperature of the background fire point pixel in the mid-infrared band (around 4 μm);
e1Th - discriminate the threshold, the reference value is taken as 3.5;
t4Th∆ - discriminating threshold, the reference value is taken as 6K;
e2Th -- discriminates the threshold, and takes a reference value of 3;
t 9Th -- discriminating threshold, the reference value is taken as 4K;
t10Th -- The threshold is determined, and the reference value is taken as 5K.
If the initial set fire point satisfies all the conditions in equations (10)~(12), it also satisfies formula (13) or (14).
In one of the six conditions, the initial fixed fire point is identified as a tentative fire point; all conditions in equations (10) to (12) are met at night.
At the time, the initial fire point is identified as a hot abnormal point, otherwise it is identified as a non-fire point.
The daytime is identified as a tentative fire point for the false fire point removal to obtain a thermal anomaly point.
5.3.5 False fire point removal
5.3.5.1 False fire point removal caused by solar flare
Calculate the flare angle of the fire point pixel.
Cos cos cos sin sin cos
Gvsvs
θ θ θ θ θ φ= − (15)
In the formula.
-- the flaming angle of the fire point pixel, °;
-- Observing the zenith angle, °;
--Sun zenith angle, °;
φ -- relative azimuth, °.
The threshold conditions for determining solar flare are.
1g aThθ < (16)
2 ρ5 ρ6( ) ( ) ( )gar nTh Th Th θ ρ ρ ∧ > ∧ > (17)
3( ) 0g a wTh Nθ < ∧ >( ) (18)
In the formula.
1aTh -- discriminate the threshold, the reference value is 2 °;
2aTh -- discriminate the threshold, the reference value is 8 °;
3aTh -- discriminant threshold, the reference value is taken as 1 2 ° ;
ρ5Th
- discriminate the threshold, the reference value is taken as 0.1;
ρ6Th
- discriminate the threshold, the reference value is taken as 0.2;
N -- The number of water body pixels in the statistics window.
If the tentative fire point pixel satisfies one of the conditions in equations (16) to (18), it is determined to be false due to solar flare.
Fire point.
5.3.5.2 False fire point removal at the edge of the desert
Set threshold conditions for identifying false fire points for the radiation characteristics of the desert edge.
E3
N1
Ρ7
4 t11
4 t12
4 4 e4 4
Fv
N Th N
N Th
Th
T Th
Th
TT Th
≥⎧
≥⎪
⎪ >⎪
『 < ⎪
⎪ ′ < ⎪
⎪ < ‘ ⎩
(19)
In the formula.
N -- the number of background fire points in the statistics window;
7v
N -- the number of valid background pixels in the statistics window;
4T ′ - the mean value of the brightness temperature of the band near the background fire point pixel 4μm, K;
e3Th - discriminate the threshold, the reference value is taken as 0.1;
n1Th -- discriminating threshold, the reference value is 4;
ρ7Th
- discriminate the threshold, the reference value is taken as 0.15;
t11Th -- discriminate the threshold, the reference value is 345K;
t12Th -- discriminate the threshold, the reference value is taken as 3K;
e4Th -- The threshold is determined. The reference value is 6.
If the tentative cell satisfies all the conditions in equation (19), it is judged to be a false fire point on the edge of the desert.
5.4 Straw burning suspected fire point extraction
Combined with the land classification data, the thermal anomaly located in the farmland is extracted as a suspected fire point for straw burning.
5.5 Estimation of reliability of suspected fire points in straw burning
Statistical analysis of the brightness and temperature characteristics of suspected fire point pixels in straw burning, and estimating the reliability of the fire point. The basis for the evaluation is. fire
The larger the 4T and 4 11( - )TT of the point pixel, the higher the fire point reliability; the difference between the fire point pixels 4T and 4 11( - )TT and the surrounding normal temperature background is larger.
The higher the fire point reliability; in the case of daytime, the fewer clouds or water bodies in the vicinity of the fire point pixel, the higher the fire point reliability. specific
Proceed as follows.
a) Calculate the difference between the fire point and the effective background pixel temperature characteristics. Statistical parameters 4Z and TZ ∆ .
TT
= (20)
TT
∆ − ∆
= (21)
b) Calculate the single-item reliability index 1 2 5, ... CCC based on the reliability discriminating ramp function ( , , ) S x α β .
1 4 t13 t14( , , )CST Th Th= (22)
2 4 e5 e7( , , )CSZ Th Th= (23)
3 e6 e7( , , )TC SZ Th Th∆= (24)
4 e 71 ( , 0, )acC SN Th= − (25)
5 e 71 ( , 0, ) awC SN Th= − (26)
The ramp function is defined as.
0;
( , , ) ( )/ ( );
1;
S xxx
β β α β α α β
≤⎧
= − − < < ⎨
⎪ ≥⎩
(27)
c) The overall reliability index is defined as the geometric mean of the single-factor reliability index as follows.
1 2 5...C CC C= (time) or 3 1 2 3C CC C= (night) (28)
In the formula.
8t13Th -- discriminating threshold, the reference value is taken 300K in the daytime and 305K in the night;
t14Th -- discriminate the threshold value, take 340K between the reference values and 320K at night;
e5Th -- discriminate the threshold, the reference value is 2.5;
e 6Th -- discriminating threshold, the reference value is 3;
e 7Th -- discriminating threshold, the reference value is taken as 6;
Aw
-- the number of water body pixels in the eight nearest pixels of the target fire point pixel;
caN
-- The number of cloud pixels in the nearest 8 pixels of the target fire point pixel.
Based on the C value (0 ≤ C ≤ 100%), the fire points are divided into low, medium and high reliability, as shown in Table 1.
Table 1 Fire point reliability classification method
C value range reliability level
0≤C< 30% low
30% ≤ C < 80%
80% ≤ C ≤ 100% high
6 Monitoring product production
Monitoring products include daily, monthly, quarterly, annual reports, etc. The report should include text, thematic maps and statistical forms. Text
The word information is information describing the results of satellite remote sensing straw burning, including time, range, satellite and sensor, monitoring fire
The distribution, number, etc. of points. The special map of straw burning includes map name, legend, scale, and suspected fire point distribution information of straw burning
And administrative area geographic information, traffic roads and airport information. The statistical table includes the longitude, latitude, and fire point of the fire.
Information such as the name and statistics of the political district.
The statistics of the number of fire points in the daily straw burning monitoring products are based on the statistics of each pixel of the single-day product of the day.
If two or more sensors monitor the same location fire point in a day, do not accumulate counts for a specific administrative area.
The statistics of the number of internal fire points are the sum of the values of the fire points occurring in the administrative area on that day. Monthly, seasonal and annual straw burning monitoring production
The statistics of the number of fire points in each administrative area of the product are the values of the fire spot pixels in the products of the current month, the current season and the current day.
Sum.
7 quality control
7.1 Satellite data quality
Before data preprocessing for suspected fire point information in straw burning, it is necessary to ensure the quality of remote sensing raw data and avoid
Data with equal quality issues participate in subsequent processing, resulting in misidentification of the results.
7.2 Geometric positioning accuracy
Before using the remote sensing data of different satellites and sensors for fire point monitoring, the geometric position registration and registration should be guaranteed.
Degree is within a pixel.
9 Appendix A
(informative appendix)
Common data sources for satellite straw monitoring
Table A.1 TERRA (AQUA)/MODIS thermal anomaly monitoring spectrum and its main use
Channel number range (μm) Main use
1 0.62 ~ 0.67 Solar flare, water edge removal, cloud detection
2 0.84 ~ 0.88 high reflection surface, solar flare, water body edge removal, cloud detection
21 3.93 ~ 3.99 (high response range) fire point detection and fire point characteristics inversion
22 3.93 ~ 3.99 (low response range) fire point detection and fire point characteristics inversion
31 10.75 ~ 11.25 Fire detection, cloud detection
32 11.75 ~ 12.25 Cloud Detection
Table A.2 NOAA/AVHRR thermal anomaly monitoring spectrum and its main use
Channel number range (μm) Main use
1 0.55 ~ 0.68 cloud and surface observations
2 0.725 ~ 1.00 Land and Water Boundary Identification
3A 1.58 ~ 1.64 Ice and Snow Recognition
3B 3.55 ~ 3.93 night cloud map, sea surface temperature
4 10.30 ~ 11.30 night cloud map, sea surface temperature
5 11.50 ~ 12.50 sea surface temperature
Table A.3 FY-1C/1D MVISR and FY-3A/3B VIRR Thermal Anomaly Monitoring Spectrum Segments and Main Uses
Channel number range (μm) Main use
1 0.58 ~ 0.68 removes highly reflective clouds and surface
2 0.84 ~ 0.89 removes highly reflective clouds and surface
3 3.55 ~ 3.95 Fire Point Detection
4 10.3 ~ 11.3 Fire Point Detection
5 11.5 ~ 12.5 Removal of thin clouds
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