CN108761447A - A kind of stony desertification judgment method based on Radar backscattering coefficients time series - Google Patents
A kind of stony desertification judgment method based on Radar backscattering coefficients time series Download PDFInfo
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- CN108761447A CN108761447A CN201810497083.8A CN201810497083A CN108761447A CN 108761447 A CN108761447 A CN 108761447A CN 201810497083 A CN201810497083 A CN 201810497083A CN 108761447 A CN108761447 A CN 108761447A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/40—Means for monitoring or calibrating
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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Abstract
The invention discloses a kind of stony desertification judgment methods based on Radar backscattering coefficients time series, multidate radar data selection is carried out to Vector parcel area to be extracted first, then radiation calibration is carried out to radar data, terrain radiant correction and speckle noise filtering, the radar data being disposed is recycled to build the time series structure based on backscattering coefficient, the stony desertification classification of subject area is judged finally by DTW algorithms, this method stony desertification judges precision height, solving the disadvantage that optical remote sensing easily is influenced to cause loss of learning due to speckle noise with Mono temporal radar by cloudy rainy day gas.
Description
Technical field
The invention belongs to Rocky Desertification Control field, especially a kind of stony desert based on Radar backscattering coefficients time series
Change judgment method.
Background technology
Rocky Desertification Region often cloud-prone and raining, and although traditional optical remote sensing images have abundant spectral information, but
It is highly prone to the influence of the multiple factors such as time, weather, this has just manufactured the acquisition of Rocky Desertification Region data sizable tired
It is difficult.Radar image has the round-the-clock imaging characteristics not constrained by weather condition of round-the-clock, image texture abundant information, atural object wheel
Clean up clear, but itself only has unicast segment information, and two methods are unfavorable for whether object area belongs to sentencing for stony desertification type
It is disconnected.So extracting Vector parcel using multidate radar image, many unfavorable factors can be overcome, effectively made up respective
Disadvantage.
Invention content
The technical problem to be solved by the present invention is to：A kind of stony desertification based on Radar backscattering coefficients time series is provided
Judgment method, to solve the influence that prior art traditional optical remote sensing images are highly prone to the multiple factors such as time, weather, radar
Image only has unicast segment information, two methods are unfavorable for the problem of whether object area belongs to the judgement of stony desertification type.
The technical solution adopted by the present invention is：A kind of stony desertification judgement side based on Radar backscattering coefficients time series
Method includes the following steps：
Step 1：The radar data in object 1 year is chosen, at least takes a radar data, and radar data each month
Polarization mode be consistent, to ensure the accuracy of somewhere rocky desertification information extraction result；
Step 2：In order to carry out quantitative expression to the original amplitude information of radar data, to the radar data in step 1
Carry out radiation calibration processing, the radiation calibration formula that uses of processing for：
PdFor backscatter intensity, PtFor transmission power, PnTo adhere to power,Reception antenna about
Elevation angle thetaelAnd azimuth angle thetaazUnder power, GEFor the current gain of system, GpFor the constant of radar processor, R is radar image
Loss, L caused by communication processsFor system loss, LaFor atmospheric loss, A is the scattering area of radar image, σ0For thunder
Up to luminance factor；
Step 3：Select the same resolution digital elevation mould for the radar data region that radiation calibration is handled in step 2
Type data, and terrain radiant correction is carried out to the data, updating formula is：
In formula：σ0For the backscattering coefficient of imaging unit after correction, λ0For the backscattering coefficient of initial imaging unit,
β1It is distance to the angle of gradient, β2For the orientation angle of gradient, δ is image incidence angle, and θ is image angle of reflection；
Step 4：Smudges noise is carried out to the radar data after being corrected in step 3 using exquisite Lee Operator Methods
Be filtered；
Step 5：Treated that radar data is divided into m rows × n according to identical Pixel size by filtered in step 4
The data that row pixel is constituted, then the value of m × n is the number of radar data in step 1, then synthesizes a width sequentially in time
Image so that the pixel value in different phase images corresponds, and the X-axis in image is longitude, and Y-axis is latitude, and Z axis is the time
Axis, then the backscattering coefficient of each pixel then constitutes the time series of backscattering coefficient, radar data back scattering
Coefficient time series expresses formula：
T={ [(x1,y1),Z1],[(x2,y2),Z2],…[(xi,yi),Zi]…,[(xm×n,ym×n),Zm×n]}
In formula：(xi, yi) be i-th of pixel latitude coordinates value, ZiIt is the back scattering system built based on i-th of pixel
Number time series；
Step 6：Rocky desertification information extraction is carried out to the time series built in step 5 using DTW algorithms, obtains DTW
Value, is denoted as D (i, j).
Step 7：With the typical stony desertification edges of regions position of radar data location in visual interpretation method selecting step five
The mixed pixel set calculates mixed pixel being averaged in backscattering coefficient value corresponding with each timing node of radar data
Value, thus constructs the time-serial position of a mixed pixel, finally calculates mixed pixel time series and stony desertification picture
The DTW values of first standard time series, the threshold value judged using the value as radar data region pixel type, are denoted as D1(i,
J), if D (i, j) < D1(i, j), then the pixel belongs to stony desertification type, if D (i, j) >=D1(i, j), then the pixel be not belonging to stone
Desertization type.
In step 4, the algorithm principle of exquisite Lee Operator Methods is：If result of calculation shows radar data pixel value size
It is more consistent, then this area belongs to homogenous region, speckle noise can be carried out using the low-pass filtering method in ENVI at this time
Filtering is carried out if result of calculation shows that radar data pixel value difference in size is larger using the high-pass filtering method in ENVI
Speckle noise filters, general it is considered that if the variance of pixel value is less than 5 it may be considered that difference is smaller；The variance of pixel value
More than or equal to 5 it may be considered that differing greatly.
In step 5, identical Pixel size is 100-200.
In step 6, DTW algorithms refer to dynamic time warping, dynamic time adjustment algorithm, algorithm extraction
The step of Vector parcel, is as follows：First, the backscattering coefficient time series for extracting typical stony desertification pixel builds stony desertification
Pixel standard time series then calculate the time series of pixel and stony desertification atural object standard time in radar data region
DTW distances between sequence, algorithmic formula are：
D (i, j)=min { D (i-1, j-1), D (i-1, j), D (i, j-1), D (i-1, j) },
In formula：I=2 ..., m；J=2,3 ..., n；D (i, j) is the time-serial position of radar data region pixel
With the minimum accumulated value of stony desertification pixel standard time series distance, as DTW values.
The advantages of the present invention over the prior art are that：
1, this method carries out radar data the filter of radiation calibration processing, terrain radiant correction processing and smudges noise
Wave processing, overcomes Mono temporal radar data due to being caused material time nodal information missing to be lacked by speckle noise image
It falls into；
2, compared with optical remote sensing extracts Vector parcel, this method chooses radar data and overcomes light as initial data
It is highly prone to the defect of the multiple factors such as time, weather influence when learning remotely-sensed data extraction Vector parcel, improves stony desertification
The precision that information judges.
Description of the drawings
The stony desertification type judging result figure of Fig. 1 embodiments 1.
Specific implementation mode
It elaborates below in conjunction with the accompanying drawings to the embodiment of the method for the present invention：
Embodiment 1
A kind of stony desertification judgment method based on Radar backscattering coefficients time series, includes the following steps：
Step 1：The radar data in object 1 year is chosen, at least takes a radar data, and radar data each month
Polarization mode be consistent, to ensure the accuracy of somewhere rocky desertification information extraction result；
It is 104 ° 2 ' 00 " to 104 ° of 49 ' 26 〞 E, 26 ° of 27 ' 58 〞 to select Guizhou Province Bijie City seven-star to close longitude and latitude span in area
It is used as scheme of the invention enforcement place to the area (hereinafter referred to as subject area) of 26 ° of 50 ' 08 〞 N.Radar data selects C-band SAR
The acquisition time of radar data, data is respectively on January 9th, 2016,5 days 2 months, March 3, April 16, May 20, June 21
Day, July 17, August 19 days, September 21 days, October 23, November 18 and December 19, data polarization mode is VV.
Step 2：In order to carry out quantitative expression to the original amplitude information of radar data, to the radar data in step 1
Carry out radiation calibration processing, the radiation calibration formula that uses of processing for：
PdFor backscatter intensity, PtFor transmission power, PnTo adhere to power,Reception antenna about
Elevation angle thetaelAnd azimuth angle thetaazUnder power, GEFor the current gain of system, GpFor the constant of radar processor, R is radar image
Loss, L caused by communication processsFor system loss, LaFor atmospheric loss, A is the scattering area of radar image, σ0For thunder
Up to luminance factor；
ENVI softwares are opened, the radar data of 12 width subject areas in step 1 is loaded into, select RadioMetric
Apply Gain and Offset tools in Correction, in the Gainand Offset Values dialog boxes of pop-up
Input radiation scaling parameter, to obtain the backscattering coefficient value of 12 width radar datas.
Step 3：Select the same resolution digital elevation mould for the radar data region that radiation calibration is handled in step 2
Type data, and terrain radiant correction is carried out to the data, updating formula is：
In formula：σ0For the backscattering coefficient of imaging unit after correction, λ0For the backscattering coefficient of initial imaging unit,
β1It is distance to the angle of gradient, β2For the orientation angle of gradient, δ is image incidence angle, and θ is image angle of reflection；
The Aster digital elevation models of subject area are loaded into ENVI softwares as calibration template.In ENVI softwares
Empirical Line Compute Factors and Correct tools in select tools case, in the dialog box of pop-up
Calibration template file is selected, correction parameter is then inputted and completes terrain radiant correction.
Step 4：Smudges noise is carried out to the radar data after being corrected in step 3 using exquisite Lee Operator Methods
Be filtered；
Exquisiteness Lee operators code is run in Matlab softwares, and data speckle noise is carried out to subject area radar data
It is filtered.The variance of result of calculation pixel value is less than 5, and display subject area radar data pixel value size is more consistent, this
When can utilize the low-pass filtering method in ENVI softwares carry out speckle noise filtering.By using subject area radar data
" SMOOTH " function in IDL can complete low-pass filtering treatment.
Step 5：Treated that radar data is divided into m rows × n according to identical Pixel size by filtered in step 4
The data that row pixel is constituted, then the value of m × n is the number of radar data in step 1, then synthesizes a width sequentially in time
Image so that the pixel value in different phase images corresponds, and the X-axis in image is longitude, and Y-axis is latitude, and Z axis is the time
Axis, then the backscattering coefficient of each pixel then constitutes the time series of backscattering coefficient, radar data back scattering
Coefficient time series expresses formula：
T={ [(x1,y1),Z1],[(x2,y2),Z2],…[(xi,yi),Zi]…,[(xm×n,ym×n),Zm×n]}
In formula：(xi, yi) be i-th of pixel latitude coordinates value, ZiIt is the back scattering system built based on i-th of pixel
Number time series；
The Layer Stacking tools in ENVI softwares are opened, each sequential is carried out Layer as a channel
Stacking completes time Series Processing of the structure based on subject area radar data backscattering coefficient.
Step 6：Rocky desertification information extraction is carried out to the time series built in step 5 using DTW algorithms, obtains DTW
Value, is denoted as D (i, j)；
Step 7：With the typical stony desertification edges of regions position of radar data location in visual interpretation method selecting step five
The certain amount pixel set, the present embodiment choose 50, are denoted as mixed pixel, calculate mixed pixel when each with radar data
The average value of the corresponding backscattering coefficient value of intermediate node, thus constructs the time-serial position of a mixed pixel,
Finally calculate the DTW values of mixed pixel time series and stony desertification pixel standard time series, the institute using the value as radar data
The threshold value that pixel type judges in region, is denoted as D1(i, j), if D (i, j) < D1(i, j), then the pixel belong to stony desertification type,
If D (i, j) >=D1(i, j), then the pixel be not belonging to stony desertification type.
The DTW values of computing object region mixed pixel time series and subject area stony desertification pixel standard time series,
It is computed, D1The value of (i, j) is 47.If the time series of pixel and stony desertification pixel standard time series in subject area
DTW values are less than 47, then the pixel belongs to stony desertification type；If the time series of pixel and stony desertification pixel standard time series
DTW values are more than or equal to 47, then the pixel is not belonging to stony desertification type.As a result it shows：Stony desertification area is in subject area
3457.62 hectares, it is 55.31% to account for subject area ratio；Non- stony desertification area is 2793.17 hectares, accounts for subject area ratio
It is 44.69%, as shown in Figure 1.
In step 4, the algorithm principle of exquisite Lee Operator Methods is：If result of calculation shows radar data pixel value size
It is more consistent, then this area belongs to homogenous region, speckle noise can be carried out using the low-pass filtering method in ENVI at this time
Filtering is carried out if result of calculation shows that radar data pixel value difference in size is larger using the high-pass filtering method in ENVI
Speckle noise filters, general it is considered that if the variance of pixel value is less than 5 it may be considered that difference is smaller；The variance of pixel value
More than or equal to 5 it may be considered that differing greatly.
In step 5, identical Pixel size is 100-200, and the present embodiment is taken as 150.
In step 6, DTW algorithms refer to dynamic time warping, dynamic time adjustment algorithm, algorithm extraction
The step of Vector parcel, is as follows：First, the backscattering coefficient time series for extracting typical stony desertification pixel builds stony desertification
Pixel standard time series then calculate the time series of pixel and stony desertification atural object standard time in radar data region
DTW distances between sequence, algorithmic formula are：
D (i, j)=min { D (i-1, j-1), D (i-1, j), D (i, j-1), D (i-1, j) },
In formula：I=2 ..., m；J=2,3 ..., n；D (i, j) is the time-serial position of radar data region pixel
With the minimum accumulated value of stony desertification pixel standard time series distance, as DTW values.
Claims (4)
1. a kind of stony desertification judgment method based on Radar backscattering coefficients time series, which is characterized in that including walking as follows
Suddenly：
Step 1：Radar data in selection object is 1 year regional, at least takes a radar data, and radar data each month
Polarization mode be consistent；
Step 2：Radiation calibration processing carried out to the radar data in step 1, the radiation calibration formula that uses of processing for：
PdFor backscatter intensity, PtFor transmission power, PnTo adhere to power,It is reception antenna about at the elevation angle
θelAnd azimuth angle thetaazUnder power, GEFor the current gain of system, GpFor the constant of radar processor, R is that radar image is passing
Loss, L caused by during broadcastingsFor system loss, LaFor atmospheric loss, A is the scattering area of radar image, σ0It is bright for radar
Spend coefficient；
Step 3：Select the same resolution digital elevation model number for the radar data region that radiation calibration is handled in step 2
According to, and terrain radiant correction is carried out to the data, updating formula is：
In formula：σ0For the backscattering coefficient of imaging unit after correction, λ0For the backscattering coefficient of initial imaging unit, β1For
Distance is to the angle of gradient, β2For the orientation angle of gradient, δ is image incidence angle, and θ is image angle of reflection；
Step 4：The filter of smudges noise is carried out to the radar data after being corrected in step 3 using exquisite Lee Operator Methods
Wave processing；
Step 5：Treated that radar data is divided into m rows × n row pictures according to identical Pixel size by filtered in step 4
Member constitute data, then the value of m × n be equal to step 1 in radar data number, then synthesize a width shadow sequentially in time
Picture so that the pixel value in different phase images corresponds, and the X-axis in image is longitude, and Y-axis is latitude, and Z axis is the time
Axis, then the backscattering coefficient of each pixel constitutes the time series of backscattering coefficient, radar data back scattering system
Number time series expresses formula：
T={ [(x1,y1),Z1],[(x2,y2),Z2],…[(xi,yi),Zi]…,[(xm×n,ym×n),Zm×n] in formula：(xi, yi)
For the latitude coordinates value of i-th of pixel, ZiIt is the backscattering coefficient time series built based on i-th of pixel；
Step 6：Rocky desertification information extraction is carried out to the time series built in step 5 using DTW algorithms, DTW values is obtained, remembers
For D (i, j)；
Step 7：With the typical stony desertification edges of regions position of radar data location in visual interpretation method selecting step five
Pixel, the pixel are known as mixed pixel, calculate mixed pixel in back scattering corresponding with each timing node of radar data
The average value of coefficient value, thus constructs the time-serial position of a mixed pixel, calculate mixed pixel time series and
The DTW values of stony desertification pixel standard time series, the threshold value judged using the value as radar data region pixel type, note
For D1(i, j), if D (i, j) < D1(i, j), then the pixel belongs to stony desertification type, if D (i, j) >=D1(i, j), the then pixel
It is not belonging to stony desertification type.
2. according to a kind of stony desertification judgment method based on Radar backscattering coefficients time series described in claim one,
It is characterized in that：In step 4, the algorithm principle of exquisite Lee Operator Methods is to carry out speckle noise using the filtering method in ENVI
Filtering.
3. according to a kind of stony desertification judgment method based on Radar backscattering coefficients time series described in claim one,
It is characterized in that：In step 5, identical Pixel size is 100-200.
4. according to a kind of stony desertification judgment method based on Radar backscattering coefficients time series described in claim one,
It is characterized in that：In step 6, the step of DTW algorithms refer to dynamic time adjustment algorithm, which extracts Vector parcel, is as follows：
First, the backscattering coefficient time series of extraction stony desertification pixel builds stony desertification pixel standard time series, then calculates
DTW distances in radar data region between the time series of pixel and stony desertification atural object standard time series, algorithm
Formula is：
D (i, j)=min { D (i-1, j-1), D (i-1, j), D (i, j-1), D (i-1, j) },
In formula：I=2 ..., m；J=2,3 ..., n；D (i, j) is the time-serial position and stone of radar data region pixel
The minimum accumulated value of desertization pixel standard time series distance, as DTW values.
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Application publication date: 20181106 |