CN110398738A - A method of utilizing remote sensing images inverting ocean surface wind speed - Google Patents
A method of utilizing remote sensing images inverting ocean surface wind speed Download PDFInfo
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- G—PHYSICS
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- 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
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- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
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- G01P5/08—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft by measuring variation of an electric variable directly affected by the flow, e.g. by using dynamo-electric effect
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- 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
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Abstract
The present invention provides a kind of new methods using remote sensing images measurement ocean surface wind speed.The present invention is to carry out geometric correction and radiant correction by obtaining the remote sensing images containing wind striped；Normalization back scattering image is converted into gray level image；Calculate gray level co-occurrence matrixes of the gray level image on specific direction (wind direction)；According to the characteristic value (energy) of the gray level co-occurrence matrixes of image, and extract its stationary value；According to the relationship of the stationary value of energy and wind speed, Wind Speed Inversion.The present invention is directed to a wide range of ocean surface wind speed monitoring requirements, utilize the ability of remote sensing technology method covered on a large scale, based on the bright dark fringe feature presented included in remote sensing images by modulation of the Ocean Wind-field to sea surface roughness, power and its spatial distribution including bright dark fringe, quantitative Treatment is carried out using data of the gray level co-occurrence matrixes to remote sensing images, for the monitoring of ocean surface wind speed, it is an innovation of the Remote Sensing for ocean surface wind speed observation, there is great practical value.
Description
Technical field
The invention belongs to remote sensing technique application and field of image processing, it is specifically a kind of can be using contained in remote sensing images
Grayscale information, the method for inverting ocean surface wind speed as would be expected.
Background technique
Sea surface wind speed retrieval is the important link for exploring and studying ocean and ocean-atmosphere interaction, is to develop and utilize ocean
Necessary basis, and the urgent need of oceanographic research now has marine forecasting and preventing and reducing natural disasters highly important
Meaning.Using before spaceborne Instrument observation wind speed, measure wind speed mainly by observation station and ship, although measurement accuracy compared with
Height, but the range observed is extremely limited, it is difficult to meet a wide range of needs observed and apply.In satellite borne sensor, (altimeter dissipates
Penetrate meter and radiometer) occur after, large-range measuring ocean surface wind speed is just achieved.Wherein, satellite altimeter is only capable of measuring star
The wind speed of lower point；Microwave scatterometer has realized the operational use of a wide range of Ocean Wind-field observation, but its spatial resolution is usual
In 25-50km；Microwave radiometer has also realized the businessization detection of Ocean Wind-field, but to calibration precision and polarized measurement request
It is higher.Meanwhile scatterometer and radiometer are unable to measure the wind field within tens kilometers of offshore and near island, are not able to satisfy measurement
The needs of the sea high-resolution wind field of certain specific regions.Satellite-borne synthetic aperture radar has round-the-clock, round-the-clock, high-resolution
The characteristics of rate ocean remote sensing is observed, can provide effective support for ocean surface wind retrieving.Using SAR inverting Ocean Wind-field, especially
It is suitable for the observations of littoral zone and island area, can overcome the shortcomings of microwave scatterometer and radiometer, and it is big in turn avoid investment
It measures manpower and material resources and carries out field observation.The existing method using SAR image inverting Ocean Wind-field is mainly by from image sheet
The wind direction that body or outside data obtain, carrys out calculation of wind speed in conjunction with Geophysical Model function.In terms of the open source information retrieved,
There has been no the methods that the realization completely the same with the present invention measures ocean surface wind speed using SAR image itself.
The present invention utilizes SAR image for the Ocean Wind-field observation requirements of the special areas such as exposed waters and littoral zone
A wide range of covering and high-resolution ability, based on being on the image because of the modulation of Ocean Wind-field included in SAR image
Existing bright dark fringe feature is carried out quantitative Treatment to the gradation data of SAR image, and is analyzed using gray level co-occurrence matrixes,
The information for obtaining Ocean Wind-field, for measuring ocean surface wind speed.
Summary of the invention
The object of the present invention is to provide a kind of new methods using SAR image measurement ocean surface wind speed.
The invention is realized by the following technical scheme:
A method of utilize remote sensing images measure ocean surface wind speed, it is characterised in that itself the following steps are included:
(1) remote sensing images containing wind striped are obtained, geometric correction and radiant correction are carried out；
(2) normalization back scattering image is converted into gray level image；
(3) gray level co-occurrence matrixes of the gray level image on specific direction (wind direction) are calculated；
(4) according to the characteristic value (energy) of the gray level co-occurrence matrixes of image, and its stationary value is extracted；
(5) according to the relationship of the stationary value of energy and wind speed, Wind Speed Inversion.
A kind of method using remote sensing images inverting ocean surface wind speed, it is characterised in that will normalization in step (2)
Back scattering image is changed into gray level image, so that calculating its gray level co-occurrence matrixes becomes feasible.Remote sensing images pixel value and ash
Angle value transformational relation is as follows:
Wherein I (i, j) is remote sensing images pixel value, and gray (i, j) is transformed gray value of image, and range is 0~15
Between, ImaxFor the gray scale maximum value in image, IminFor the minimum gray value in image.
A kind of method using remote sensing images inverting ocean surface wind speed, it is characterised in that gray scale is calculated in step (3)
The gray level co-occurrence matrixes of image (wind direction) in particular directions utilize the substantially uniform relationship in wind striped direction and wind direction, reduce
Unnecessary calculating.
A kind of method using remote sensing images inverting ocean surface wind speed, it is characterised in that according to step in step (4)
(3) gray level co-occurrence matrixes of gained image, find out characteristic value, enable the characteristics of image quantitative expression of wind striped.This place
With the calculation formula of characteristic value are as follows:
Wherein p (i, j) is the element of gray level co-occurrence matrixes, and i, j are positive integer, and T is energy.Then the stabilization of energy is extracted
Value extracts the method for stationary value herein are as follows: its standard deviation of every 8 data point calculations and mean value, when the standard deviation of this 8 points is less than
Its mean value 1% when, using the mean value of 8 points at this time as the stationary value of energy.
A kind of method using remote sensing images inverting ocean surface wind speed, it is characterised in that in step (5) characteristic value with
The relationship of wind speed can be finally inversed by ocean surface wind speed by characteristic value by this relationship.Characteristic value and ocean surface wind speed relationship are as follows:
W=-76*Ts+14
Further, radiant correction formula is as follows in step (1):
I=10 × lg [(X+A1)/A2]+10×lg[sin(θ)]
Wherein, I is normalization backscattering coefficient, and X is intensity, A1For offset, A2For gain, θ is incidence angle.
Middle TsFor the stationary value of the energy of extraction, W is wind speed (unit m/s).
Specifically, Ocean Wind-field can cause the variation of sea surface roughness, and be imaged on remote sensing images, be rendered as light and shade
Between or distribution wind striped texture information.Its principle is: for Ocean Wind-field by effect of the wind-stress to sea, modulation sea is coarse
Degree.Sea surface roughness is bigger, and the back scattering that sensor receives is bigger；Conversely, the back scattering that sensor receives is smaller,
Therefore light and dark striped can be generated on the image.In remote sensing images, the information such as position, intensity of bright dark fringe mainly depend on
In the size and its distribution of Ocean Wind-field, there is certain relationship between the two.By this relationship, it can use remote sensing images
The texture information of middle wind striped directly extracts and obtains Ocean Wind-field information, carries out wind speed retrieval.
The present invention is exactly the wind striped characteristic information presented in remote sensing images using Ocean Wind-field, including the strong of wind striped
Weak and its spatial distribution characteristic converts gray level image for the normalization back scattering image of remote sensing, and utilizes gray scale symbiosis square
Battle array and its characteristic value by the relationship of characteristic value and ocean surface wind speed obtain the wind speed information on sea.
The beneficial effects of the present invention are:
Carrying out a wide range of monitoring to Ocean Wind-field is the needs for studying marine environment, ocean-atmosphere interaction, is exploitation and benefit
With the basis of ocean.The range of traditional means (ship, buoy etc.) observation is extremely limited, it is difficult to meet a wide range of observation and application
Needs, and manpower consumption and economic cost are higher.Remote sensing monitoring is a kind of very effective Ocean Wind-field monitoring means.This
Invention utilizes a wide range of covering energy of remote sensing technology method for the demand of the monitoring of a wide range of Ocean Wind-field and wind resource assessment
Power, based on the bright dark fringe feature presented included in remote sensing images by modulation of the Ocean Wind-field to sea surface roughness, packet
The power and its spatial distribution characteristic for including bright dark fringe convert gray level image for remote sensing images, and utilize gray level co-occurrence matrixes
And its characteristic value obtains the wind speed information on sea by the relationship of characteristic value and ocean surface wind speed, supervises for a wide range of Ocean Wind-field
It surveys and wind resource is assessed, be an innovation of the Remote Sensing for Ocean Wind-field observation, there is great practical value.
Detailed description of the invention
Fig. 1 is the Technology Roadmap using remote sensing images measurement ocean surface wind speed；
Fig. 2 is remote sensing images typically containing wind striped；
Fig. 3 is the gray level image that typical wind striped remote sensing images are converted to；
Fig. 4 is the energy that typical wind striped remote sensing images are drawn up in wind；
Fig. 5 is the scatter plot and fit correlation of the energy that wind is drawn up and wind speed；
Fig. 6 is the wind speed that is calculated of fit correlation figure compared with analyzing wind speed again.
Specific embodiment
With reference to the accompanying drawing, implementation of the invention is illustrated:
Embodiment 1
It is according to the present invention using remote sensing images measurement ocean surface wind speed method tested, technology path as shown in Figure 1,
Specifically comprise the following steps:
(1) remote sensing images containing wind striped information are obtained, radiant correction is carried out to image, strength information is converted to and returns
One changes backscattering coefficient, then carries out geometric correction, is allowed to corresponding with actual geographic position: choosing has high-resolution
Remote sensing images, the clarity and integrality of check image wind striped.Radiant correction is carried out to image, the intensity value of image is turned
It is changed to normalization backscattering coefficient.Then, geometric correction is carried out to image, image is transformed into opposite with actual geographic position
It answers.
The radiant correction formula of the satellite data of different-format slightly has difference, and radiant correction formula provided herein calculates
Formula is as follows:
I=10 × lg [(X+A1)/A2]+10×lg[sin(θ)]
Wherein, I is normalization backscattering coefficient, and X is intensity, A1For offset, A2For gain, θ is incidence angle.
Typical geometric correction method is multinomial correction method, regards the structural strain's of remote sensing images as translation, scaling, rotation
Turn, the basic deformation comprehensive function of partial twist and more high order is as a result, then coordinate relationship can between the image respective point of correction front and back
To be expressed with a multinomial, due to the uncertainties such as the parameter of satellite, when using different satellite datas, geometric correction
Formula is also not quite similar.
(2) image for normalizing backscattering coefficient is converted into gray level image:
Due to needing to calculate the gray level co-occurrence matrixes of image, so needing to convert the image for normalizing backscattering coefficient
For gray level image.In view of the computation complexity of gray level co-occurrence matrixes, tonal range takes 0-15, totally 16 rank.It will normalize backward
The calculation formula that scattering coefficient is converted to gray scale is as follows:
Wherein I (i, j) is the pixel value for normalizing backscattering coefficient image, and gray (i, j) is transformed image ash
Angle value, range is between 0~15, ImaxFor the gray scale maximum value in image, IminFor the minimum gray value in image.
(3) gray level co-occurrence matrixes of image are calculated:
According to the definition of gray level co-occurrence matrixes, the gray level co-occurrence matrixes of image are calculated (with reference to based on matrix element interpolation
The calculation method proposed in the calculation method and application of any gray level co-occurrence matrixes), it is assumed that the step-length of GLCM to be asked is d, angle
For φ, i.e. pixel is (dcos φ, dsin φ) to relative position, then seeking its gray level co-occurrence matrixes G, the specific method is as follows:
Finding out relative position is integer and 4 GLCM closest to target position to be asked, and is denoted as C respectively11、C12、C21、C22,
The corresponding relative position met is respectively
(floor (dcos φ), floor (dsin φ)),
(ceiling (dcos φ), floor (dsin φ)),
(floor (dcos Φ), ceiling (dsin Φ)),
(ceiling (dcos Φ), ceiling (dsin Φ)).Wherein, floor, which is represented, is rounded downwards, ceiling
Representative rounds up, and
G11(m,n；D, Φ)=G11(m,n；floor(d·cosΦ),floor(d·sinΦ))
G12、G21、G22It is similar to obtain.Finding out relative position using bilinear interpolation is
The GLCM of (dcos Φ, dsin Φ), formula are as follows:
C (m, n)=(1-a) (1-b) C11(m, n)+a (1-b) C12(m, n)+(1-a) bC21(m, n)+abC22(m, n)
Wherein G11,G12,G21,G22For the corresponding gray level co-occurrence matrixes in four positions of arest neighbors, a=dcos Φ-
Floor (dcos Φ), b=dsin Φ-floor (dsin Φ).
(4) calculate and extract the characteristic value of gray level co-occurrence matrixes:
According to the formula of Halick, the characteristic value of gray level co-occurrence matrixes under different step-lengths is calculated.Calculation formula is as follows:
Wherein p (i, j) is the element of gray level co-occurrence matrixes, and T is energy.Then the stationary value for extracting energy, is extracted herein
The method of stationary value are as follows: its standard deviation of every 8 data point calculations and mean value, when the standard deviation of this 8 points is less than the 1% of its mean value
When, using the mean value of 8 points at this time as the stationary value of energy.
(5) relationship of the characteristic value based on gray level co-occurrence matrixes and wind speed calculates wind according to the characteristic value found out in (4)
Speed.Calculation formula is as follows:
W=-76*Ts+14
Wherein TsFor the stationary value of the energy of extraction, W is wind speed (unit m/s).
The scatter plot and its fit correlation of energy and wind speed that image containing wind striped is drawn up in wind as shown in figure 5,
Fig. 6 is the comparison diagram that the wind speed that fit correlation is calculated and ECMWF analyze wind speed again.Comparing result is shown, with present invention side
Method calculation of wind speed and ECMWF analyze data consistency with higher again, and correlation is very high, and root-mean-square error is only 1.44m/s,
Show that wind speed retrieval works well.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Made any modifications, equivalent replacements, and improvements etc., is all included in the scope of protection of the present invention within principle.
Claims (4)
1. a kind of method using remote sensing images inverting ocean surface wind speed, which comprises the following steps:
(1) remote sensing images containing wind striped are directed to, radiant correction and geometric correction are carried out；The radiant correction refers to image
Intensity value be converted to normalization backscattering coefficient；The geometric correction, which refers to, utilizes typical multinomial geometric correction side
Method, image is corresponding with ground actual geographic position；
(2) normalization backscattering coefficient image is converted into gray level image；
(3) gray level co-occurrence matrixes of the gray level image in wind direction are calculated；
(4) according to the gray level co-occurrence matrixes of image, characteristic value is calculated；The characteristic value is energy T, and calculation formula is as follows:
Wherein p (i, j) is the element of gray level co-occurrence matrixes, and i, j are positive integer, and T is energy；Then the stationary value of energy is extracted,
The method of stationary value is extracted herein are as follows: its standard deviation of every 8 data point calculations and mean value, when the standard deviation of this 8 points is less than it
Mean value 1% when, using the mean value of 8 points at this time as the stationary value of energy；
(5) according to the relationship of the stationary value of energy and wind speed, Wind Speed Inversion；Specific formula is as follows:
W=-76*Ts+14
Wherein TsFor by the stationary value of the energy extracted, W is wind speed, unit m/s.
2. a kind of method using remote sensing images inverting ocean surface wind speed as described in claim 1, it is characterised in that in step (2)
The feature of grain distribution containing wind striped on the investigation remote sensing images, wind striped refer to that bright dark fringe, which is presented, to be spaced apart；It will normalization
Backscattering coefficient image is converted into gray level image, makes to calculate its gray level co-occurrence matrixes；Normalization processing method are as follows:
(1) by screening, the maximum value (I of all pixels in the image is obtainedmax) and minimum value (Imin)；
(2) the Normalized Grey Level value of any pixel point is calculated, calculation formula is as follows:
Wherein I (i, j) be remote sensing images pixel value, gray (i, j) be transformed gray value of image, range be 0~15 between,
ImaxFor the gray scale maximum value in image, IminFor the minimum gray value in image.
3. a kind of method using remote sensing images inverting ocean surface wind speed as described in claim 1, it is characterised in that in step (3)
When wind striped direction is consistent with wind direction, gray level co-occurrence matrixes of the gray level image in wind direction are calculated.
4. a kind of method using remote sensing images inverting ocean surface wind speed as described in claim 1, it is characterised in that in step (1)
Radiant correction formula is as follows:
I=10 × lg [(X+A1)/A2]+10×lg[sin(θ)]
Wherein, I is normalization backscattering coefficient, and X is intensity, A1For offset, A2For gain, θ is incidence angle.
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| CN111812646A (en) * | 2020-07-01 | 2020-10-23 | 自然资源部第二海洋研究所 | Method and system for inverting sea surface wind speed by utilizing synthetic aperture radar image |
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| CN111812646A (en) * | 2020-07-01 | 2020-10-23 | 自然资源部第二海洋研究所 | Method and system for inverting sea surface wind speed by utilizing synthetic aperture radar image |
| CN111862005A (en) * | 2020-07-01 | 2020-10-30 | 自然资源部第二海洋研究所 | Method and system for accurately positioning tropical cyclone center by using synthetic radar image |
| CN111862005B (en) * | 2020-07-01 | 2023-11-17 | 自然资源部第二海洋研究所 | Method and system for precisely positioning tropical cyclone center by utilizing synthetic radar image |
| CN112801332A (en) * | 2020-11-18 | 2021-05-14 | 国网江苏省电力有限公司江阴市供电分公司 | Short-term wind speed prediction method based on gray level co-occurrence matrix |
| CN112801332B (en) * | 2020-11-18 | 2024-03-26 | 国网江苏省电力有限公司江阴市供电分公司 | Short-term wind speed prediction method based on gray level co-occurrence matrix |
| CN113037310A (en) * | 2021-03-03 | 2021-06-25 | 深圳市富创优越科技有限公司 | Transceiver for boats and ships with discernment early warning function |
| CN114324973A (en) * | 2022-03-17 | 2022-04-12 | 南方海洋科学与工程广东省实验室(广州) | Typhoon wind speed inversion method and device, electronic equipment and storage medium |
| CN115009472A (en) * | 2022-05-06 | 2022-09-06 | 大连环信科技有限公司 | Movable wind energy collection cluster system with wind energy gathering guidance |
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