CN105160681A - Sea level oil spill monitoring method and apparatus - Google Patents
Sea level oil spill monitoring method and apparatus Download PDFInfo
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- CN105160681A CN105160681A CN201510570503.7A CN201510570503A CN105160681A CN 105160681 A CN105160681 A CN 105160681A CN 201510570503 A CN201510570503 A CN 201510570503A CN 105160681 A CN105160681 A CN 105160681A
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Abstract
The invention relates to a sea level oil spill monitoring method and an apparatus, wherein the method comprises the steps of obtaining oil spill source information and oil spill area of an offshore oil depot based on an oil spill area image monitored by radar; obtaining a sea level wind field parameter forecasted by a atmosphere model and a flow field parameter forecasted by a sea model, and simulating the oil spill drift diffusion trend based on the sea level wind field parameter, the flow field parameter oil and the oil spill source information using an oil particle model; judging if the spatial geographic coordinate deviation of the oil spill source information, the oil spill area of the offshore oil depot and the spatial geographic coordinate of the oil spill drift diffusion trend is greater than a preset threshold, and when the spatial geographic coordinate deviation is less than or equal to the preset threshold, the area corresponding to the oil spill source information and the oil spill area is a real oil spill area. SAR remote sensing technology is used to obtain the monitored data of the oil spill state, and the monitored data is used for mutual correction with the prediction result of the oil particle model; the false information in the SAR oil spill monitored result can be removed; the deviation of the simulation result of the oil particle model can be avoided; and the real oil spill area can be obtained.
Description
Technical field
The present invention relates to synthetic-aperture radar and marine numerical simulation technical field, particularly a kind of offshore spilled oil monitoring method and device.
Background technology
From the sixties in 20th century, almost the oil spill accident of oil spillage summation nearly ten thousand tons all can be had all over the world to occur every year, once marine, oil spill accident occur, by marine environment even Global Ecological circulation cause serious impact.Since the nineties, along with the enhancing of people of various countries' environmental consciousness, marine oil overflow accident also more and more receives much concern.In nearly decades, the consequence that great marine oil overflow accident is brought makes people startling, no matter because the oil spill accident that causes of atrocious weather or artificial fault, the destruction that these oil spill accidents cause environment and be all beyond measure to the loss that economy is brought.
As time goes on, the economy of China is developing rapidly, along with necessarily a large amount of energy demands, the thus exploitation of offshore petroleum resources, one of transport and the storage major issue becoming development.But due to petroleum pipeline break, the generation of the Accidental Oil Spill accident such as littoral Leakage of Oil Storage, cause huge destruction to China coastal seas bank marine environment, marine ecology and marine economy.Talien New Port on July 16th, 2010 area belongs to an oil pipeline blast on fire of PetroChina Company Limited., and causing a large amount of crude oil leakages to enter sea, bring huge harm to Marine Environment of Bohai Sea etc., has been marine oil overflow contamination accident largest since there is record in China.On November 25th, 2013, Qingdao Huang Island oil pipeline breaks, and causes serious ecocatas-trophe and great economic loss.According to incompletely statistics; from 1980 to 2007, China there occurs more than 140 oil spill accident, although China accelerates the construction of marine oil overflow emergency reaction system in recent years; but still there are problems, the requirement of national shipping development and environmental protection can't be adapted to completely.In sum; the construction strengthening marine oil overflow emergency reaction system is extremely urgent; the particularly dynamic monitoring of oil spilling and prediction; should as the most important thing of marine oil overflow emergency reaction System Construction; research and develop novel marine oil overflow monitoring technology, significant to the development of marine environmental protection and marine economy.
In prior art, synthetic-aperture radar (English full name: SyntheticApertureRadar, english abbreviation: SAR) be a kind of active satellite microwave detector with higher spatial resolution, its physical oceangraphy research direction being limited by conventional observation that appears as provides abundant data.SAR can round-the-clock continuous acquisition be to the large-area image of ocean surface on its orbit, and high resolving power means the accurate of the monitoring of oil spilling source and oil spill area.
In addition, the research for oil spilling diffusion tendency adopts the mode of numerical model mostly, and wherein " elaioleucite model " is generally used.Elaioleucite method is by a large amount of grains molecular " cloud cluster " simulation of carbon concentration field, the wherein probe material of each particle characterization some.In elaioleucite model, the advection process of particle has Lagrangian character, available Lagrangian method simulation.The turbulent fluctuation diffusion process that shear flow and turbulent flow cause belongs to random motion, the available random method of walking about realizes simulation, also a kind of random flow field is considered as by turbulent flow, the motion of each model particle in field of turbulent flow is then similar to the Brownian movement of fluid molecule, causes whole particle " cloud cluster " diffusion in water body due to the random motion of each particle.This analogy method is actually the combination of Deterministic Methods and randomization method, namely adopts Deterministic Methods simulation advection process, adopts randomization method analog spread process.
But realizing in process of the present invention, inventor finds that prior art at least exists following problem:
Although SAR has the advantage of round-the-clock, round-the-clock and high resolution observations ocean, but can only its oil spilling state of inverting for offshore spilled oil, following oil spilling state can not be forecast, and due to the reason of extraction algorithm CFAR itself, oil spilling result there will be deceptive information, namely doubtful oil spilling point is also classified as true oil spilling; Although elaioleucite model can simulate oil spilling diffusion tendency, the accuracy of starting condition (wind field and flow field) directly governs the accuracy predicted the outcome.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of marine oil spill monitoring technology, can provide optimum monitoring result to offshore spilled oil.
The technical scheme that the present invention solves the problems of the technologies described above is as follows: a kind of offshore spilled oil monitoring method comprises:
According to the oil spilling area image of radar monitoring, obtain oil spilling oil sources information and the oil spill area of marine oil depot;
The flow field parameter that the Ocean Wind-field parameter of acquisition Atmospheric models forecast and ocean model forecast, according to the Driftdiffusion trend of Ocean Wind-field parameter, flow field parameter oil and oil spilling oil sources Information Pull elaioleucite modeling oil spilling;
Judge whether the space and geographical grid deviation of the oil spilling oil sources information of marine oil depot and the Driftdiffusion trend of oil spill area and oil spilling is greater than predetermined threshold value;
When space and geographical grid deviation is less than or equal to predetermined threshold value, determine that oil spilling oil sources information and region corresponding to oil spill area are real oil spilling region.
The invention has the beneficial effects as follows: use microwave radar technology SAR the most advanced now, Real-Time Monitoring is carried out to marine oil spill; The elaioleucite model adopting international mature to use, predicts oil spilling diffusion tendency; Utilize SAR remote sensing technology obtain the Monitoring Data of oil spilling state, mutually correct with predicting the outcome of elaioleucite model, the deceptive information in SAR spilled oil monitoring result can not only be removed, avoid the deviation of elaioleucite model simulation results simultaneously, finally obtain real oil spilling point.
On the basis of technique scheme, the present invention can also do following improvement.
Further, the described oil spilling area image according to radar monitoring, the oil spilling oil sources information and the oil spill area that obtain marine oil depot comprise:
Using the probability density function of Gaussian distribution as described oil spilling area image, and using oil spilling area image described in view picture as reference window, calculate average and the standard deviation of each image pixel elements gray scale in described oil spilling area image, the average of described gray scale and standard deviation are defined as the Gaussian Distribution Parameters of described oil spilling area image;
The probability density function of the arbitrary image pixel elements of described oil spilling area image is determined according to the Gaussian Distribution Parameters of described oil spilling area image, in oil spilling area image described in statistical computation, the average of each image pixel elements brightness of image and standard deviation, be defined as the probability density function parameter of described oil spilling area image by the average of brightness of image and standard deviation;
According to the probability density function parameter of default false-alarm probability and described oil spilling area image, substitute in probability density function, obtain the partition threshold of image, more described oil spilling area image is split according to described partition threshold, obtain oil spilling oil sources information and the oil spill area of marine oil depot.
Further, the flow field parameter that the Ocean Wind-field parameter of described acquisition Atmospheric models forecast and ocean model forecast, the Driftdiffusion trend according to Ocean Wind-field parameter, flow field parameter oil and oil spilling oil sources Information Pull elaioleucite modeling oil spilling comprises:
Utilize elaioleucite model that oil film is carried out particlized subdivision, and each elaioleucite is identified respectively;
The flow field parameter that the Ocean Wind-field parameter of acquisition Atmospheric models forecast and ocean model forecast;
The Ocean Wind-field parameter of the mark of each elaioleucite, Atmospheric models forecast and the flow field parameter forecast of ocean model are followed the tracks of the drift that each elaioleucite occurs under the effect of wind field and ocean current, obtain the Driftdiffusion trend of oil spilling.
Further, describedly judge whether the space and geographical grid deviation of the oil spilling oil sources information of marine oil depot and the Driftdiffusion trend of oil spill area and oil spilling is greater than predetermined threshold value and comprises:
Obtain geographic coordinate and the oil spill area of oil spilling point corresponding to the oil spilling oil sources information of marine oil depot;
Obtain the geographic coordinate that the Driftdiffusion trend of oil spilling is corresponding;
On described oil spilling area image, calculate the distance between the geographic coordinate of the oil spilling point geographic coordinate corresponding with the Driftdiffusion trend of oil spilling;
Distance between the geographic coordinate that the geographic coordinate of oil spilling point is corresponding with the Driftdiffusion trend of oil spilling is less than predetermined threshold value, determines that the geographic coordinate of oil spilling point is real oil spilling point.
Further, a kind of offshore spilled oil monitoring device, comprising:
Information acquisition unit, for the oil spilling area image according to radar monitoring, obtains oil spilling oil sources information and the oil spill area of marine oil depot;
Trend analogue unit, the flow field parameter that Ocean Wind-field parameter and ocean model for obtaining Atmospheric models forecast are forecast, according to the Driftdiffusion trend of Ocean Wind-field parameter, flow field parameter oil and oil spilling oil sources Information Pull elaioleucite modeling oil spilling;
Threshold decision unit, whether the space and geographical grid deviation for the Driftdiffusion trend of the oil spilling oil sources information and oil spill area and oil spilling that judge marine oil depot is greater than predetermined threshold value;
Area determination unit, for when space and geographical grid deviation is less than or equal to predetermined threshold value, determines that oil spilling oil sources information and region corresponding to oil spill area are real oil spilling region.
Further, described information acquisition unit comprises:
Gray count module, for using the probability density function of Gaussian distribution as described oil spilling area image, and using oil spilling area image described in view picture as reference window, calculate average and the standard deviation of each image pixel elements gray scale in described oil spilling area image, the average of described gray scale and standard deviation are defined as the Gaussian Distribution Parameters of described oil spilling area image;
Brightness calculation module, for determining the probability density function of the arbitrary image pixel elements of described oil spilling area image according to the Gaussian Distribution Parameters of described oil spilling area image, in oil spilling area image described in statistical computation, the average of each image pixel elements brightness of image and standard deviation, be defined as the probability density function parameter of described oil spilling area image by the average of brightness of image and standard deviation;
Threshold segmentation module, for the probability density function parameter by default false-alarm probability and described oil spilling area image, substitute in probability density function, obtain the partition threshold of image, again described oil spilling area image is split according to described partition threshold, obtain oil spilling oil sources information and the oil spill area of marine oil depot.
Further, described trend analogue unit comprises:
Mark subdivision module, for utilizing elaioleucite model that oil film is carried out particlized subdivision, and identifies respectively to each elaioleucite;
Parameter acquisition module, the flow field parameter that Ocean Wind-field parameter and ocean model for obtaining Atmospheric models forecast are forecast;
Drift tracking module, follows the tracks of for the Ocean Wind-field parameter of the mark according to each elaioleucite, Atmospheric models forecast and the flow field parameter forecast of ocean model the drift that each elaioleucite occurs under the effect of wind field and ocean current, obtains the Driftdiffusion trend of oil spilling.
Further, described threshold decision unit comprises:
First acquisition module, the geographic coordinate of the oil spilling point that the oil spilling oil sources information for obtaining marine oil depot is corresponding and oil spill area;
Second acquisition module, the geographic coordinate that the Driftdiffusion trend for obtaining oil spilling is corresponding;
Distance calculation module, at described oil spilling area image, calculates the distance between the geographic coordinate of the oil spilling point geographic coordinate corresponding with the Driftdiffusion trend of oil spilling;
Oil spilling point determination module, is less than predetermined threshold value for the distance between the geographic coordinate that the geographic coordinate when oil spilling point is corresponding with the Driftdiffusion trend of oil spilling, determines that the geographic coordinate of oil spilling point is real oil spilling point.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of offshore spilled oil monitoring method of the present invention;
Fig. 2 is the process flow diagram of step S101 in Fig. 1 of the present invention;
Fig. 3 is the process flow diagram of step S102 in Fig. 1 of the present invention;
Fig. 4 is the process flow diagram of step S103 in Fig. 1 of the present invention;
Fig. 5 is the structural drawing of offshore spilled oil monitoring device of the present invention;
Fig. 6 is the structural drawing of information acquisition unit 501 in Fig. 5 of the present invention;
Fig. 7 is the structural drawing of trend analogue unit 502 in Fig. 5 of the present invention;
Fig. 8 is the structural drawing of threshold decision unit 503 in Fig. 5 of the present invention.
Embodiment
Be described principle of the present invention and feature below in conjunction with accompanying drawing, example, only for explaining the present invention, is not intended to limit scope of the present invention.
Fig. 1 is the process flow diagram of a kind of offshore spilled oil monitoring method of the present invention, and the present invention to help each other joint development based on the complementation of both synthetic-aperture radar and elaioleucite tracer technique, and see Fig. 1, the method comprises:
Step S101: according to the oil spilling area image of radar monitoring, obtains oil spilling oil sources information and the oil spill area of marine oil depot.
In this step, utilize satellite-borne synthetic aperture radar to obtain area image, use CFAR method to set up threshold values, detect each pixel cell of image fast, determine oil spill area.
Particularly, see Fig. 2, step S101 comprises the following steps.
Step S1011: using the probability density function of Gaussian distribution as described oil spilling area image, and using oil spilling area image described in view picture as reference window, calculate average and the standard deviation of each image pixel elements gray scale in described oil spilling area image, the average of described gray scale and standard deviation are defined as the Gaussian Distribution Parameters of described oil spilling area image.
In this step, obtain satellite-borne SAR image, choose Gauss model as probability density function of the present invention
Particularly, Gaussian probability-density function model:
Above-mentioned model meets central limit theorem and following assumed condition:
(1) any scattering unit in each resolution element can not affect other scattering units to a great extent.This assumed condition is all set up in most condition such as field, forest, ocean etc.
(2) phase place of each scattering unit is obeyed on [-π, π] and is uniformly distributed.There will be phase offset in a big way when the slant range resolution of radar is more much bigger than wavelength, now need to meet being uniformly distributed on [-π, π].
(3) the phase place stochastic variable of each scattering unit is uncorrelated mutually, and some relevant scattering units can form a scattering center automatically.
(4) uncorrelated mutually between the amplitude stochastic variable of each scattering unit and phase place stochastic variable.This is the phase delay because Signal transmissions causes, and has nothing to do with the amplitude of scattering unit.
For sea, the determination in homogeneity district is relevant with the yardstick of object and background, and when sea is tranquil, smooth can be used as homogeneity district to Small object, and when sea wave is larger, homogeneity district can be used as to general objective in sea.Almost under any circumstance, sea SAR image all meets above four assumed conditions and central limit theorem.
Step S1012: the probability density function determining the arbitrary image pixel elements of described oil spilling area image according to the Gaussian Distribution Parameters of described oil spilling area image, in oil spilling area image described in statistical computation, the average of each image pixel elements brightness of image and standard deviation, be defined as the probability density function parameter of described oil spilling area image by the average of brightness of image and standard deviation.
In this step, determine probability density function, estimation distribution function parameter.
Particularly, using the probability density function of Gaussian distribution as SAR image, and using entire image as reference window, the average μ of each image pixel elements gray scale of statistical computation
iand standard deviation sigma
i, as SAR ocean imagery Gaussian Distribution Parameters, to determine the probability density function of this image i-th unit, that is:
When wave is larger, it is comparatively large that the shape parameter values of probability density function can become, and now the degree of scatter of function value can become large, thus reduces accuracy of detection and speed.But in oil spilling region, because the coefficient of viscosity of oil is comparatively large, can not produces because wave is excessive and fluctuate widely, when the propagation of ocean waves is close to oil spilling region, fluctuation can reduce, and affects detection speed and efficiency in the spilled oil monitoring technology that therefore this respect proposes in the present invention without the need to worrying.
Step S1013: according to the probability density function parameter of default false-alarm probability and described oil spilling area image, substitute in probability density function, obtain the partition threshold of image, again described oil spilling area image is split according to described partition threshold, obtain oil spilling oil sources information and the oil spill area of marine oil depot.
In this step, calculate pixel cell detection threshold, detect oil spilling fast.
Particularly, it is reference windows that CFAR method gets entire image to each pixel exactly, determines a threshold values according to the statistical property of reference windows, makes following detection have invariable false alerting:
Now threshold values is x
0false-alarm probability be:
Therefore, given CFAR is only needed just can to calculate a threshold values according to the average of image pixel and standard deviation, that is:
μ in formula
iand σ
irepresent average and the standard deviation of each image pixel elements gray scale, P
furepresent given CFAR.When calculating the detection threshold x of each pixel cell
0time, the SAR satellite image obtained is detected, detection can be completed rapidly.
Judge whether oil spilling point, remove ground unrest, output detections result.
After detection terminates, need to use count filter filtering to remove ground unrest etc.The count filter that this algorithm adopts, concerning each point, if around it in 5 × 5 regions dim spot number be greater than setting value, then this some position target, otherwise be ground unrest.Concrete implementation step is as follows:
(1) according to the high-resolution of SAR image, oil spill area is set with regard to minimum value;
(2) to detecting to a pixel cell, using count filter filtering, adding up the area of qualified pixel composition;
(3) if statistics area ratio we the area that arranges be greater than our setting value, then can think that this panel region is real goal, otherwise be ground unrest.
Removal noise after filtering completes, output detections result figure.Whole flow scheme can complete at short notice, to reach the rapid reaction object of SAR spilled oil monitoring.
Step S102: the flow field parameter that the Ocean Wind-field parameter of acquisition Atmospheric models forecast and ocean model forecast, according to the Driftdiffusion trend of Ocean Wind-field parameter, flow field parameter oil and oil spilling oil sources Information Pull elaioleucite modeling oil spilling.
In this step, using SAR oil spilling source as starting condition, the ocean dynamical environment parameter that the flow field that the wind field of Atmospheric models forecast and ocean model forecast provides, adopts the Driftdiffusion of elaioleucite model prediction oil spilling, predicts oil spill area sometime.
Particularly, see Fig. 3, step S102 comprises the following steps.
Step S1021: utilize elaioleucite model that oil film is carried out particlized subdivision, and each elaioleucite is identified respectively.
In this step, oil film is carried out particlized subdivision, and fast identification is carried out to each elaioleucite, make each elaioleucite Lagrange drift can occur under the effect of wind field and ocean current, guarantee in calculating spilled oil drift and diffusion process, its state of tracking in time can change, obtain and predict the outcome accurately.
Step S1022: the flow field parameter that the Ocean Wind-field parameter of acquisition Atmospheric models forecast and ocean model forecast.
In this step, the flow field that Ocean Wind-field and ocean model based on Atmospheric models forecast forecast provides ocean dynamical environment parameter, sets up the drift orbit computing formula for each elaioleucite:
Wherein, S
0for the initial position of elaioleucite, V
tfor the drift velocity of t elaioleucite, be the function of room and time, elaioleucite is with speed V
tafter time step Δ t, drift to S, this formula have employed Lagrangian back tracking method, and its core solves V exactly
t, V here
tthe synthesis of the component velocity that each marine environment dynamic factors mechanism produces, as the V of prediction elaioleucite drift orbit
tform primarily of wind drift speed and surface velocity.
Here wind drift speed calculation method is as follows:
V
w＝C
d·W
Wherein V
wfor wind drift speed, W is the 10 meters of wind speed in surface, sea, C
dfor wind drift coefficient.
Model, according to the Drift Process of each elaioleucite, calculates the Drift Process of oil film barycenter, thus dopes the Drift Process of whole oil film.
Step S1023: the Ocean Wind-field parameter of the mark of each elaioleucite, Atmospheric models forecast and the flow field parameter forecast of ocean model are followed the tracks of the drift that each elaioleucite occurs under the effect of wind field and ocean current, obtain the Driftdiffusion trend of oil spilling.
In this step, random walk method is adopted to simulate elaioleucite diffusion process.The diffusion length of oil film can be decomposed into east, two, north component, calculates according to following formula:
Wherein, x
ddrepresent oil slick's pervasion distance east orientation amount; y
ddrepresent oil slick's pervasion distance north orientation amount; D
xrepresent the horizontal proliferation coefficient of east-west direction; D
yrepresent the horizontal proliferation coefficient of North and South direction; T represents time step; γ is random number, and the span of γ is | γ | and < 1.
Export the diffusion tendency of the oil spilling in any moment and the geographic position of each elaioleucite.
Step S103: judge whether the space and geographical grid deviation of the oil spilling oil sources information of marine oil depot and the Driftdiffusion trend of oil spill area and oil spilling is greater than predetermined threshold value.
In this step, utilize SAR remote sensing technology obtain the Monitoring Data of oil spilling state, mutually correct with predicting the outcome of elaioleucite model, the deceptive information in SAR spilled oil monitoring result can not only be removed, avoid the deviation of elaioleucite model simulation results simultaneously, finally obtain real oil spilling point.
Particularly, see Fig. 4, the idiographic flow of step S103 comprises:
Step S1031: the geographic coordinate and the oil spill area that obtain oil spilling point corresponding to the oil spilling oil sources information of marine oil depot.
In this step, sometime, the SAR image of acquisition, according to the flow process of Fig. 2, obtains the testing result of oil spilling point, and calculates oil spilling point R
sARgeographic position, i.e. longitude, latitude.
Step S1032: obtain the geographic coordinate that the Driftdiffusion trend of oil spilling is corresponding.
In this step, elaioleucite model, according to Fig. 3 prediction, with SAR image mutually in the same time, the spilled oil simulation result of same area, same gets oil spilling point R
oillongitude and latitude.
Step S1033: on described oil spilling area image, calculates the distance between the geographic coordinate of the oil spilling point geographic coordinate corresponding with the Driftdiffusion trend of oil spilling.
In this step, both calculating | R
sAR-R
oil|, and set reduced parameter ε;
Concrete, ε repeatedly adjusts: first time is set as ε
0=100 meters, by the contrast with SAR Remotely sensed acquisition result, if both directly distinguish comparatively large, then ε
i=ε
0+ 100 × i, i=1 ... N iterative computation, corresponding each ε
icalculate the number N of SAR oil spilling point respectively
sAR, and elaioleucite model prediction oil spilling point N
oil.
Step S1034: the distance between the geographic coordinate that the geographic coordinate of oil spilling point is corresponding with the Driftdiffusion trend of oil spilling is less than predetermined threshold value, determines that the geographic coordinate of oil spilling point is real oil spilling point.
In this step, when SAR oil spilling points N
sARwith elaioleucite model prediction oil spilling point N
oil, both have the data of 2/3 to overlap, then optimization, then Output rusults both thinking.
In step S104, when space and geographical grid deviation is less than or equal to predetermined threshold value, determine that oil spilling oil sources information and region corresponding to oil spill area are real oil spilling region.
Present embodiments provide a kind of spilled oil monitoring forecasting techniques based on SAR remote sensing and elaioleucite model.When marine oil overflow occurs, obtain SAR remote sensing images (comprising existing all types SAR:Radarsat-2, TerraSAR-X/TanDEM-X, Cosmo-SkyMed and Sentinel) immediately, obtain oil spilling source by carrying out geography correction to image; Using oil spilling source as the flow field that starting condition, Atmospheric models forecast wind field and ocean model forecast as driving, by elaioleucite model prediction oil spilling diffusion tendency; Again obtain SAR image sometime when what predict, obtain possibility oil spilling point and area coverage on image by CFAR; The oil spilling situation utilizing SAR remote sensing technology to monitor and elaioleucite tracer technique analog result contrast, if the two error is larger, so constantly revise simulation reduced parameter, when SAR oil spilling is counted and elaioleucite model prediction oil spilling point, both have the data of 2/3 to overlap, then think and both optimizations then monitored real oil spilling point and overlay area.
As shown in Figure 5, present invention also offers a kind of offshore spilled oil monitoring device, comprising: information acquisition unit 501, trend analogue unit 502, threshold decision unit 503 and area determination unit 504.
Information acquisition unit 501, for the oil spilling area image according to radar monitoring, obtains oil spilling oil sources information and the oil spill area of marine oil depot.
Trend analogue unit 502, the flow field parameter that Ocean Wind-field parameter and ocean model for obtaining Atmospheric models forecast are forecast, according to the Driftdiffusion trend of Ocean Wind-field parameter, flow field parameter oil and oil spilling oil sources Information Pull elaioleucite modeling oil spilling.
Threshold decision unit 503, whether the space and geographical grid deviation for the Driftdiffusion trend of the oil spilling oil sources information and oil spill area and oil spilling that judge marine oil depot is greater than predetermined threshold value.
Area determination unit 504, for when space and geographical grid deviation is less than or equal to predetermined threshold value, determines that oil spilling oil sources information and region corresponding to oil spill area are real oil spilling region.
As shown in Figure 6, described information acquisition unit 501 comprises: gray count module 601, brightness calculation module 602 and Threshold segmentation module 603.
Gray count module 601, for using the probability density function of Gaussian distribution as described oil spilling area image, and using oil spilling area image described in view picture as reference window, calculate average and the standard deviation of each image pixel elements gray scale in described oil spilling area image, the average of described gray scale and standard deviation are defined as the Gaussian Distribution Parameters of described oil spilling area image.
Brightness calculation module 602, for determining the probability density function of the arbitrary image pixel elements of described oil spilling area image according to the Gaussian Distribution Parameters of described oil spilling area image, in oil spilling area image described in statistical computation, the average of each image pixel elements brightness of image and standard deviation, be defined as the probability density function parameter of described oil spilling area image by the average of brightness of image and standard deviation.
Threshold segmentation module 603, for the probability density function parameter by default false-alarm probability and described oil spilling area image, substitute in probability density function, obtain the partition threshold of image, again described oil spilling area image is split according to described partition threshold, obtain oil spilling oil sources information and the oil spill area of marine oil depot.
As shown in Figure 7, described trend analogue unit 502 comprises: mark subdivision module 701, parameter acquisition module 702 and drift tracking module 703.
Mark subdivision module 701, for utilizing elaioleucite model that oil film is carried out particlized subdivision, and identifies respectively to each elaioleucite;
Parameter acquisition module 702, the flow field parameter that Ocean Wind-field parameter and ocean model for obtaining Atmospheric models forecast are forecast;
Drift tracking module 703, follow the tracks of for the Ocean Wind-field parameter of the mark according to each elaioleucite, Atmospheric models forecast and the flow field parameter forecast of ocean model the drift that each elaioleucite occurs under the effect of wind field and ocean current, obtain the Driftdiffusion trend of oil spilling.
As shown in Figure 8, described threshold decision unit 503 comprises: the first acquisition module 801, second acquisition module 802, distance calculation module 803 and oil spilling point determination module 804.
First acquisition module 801, the geographic coordinate of the oil spilling point that the oil spilling oil sources information for obtaining marine oil depot is corresponding and oil spill area;
Second acquisition module 802, the geographic coordinate that the Driftdiffusion trend for obtaining oil spilling is corresponding;
Distance calculation module 803, at described oil spilling area image, calculates the distance between the geographic coordinate of the oil spilling point geographic coordinate corresponding with the Driftdiffusion trend of oil spilling;
Oil spilling point determination module 804, is less than predetermined threshold value for the distance between the geographic coordinate that the geographic coordinate when oil spilling point is corresponding with the Driftdiffusion trend of oil spilling, determines that the geographic coordinate of oil spilling point is real oil spilling point.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (8)
1. an offshore spilled oil monitoring method, is characterized in that, comprising:
According to the oil spilling area image of radar monitoring, obtain oil spilling oil sources information and the oil spill area of marine oil depot;
The flow field parameter that the Ocean Wind-field parameter of acquisition Atmospheric models forecast and ocean model forecast, according to the Driftdiffusion trend of Ocean Wind-field parameter, flow field parameter oil and oil spilling oil sources Information Pull elaioleucite modeling oil spilling;
Judge whether the space and geographical grid deviation of the oil spilling oil sources information of marine oil depot and the Driftdiffusion trend of oil spill area and oil spilling is greater than predetermined threshold value;
When space and geographical grid deviation is less than or equal to predetermined threshold value, determine that oil spilling oil sources information and region corresponding to oil spill area are real oil spilling region.
2. offshore spilled oil monitoring method according to claim 1, is characterized in that, the described oil spilling area image according to radar monitoring, and the oil spilling oil sources information and the oil spill area that obtain marine oil depot comprise:
Using the probability density function of Gaussian distribution as described oil spilling area image, and using oil spilling area image described in view picture as reference window, calculate average and the standard deviation of each image pixel elements gray scale in described oil spilling area image, the average of described gray scale and standard deviation are defined as the Gaussian Distribution Parameters of described oil spilling area image;
The probability density function of the arbitrary image pixel elements of described oil spilling area image is determined according to the Gaussian Distribution Parameters of described oil spilling area image, in oil spilling area image described in statistical computation, the average of each image pixel elements brightness of image and standard deviation, be defined as the probability density function parameter of described oil spilling area image by the average of brightness of image and standard deviation;
According to the probability density function parameter of default false-alarm probability and described oil spilling area image, substitute in probability density function, obtain the partition threshold of image, more described oil spilling area image is split according to described partition threshold, obtain oil spilling oil sources information and the oil spill area of marine oil depot.
3. offshore spilled oil monitoring method according to claim 1, it is characterized in that, the flow field parameter that the Ocean Wind-field parameter of described acquisition Atmospheric models forecast and ocean model forecast, the Driftdiffusion trend according to Ocean Wind-field parameter, flow field parameter oil and oil spilling oil sources Information Pull elaioleucite modeling oil spilling comprises:
Utilize elaioleucite model that oil film is carried out particlized subdivision, and each elaioleucite is identified respectively;
The flow field parameter that the Ocean Wind-field parameter of acquisition Atmospheric models forecast and ocean model forecast;
The Ocean Wind-field parameter of the mark of each elaioleucite, Atmospheric models forecast and the flow field parameter forecast of ocean model are followed the tracks of the drift that each elaioleucite occurs under the effect of wind field and ocean current, obtain the Driftdiffusion trend of oil spilling.
4. offshore spilled oil monitoring method according to claim 1, is characterized in that, describedly judges whether the space and geographical grid deviation of the oil spilling oil sources information of marine oil depot and the Driftdiffusion trend of oil spill area and oil spilling is greater than predetermined threshold value and comprises:
Obtain geographic coordinate and the oil spill area of oil spilling point corresponding to the oil spilling oil sources information of marine oil depot;
Obtain the geographic coordinate that the Driftdiffusion trend of oil spilling is corresponding;
On described oil spilling area image, calculate the distance between the geographic coordinate of the oil spilling point geographic coordinate corresponding with the Driftdiffusion trend of oil spilling;
Distance between the geographic coordinate that the geographic coordinate of oil spilling point is corresponding with the Driftdiffusion trend of oil spilling is less than predetermined threshold value, determines that the geographic coordinate of oil spilling point is real oil spilling point.
5. an offshore spilled oil monitoring device, is characterized in that, comprising:
Information acquisition unit, for the oil spilling area image according to radar monitoring, obtains oil spilling oil sources information and the oil spill area of marine oil depot;
Trend analogue unit, the flow field parameter that Ocean Wind-field parameter and ocean model for obtaining Atmospheric models forecast are forecast, according to the Driftdiffusion trend of Ocean Wind-field parameter, flow field parameter oil and oil spilling oil sources Information Pull elaioleucite modeling oil spilling;
Threshold decision unit, whether the space and geographical grid deviation for the Driftdiffusion trend of the oil spilling oil sources information and oil spill area and oil spilling that judge marine oil depot is greater than predetermined threshold value;
Area determination unit, for when space and geographical grid deviation is less than or equal to predetermined threshold value, determines that oil spilling oil sources information and region corresponding to oil spill area are real oil spilling region.
6. offshore spilled oil monitoring device according to claim 5, is characterized in that, described information acquisition unit comprises:
Gray count module, for using the probability density function of Gaussian distribution as described oil spilling area image, and using oil spilling area image described in view picture as reference window, calculate average and the standard deviation of each image pixel elements gray scale in described oil spilling area image, the average of described gray scale and standard deviation are defined as the Gaussian Distribution Parameters of described oil spilling area image;
Brightness calculation module, for determining the probability density function of the arbitrary image pixel elements of described oil spilling area image according to the Gaussian Distribution Parameters of described oil spilling area image, in oil spilling area image described in statistical computation, the average of each image pixel elements brightness of image and standard deviation, be defined as the probability density function parameter of described oil spilling area image by the average of brightness of image and standard deviation;
Threshold segmentation module, for the probability density function parameter by default false-alarm probability and described oil spilling area image, substitute in probability density function, obtain the partition threshold of image, again described oil spilling area image is split according to described partition threshold, obtain oil spilling oil sources information and the oil spill area of marine oil depot.
7. offshore spilled oil monitoring device according to claim 5, is characterized in that, described trend analogue unit comprises:
Mark subdivision module, for utilizing elaioleucite model that oil film is carried out particlized subdivision, and identifies respectively to each elaioleucite;
Parameter acquisition module, the flow field parameter that Ocean Wind-field parameter and ocean model for obtaining Atmospheric models forecast are forecast;
Drift tracking module, follows the tracks of for the Ocean Wind-field parameter of the mark according to each elaioleucite, Atmospheric models forecast and the flow field parameter forecast of ocean model the drift that each elaioleucite occurs under the effect of wind field and ocean current, obtains the Driftdiffusion trend of oil spilling.
8. offshore spilled oil monitoring device according to claim 5, is characterized in that, described threshold decision unit comprises:
First acquisition module, the geographic coordinate of the oil spilling point that the oil spilling oil sources information for obtaining marine oil depot is corresponding and oil spill area;
Second acquisition module, the geographic coordinate that the Driftdiffusion trend for obtaining oil spilling is corresponding;
Distance calculation module, at described oil spilling area image, calculates the distance between the geographic coordinate of the oil spilling point geographic coordinate corresponding with the Driftdiffusion trend of oil spilling;
Oil spilling point determination module, is less than predetermined threshold value for the distance between the geographic coordinate that the geographic coordinate when oil spilling point is corresponding with the Driftdiffusion trend of oil spilling, determines that the geographic coordinate of oil spilling point is real oil spilling point.
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