CN104635242B - Sand storm monitoring method based on multi-source satellite remote sensing data - Google Patents
Sand storm monitoring method based on multi-source satellite remote sensing data Download PDFInfo
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- CN104635242B CN104635242B CN201510084424.5A CN201510084424A CN104635242B CN 104635242 B CN104635242 B CN 104635242B CN 201510084424 A CN201510084424 A CN 201510084424A CN 104635242 B CN104635242 B CN 104635242B
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Abstract
The invention relates to the technical field of atmospheric environment monitoring and particularly relates to a sand storm monitoring method based on multi-source satellite remote sensing data. The sand storm monitoring method for monitoring sand storm more accurately comprises the following steps: obtaining satellite detecting initial data; calculating a ratio of a near-infrared albedo to a visible light albedo in the initial data, and calculating a difference value between an infrared brightness temperature and a thermal infrared brightness temperature in the initial data; performing brightness temperature calculating of two wavebands of an infrared splitting window on the initial data; if the calculated results of the ratio, the difference value and the brightness temperature calculated results of the infrared splitting window are within corresponding regions, indicating the identified results as a sand storm region.
Description
Technical field
The present invention relates to atmosphere environment supervision technical field, especially with regard to a kind of sand of satellite remote sensing date based on how far
Dust storm monitoring method.
Background technology
Sandstorm is a kind of relatively conventional natural phenomena caused by special geographical environment and meteorological condition, main to send out
In desert and its arid and semi-arid regions closed on, north African, the Middle East, the Central Asia and South Asia, East Asia, North America, Australia are for life
The main sandstorm generating region in the world, western China is the part in Central Asia sandstorm area, and northern territory is East Asia sandstorm
The part in area.The frequent of sandstorm is one of important symbol of ecological deterioration, and sandstorm is a kind of meteorological disaster, is also
Serious ecological environment problem.Define according to meteorology, dust and sand weather is generally divided into strong chromatic number, sandstorm, sand and floating dust
Deng 4 intensity ranks.
Advanced satellite remote sensing platform, is the important means of Dust Storm Monitoring, and ground based observa tion is limited by space-time condition, it is impossible to
Form all standing, quick, uniform Dust Storm Monitoring.Currently, the satellite with multi light spectrum hands data retrieval capabilities is put down
Platform has Chinese wind and cloud one (FY-1) series, Chinese FY-2 (FY-2) series, Chinese wind and cloud three (FY-3) series, the U.S.
NOAA series, U.S. EOS/MODIS series, Europe METOP series etc..These satellite platforms, the monitoring for sandstorm provides rich
Rich data resource, possess the spectral band of suitable Dust Storm Monitoring mostly, it is possible to achieve sandstorm information is accurately identified
And quantitative Analysis.
At present, included based on the sandstorm recognition methodss of satellite remote sensing：Infrared division window difference arithmetic, it is given earlier
The thinking of sand and dust quantitative judge；Using 3.7 μm of middle-infrared bands reflected radiation characteristic special for sand and dust, with reference to multiband number
According to sand and dust recognition methodss；Based on enhanced LUT Method of satellite image etc..Above method can partly solve sand and dust identification
Problem, but all there is obvious limitation, lack real quantitative Analysis ability, it is impossible to well adapt to omnibearing sand and dust prison
Survey demand.
The content of the invention
The present invention is just allowing for the not enough and defect of dust detection method in prior art, it is proposed that cover towards the whole world
Lid, round-the-clock, multiple dimensioned, multi-source data comprehensive dust detection using remote sensing method, are adapted to the concordance monitoring of global range, for
Strong chromatic number, general sand and dust process and weak floating dust have good adaptability, can apply to real-time monitoring.Meanwhile, according to sand
Dirt recognition result, gives the computational methods of dust intensity index, and the Quantitative Monitoring for making sand and dust is possibly realized.
A kind of Dust Storm Monitoring method based on satellite remote sensing date is embodiments provided, including,
Obtain the primary data of satellite sounding；
The ratio of near-infrared and visible albedo in primary data is calculated, and calculates primary data mid-infrared and thermal infrared
The difference of bright temperature；
The bright temperature that two wave bands of infrared division window are carried out to the primary data is calculated；
If the ratio, difference and the bright temperature result of calculation of infrared division window are in corresponding interval interior, sand and dust identification knot
Fruit is sand and dust area.
According to embodiments of the present invention of a kind of described Dust Storm Monitoring method based on satellite remote sensing date enters one
The aspect of step, also includes among the primary data for obtaining satellite monitoring, resampling is carried out to Multi-sensor satellite remote sensing and is inserted
Value process, to overlapping region temporal-spatial fusion process is carried out, and sun altitude is filtered more than 70 ° using sun altitude cosine formula
Multi- source Remote Sensing Data data.
According to embodiments of the present invention another of a kind of described Dust Storm Monitoring method based on satellite remote sensing date enters
The aspect of one step, calculate primary data in near-infrared and visible albedo ratio, and calculate primary data mid-infrared with
Also include before the difference of the bright temperature of thermal infrared, carry out basic threshold value using the bright temperature of Thermal infrared bands and sentence knowledge, when Thermal infrared bands it is bright
Temperature is possible sand and dust area when being more than threshold values.
Another of a kind of Dust Storm Monitoring method based on satellite remote sensing date described according to embodiments of the present invention enters
The aspect of one step, calculate primary data in near-infrared and visible albedo ratio, and calculate primary data mid-infrared with
Also include in the difference of the bright temperature of thermal infrared：
Calculate the difference of mid-infrared and the bright temperature of thermal infrared：
DVmir=T3.7-T11；
Wherein, T3.7For the brightness temperature of 3.7 mu m wavebands, T11For the brightness temperature of 11 mu m wavebands, when difference DVmirFirst
It is possible sand and dust area when in interval；
Calculate the ratio of near-infrared and visible albedo：
RVnir=R1.6/R0.85；
Wherein R1.6For 1.6 mu m waveband albedos, R0.85For 0.85 mu m waveband albedo, when ratio R VnirIn second interval
When, it is possible sand and dust area.
Another of a kind of Dust Storm Monitoring method based on satellite remote sensing date described according to embodiments of the present invention enters
The aspect of one step, the first interval is also divided into the first subinterval and the second subinterval, and it is sub that the second interval is also divided into the 3rd
Interval and the 4th subinterval.
Another of a kind of Dust Storm Monitoring method based on satellite remote sensing date described according to embodiments of the present invention enters
The aspect of one step, first calculates the difference of mid-infrared and the bright temperature of thermal infrared, then calculates the ratio of near-infrared and visible albedo, when
When the difference belongs to the second subinterval, the ratio belongs to the 4th subinterval, then be possible strong sand and dust area；When the difference
When belonging to the first subinterval, the ratio belongs to the 3rd subinterval or belongs to the 4th subinterval, then be possible weak sand and dust area.
Another of a kind of Dust Storm Monitoring method based on satellite remote sensing date described according to embodiments of the present invention enters
The aspect of one step, first calculates the ratio of near-infrared and visible albedo, then calculates the difference of mid-infrared and the bright temperature of thermal infrared, when
When the ratio belongs to four subintervals, the difference belongs to the second subinterval, then be possible strong sand and dust area；When the ratio
When belonging to three subintervals, the difference belongs to the first subinterval, then be possible Ruo sand and dust area, and the difference belongs to second
Subinterval, then be possible weak sand and dust area.
Another of a kind of Dust Storm Monitoring method based on satellite remote sensing date described according to embodiments of the present invention enters
The aspect of one step, the primary data is carried out two wave bands of infrared division window bright temperature calculate further include,
When for possible strong sand and dust area when, the ratio calculation that the bright temperature of infrared division window is carried out to the primary data is：
Wherein T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands, then RVfirBelong to 3rd interval
When, then it is sand and dust area；
When for possible Ruo sand and dust area and weak sand and dust area when, the difference of the bright temperature of infrared division window is carried out to the primary data
Value is calculated as：
DVfir=T12-T11；
Wherein T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands, when for possible most weak sand and dust
Area DVfirThen it is sand and dust area when belonging to five subintervals, when for possible weak sand and dust area DVfirWhen belonging to six subintervals, then for
Sand and dust area.
Another of a kind of Dust Storm Monitoring method based on satellite remote sensing date described according to embodiments of the present invention enters
The aspect of one step, after calculating primary data, the difference belongs to the second subinterval and the ratio belongs to the 4th sub-district
Between, the infrared division windowResult of calculation belong to 3rd interval, then be sand and dust area, wherein, T11
For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands；
After calculating primary data, the difference belongs to the first subinterval and the ratio belongs to the 3rd subinterval,
The infrared division window DVfir=T12-T11Checkout result belong to the 5th subinterval, then be sand and dust area, wherein, T11For 11 μm of ripples
The brightness temperature of section, T12For the brightness temperature of 12 mu m wavebands；
After calculating primary data, the difference belongs to the first subinterval and the ratio belongs to the 4th subinterval,
The infrared division window DVfir=T12-T11Checkout result belong to the 6th subinterval, then be sand and dust area.
Another of a kind of Dust Storm Monitoring method based on satellite remote sensing date described according to embodiments of the present invention enters
The aspect of one step, also includes after sand and dust recognition result is obtained, and calculates dust intensity index：
Wherein R1.6For 1.6 mu m waveband albedos, T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands
Degree, DDI represents dust intensity index.
By the method for the embodiment of the present invention, sandstorm can be more accurately judged, and can provide accurate sand
Dust storm intensity index, comprehensively utilize multiwave satellite remote sensing date, towards global range, multi-spatial scale, varying strength
Dust and sand weather, proposes comprehensive sand and dust recognition methodss, can efficiently solve dynamic monitoring, GLOTRAC global tracking, the multiple dimensioned sky of sand and dust
Between the difficult problem such as quantitative analyses.
Description of the drawings
Technical scheme in order to be illustrated more clearly that the embodiment of the present invention, below will be to making needed for embodiment description
Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present invention, for
For those of ordinary skill in the art, on the premise of not paying creative work, can be obtaining other according to these accompanying drawings
Accompanying drawing.In the accompanying drawings：
Fig. 1 show a kind of flow chart of the Dust Storm Monitoring method based on satellite remote sensing date of the embodiment of the present invention；
Fig. 2 show a kind of flow process of the Dust Storm Monitoring method based on Multi-sensor satellite remote sensing of the embodiment of the present invention
Figure；
Fig. 3 show a kind of flow process of the Dust Storm Monitoring method based on Multi-sensor satellite remote sensing of the embodiment of the present invention
Figure.
Specific embodiment
Purpose, technical scheme and advantage to make the embodiment of the present invention becomes more apparent, below in conjunction with the accompanying drawings to this
Bright embodiment is described in further details.Here, the schematic description and description of the present invention is used to explain the present invention, but and
It is not as a limitation of the invention.
It is illustrated in figure 1 a kind of flow chart of the Dust Storm Monitoring method based on satellite remote sensing date of the embodiment of the present invention.
Including step 101, the primary data of satellite sounding is obtained.
Step 102, calculates the ratio of near-infrared and visible albedo in primary data, and calculates primary data mid-infrared
With the difference of the bright temperature of thermal infrared.
Step 103, the bright temperature that two wave bands of infrared division window are carried out to the primary data is calculated.
Step 104, if the result of calculation of the ratio, difference and infrared division window is in corresponding interval interior, sand and dust
Recognition result is sand and dust area.
Sequencing is not limited to two calculating in above-mentioned steps 102.
As one embodiment of the present of invention, also include among the step 101, weight is carried out to Multi-sensor satellite remote sensing
Sampling and interpolation processing, to overlapping region temporal-spatial fusion process is carried out.
As one embodiment of the present of invention, carry out also including after temporal-spatial fusion process above-mentioned, using altitude of the sun
Angle cosine formula filters data of the sun altitude more than 70 °.
As one embodiment of the present of invention, also included before step 102, carried out substantially using the bright temperature of Thermal infrared bands
Threshold value sentences knowledge, is possible sand and dust area when the bright temperature of Thermal infrared bands is more than threshold values.
As one embodiment of the present of invention, also include in a step 102, calculate the difference of mid-infrared and the bright temperature of thermal infrared
Value：
DVmir=T3.7-T11；
Wherein, T3.7For the brightness temperature of 3.7 mu m wavebands, T11For the brightness temperature of 11 mu m wavebands, when difference DVmirFirst
It is possible sand and dust area when in interval.Such as value 20K<DVmir<70K be possible sand and dust area, i.e. first interval for (20K,
70K), be further divided in the first interval the first subinterval (20K, 30K], the second subinterval (30K, 70K).Described son
Interval division can be not quite similar, and will not be described here.
Calculate the ratio of near-infrared and visible albedo：
RVnir=R1.6/R0.85；
Wherein R1.6For 1.6 mu m waveband albedos, R0.85For 0.85 mu m waveband albedo, when ratio R VnirIn second interval
When, it is possible sand and dust area.Such as value 0.8<RVnir<1.5 be possible sand and dust area, i.e. second interval for (0.8,1.5),
Be further divided in the second interval the 3rd subinterval (0.8,1], the 4th subinterval (1,1.5).The division in described subinterval
Can be not quite similar, will not be described here.
As one embodiment of the present of invention, also include in a step 102, first calculate the difference of mid-infrared and the bright temperature of thermal infrared
Value, then calculate the ratio of near-infrared and visible albedo, when the difference belongs to the second subinterval, the ratio belongs to the
Four subintervals, then be possible strong sand and dust area；When the difference belongs to the first subinterval, the ratio belongs to the 3rd sub-district
Between, then it is possible Ruo sand and dust area, the ratio belongs to the 4th subinterval, then be possible weak sand and dust area.
As one embodiment of the present of invention, also include in a step 102, first calculate near-infrared and visible albedo
Ratio, then the difference of mid-infrared and the bright temperature of thermal infrared is calculated, when the ratio belongs to four subintervals, the difference belongs to
Two subintervals, then be possible strong sand and dust area；When the ratio belongs to three subintervals, the difference belongs to the first sub-district
Between, then it is possible Ruo sand and dust area, the difference belongs to the second subinterval, then be possible weak sand and dust area.
As one embodiment of the present of invention, also include in step 103, when for possible strong sand and dust area when, to described
Primary data carries out the ratio calculation of the bright temperature of two wave bands of infrared division window：
Wherein T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands, then RVfirBelong to 3rd interval
When, then be sand and dust area, such as described 3rd interval for (1,1.5), i.e., 1<RVfir<It is sand and dust area when 1.5；
When for possible Ruo sand and dust area and weak sand and dust area when, two wave bands of infrared division window are carried out to the primary data
The mathematic interpolation of bright temperature is：
DVfir=T12-T11；
Wherein T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands, when for possible most weak sand and dust
Area DVfirThen it is sand and dust area when belonging to five subintervals, when for possible weak sand and dust area DVfirWhen belonging to six subintervals, then for
Sand and dust area, the such as the 4th it is interval be (0.5K, 5K), wherein also divide have the 5th subinterval (0.5K, 1.5K], the 6th subinterval
(1.5K, 5K), when for possible Ruo sand and dust area DVfirBelong to (0.5K, 1.5K], then it is sand and dust area, when for possible weak sand and dust
Area DVfirBelong to (1.5K, 5K), be then sand and dust area.The division in described subinterval can be not quite similar, and will not be described here.
As one embodiment of the present of invention, after calculating primary data, the difference belong to the second subinterval and
The ratio belongs to the 4th subinterval, the infrared division windowResult of calculation belong to the 3rd area
Between, then it is sand and dust area, wherein, T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands；
After calculating primary data, the difference belongs to the first subinterval and the ratio belongs to the 3rd subinterval,
The infrared division window DVfir=T12-T11Checkout result belong to the 5th subinterval, then be sand and dust area, wherein, T11For 11 μm of ripples
The brightness temperature of section, T12For the brightness temperature of 12 mu m wavebands；
After calculating primary data, the difference belongs to the first subinterval and the ratio belongs to the 4th subinterval,
The infrared division window DVfir=T12-T11Checkout result belong to the 6th subinterval, then be sand and dust area.
As one embodiment of the present of invention, after calculating primary data, the ratio belong to the 4th subinterval and
The difference belongs to the second subinterval, the infrared division windowResult of calculation belong to the 3rd area
Between, then it is sand and dust area, wherein, T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands；
After calculating primary data, the ratio belongs to the 3rd subinterval and the difference belongs to the first subinterval,
The infrared division window DVfir=T12-T11Checkout result belong to the 5th subinterval, then be sand and dust area, wherein, T11For 11 μm of ripples
The brightness temperature of section, T12For the brightness temperature of 12 mu m wavebands；
After calculating primary data, the ratio belongs to the 4th subinterval and the difference belongs to the first subinterval,
The infrared division window DVfir=T12-T11Checkout result belong to the 6th subinterval, then be sand and dust area.
As one embodiment of the present of invention, also include after step 104, calculate dust intensity index：
Wherein R1.6For 1.6 mu m waveband albedos, T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands
Degree, DDI represents dust intensity index, is the dimensionless number between a 1-100, is worth bigger expression dust intensity stronger.
As one embodiment of the present of invention, for the sand and dust recognition result of step 104, using small component minimizing technology,
The removal for completing noise, erroneous judgement point or region is processed；Simultaneously as the impact of cloud, landform or other factorses, in recognition result
Some orifice regions occur inside Connected component, the present invention carries out morphological operations, goes using structure variable matrix and recognition result
Except these orifice regions.
By the method for the embodiments of the present invention, sandstorm can be more accurately judged, and can be given accurately
Sand index, multiwave satellite remote sensing date is comprehensively utilized, towards global range, multi-spatial scale, different strong
The dust and sand weather of degree, proposes comprehensive sand and dust recognition methodss, can efficiently solve dynamic monitoring, GLOTRAC global tracking, many chis of sand and dust
The difficult problems such as degree spatial quantitative analysis.
It is illustrated in figure 2 a kind of flow process of the Dust Storm Monitoring method based on Multi-sensor satellite remote sensing of the embodiment of the present invention
Figure.
Including step 201, the Multi-sensor satellite remote sensing file of multiple format is read, parse the complex data of every kind of data
Structure, by remotely-sensed data real physical quantity is converted to, and obtains the memory object entity that can carry out unifying subsequent treatment.
Step 202, to remotely-sensed data space projection process is carried out, and is first depending on location information, sets up the Jing of view field
Latitude look-up table；Then shortest path near stratum exhaust algorithm is adopted, space interpolation process is carried out；Finally complete according to interpolation
Longitude and latitude synopsis, by each wave band data projection transform is carried out.
Step 203, judges whether data include multiple observation times and with overlapping region, if necessary at space-time fusion
Reason, then carry out step 204 and process；If it is not required, then directly carry out step 205 processing.
Step 204, for the data for needing overlapping region to process, using minimum satellite vehicle zenith angle priority algorithm data is carried out
Fusion treatment.
Step 205, after obtaining the consistent data of time-space registration, using sun altitude cosine formula, for visible ray and
Near-infrared data carries out correcting process, and data of the sun altitude more than 70 ° will be ignored.
Step 206, starts the cycle over the data for processing each effective pixel, carries out sand and dust identifying processing, reads each pixel
The physical quantity of the wave bands such as visible ray, near-infrared, mid-infrared, 2 infrared division windows constitutes primary data.
Step 207, starts sand and dust identifying processing, carries out basic threshold value first by the bright temperature of Thermal infrared bands and sentences knowledge, bright temperature
Pixel less than 290K can sentence knowledge as knowledge is tentatively sentenced into next step sand and dust；Pixel of the bright temperature more than 290K, then excluding is
The possibility of sand and dust, two-value data is designated as 0, proceeds to next pixel and processes.Threshold values 290K in this step is the Jing of inventor
Value is tested, other bright temperature value, the 290K in this step can be adopted to be intended merely to using an explanation implemented as scheme, should not do
Limit and understand.
In this step, the property of the warm property landscape object of low albedo in being shown as mostly due to sand and dust, using thermal infrared
Passage carries out basic threshold value and sentences knowledge, and main target is to determine that preliminary sand and dust are demarcated with earth's surface, reduces sand and dust identification range, improves
Accuracy of identification, this is even more important in desert area.Threshold value uses 11.0 μm of Thermal infrared bands data of satellite, carries out long-time statistical point
Analysis, determines that sand and dust and the boundary of earth's surface are concentrated near 290K.
Step 208, according to mid-infrared and thermal infrared dual channel difference (DVmir) do and sentence knowledge, work as 30K<DVmir<During 70K, then just
Strong sand and dust are judged to, into next step knowledge is sentenced；Work as 20K<DVmir<During=30K, then just weak sand and dust are judged to, into next step knowledge is sentenced；When
DVmirNot when the two are interval, then knowledge is sentenced for non-sand and dust, two-value data is designated as into 0, proceed to next pixel and process.
In this step, the mu m waveband of mid-infrared 3.7 has significantly reflection to sand and dust, especially strong sand and dust.Actually used
In, the difference using 3.7 mu m wavebands and 11 mu m wavebands is as follows as knowledge foundation, computing formula is sentenced：
DVmir=T3.7-T11
Wherein T3.7For the brightness temperature of 3.7 mu m wavebands, T11For the brightness temperature of 11 mu m wavebands, condition 20.0K is met<
DVmir<70.0K, as sand and dust knowledge condition is sentenced.
Step 209, for 30K<DVmir<The strong sand and dust area of 70K, is further sentenced using near-infrared with visible ray ratio
Know, when ratio meets condition 1<RVnir<May be further sand and dust area when 1.5, knowledge be sentenced into next step, otherwise, by two-value number
According to being designated as 0, proceed to next pixel and process.
Near infrared channels go for sand and dust identification, especially strong sand and dust area, and near-infrared has substantially with visible channel
Diversity, the ratio for introducing two passages recognizes main criterion as strong sand and dust, and computing formula is as follows：
RVnir=R1.6/R0.85
Wherein R1.6For 1.6 mu m waveband albedos, R0.85For 0.85 mu m waveband albedo.
Step 210, subsequent steps 209 further carry out sentencing knowledge using infrared division window ratio e index, when meeting condition
RVfir>When 1, then this pixel of knowledge is sentenced for sand and dust area, two-value data is designated as 1, complete this pixel identification；The two-value if being unsatisfactory for
Data are designated as 0, are processed into next pixel.
Attenuation by absorption of 2 wave bands of infrared division window to sand and dust is variant, can be especially right as the criterion of sand and dust identification
In weak sand and dust area, infrared division window wave section compares other wave bands, with the reflection of more preferable diversity.Knowledge is sentenced for strong sand and dust to use
The Ratio index of the bright temperature of the infrared wave band of division window 2, used as sand and dust identical criterion, computing formula is as follows：
Wherein T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands, then RVfir>1 knows as sand and dust
Other criterion.
Step 211, for 20K<DVmir<The weak sand and dust area of 30K, is further sentenced using near-infrared with visible ray ratio
Know, this ratio is divided into into two kinds of situations, i.e.,：0.8<RVnir<=1 and 1<RVnir<1.5, respectively enter next step and sentence knowledge, if not
Meet the two conditions, then sentence knowledge for non-sand and dust, two-value data is designated as into 0, proceed to next pixel and process.
Step 212, for 0.8<RVnir<1 situation, further carries out sentencing knowledge using infrared division window difference, works as satisfaction
Condition 0.5K<DVfir<During=1.5K, then this pixel of knowledge is sentenced for sand and dust area, two-value data is designated as 1, complete this pixel identification；If
It is unsatisfactory for, two-value data is designated as 0, is processed into next pixel.
For weaker sand and dust are using the difference of the bright temperature of the infrared wave band of division window 2, used as sand and dust identical criterion, computing formula is such as
Under：
DVfir=T12-T11
Wherein T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands, then 0.5K<DVfir<5K conducts
The criterion of sand and dust identification.
Step 213, for 1<RVnir<1.5 situation, further carries out sentencing knowledge using infrared division window difference, works as satisfaction
Condition 1.5K<DVfir<During 5K, then this pixel of knowledge is sentenced for sand and dust area, two-value data is designated as 1, complete this pixel identification；If discontented
It is sufficient then two-value data is designated as 0, processed into next pixel.
Step 214, circulation is completed after the sand and dust identification of all effective pixels, finally gives a sand and dust identification two-value number
According to 1 is represented as sand and dust area, and 0 indicates without sand and dust.
Step 215, according to sand and dust identification data, reads the near-infrared albedo and the infrared ripple of division window 2 of sand and dust area pixel
Duan Liangwen, using dust intensity computation model, obtains the dust intensity index of each sand and dust pixel.
Wherein R1.6For 1.6 mu m waveband albedos, T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands
Degree, DDI represents dust intensity index, is the dimensionless number between a 1-100, is worth bigger expression dust intensity stronger.
In the prior art, dust intensity index can be calculated by optical thickness, sets up synopsis and the light for collecting
Learn thickness to be compareed, it is also possible to obtain dust intensity index, above-mentioned steps be the present inventor provide it is a kind of newly
The computational methods of dust intensity index.
Step 216, occurs some isolated zonules in sand and dust recognition result, these zonules be probably noise,
Erroneous judgement point or region, the present invention defines a structure variable matrix and each pixel using soiline-alkali plants and small component minimizing technology
Computing is carried out, so as to sentence isolated zonule is known, and removed in the result.
Step 217, equally, based on the continuous distribution characteristic of sand and dust, but due to the impact of cloud, landform or other factorses,
Some orifice regions, one algorithm mould based on morphological image of present invention design occurs inside the Connected component of recognition result
Type, using rational structure variable matrix and recognition result image morphological operations are carried out, and remove these orifice regions, it is ensured that sand and dust
Continuous distribution characteristic.
Step 218, after result corrects process, sand and dust recognition result can be according to science data and image two ways
Output, science data record the intensity index of each sand and dust pixel, can be used for follow-up analysis and application；Image includes sand and dust
Color composite image, sand and dust identification image, dust intensity index image etc..
Fig. 3 show a kind of flow process of the Dust Storm Monitoring method based on Multi-sensor satellite remote sensing of the embodiment of the present invention
Figure.
Basic step is similar with Fig. 2, differs primarily in that sand and dust recognition sequence, and Fig. 3 completes the basic threshold of Thermal infrared bands
Value is sentenced after knowledge, first carries out sentencing knowledge using near-infrared and visible ray ratio, then reuses mid-infrared and does with thermal infrared dual channel difference
Sand and dust sentence knowledge, and Main change is shown in step 308-313, step 301-307 and step 314-318 and step 201-207 and step
214-218 is identical, repeats in same section no longer the present embodiment.
Step 308, according to near-infrared and visible ray ratio (RVnir) carry out sentencing knowledge, this ratio is divided into into two kinds of situations,
I.e.：0.8<RVnir≤ 1 and 1<RVnir<1.5, respectively enter next step and sentence knowledge, be such as unsatisfactory for the two conditions, then knowledge is sentenced for non-sand
Dirt, by two-value data 0 is designated as, and is proceeded to next pixel and is processed.
Step 309, for 1<RVnir<1.5 strong sand and dust area, further using mid-infrared and thermal infrared dual channel difference
(DVmir) do and sentence knowledge, when difference meets condition 30K<DVmir<May be further sand and dust area during 70K, into next step knowledge is sentenced,
Otherwise, two-value data is designated as into 0, proceeds to next pixel and process.
Step 310, subsequent steps 209 further carry out sentencing knowledge using infrared division window ratio e index, when meeting condition
RVfir>When 1, then this pixel of knowledge is sentenced for sand and dust area, two-value data is designated as 1, complete this pixel identification.
Step 311, for 0.8<RVnir≤ 1 weak sand and dust area, further using mid-infrared and thermal infrared dual channel difference
(DVmir) carry out sentencing knowledge, for weak sand and dust area, this difference (DVmir) two kinds of situations can be divided into, i.e.,：20K<DVmir≤ 30K and
30K<DVmir<70K, respectively enters next step and sentences knowledge, is such as unsatisfactory for the two conditions, then knowledge is sentenced for non-sand and dust, by two-value data
0 is designated as, next pixel is proceeded to and is processed.
Step 312, for 20K<DVmirThe situation of≤30K, further carries out sentencing knowledge using infrared division window difference, when full
Sufficient condition 0.5K<DVfirDuring≤1.5K, then this pixel of knowledge is sentenced for sand and dust area, two-value data is designated as 1, complete this pixel identification.
Step 313, for 30K<DVmir<The situation of 70K, further carries out sentencing knowledge using infrared division window difference, when full
Sufficient condition 1.5K<DVfir<During 5K, then this pixel of knowledge is sentenced for sand and dust area, two-value data is designated as 1, complete this pixel identification.
By the method for the embodiments of the present invention, sandstorm can be more accurately judged, and can be given accurately
Sand index, multiwave satellite remote sensing date is comprehensively utilized, towards global range, multi-spatial scale, different strong
The dust and sand weather of degree, proposes comprehensive sand and dust recognition methodss, can efficiently solve dynamic monitoring, GLOTRAC global tracking, many chis of sand and dust
The difficult problems such as degree spatial quantitative analysis.By the method for the embodiments of the present invention, apparatus and system,.
Particular embodiments described above, has been carried out further in detail to the purpose of the present invention, technical scheme and beneficial effect
Describe in detail it is bright, should be understood that the foregoing is only the present invention specific embodiment, the guarantor being not intended to limit the present invention
Shield scope, all any modification, equivalent substitution and improvements within the spirit and principles in the present invention, done etc., should be included in this
Within the protection domain of invention.
Claims (8)
1. a kind of Dust Storm Monitoring method based on satellite remote sensing date, it is characterised in that include,
Obtain the primary data of satellite sounding；
The ratio of near-infrared and visible albedo in primary data is calculated, and calculates primary data mid-infrared and the bright temperature of thermal infrared
Difference；
The bright temperature that two wave bands of infrared division window are carried out to the primary data is calculated；
If in corresponding interval, recognition result is sand and dust for the ratio, difference and the bright temperature result of calculation of infrared division window
Area；
Calculate dust intensity index：
Wherein, R1.6For 1.6 mu m waveband albedos, T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands,
DDI represents dust intensity index.
2. a kind of Dust Storm Monitoring method based on satellite remote sensing date according to claim 1, it is characterised in that obtaining
Also include among the primary data for obtaining satellite sounding, resampling and interpolation processing are carried out to Multi-sensor satellite remote sensing, to overlapping
Region carries out temporal-spatial fusion process, and using sun altitude cosine formula data of the sun altitude more than 70 ° are filtered.
3. a kind of Dust Storm Monitoring method based on satellite remote sensing date according to claim 1, it is characterised in that in meter
The ratio of near-infrared and visible albedo in primary data is calculated, and calculates the difference of primary data mid-infrared and the bright temperature of thermal infrared
Also include before, carry out basic threshold value using the bright temperature of Thermal infrared bands and sentence knowledge, being when the bright temperature of Thermal infrared bands is more than threshold values can
The sand and dust area of energy.
4. a kind of Dust Storm Monitoring method based on satellite remote sensing date according to claim 1, it is characterised in that in meter
The ratio of near-infrared and visible albedo in primary data is calculated, and calculates the difference of primary data mid-infrared and the bright temperature of thermal infrared
In also include：
Calculate the difference of mid-infrared and the bright temperature of thermal infrared：
DVmir=T3.7-T11；
Wherein, T3.7For the brightness temperature of 3.7 mu m wavebands, T11For the brightness temperature of 11 mu m wavebands, when difference DVmirIn first interval
It is possible sand and dust area when interior；
Calculate the ratio of near-infrared and visible albedo：
RVnir=R1.6/R0.85；
Wherein R1.6For 1.6 mu m waveband albedos, R0.85For 0.85 mu m waveband albedo, when ratio R VnirIn second interval, it is
Possible sand and dust area.
5. a kind of Dust Storm Monitoring method based on satellite remote sensing date according to claim 4, it is characterised in that described
First interval is also divided into the first subinterval and the second subinterval, and the second interval is also divided into the 3rd subinterval and the 4th sub-district
Between.
6. a kind of Dust Storm Monitoring method based on satellite remote sensing date according to claim 5, it is characterised in that first count
Calculate the difference of mid-infrared and the bright temperature of thermal infrared, then calculate the ratio of near-infrared and visible albedo, when the difference belongs to the
During two subintervals, the ratio belongs to the 4th subinterval, then be possible strong sand and dust area；When the difference belongs to the first subinterval
When, the ratio belongs to the 3rd subinterval, then be possible Ruo sand and dust area, and the ratio belongs to the 4th subinterval, then for can
The weak sand and dust area of energy.
7. a kind of Dust Storm Monitoring method based on satellite remote sensing date according to claim 5, it is characterised in that first count
Calculate the ratio of near-infrared and visible albedo, then calculate the difference of mid-infrared and the bright temperature of thermal infrared, when the ratio belongs to the
During four subintervals, the difference belongs to the second subinterval, then be possible strong sand and dust area；When the ratio belongs to the 3rd subinterval
When, the difference belongs to the first subinterval, then be possible Ruo sand and dust area, and the difference belongs to the second subinterval, then for can
The weak sand and dust area of energy.
8. a kind of Dust Storm Monitoring method based on satellite remote sensing date according to claim 6 or 7, it is characterised in that
The bright temperature that two wave bands of infrared division window are carried out to the primary data is calculated, and is further included,
When for possible strong sand and dust area when, infrared division window ratio calculation is carried out to the primary data is：
Wherein T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands, work as RVfirWhen belonging to 3rd interval, then
For sand and dust area；
When for possible Ruo sand and dust area and weak sand and dust area when, infrared division window mathematic interpolation is carried out to the primary data is：
DVfir=T12-T11；
Wherein T11For the brightness temperature of 11 mu m wavebands, T12For the brightness temperature of 12 mu m wavebands, when for possible Ruo sand and dust area
DVfirThen it is sand and dust area when belonging to five subintervals, when for possible weak sand and dust area DVfirThen it is sand when belonging to six subintervals
Dirt area.
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