CN106872466A - A kind of lake ice freeze thawing monitoring method and system based on dynamic Decomposition of Mixed Pixels method - Google Patents
A kind of lake ice freeze thawing monitoring method and system based on dynamic Decomposition of Mixed Pixels method Download PDFInfo
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Abstract
The present invention provides a kind of lake ice freeze thawing monitoring method and system based on dynamic Decomposition of Mixed Pixels method.Methods described includes S1, based on lake particular optical image and passive microwave remote sensing data, obtains the bright temperature value of lake mixed pixel and the bright temperature value of loke shore Pure pixel；S2, based on lake particular optical image and the bright temperature value of lake mixed pixel, the area ratio of lake and loke shore in the lake mixed pixel is obtained by Overlap Analysis；S3, based on the bright temperature value of lake mixed pixel, the bright temperature value of loke shore Pure pixel and lake and loke shore area ratio in the lake mixed pixel, the bright temperature value of lake Pure pixel of the lake mixed pixel is obtained using linear spectral unmixing method, to monitor lake ice freeze thawing phenomenon.Passive microwave remote sensing data is applied to the present invention sub-pixed mapping lake freeze thawing monitoring of Asia high, obtains the bright temperature information in lake in sub-pixed mapping, realizes Asia passive microwave remote sensing sub-pixed mapping lake ice freeze thawing monitoring high.
Description
Technical field
The present invention relates to lake ice freeze thawing monitoring technical field, more particularly, to one kind based on dynamic Decomposition of Mixed Pixels
The lake ice freeze thawing monitoring method and system of method.
Background technology
Based on Qinghai-Tibet Platean, by the mountain ranges such as the Himalayas, Kun Lun Mountain, Hengduanshan Mountains In China, the Qilian mountains and Tianshan Mountains and plateau
The Asia region high of area composition, between 2000 to 8844m, mean sea level is about 4046m to altitude ranges, is global High aititude
Lake area the most intensive, domestic lake spreads all over the place, and area there are about 1210 more than 1km2.
Lake ice parameter is one of important sensitive factor of whole world change, and the weather and environment of Asia high are to the region earth
System model has important influence, is the most sensitive region of Global climate change, is also the hot spot region of current research, high
Mountain lake is very sensitive for climate change, particularly the time of high mountain lake freeze thawing and duration, is often expected to, for recording, use
In announcement regional climate and environmental change feature.
This area's physical geographic environment feature both high and cold, causes the area uninhabited, and lake monitoring station lacks, and makes
Obtain lake freeze thawing parameter to be difficult to be obtained from ground monitoring, particularly period of history lake ice does not observe data substantially, therefore, generally
Needs carry out the acquisition of freeze thawing state by history remote sensing observations data and existing observation data.Wherein it is usually used in monitoring lake to freeze
The optical remote sensing data melted mainly have AVHRR (Advanced Very High Resolution Radiometer), MODIS
(Moderate Resolution Imaging Spectroradiometer) etc., conventional passive microwave remote sensing data will have
SSMI/S (Special Sensor Microwave Imager/Sounder), AMSR-E (Advanced Microwave
Scanning Radiometer-Earth Observing System)、FY3 MWRI(Microwave Radiation
) and AMSR2 (The Advanced Microwave Scanning Radiometer 2) etc. Imager.
Asia atmosphere convection high is enlivened, and often has cloud cover, to be have impact on and effectively obtain lake when optical pickocff passes by
Information is melted in frost, so that optical image has the serious problems of shortage of data.Such as Kropacek (2013) utilizes MODIS optics
During 59 lake freezing-thawing conditions of product surveillance Qinghai-Tibet Platean, for the consideration polluted to cloud, selection is closed using through maximum accumulated snow
Into the monitoring lake freeze thawing of eight days Snow Products of MYD10A2, but existed at least 8 from the data monitoring lake freeze thawing situation
The monitoring error of even 16 days more than it.
And microwave radiance transfer remotely-sensed data has round-the-clock observing capacity, influenceed less by sexual intercourse weather conditions, over the ground
Observation space-time expending is strong, and detection to frozen water phase transformation has compared with high sensitivity, is particularly suitable for ice and snow freeze thawing study on monitoring,
It is widely used in the monitoring of land table permafrost change, snow-cover variation monitoring and sea ice variation monitoring.But due to passive microwave radiation
Score resolution is coarse, and mixed pixel effect is serious, causes it to be greatly limited in lake freeze thawing variation monitoring, and does not have
Having can monitor a large amount of lake freeze thawing situations as optical data.
At present Asia region high using the lake of passive microwave remote sensing data study on monitoring be concentrated mainly on Qinghai Lake with
And the large-size lake such as Nam Co, or even also only have 35 large-size lakes in the lake that whole Northern Hemisphere region is properly used to monitor.
And Asia region high lake is densely distributed, clearly and area's weather and environmental change band are understood in depth from the angle of lake freeze thawing
The influence and response for coming, it is to be understood that the freeze thawing situation in the more lakes in the area.Although passive microwave remote sensing data mixed pixel is imitated
Answer obvious, but the related data of the lake freeze thawing in Asia region high can be obtained in optical remote sensing and ground observation, it is passive to make
Microwave remote sensing data become a kind of valuable material of monitoring lake freeze thawing.
Generally for more finer earth's surface monitoring feature information are obtained from the passive microwave image of coarse resolution, often
There are following several solutions, such as increasing of pixel analysis technology, remote sensing image NO emissions reduction technology and combination multi- source Remote Sensing Data data
Strong resolution technique.Area of lake is often relatively small compared with the pixel resolution of passive microwave remote sensing data；Lake region
Information is recorded only in a limited number of pixel even single pixel (when area of lake is small more than a microwave pixel).
And satellite sensor is in a kind of state of relative motion with earth's surface lake position, sensor revisits capture record lake region letter
The pixel center point coordinate of breath always changes, and the area of lake for causing single pixel to be captured also changes therewith, causes to pass
The enhanced method of the resolution ratio such as the passive microwave of system is difficult to be applicable.
Aggregate analysis shows, in global change research due, Asia high, particularly Qinghai-Tibet Platean, river lake ice freeze thawing number
According to comparing missing；Current China only has the lake ice routine observation data of Qinghai Lake in recent years and less Lake Namco, therefore goes through
The acquisition of the lake ice freeze thawing data in history period just seems extremely important.Microwave radiance transfer remotely-sensed data can be used for recalling history
The observation of period lake ice freeze thawing, but the problem for existing is, current various methods can be realized carrying out Big Lakess and monitored, but
It is the problems such as signal often occurs smudgy, differentiation is improper in the case of small lakes.Therefore need to take into full account data
The exploitation of availability methodology, and the problem of its intrinsic spatial resolution is broken through, so that for more lakes provide lake ice freeze thawing
Parameter information.
The content of the invention
The present invention provide it is a kind of overcome above mentioned problem or solve the above problems at least in part based on dynamic mixing picture
The lake ice freeze thawing monitoring method and system of first decomposition method.
According to an aspect of the present invention, there is provided a kind of lake ice freeze thawing monitoring side based on dynamic Decomposition of Mixed Pixels method
Method, including：
S1, based on lake particular optical image and passive microwave remote sensing data, obtains the bright temperature value of lake mixed pixel and lake
The bright temperature value of bank Pure pixel；
S2, based on lake particular optical image and the bright temperature value of lake mixed pixel, obtains described by Overlap Analysis
The area ratio of lake and loke shore in the mixed pixel of lake；
S3, based on the bright temperature value of lake mixed pixel, the bright temperature value of loke shore Pure pixel and the lake mixing picture
Lake and loke shore area ratio, the pure picture in lake of the lake mixed pixel is obtained using linear spectral unmixing method in unit
The bright temperature value of unit, to monitor lake ice freeze thawing phenomenon.
According to another aspect of the present invention, a kind of lake ice freeze thawing monitoring based on dynamic Decomposition of Mixed Pixels method is also provided
System, including：
Preliminary bright temperature data acquisition module, for based on lake particular optical image and passive microwave remote sensing data, obtaining
The bright temperature value of lake mixed pixel and the bright temperature value of loke shore Pure pixel；
Lake and land percentage module, for based on lake particular optical image and the bright temperature of lake mixed pixel
Value, the area ratio of lake and loke shore in the lake mixed pixel is obtained by Overlap Analysis；
The accurate acquisition module of dynamic, for based on the bright temperature value of lake mixed pixel, the bright temperature of loke shore Pure pixel
Lake and loke shore area ratio in value and the lake mixed pixel, obtain the lake and mix using linear spectral unmixing method
The bright temperature value of lake Pure pixel of pixel is closed, to monitor lake ice freeze thawing phenomenon.
A kind of lake ice freeze thawing monitoring method and system based on dynamic Decomposition of Mixed Pixels method that the application is proposed, with reference to lake
Pool particular optical image and passive microwave remote sensing data, dynamically obtain the ratio value of lake and loke shore in passive microwave pixel,
Microwave radiance transfer dynamic mixed pixel linear decomposition is carried out, so as to obtain the bright temperature value of lake Pure pixel；The lake is pure
The bright temperature value of pixel can be used to monitor lake ice freeze thawing phenomenon.
Herein described method can realize that the passive microwave remote sensing data that will be generally used for the monitoring of large scale earth's surface is applied to
The sub-pixed mapping level lake freeze thawing monitoring of Asia high, obtains the bright temperature information in lake in the sub-pixed mapping, is capable of achieving Asia ground high
Area's passive microwave remote sensing sub-pixed mapping lake ice freeze thawing monitoring.
Brief description of the drawings
Fig. 1 is a kind of lake ice freeze thawing monitoring method flow chart based on dynamic Decomposition of Mixed Pixels method of the present invention；
Fig. 2 is rectangle dynamic buffering schematic diagram of the present invention；
Fig. 3 is a kind of lake ice freeze thawing monitoring system schematic diagram based on dynamic Decomposition of Mixed Pixels method of the present invention；
Fig. 4 a are the bright temperature schematic diagram in Qinghai Lake long-term sequence lake of the present invention；
Fig. 4 b are the bright temperature schematic diagram in Hoh Xil Lake long-term sequence lake of the present invention；
Fig. 4 c are the present invention up to the then bright temperature schematic diagram in wrong long-term sequence lake；
Fig. 4 d are the bright temperature schematic diagram in Sai Ku lakes long-term sequence lake of the present invention；
Fig. 4 e are the bright temperature schematic diagram in Ba Mu of the present invention mistake long-term sequence lakes；
Fig. 4 f invite the bright temperature schematic diagram in cloth mistake long-term sequence lake for the present invention is visitd；
Fig. 4 g are the bright temperature schematic diagram in hole of the present invention mistake long-term sequence lake；
Fig. 5 a are the present invention to two kinds of bright temperature contrast schematic diagrams in information enhancement method lake up to then mistake；
Fig. 5 b are the present invention to visiing two kinds of bright temperature contrast schematic diagrams in information enhancement method lake for inviting cloth wrong.
Specific embodiment
With reference to the accompanying drawings and examples, specific embodiment of the invention is described in further detail.Hereinafter implement
Example is not limited to the scope of the present invention for illustrating the present invention.
The region of present invention specific implementation is Asia high, and the Asia high refers to that Central Asia is with Qinghai-Tibet Platean
The High aititude region at center.The present invention chooses area discrepancy obvious six lakes in Asia high to be frozen as lake ice is implemented
Melt the object of monitoring, they be respectively Hoh Xil Lake, up to then mistake, Sai Kuhu, Ba Mu are wrong, visit and invite cloth wrong and hole is wrong.It is spaceborne
The average area of lake that passive microwave sensors A MSR-E pixels capture this six lakes accounts for pixel area ratio from big to small
Respectively 0.57,0.55,0.41,0.37,0.28 and 0.22, such as table 1.
Table 1
The data that are used have four kinds during present invention specific implementation, including：AMSR-E passive microwave remote sensing datas,
Landsat TM image datas, day by day the AMSR-E data of enhancing resolution ratio and cloudless MODIS data.Wherein from described
AMSR-E passive microwave remote sensing datas extract lake and the bright temperature value in loke shore region；Calculated from the Landsat TM image datas
Lake and the changeable weight in lake；From it is described enhancing resolution ratio AMSR-E data extract the bright temperature value in lake, and with mix picture
The bright temperature value that first decomposition method is extracted carries out effect comparing；And from the MODIS data cloudless day by day as extraction lake
The checking data of freeze thawing parameter.
The AMSR-E passive microwave remote sensing datas are by microwave radiance transfer spoke meter observation data observation gained.It is described passive
Microwave spoke meter has 12 imager passages of horizontal polarization and vertical polarization, and frequency is respectively 6.9GHz, 10.65GHz,
18.7GHz, 23.8GHz, 36.5GHz, 89.0GHz, because ice and water emissivity under 18.7GHz passages differ greatly (Che
Deng 2009；Tao etc., 2014), therefore the present invention is main based on the V polarization datas of 18.7GHz, wherein 18.7GHz's is original
The resolution ratio 27*16km of data.
The Landsat TM image datas are by Landsat-5 moonscopes gained.The Landsat-5 satellites are in 1984
Successful launch carried TM (Thematic Mapper) sensor of 30*30m spatial resolutions to operational failure in 2011.
Landsat-5 satellites continue apparent survey over the ground during running, and obtain a large amount of earth's surface overlay areas comprehensively, high-quality history
Data, are resource management, ECOLOGICAL ENVIRONMENTAL MONITORING, and geologic survey etc. is there is provided abundant data resource.The present invention is utilized
Landsat-5 data and the AMSR-E pixel that passes by are laid out analysis, calculate lake loke shore area ratio in AMSR-E pixels.
The AMSR-E data of the enhancing resolution ratio are by U.S.'s Brigham Young University (Brigham Young
University, BYU) microwave remote sensing earth team (Microwave Earth Remote Sensing group, MERS)
Using AMSR-E data combination scatterometer image according to image reconstruction algorithm (Long etc., 1998；Early etc., 2001) generation
Strengthen the image of resolution ratio.The AMSR-E data of the enhancing resolution ratio are different in the spatial resolution of different frequency, wherein
The resolution ratio of 6GHz, 10GHz, 18GHz passage is 7.5* for the resolution ratio of 12.5*12.5km, 23GHz and 36GHz passage
The resolution ratio of 7.5km, 89GHz passage is 2.5*2.5km.The present invention is differentiated from the enhancing of globular projection 18.7GHz V polarization
The AMSR-E data pick-ups of rate up to then it is wrong with visit the lake bright temperature of inviting cloth mistake and compare data as effect.
Day by day the cloudless MODIS data be Qinghai-Tibet Platean MODIS day by day cloudless Snow Cover Area data set (Qiu Yubao etc.,
2016) product cloudless day by day developed according to MOD10A1 and MYD10A1 in a text.The Qinghai-Tibet MODIS cloudless products day by day
Snow face volume data is concentrated includes that land, accumulated snow, lake water and lake ice lake do not know the terrain classification of these four Regional Sustainable Development of The Qinghai tibet Plateau.
Base of the present invention is verified using the lake water and lake ice situation of change of the Qinghai-Tibet MODIS cloudless Snow Cover Area data sets day by day
In dynamic Decomposition of Mixed Pixels method lake ice freeze thawing monitoring method lake freezing-thawing condition to monitoring result.
As shown in figure 1, a kind of lake ice freeze thawing monitoring method based on dynamic Decomposition of Mixed Pixels method of the present invention, including：
S1, based on lake particular optical image and passive microwave remote sensing data, obtains the bright temperature value of lake mixed pixel and lake
The bright temperature value of bank Pure pixel；
S2, based on lake particular optical image and the bright temperature value of lake mixed pixel, obtains described by Overlap Analysis
The area ratio of lake and loke shore in the mixed pixel of lake；
S3, based on the bright temperature value of lake mixed pixel, the bright temperature value of loke shore Pure pixel and the lake mixing picture
Lake and loke shore area ratio, the pure picture in lake of the lake mixed pixel is obtained using linear spectral unmixing method in unit
The bright temperature value of unit, to monitor lake ice freeze thawing phenomenon.
Passive microwave remote sensing data described in the present embodiment is AMSR-E passive microwave remote sensing datas；The particular optical image
It is high-resolution optical image, specially Landsat TM image datas.
The spatial resolution of passive microwave remote sensing data is low, and single pixel can capture several different types of topographical features
Information, mixed pixel effect is serious.Passive microwave sensor be also subject to during earth's surface information is obtained it is some other because
Element influence, including the produced irrelevant signal of polarization effect etc. of calibration calibration, the energy radiation of sensor, and from it is outer
Space energy radiates the influence with earth atmosphere.
The present embodiment selects AMSR-E L2A bright temperature datas, the AMSR-E L2A bright temperature datas to provide flat via data
Platform has carried out radiation calibration basic handling related to information smoothing etc..The land of the single pixel of the AMSR-E L2A bright temperature datas
The bright temperature value of table, by the area weight integral representation of the true bright temperature value of each atural object being distributed in the pixel, formula is as follows：
Formula (1) represents the bright temperature TB ' (x that passive microwave sensor is received0, yo) it is by detecting center (x0, yo)
The bright temperature TB (x, y) of each atural object in pixel integrates what is asked for by area weight,It is the antenna gain of sensor.
The present invention is analyzed using the passive microwave remote sensing data, with reference to the lake particular optical image to described
Lake in the pixel of passive microwave remote sensing data carries out the positioning of position and coordinate, it is first determined the bright temperature value of lake mixed pixel
With the bright temperature value of loke shore Pure pixel；Lake and loke shore ratio in the lake mixed pixel are further determined that, so as to obtain lake
The bright temperature value of Pure pixel.The bright temperature value of lake Pure pixel is the most important data for monitoring lake ice freeze thawing phenomenon.
Used as an optional embodiment, the S1 is further included：
S1.1, the edge in lake is obtained using edge detection method from the lake particular optical image；Based on the lake
Pool particular optical image and the pixel position comparative analysis of the passive microwave remote sensing data and the edge in the lake, obtain institute
State the lake center of passive microwave remote sensing data；
S1.2, from the passive microwave remote sensing data, the nearest bright temperature of microwave pixel of lake center described in selected distance
It is the bright temperature value of lake mixed pixel to be worth；From the passive microwave remote sensing data, lake center is nearest described in selected distance
Multiple loke shore Pure pixels the bright temperature value of microwave pixel, be the bright temperature value of loke shore Pure pixel after taking average.
Passive microwave remote sensing data is too low due to image resolution ratio, therefore the present embodiment utilizes high-resolution Landsat
The position in corresponding lake in TM image datas, is compared point with the position in the lake of the pixel of the passive microwave remote sensing data
Analysis, determines lake center in the pixel of the passive microwave remote sensing data.
The lake region earth's surface information detected when satellite passes by, it will usually be recorded centrally in neighbouring several pixels,
And the latitude and longitude coordinates of microwave pixel centre coordinate point fine difference can all occur when revisiting every time；And passive microwave remote sensing number
According to resolution ratio it is low, therefore with high-resolution lake particular optical image be contrast, be compared analysis.Make described passive micro-
Lake and loke shore in lake and loke shore pixel in the pixel of ripple remotely-sensed data and high-resolution lake particular optical image
Image positional relationship coincidence of trying one's best it is consistent；As long as during the lake in high-resolution lake particular optical image is so determined
Heart point, it is possible to the central point in lake in the pixel of the passive microwave remote sensing data is obtained according to corresponding position relationship, is entered
And obtain the coordinate of lake center point, i.e., the lake center in the pixel of described passive microwave remote sensing data.
After determining lake center, one or more the microwave pixels with where the lake are the bright temperature of lake mixed pixel
Value, includes the bright temperature value in pure lake and the bright temperature value of pure loke shore in the bright temperature value of lake mixed pixel.
Choose from lake center enough away from pixel obtain the bright temperature value of loke shore Pure pixel.Because the limited area in lake,
As long as so choosing pixel remote enough is obtained with pure loke shore, so as to obtain the bright temperature value of loke shore Pure pixel.
Used as an optional embodiment, the S2 is further included：
S2.1, based on passive microwave remote sensing data, obtains lake mixed pixel；With in the lake of the lake mixed pixel
The rectangular area of the spatial resolution of particular sensor CF is generated centered on the heart；
S2.2, analysis is laid out based on the rectangular area with the lake particular optical image, decomposites the lake
The ratio of lake and loke shore in pool mixed pixel.
Passive microwave remote sensing data selected by the present embodiment observes data observation gained by microwave radiance transfer spoke meter, and
Satellite is in the state of constantly motion in air to surface scanning process high with the earth, therefore during sensor is revisited, sees every time
Pixel position can all occur minor shifts in the passive microwave remote sensing data for measuring, and the lake for being captured/loke shore area is ceaselessly
Change, in addition to the lake that area is far smaller than pixel resolution.Therefore the observation data repeatedly passed by satellite are needed
Comprehensive analysis is carried out, and analysis is laid out with reference to high-resolution Landsat TM image datas, determine the lake mixing
The ratio of lake and loke shore in pixel.
Specifically, the bright temperature value of lake Pure pixel described in the S3 meets：
TBsensor=aTBlake+bTBland (2)
Wherein, TBsensorIt is the bright temperature of lake mixed pixel of the single microwave pixel of the bright temperature value of lake mixed pixel
Value；
TBlakeIt is the bright temperature value of lake Pure pixel, lake region is bright in representing the bright temperature value of lake mixed pixel
Temperature value；
TBlandIt is the bright temperature value of loke shore Pure pixel, represents that lake mixed pixel bright temperature value Mid-continent domain is bright
Temperature value；
A is the area weight of lake region in the bright temperature value of lake mixed pixel；
B is the area weight in lake mixed pixel bright temperature value Mid-continent domain；
Wherein, the ratio of a and b is the ratio of lake and loke shore in the lake mixed pixel.
The present invention carries out linear spectral unmixing based on area of lake, wherein assuming what passive microwave radiometer was captured
Land table information is homogeneous, and the earth's surface land information for being obtained is only relevant with the area of atural object, ignores the less factor of other influences.
The bright temperature of the bright temperature in lake region and land area in formula (2) all includes the influence of the factors such as air, and lake face
Product weight a and loke shore area weight b is calculated by high-resolution Landsat TM optical images.
Used as an optional embodiment, the S1.2 is further included：Choose 1 centered on the lake center
The bright temperature value of microwave pixel is the bright temperature value of lake mixed pixel；
The bright temperature value of microwave pixel of the nearest 2-3 of lake center described in selected distance pure loke shore pixels and do it is average after
It is the bright temperature value of loke shore Pure pixel.
Specifically, the coordinate of the lake mixed pixel meets：
Wherein, (X, Y) is the coordinate of the lake center, (Xi, Yi) be the passive microwave remote sensing data any pixel
The coordinate of central point, (Xmin,Ymin) it is spaceborne bright temperature data coordinate corresponding to the bright temperature value of lake mixed pixel.
Used as an optional embodiment, the S2.1 is further included：
S2.1.1, generates the first border circular areas and the second border circular areas respectively centered on the lake center；
S2.1.2, obtains the minimum outsourcing rectangle of first border circular areas and second border circular areas, based on isogonism
Transverse axis cyclotomy post projection coordinate system characteristic, obtains the specific microwave frequency pixel resolution with the passive microwave remote sensing data
The rectangular area of the same size.
The size of the size of first border circular areas and second border circular areas is according to the passive microwave remote sensing number
According to a Pixel size difference and choose different sizes；Whether which kind of size, the present embodiment is justified by described first
What the isogonism transverse axis cyclotomy post projection coordinate system characteristic of the minimum outsourcing rectangle of shape region and second border circular areas was obtained
The rectangular area is equal with a Pixel size of the passive microwave remote sensing data.
Specifically, the radius of first border circular areas is a spatial resolution value of specific microwave frequency, described second
The radius of border circular areas is another spatial resolution value of specific microwave frequency.
The present embodiment uses passive microwave sensors A MSR-E pixels, and the pixel size of the AMSR-E pixels is 27*16
Kilometer a, spatial resolution value is 16 kilometers, and another spatial resolution value is 27 kilometers, therefore described first circular
The radius in region is 8 kilometers, and the radius of second border circular areas is 13.5 kilometers.
By the area of lake that passive microwave sensors A MSR-E pixels are captured is not stop change, in order to accurately obtain
Lake and weight of the loke shore in each pixel, the present embodiment delay centered on from the closest AMSR-E pixels point of lake center
A rectangular area of 27*16km is gone out, the lake lake that each satellite revisits pixel is then gone out by Overlap Analysis dynamic calculation
Bank area weight.The lake that will finally obtain substitutes into formula (2) with the ratio of loke shore, decomposites lake region in each pixel
Bright temperature value.
The present embodiment first buffers into two border circular areas in WGS84 projection coordinates system using a bit：
First border circular areas are expressed as：(Xi-a)2+(Yi-b)2=82
Second border circular areas are expressed as：(Xi-a)2+(Yi-b)2=13.52
The minimum outsourcing rectangle of two circles is asked for again, then according to isogonism transverse axis cyclotomy post projection coordinate system characteristic, is obtained
27*16km rectangle IJKL are obtained, as shown in Figure 2.Finally calculate the satellite rectangle IJKL that passes by daily, and with it is high-resolution
Landsat TM optical image Overlap Analysis, dynamic Decomposition goes out the ratio in loke shore and lake.
As shown in figure 3, the present invention also provides a kind of lake ice freeze thawing monitoring system based on dynamic Decomposition of Mixed Pixels method, bag
Include：
Preliminary bright temperature data acquisition module, for based on lake particular optical image and passive microwave remote sensing data, obtaining
The bright temperature value of lake mixed pixel and the bright temperature value of loke shore Pure pixel；
Lake and land percentage module, for based on lake particular optical image and the bright temperature of lake mixed pixel
Value, the area ratio of lake and loke shore in the lake mixed pixel is obtained by Overlap Analysis；
The accurate acquisition module of dynamic, for based on the bright temperature value of lake mixed pixel, the bright temperature of loke shore Pure pixel
Lake and loke shore area ratio in value and the lake mixed pixel, obtain the lake and mix using linear spectral unmixing method
The bright temperature value of lake Pure pixel of pixel is closed, to monitor lake ice freeze thawing phenomenon.
It is beneficial that the present invention a kind of lake ice freeze thawing monitoring method and system based on dynamic Decomposition of Mixed Pixels method are reached
Effect can be obtained by following comparative analysis.
(1) Contrast on effect of mixed pixel dynamic Decomposition result
Fig. 4 a- Fig. 4 g, Fig. 4 a be refer to for the bright temperature schematic diagram in Qinghai Lake long-term sequence lake of the present invention, figure ba is this hair
The bright bright temperature schematic diagram in Hoh Xil Lake long-term sequence lake, Fig. 4 c illustrate for the present invention up to the then wrong bright temperature in long-term sequence lake
Figure, Fig. 4 d are the bright temperature schematic diagram in Sai Ku lakes long-term sequence lake of the present invention, and Fig. 4 e are Ba Mu of the present invention mistake long-term sequences lake
Bright temperature schematic diagram is moored, Fig. 4 f invite the bright temperature schematic diagram in cloth mistake long-term sequence lake for the present invention is visitd, and Fig. 4 g are hole of the present invention wrong long
The bright temperature schematic diagram in time series lake.
Using Decomposition of Mixed Pixels method to Hoh Xil Lake, up to then mistake, Sai Kuhu, Ba Mu are wrong, visit and invite cloth wrong and hole is wrong
The bright temperature in lake region of (wherein Qinghai Lake is served only for contrast) carries out resolution process at six.Utilization is can be seen that from Fig. 4 a- Fig. 4 g
The bright temperature curve of lake long-term sequence that mixed pixel linear dynamic decomposition method is obtained is than the original bright temperature curve of mixed pixel
The real features of lake freeze thawing change can more be protruded.Wherein effect is the most significantly that visiing for Fig. 4 f invites cloth wrong, using AMSR-E
Original bright temperature data can not detect the bright temperature variation characteristic of the lake freeze thawing substantially, but be processed by mixed pixel linear decomposition
Afterwards, the bright temperature curve in its long-term sequence lake is similar with the bright temperature curvilinear motion feature in large-size lake Qinghai, and discomposing effect is good.
But from the point of view of the bright temperature curve after the wrong pixel analysis treatment in Fig. 4 g holes, its effect is not it is obvious that having more
Noise, by Fourier filtering treatment after its lake freeze thawing variation characteristic effect trend it is also not too much obvious.In Fig. 4 a- Fig. 4 g
Mixed pixel linear decomposition method be can be seen that in the lake object area about AMSR-E pixels 0.3 for being detected, its discomposing effect
Already close to the limit.
(2) enhancing resolution ratio bright temperature data compares analysis
In order to further analyze the practicality of lake Decomposition of Mixed Pixels method, the MERS team agglomerations of U.S. BYU are quoted
Resolution ratio is analyzed for the AMSR-E 18.7GHz V polarization datas of the enhancing resolution ratio of 12.5*12.5km.
Selection invites wrong two lakes of cloth example as a comparison with visiing up to then wrong, and Fig. 5 a are the present invention to up to two kinds of then wrong letters
The breath bright temperature contrast schematic diagram in Enhancement Method lake；Fig. 5 b are the present invention to visiing two kinds of bright temperature in information enhancement method lake for inviting cloth wrong
Contrast schematic diagram.From up to then it is wrong with visit the bright temperature curve in lake of inviting cloth two AMSR-E data of the enhancing resolution ratio in lake of mistake can
Find out, the AMSR-E data for strengthening resolution ratio highlight not obvious humidification for lake freeze thawing characteristic signal.From
Seen up to the then bright temperature curve in wrong lake, although the AMSR-E data of enhancing resolution ratio can be from the bright temperature for generally distinguishing the lake reluctantly
Freeze thawing characteristic information, but its data noise is more；And from the point of view of smaller lake is visitd and invites cloth mistake, strengthen the AMSR-E numbers of resolution ratio
Its lake freeze thawing characteristic signal is shown according to that can not embody.Find that Decomposition of Mixed Pixels method is supervised for lake freeze thawing by comparing
Surveying in application will more be applicable than combining the method for other image reconstructions enhancing AMSR-E resolution ratio.
(3) Contrast on effect that Decomposition of Mixed Pixels freeze thawing differentiates
After Decomposition of Mixed Pixels treatment is carried out to the bright temperature of lake region pixel, using TIMESAT (Time-series of
Satellite sensor data) software extraction lake freeze thawing parameter.TIMESAT software systems are initially to be applied to treatment length
The NDVI data of time series, are changed with the cyclical growth for monitoring plant[25][26].In view of TIMESAT software systems have soon
The ability of the long-term sequence data of speed treatment seasonal variety and the bright temperature changed in lake freeze thawing with reference to passive microwave data
Periodic law, lake bright temperature data is embedded into the software algorithm, and combining simple visually correction using the software systems carries
Take lake freeze thawing parameter.
Passive microwave data lake freeze thawing parameter extraction out after, with Qinghai-Tibet MODIS cloudless accumulated snow faces day by day
, used as checking data, up to then mistake, storehouse match lake is with Hoh Xil Lake as checking lake for selection for volume data collection.By to Qinghai-Tibet Platean
MODIS cloudless Snow Cover Area data set, mask cuttings day by day, the MODIS lakes ice/water area change for obtaining long-term sequence is bent
Line, lake freeze thawing parameter is extracted by using coverage of water 90% and 20% as threshold value.Empirical tests, are carried using AMSR-E data
Freeze to melt the Pearson correlation coefficients point of result with lake in the lake that the lake freeze thawing result for taking is extracted with the cloudless data of MODIS
Wei 0.968 and 0.987.
The application is based on mixed pixel dynamic linear decomposition principle, based on high-resolution optical image, invention
A kind of dynamic mixed pixel decomposition method of lake ice freeze thawing microwave information, can be applied to the satellite-borne microwave sensing of middle low resolution
Device, such as AMSR-E, greatly expand the application power of passive microwave mixed pixel, it is can be used for middle small lakes freeze thawing parameter
Extract, the contrast verification that lake ice freeze thawing is monitored, the Pearson of its freeze thawing time are carried out by cloudless MODIS snow ices data day by day
Coefficient correlation is more than 0.96, it is believed that the method precision that paper is proposed is higher.
Being analyzed by Comparative result to obtain：Compare through the AMSR-E bright temperature datas with enhancing resolution ratio, using mixing
Pixel dynamic Decomposition method is in terms of lake freeze thawing information enhancement than combining increasing of the scatterometer image according to image reconstruction algorithm
Strong result is more applicable.Mixed pixel dynamic Decomposition method can be generally applicable to area of lake and account for the single pixels more than 30% of AMSR-E
Lake, apply in lake pixel scale.
It is special by speciality itself and loke shore surrounding geographical environment in lake shape and lake during lake between 20~30%
Influence is levied, discomposing effect has certain uncertainty；Analyzed by the mixed pixel dynamic Decomposition method to SSMIS data, knot
Fruit shows that the method can be applied in different historical datas and the now data of development higher resolution.The method is equally
It is applicable to the freeze thawing monitoring of other water in cold regions body surface types, such as bay sea ice freeze thawing monitoring, or elongated river
River ice is monitored, such as yellow river ice flood monitoring and warning.
Current passive microwave remote sensing data is in the situation that many stars continuously acquire data, and the method for the invention can dash forward
The spatial resolution precision limitation of broken data in itself, obtains the freeze thawing information of more lake ice to greatest extent, or when next
In generation, more high-resolution passive microwave data provided the monitoring thinking of enhancing freeze thawing information.
Finally, the present processes are only preferably embodiment, are not intended to limit the scope of the present invention.It is all
Within the spirit and principles in the present invention, any modification, equivalent substitution and improvements made etc. should be included in protection of the invention
Within the scope of.
Claims (9)
1. a kind of lake ice freeze thawing monitoring method based on dynamic Decomposition of Mixed Pixels method, it is characterised in that including：
S1, based on lake particular optical image and passive microwave remote sensing data, obtains the bright temperature value of lake mixed pixel and loke shore is pure
The bright temperature value of net pixel；
S2, based on lake particular optical image and the bright temperature value of lake mixed pixel, the lake is obtained by Overlap Analysis
The area ratio of lake and loke shore in mixed pixel；
S3, based in the bright temperature value of lake mixed pixel, the bright temperature value of loke shore Pure pixel and the lake mixed pixel
Lake and loke shore area ratio, the lake Pure pixel for obtaining the lake mixed pixel using linear spectral unmixing method are bright
Temperature value, to monitor lake ice freeze thawing phenomenon.
2. the method for claim 1, it is characterised in that the S1 is further included：
S1.1, the edge in lake is obtained using edge detection method from the lake particular optical image；It is special based on the lake
Determine optical image and the pixel position comparative analysis of the passive microwave remote sensing data and the edge in the lake, obtain the quilt
The lake center of dynamic microwave remote sensing data；
S1.2, from the passive microwave remote sensing data, the nearest bright temperature value of microwave pixel of lake center described in selected distance is
The bright temperature value of lake mixed pixel；From the passive microwave remote sensing data, nearest many of lake center described in selected distance
The bright temperature value of microwave pixel of individual loke shore Pure pixel, is the bright temperature value of loke shore Pure pixel after taking average.
3. method as claimed in claim 2, it is characterised in that the S2 is further included：
S2.1, based on passive microwave remote sensing data, obtains lake mixed pixel；Lake center with the lake mixed pixel is
It is centrally generated the rectangular area of the spatial resolution of particular sensor CF；
S2.2, analysis is laid out based on the rectangular area with the lake particular optical image, is decomposited the lake and is mixed
Close the ratio of lake and loke shore in pixel.
4. method as claimed in claim 3, it is characterised in that the bright temperature value of lake Pure pixel described in the S3 meets：
TBsensor=aTBlake+bTBland
Wherein, TBsensorIt is the bright temperature value of lake mixed pixel of the single microwave pixel of the bright temperature value of lake mixed pixel；
TBlakeIt is the bright temperature value of lake Pure pixel, represents the bright temperature value in lake region in the bright temperature value of lake mixed pixel；
TBlandIt is the bright temperature value of loke shore Pure pixel, represents the bright temperature value in lake mixed pixel bright temperature value Mid-continent domain；
A is the area percentage weight of lake region in the bright temperature value of lake mixed pixel；
B is the area percentage weight in lake mixed pixel bright temperature value Mid-continent domain；
Wherein, the ratio of a and b is the area ratio of lake and loke shore in the lake mixed pixel.
5. method as claimed in claim 2, it is characterised in that the S1.2 is further included：Choose with the lake center
Centered on 1 bright temperature value of microwave pixel be the bright temperature value of lake mixed pixel；
The bright temperature value of microwave pixel of the nearest 2-3 of lake center described in selected distance pure loke shore pixels and do it is average after be institute
State the bright temperature value of loke shore Pure pixel.
6. the method as described in claim 2 or 5, it is characterised in that the coordinate of the lake mixed pixel meets：
Wherein, (X, Y) is the coordinate of the lake center, (Xi,Yi) be the passive microwave remote sensing data any pixel center
The coordinate of point, (Xmin,Ymin) it is spaceborne bright temperature data coordinate corresponding to the bright temperature value of lake mixed pixel.
7. method as claimed in claim 3, it is characterised in that the S2.1 is further included：
S2.1.1, generates the first border circular areas and the second border circular areas respectively centered on the lake center；
S2.1.2, obtains the minimum outsourcing rectangle of first border circular areas and second border circular areas, based on isogonism transverse axis
Cyclotomy post projection coordinate system characteristic, obtains the specific microwave frequency pixel resolution size with the passive microwave remote sensing data
The consistent rectangular area.
8. method as claimed in claim 7, it is characterised in that the radius of first border circular areas is specific microwave frequency
One spatial resolution value, the radius of second border circular areas is another spatial resolution value of specific microwave frequency.
9. a kind of lake ice freeze thawing monitoring system based on dynamic Decomposition of Mixed Pixels method, it is characterised in that including：
Preliminary bright temperature data acquisition module, for based on lake particular optical image and passive microwave remote sensing data, obtaining lake
The bright temperature value of mixed pixel and the bright temperature value of loke shore Pure pixel；
Lake and land percentage module, for based on lake particular optical image and the bright temperature value of lake mixed pixel, leading to
Cross the area ratio that Overlap Analysis obtain lake and loke shore in the lake mixed pixel；
The accurate acquisition module of dynamic, for based on the bright temperature value of lake mixed pixel, the bright temperature value of loke shore Pure pixel and
Lake and loke shore area ratio, the lake mixing picture is obtained using linear spectral unmixing method in the lake mixed pixel
The bright temperature value of lake Pure pixel of unit, to monitor lake ice freeze thawing phenomenon.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107749144A (en) * | 2017-09-28 | 2018-03-02 | 成都理工大学 | A kind of flood level method for early warning of ice-lake breach and its application |
| CN107749144B (en) * | 2017-09-28 | 2019-11-22 | 成都理工大学 | A kind of flood level method for early warning of ice-lake breach and its application |
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| CN113252183A (en) * | 2021-07-06 | 2021-08-13 | 河南工业大学 | Processing method of 89GHz data for Antarctic ice cover surface snow melting detection |
| CN113610708A (en) * | 2021-07-28 | 2021-11-05 | 国家卫星气象中心(国家空间天气监测预警中心) | Mapping method and device for passive satellite remote sensing flood information |
| CN113610708B (en) * | 2021-07-28 | 2023-11-17 | 国家卫星气象中心(国家空间天气监测预警中心) | Imaging method and device for passive microwave remote sensing flood information |
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