CN107782700B - A kind of AVHRR Reflectivity for Growing Season method for reconstructing, system and device - Google Patents
A kind of AVHRR Reflectivity for Growing Season method for reconstructing, system and device Download PDFInfo
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Abstract
The present invention provides a kind of AVHRR Reflectivity for Growing Season method for reconstructing, system and device, which comprises is removed invalid value processing to original ground surface reflectivity data；The synthesis processing of specified time resolution ratio is carried out to effective original ground surface reflectivity data that processing obtains；Based on the synthesis earth's surface reflectivity data that synthesis processing obtains, normalized differential vegetation index NDVI is calculated, and is based on the NDVI, rebuilds NDVI coenvelope line using given algorithm；Based on the NDVI and the NDVI coenvelope line, cloud detection is carried out to the synthesis earth's surface reflectivity data, removes the data influenced by cloud；The resulting remaining data of data and the NDVI coenvelope line are influenced by cloud based on removal, by Function Fitting, obtains the calculating reflectivity data of any time in specified time, the continuous Reflectivity for Growing Season of reconstruction time.The cloud that the present invention can be effectively removed on the basis of not influencing versatility in Reflectivity for Growing Season reconstruction interferes and carries out Missing Data Filling.
Description
Technical field
The present invention relates to technical field of data processing, more particularly, to a kind of AVHRR Reflectivity for Growing Season method for reconstructing,
System and device.
Background technique
The AVHRR sensor being mounted on NOAA satellite obtains global image daily, provides a large amount of monitoring atmosphere, sea
Foreign, vegetation and land table characteristic spectral information, forms the long-time whole world image sequence of a daily resolution ratio.
Based on AVHRR data, using different data processing method, multiple long-term sequence data sets have been generated at present,
These data sets have different spatial and temporal resolution and time span.Wherein, most representative a set of long-term sequence data
Collection is the global NDVI and Reflectivity for Growing Season by the daily resolution ratio of the LTDR project construction.But LTDR AVHRR NDVI and ground
It include a large amount of cloud interference information in table reflectivity product, and the NDVI of some times and Reflectivity for Growing Season data lack completely
It loses.The seriously polluted application for constraining these products in the monitoring of land table of Reflectivity for Growing Season and NDVI product medium cloud etc., and
It will lead to the space-time inconsistency of Remote sensing parameters high-grade products.
In view of the above-mentioned problems, there are many method for rebuilding NDVI time-serial position, generally speaking these methods at present
Time-domain and frequency domain method two major classes can be divided into.A kind of wherein TSCD algorithm of the propositions such as Tang, it is anti-for MODIS earth's surface
Penetrate cloud detection and the Missing Data Filling of rate data.TSCD algorithm can obtain good effect in earth's surface stabilization or slow variation
Fruit, but this method depends on the reflectivity data and other associated ancillary informations of blue wave band.Therefore, TSCD algorithm is difficult directly
Connect the cloud detection for AVHRR data and data reconstruction.
Summary of the invention
In order to overcome the above problem or at least be partially solved the above problem, it is anti-that the present invention provides a kind of AVHRR earth's surface
Penetrate rate method for reconstructing, system and device, with reach effectively remove AVHRR Reflectivity for Growing Season rebuild in cloud interfere and lacked
It is worth the purpose of filling.
In a first aspect, the present invention provides a kind of AVHRR Reflectivity for Growing Season method for reconstructing, comprising: S1, it is regular based on setting,
Invalid value processing is removed to original ground surface reflectivity data, obtains effective original ground surface reflectivity data；S2 has to described
The synthesis processing that original ground surface reflectivity data carries out specified time resolution ratio is imitated, synthesis earth's surface reflectivity data is obtained；S3, base
In the synthesis earth's surface reflectivity data, normalized differential vegetation index NDVI is calculated, and is based on the NDVI, utilizes given algorithm weight
Build NDVI coenvelope line；S4 is based on the NDVI and the NDVI coenvelope line, using given decision condition, to the synthesis
Reflectivity for Growing Season data carry out cloud detection, remove the data influenced by cloud, obtain the Reflectivity for Growing Season for meeting credit rating requirement
Data；S5 passes through letter based on the Reflectivity for Growing Season data for meeting credit rating requirement and the NDVI coenvelope line
Number fitting, obtains the calculating reflectivity data of any time in specified time, the continuous Reflectivity for Growing Season of reconstruction time.
Wherein, if the red spectral band reflectivity that setting rule described in step S1 includes: any pixel point is greater than the picture
The near infrared band reflectivity of member point, then determine that the Reflectivity for Growing Season of the pixel point is invalid value；And/or if any pixel point
Red spectral band and near infrared band enhancing vegetation index be greater than NDVI, then determine that the Reflectivity for Growing Season of the pixel point is invalid
Value.
Wherein, the step of S2 further comprises: if in the synthesis window of the specified time resolution ratio, exist to
Few two effective original ground surface reflectivity datas synthesize institute then using the NDVI maximum value synthetic method of observation angle constraint
State effective original ground surface reflectivity data；Alternatively, if there are described in one in the synthesis window of the specified time resolution ratio
Effective original ground surface reflectivity data, then as the synthesis earth's surface reflectivity data；Alternatively, if in the specified time
In the synthesis window of resolution ratio, effective original ground surface reflectivity data is not present, then with effective original in the specified time limit
The mean value of beginning Reflectivity for Growing Season data is as the synthesis earth's surface reflectivity data.
Wherein, the NDVI maximum value synthetic method constrained using observation angle synthesizes effective original ground surface reflection
The step of rate data, further comprises: anti-to effective original ground surface in the synthesis window of the specified time resolution ratio
The view zenith angle for penetrating rate data is arranged by sequence from small to large；Based on two observation the smallest in the sequence
The corresponding effective original ground surface reflectivity data of zenith angle, calculates separately corresponding NDVI；Choose biggish institute in the two
The corresponding effective original ground surface reflectivity data of corresponding NDVI is stated, as the synthesis earth's surface reflectivity data.
Wherein, described in step S3 based on the NDVI, the step of rebuilding NDVI coenvelope line using given algorithm into
One step includes:, by interative computation, to be minimized given using the penalized least-squares Return Law based on Three-dimensional DCT
The first cost function comprising time series of NDVI value vector, obtain optimal time sequence NDVI value vector estimate；Based on institute
The estimation of optimal time sequence NDVI value vector is stated, the NDVI coenvelope line is constructed.
Wherein, the step of S4 further comprises: being based on the corresponding NDVI of the synthesis earth's surface reflectivity data, successively
Judge whether any moment NDVI meets given decision condition as follows:
|NDVIi-NDVI_Envi| > α × NDVI_Envi；
In formula, NDVIiIndicate the NDVI value at the i-th moment, NDVI_EnviIndicate the NDVI at the i-th moment of NDVI coenvelope line
Value, α indicate given threshold；
If judgement knows that the i-th moment NDVI meets the given Rule of judgment, determine that the i-th moment NDVI is corresponding
Synthesizing earth's surface reflectivity data is the data influenced by cloud；Remove described is influenced in the synthesis earth's surface reflectivity data by cloud
Data, the Reflectivity for Growing Season data of credit rating requirement are met described in acquisition.
Wherein, the step of S5 further comprises: based on it is described meet credit rating requirement Reflectivity for Growing Season data,
Acquisition time sequence infrared and near infrared band reflectivity point set；Based on described infrared and near infrared band reflectivity point set, with
And the NDVI coenvelope line minimizes the second cost function by interative computation, fitting is given using quadratic polynomial function
The Reflectivity for Growing Season data for meeting credit rating requirement, the calculating for obtaining any time in specified time are anti-in time window
Penetrate rate data；The calculating reflectivity data based on any time, the earth's surface for rebuilding Time Continuous in the specified time are anti-
Penetrate rate.
Wherein, the specified time resolution ratio is 8 days resolution ratio.
Second aspect, the present invention provide a kind of AVHRR Reflectivity for Growing Season reconstructing system, comprising: data preprocessing module is used
In based on setting rule, invalid value processing is removed to original ground surface reflectivity data, obtains effective original ground surface reflectivity
Data；Valid data synthesis module, for carrying out the conjunction of specified time resolution ratio to effective original ground surface reflectivity data
At processing, synthesis earth's surface reflectivity data is obtained；NDVI coenvelope line rebuilds module, for being based on the synthesis Reflectivity for Growing Season
Data calculate normalized differential vegetation index NDVI, and are based on the NDVI, rebuild NDVI coenvelope line using given algorithm；Yun Jian
Module is surveyed, for being based on the NDVI and the NDVI coenvelope line, using given decision condition, to the synthesis earth surface reflection
Rate data carry out cloud detection, remove the data influenced by cloud, obtain the Reflectivity for Growing Season data for meeting credit rating requirement；Earth's surface
Reflectivity rebuilds module, for wrapping based on the Reflectivity for Growing Season data for meeting credit rating requirement and on the NDVI
Winding thread obtains the calculating reflectivity data of any time in specified time by Function Fitting, and the continuous earth's surface of reconstruction time is anti-
Penetrate rate.
The third aspect, the present invention provide a kind of AVHRR Reflectivity for Growing Season reconstructing device, comprising: at least one processor, extremely
A few processor, communication interface and bus；The memory, the processor and the communication interface are complete by the bus
At mutual communication, the communication interface is for the AVHRR Reflectivity for Growing Season reconstructing device and original ground surface reflectivity number
According to the information transmission between storage equipment；The computer program that can be run on the processor is stored in the memory,
The processor realizes Reflectivity for Growing Season method for reconstructing as discussed when executing described program.
A kind of AVHRR Reflectivity for Growing Season method for reconstructing, system and device provided by the invention, to daily temporal resolution
AVHRR Reflectivity for Growing Season data polymerize on the basis of, the NDVI coenvelope line of continuously smooth in reconstruction time sequence, and
NDVI and its coenvelope line based on time series detect the reflectivity influenced by cloud, finally with continuously smooth in time series
NDVI coenvelope line is constraint, carries out the reconstruction of the Reflectivity for Growing Season of the Reflectivity for Growing Season Time Continuous based on high quality, can
The cloud effectively removed in Reflectivity for Growing Season reconstruction interferes and can effectively carry out Missing Data Filling.Simultaneously because the present invention independent of
Any auxiliary information, equally can be general effective for the reconstruction of the different sensing datas such as MODIS, VIIRS, FY, Landsat
Property is strong, has broad application prospects.
Detailed description of the invention
Fig. 1 is a kind of flow chart of AVHRR Reflectivity for Growing Season method for reconstructing of the embodiment of the present invention；
Fig. 2 is that the embodiment of the present invention is a kind of effective primitively using the NDVI maximum value synthetic method synthesis of observation angle constraint
The process flowchart of table reflectivity data；
Fig. 3 is a kind of process flowchart for rebuilding NDVI coenvelope line of the embodiment of the present invention；
Fig. 4 is a kind of process flowchart of cloud detection of the embodiment of the present invention；
Fig. 5 is that the embodiment of the present invention is a kind of based on the Reflectivity for Growing Season data and NDVI coenvelope that meet credit rating requirement
The process flowchart of line reconstruction Reflectivity for Growing Season；
Fig. 6 is a kind of structural schematic diagram of AVHRR Reflectivity for Growing Season reconstructing system of the embodiment of the present invention；
Fig. 7 is a kind of structural block diagram of AVHRR Reflectivity for Growing Season reconstructing device of the embodiment of the present invention；
Fig. 8 is the l-G simulation test flow chart that AVHRR NDVI and Reflectivity for Growing Season are rebuild according to the embodiment of the present invention；
Fig. 9 (a) is 1992 to 2005 area the Zhangbei vegetation pattern websites rebuild according to the embodiment of the present invention
The NDVI and Reflectivity for Growing Season time series simulation curve of LTDR AVHRR and GLASS AVHRR and SG AVHRR NDVI's
Time series simulation curve；
Fig. 9 (b) is 1992 to 2005 area the Yucheng vegetation pattern websites rebuild according to the embodiment of the present invention
The NDVI and Reflectivity for Growing Season time series simulation curve of LTDR AVHRR and GLASS AVHRR and SG AVHRR NDVI's
Time series simulation curve；
Fig. 9 (c) is 1992 to 2005 area the Puechabon vegetation pattern websites rebuild according to the embodiment of the present invention
The NDVI and Reflectivity for Growing Season time series simulation curve of LTDR AVHRR and GLASS AVHRR and SG AVHRR NDVI's
Time series simulation curve；
Fig. 9 (d) is 1992 to 2005 area the Larose vegetation pattern websites rebuild according to the embodiment of the present invention
The NDVI and Reflectivity for Growing Season time series simulation curve of LTDR AVHRR and GLASS AVHRR and SG AVHRR NDVI's
Time series simulation curve；
Fig. 9 (e) is 1992 to 2005 area the Wankama vegetation pattern websites rebuild according to the embodiment of the present invention
The NDVI and Reflectivity for Growing Season time series simulation curve of LTDR AVHRR and GLASS AVHRR and SG AVHRR NDVI's
Time series simulation curve；
Fig. 9 (f) is 1992 to 2005 area the Turco vegetation pattern website LTDR rebuild according to the embodiment of the present invention
The NDVI and Reflectivity for Growing Season time series simulation curve of AVHRR and GLASS AVHRR and the time sequence of SG AVHRR NDVI
Column simulation curve；
Figure 10 is the whole world emulation of the 9 days January in 2010 constructed according to the embodiment of the present invention and Reflectivity for Growing Season on July 12
Distribution map.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached in the embodiment of the present invention
Figure, is clearly and completely described the technical solution in the present invention, it is clear that described embodiment is one of the invention
Divide embodiment, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making
Every other embodiment obtained, shall fall within the protection scope of the present invention under the premise of creative work.
As the one aspect of the embodiment of the present invention, the present embodiment provides a kind of AVHRR Reflectivity for Growing Season method for reconstructing, ginsengs
Fig. 1 is examined, is a kind of flow chart of AVHRR Reflectivity for Growing Season method for reconstructing of the embodiment of the present invention, comprising:
S1 is removed invalid value processing to original ground surface reflectivity data, is obtained effectively primitively based on setting rule
Table reflectivity data.
It is to be understood that running AVHRR sensor is acquired and stores to daily earth surface image data, it is based on
These image datas are that original ground surface is anti-using the long-term sequence Reflectivity for Growing Season data set that certain processing method generates
Penetrate rate data.Due to there are the various factors such as interference, there can be some invalid values in these original ground surface reflectivity datas.Consider
To various disturbing factors, corresponding invalid value judgment rule is set, original ground surface reflectivity number is gone out according to the setting Rules Filtering
Invalid value in is effective original ground surface reflectivity data in remaining original ground surface reflectivity data.
It is wherein optional, if setting rule described in step S1 include: any pixel point red spectral band reflectivity it is big
In the near infrared band reflectivity of the pixel point, then determine that the Reflectivity for Growing Season of the pixel point is invalid value；And/or it is if any
Red spectral band and near infrared band the enhancing vegetation index of pixel point are greater than NDVI, then determine that the Reflectivity for Growing Season of the pixel point is
Invalid value.
It is to be understood that the original ground surface reflectivity data to daily temporal resolution screens, determine effectively original
Reflectivity for Growing Season data, screening rule include: for each pixel point, if its red spectral band reflectivity is greater than near infrared band
Reflectivity then determines that the Reflectivity for Growing Season of the pixel point is invalid value；In addition, if the red spectral band and near-infrared of a pixel point
Wave band enhancing vegetation index is all larger than NDVI, then determines that the Reflectivity for Growing Season of the pixel point is also invalid value.
S2, the synthesis for carrying out specified time resolution ratio to effective original ground surface reflectivity data are handled, and obtain synthesis
Reflectivity for Growing Season data.
It is to be understood that can not have been eliminated when above-mentioned steps remove the invalid value in the reflectivity data of original ground surface
Imitate the cloud interference in the reflectivity data of original ground surface.In order to reduce the influence of cloud and atmosphere to AVHRR Reflectivity for Growing Season as far as possible,
The AVHRR Reflectivity for Growing Season of daily temporal resolution is synthesized.In order to reach corresponding resolution requirements, setting data are closed
At temporal resolution, and effective original ground surface reflectivity data is polymerize according to the temporal resolution, the number after synthesis
According to as synthesis earth's surface reflectivity data.In one embodiment, the specified time resolution ratio is 8 days resolution ratio.
S3 is based on the synthesis earth's surface reflectivity data, calculates normalized differential vegetation index NDVI, and be based on the NDVI,
NDVI coenvelope line is rebuild using given algorithm.
It is to be understood that the Reflectivity for Growing Season of synthesis still includes the information of a large amount of clouds.Therefore, according to synthesis earth surface reflection
It is discontinuous in the NDVI time series that rate data are calculated.The NDVI being calculated in view of the Reflectivity for Growing Season influenced by cloud
It is worth relatively low, to be influenced using correlation method screening by cloud Reflectivity for Growing Season.With specific reference to the earth's surface for the synthesis that above-mentioned steps obtain
Reflectivity data calculates the corresponding normalized differential vegetation index NDVI of data.Filter out for convenience wherein by cloud influenced it is smaller or
The data not influenced by cloud, the i.e. biggish data of NDVI value utilize certain data re-establishing method according to the NDVI obtained is calculated
Rebuild NDVI coenvelope line, such as the penalized least-squares Return Law based on Three-dimensional DCT.
S4 is based on the NDVI and the NDVI coenvelope line, using given decision condition, to the synthesis earth surface reflection
Rate data carry out cloud detection, remove the data influenced by cloud, obtain the Reflectivity for Growing Season data for meeting credit rating requirement.
It is to be understood that cloud etc. generally results in the negative bias noise of NDVI value, this step to the influence of Reflectivity for Growing Season
It is middle that the reflectivity influenced by remaining cloud is detected using the NDVI and its coenvelope line of time series.By detecting conjunction one by one
Whether meet given Rule of judgment at the corresponding NDVI and NDVI coenvelope line of any time in Reflectivity for Growing Season data, judgement should
Whether the synthesis earth's surface reflectivity data at moment is influenced by cloud.Then pass through the party in removal synthesis earth's surface reflectivity data
The data influenced by cloud that method filters out, the remaining data got are the Reflectivity for Growing Season number for meeting credit rating requirement
According to.
S5 is passed through based on the Reflectivity for Growing Season data for meeting credit rating requirement and the NDVI coenvelope line
Function Fitting obtains the calculating reflectivity data of any time in specified time, the continuous Reflectivity for Growing Season of reconstruction time.
It is to be understood that after eliminating invalid data and the data influenced by cloud according to above-mentioned steps, according to acquisition
The Reflectivity for Growing Season data and NDVI coenvelope line number evidence for meeting credit rating requirement, using certain data fitting method,
The corresponding Reflectivity for Growing Season data for meeting credit rating requirement in fitting designated time period.Then it is minimized by interative computation
Second cost function calculates the reflectivity data for obtaining any time in the designated time period, i.e. calculating reflectivity data.Finally
According to the continuous Reflectivity for Growing Season of calculating reflectivity data reconstruction time at all moment in the designated time period.
A kind of AVHRR Reflectivity for Growing Season method for reconstructing provided in an embodiment of the present invention, according to synthesis earth's surface reflectivity data
NDVI rebuild NDVI coenvelope line, and based on NDVI and NDVI coenvelope line to synthesis Reflectivity for Growing Season data carry out cloud inspection
It surveys, effectively rejects the data influenced by cloud, be based ultimately upon the remaining data not influenced by cloud and NDVI coenvelope line, realize the time
Effective reconstruction of continuous Reflectivity for Growing Season, the cloud that can be effectively removed in Reflectivity for Growing Season reconstruction are interfered and can effectively be carried out scarce
The filling of mistake value；Simultaneously because the present invention is independent of any auxiliary information, equally can effective for MODIS, VIIRS, FY,
The reconstruction of the difference sensing data such as Landsat, it is versatile, it has broad application prospects.
In another embodiment, the step of S2 further comprises: if in the synthesis of the specified time resolution ratio
In window, there are at least two effective original ground surface reflectivity datas, then using the NDVI maximum value of observation angle constraint
Synthetic method synthesizes effective original ground surface reflectivity data；Alternatively, if the specified time resolution ratio synthesis window
Interior, there are effective original ground surface reflectivity datas, then as the synthesis earth's surface reflectivity data；Alternatively,
If effective original ground surface reflectivity data is not present in the synthesis window of the specified time resolution ratio, then with specified
The mean value of effective original ground surface reflectivity data is as the synthesis earth's surface reflectivity data in the time limit.
It is to be understood that as described in above-described embodiment, in order to reach corresponding resolution requirements, set Data Synthesis when
Between resolution ratio, Data Synthesis carries out in the synthesis window of the temporal resolution.For convenience of understanding, it is with 8 days temporal resolutions
The citing of specified time resolution ratio is illustrated.It is invalid due to having carried out removal to original ground surface reflectivity data in previous step
Value processing, therefore in 8 days time windows, remaining effective original ground surface reflectivity data number is there are three kinds of situations, i.e., and 0
A, 1 and at least two.
The case where being at least two for effective original ground surface reflectivity data remaining in 8 days time windows, using observation
The NDVI maximum value synthetic method of angle restriction synthesizes the effective original ground surface reflectivity data of this at least two, composite result
As the synthesis earth's surface reflectivity data in this synthesis window；For effective original ground surface reflection remaining in 8 days time windows
The situation that rate data are 1, it is directly that effective original ground surface reflectivity data is anti-as the synthesis earth's surface in this synthesis window
Penetrate rate data；In the case of effective original ground surface reflectivity data remaining in 8 days time windows is 0, specified year is calculated
The average value of effective original ground surface reflectivity data in limit, and using the average value as the synthesis earth surface reflection in this synthesis window
Rate data.
Wherein optionally, the NDVI maximum value synthetic method constrained using observation angle, synthesis are described effectively primitively
Table reflectivity data is further processed step with reference to Fig. 2, is a kind of NDVI constrained using observation angle of the embodiment of the present invention
Maximum value synthetic method synthesizes the process flowchart of effective original ground surface reflectivity data, comprising:
S21, the sight in the synthesis window of the specified time resolution ratio, to effective original ground surface reflectivity data
Observation apex angle is arranged by sequence from small to large.
Still it is illustrated by the citing of specified time resolution ratio of 8 days temporal resolutions, it can be understood as, for 8 day time
At least two effective original ground surface reflectivity datas in window, obtain the view zenith angle of each valid data, and according to sight
The sequence of observation apex angle from small to large is ranked up corresponding effective original ground surface reflectivity data.
S22, based on the corresponding effective original ground surface reflection of two view zenith angles the smallest in the sequence
Rate data calculate separately corresponding NDVI.
It is to be understood that it is corresponding effectively to choose wherein the smallest two view zenith angles according to the sequence of above-mentioned steps
Original ground surface reflectivity data calculates separately corresponding NDVI.
S23 chooses the corresponding effective original ground surface reflectivity data of the biggish corresponding NDVI in the two, makees
For the synthesis earth's surface reflectivity data.
It is to be understood that calculating corresponding two NDVI of the minimum view zenith angle of two obtained according to above-mentioned steps
Value chooses the corresponding effective original ground surface reflectivity data of NDVI value the greater, using the data as the conjunction in this synthesis window
At Reflectivity for Growing Season data.
A kind of AVHRR Reflectivity for Growing Season method for reconstructing provided in an embodiment of the present invention can carry out specified time point on demand
The Reflectivity for Growing Season Data Synthesis of resolution, so as to effectively reduce the influence of cloud and atmosphere to AVHRR Reflectivity for Growing Season.
On the basis of the above embodiments, it wherein described in step S3 based on the NDVI, is rebuild using given algorithm
NDVI coenvelope line is further processed step with reference to Fig. 3, is a kind of processing for rebuilding NDVI coenvelope line of the embodiment of the present invention
Process flow diagram flow chart, comprising:
S31 is minimized using the penalized least-squares Return Law based on Three-dimensional DCT by interative computation
Given the first cost function comprising time series of NDVI value vector obtains the estimation of optimal time sequence NDVI value vector.
It is to be understood that enabling the NDVI value x in vector X comprising time seriesi, i=1,2 ..., n, W is diagonal matrix, packet
Containing corresponding NDVI value xiWeight wi.The penalized least-squares Return Law based on Three-dimensional DCT is as follows by minimizing
First cost function obtains the optimal smoothing estimation of X
In formula, X indicates that time series of NDVI value vector, W indicate the weight matrix of time series of NDVI value,Indicate X's
Most there is estimation, D indicates Laplace operator, and s indicates scalar constant, can determineSmoothness.
By interative computation, above-mentioned first cost function is minimized, obtains estimation when the first cost function is minimized
ValueUsing II class discrete cosine transform ,+1 iteration of kth is obtainedIt is represented by following form:
In formula,WithThe estimated value for respectively indicating the X of kth time and the acquisition of+1 interative computation of kth, when X is indicated
Between sequence NDVI value vector, W indicate time series of NDVI value weight matrix, Γ is diagonal matrix.
Each component of Γ can be calculated by following formula in above formula:
Γi,i=(1+s (2-2cos ((i-1) π/n))2)-1；
In formula, ΓI, iIndicate that i-th the i-th column element of row of diagonal matrix Γ, s indicate scalar constant, can determineIt is flat
Slippage degree, i indicate that the i-th row of diagonal matrix Γ or the i-th column, n indicate the line number or columns of diagonal matrix Γ.
Due to the influence of the factors such as cloud, cause NDVI value relatively low.Therefore, these relatively low NDVI value quilts in an iterative process
Lesser weight is imparted, and the NDVI value of high quality then has been assigned biggish weight.The each element of weight matrix W calculates public
Formula is as follows:
In formula, wiIndicate i-th of NDVI value xiRespective weights, uiIndicate studentized residuals.
Above formula middle school biochemistry residual error uiIt calculates according to the following formula:
In formula, uiIndicate studentized residuals,Indicate i-th of observation residual error, s indicates scalar constant, can
It determinesSmoothness, MAD indicate median absolute deviation.
S32 is estimated based on the optimal time sequence NDVI value vector, constructs the NDVI coenvelope line.
It is to be understood that obtaining the optimal estimation of time series of NDVI value vector X in above-mentioned stepsLater, according to this
The element of optimal estimation vector constructs NDVI coenvelope line.
A kind of AVHRR Reflectivity for Growing Season method for reconstructing provided in an embodiment of the present invention can using discrete cosine transform method
Realize the quick reconstruction of NDVI coenvelope line, and entire reconstruction process is full-automatic, is especially suitable for the global number of long-term sequence
According to processing.
It on the basis of the above embodiments, is the embodiment of the present invention wherein the S4's is further processed step with reference to Fig. 4
A kind of process flowchart of cloud detection, comprising:
S41 is based on the corresponding NDVI of the synthesis earth's surface reflectivity data, successively judges whether any moment NDVI meets
Decision condition is given as follows:
|NDVIi-NDVI_Envi| > α × NDVI_Envi；
In formula, NDVIiIndicate the NDVI value at the i-th moment, NDVI_EnviIndicate the NDVI at the i-th moment of NDVI coenvelope line
Value, α indicate given threshold.
It is to be understood that cloud interference will affect the value of the NDV of table reflectivity data, in root as described in above-described embodiment
After NDVI the and NDVI coenvelope line for obtaining synthesis earth's surface reflectivity data according to above-described embodiment, wrapped according on NDVI and NDVI
Winding thread screens the synthesis earth's surface reflectivity data influenced by cloud.Specifically, judging in given time period any time one by one first
Whether NDVI meets given decision condition as follows:
|NDVIi-NDVI_Envi| > α × NDVI_Envi；
In formula, NDVIiIndicate the NDVI value at the i-th moment, NDVI_EnviIndicate the NDVI at the i-th moment of NDVI coenvelope line
Value, α indicate given threshold.
S42 determines described NDVI pairs of i-th moment if judgement knows that the i-th moment NDVI meets the given Rule of judgment
The synthesis earth's surface reflectivity data answered is the data influenced by cloud.
It is to be understood that for the NDVI value NDVI at the i-th momentiDecision condition is given in above-mentioned steps if met,
Think that the Reflectivity for Growing Season at the moment is influenced by cloud etc..Otherwise it is assumed that the Reflectivity for Growing Season at the moment is high-quality, not by cloud
Deng influence.
S43 removes the data influenced by cloud in the synthesis earth's surface reflectivity data, meets quality described in acquisition
The Reflectivity for Growing Season data of class requirement.
It is to be understood that after filtering out the data influenced by cloud according to above-mentioned steps, by these data from synthetically
It is rejected in table reflectivity data, remainder data is the Reflectivity for Growing Season data for meeting credit rating requirement.
A kind of AVHRR Reflectivity for Growing Season method for reconstructing provided in an embodiment of the present invention, according to NDVI and NDVI coenvelope line,
Remaining cloud in earth's surface reflectivity data is detected, all reflectivity influenced by cloud is rejected, only retains high-quality ground
Table reflectivity data, to merge the coenvelope line of NDVI, continuous Reflectivity for Growing Season in reconstruction time sequence.
It on the basis of the above embodiments, is the embodiment of the present invention wherein the S5's is further processed step with reference to Fig. 5
It is a kind of to rebuild the processed of Reflectivity for Growing Season based on the Reflectivity for Growing Season data and NDVI coenvelope line that meet credit rating requirement
Journey flow chart, comprising:
S51, based on the Reflectivity for Growing Season data for meeting credit rating requirement, acquisition time sequence infrared and near-infrared
Wave band reflectivity point set.
It is to be understood that enabling (ti,Ii), i=1,2 ..., m meets what credit rating required for what is obtained according to upper embodiment
The time series point set of Reflectivity for Growing Season data, wherein tiFor time, IiFor the reflectivity of different-waveband.This example with feux rouges and
It is handled near infrared band reflectivity, thereforeWhereinWithRespectively indicate tiMoment
Feux rouges and near infrared band reflectivity.
S52, it is secondary based on described infrared and near infrared band reflectivity point set and the NDVI coenvelope line, utilization
Polynomial function, it is described in fitting given time window to meet credit rating by interative computation the second cost function of minimum
It is required that Reflectivity for Growing Season data, obtain specified time in any time calculating reflectivity data.
It is to be understood that after obtaining feux rouges and near infrared band reflectivity according to above-mentioned steps, to each data point,
Utilize quadratic polynomial function f (t)=at2+ bt+c is fitted 2n+1 Reflectivity for Growing Season data in synthesis window, that is, utilizes iteration
Following second cost function of algorithmic minimizing:
In formula, J (Xi) indicate cost function, Xi=(ared,bred,cred,aNIR,bNIR,cNIR)TIndicate quadratic polynomial letter
Several coefficients, fred(ti) and fNIR(ti) the quadratic polynomial function of feux rouges and near infrared band is respectively indicated,WithPoint
It Biao Shi not tiMoment feux rouges and near infrared band reflectivity, NDVI_SimiIndicate the reflectivity using quadratic polynomial Function Fitting
Data calculate the NDVI, NDVI_Env obtainediIndicate the NDVI value at the i-th moment of NDVI coenvelope line, N indicates the big of synthesis window
It is small.
After the coefficient for obtaining above-mentioned fitting quadratic polynomial function by above-mentioned interative computation, quadratic polynomial is utilized
Function fred(ti) and fNIR(ti) calculate separately tiThe feux rouges and near infrared band reflectivity at moment obtain and calculate reflectivity number
According to.
S53, the calculating reflectivity data based on any time, rebuilds the earth's surface of Time Continuous in the specified time
Reflectivity.
It is to be understood that after the feux rouges and near infrared band reflectivity for obtaining any time based on above-mentioned steps, benefit
Carry out the reconstruction of the Reflectivity for Growing Season of the Time Continuous of corresponding wave band respectively with the two wave band reflectivity.
A kind of AVHRR Reflectivity for Growing Season method for reconstructing provided in an embodiment of the present invention, using meet credit rating requirement
Reflectivity for Growing Season data and NDVI coenvelope line, by Reflectivity for Growing Season data in quadratic polynomial Function Fitting synthesis window,
Realize the reconstruction of the Reflectivity for Growing Season of feux rouges and near infrared band Time Continuous, any parameter that no setting is required rebuilds earth surface reflection
Process stabilization, the quick and high degree of automation of rate.
As the other side of the embodiment of the present invention, the present embodiment provides a kind of AVHRR Reflectivity for Growing Season reconstructing system,
It is a kind of structural schematic diagram of AVHRR Reflectivity for Growing Season reconstructing system of the embodiment of the present invention, comprising: data prediction with reference to Fig. 6
Module 1, valid data synthesis module 2, NDVI coenvelope line rebuild module 3, cloud detection module 4 and Reflectivity for Growing Season and rebuild module
5。
Wherein, data preprocessing module 1 is used to be removed in vain original ground surface reflectivity data based on setting rule
Value processing, obtains effective original ground surface reflectivity data；Valid data synthesis module 2 is used to reflect effective original ground surface
Rate data carry out the synthesis processing of specified time resolution ratio, obtain synthesis earth's surface reflectivity data；NDVI coenvelope line rebuilds mould
Block 3 is used to be based on the synthesis earth's surface reflectivity data, calculates normalized differential vegetation index NDVI, and be based on the NDVI, utilizes
Given algorithm rebuilds NDVI coenvelope line；Cloud detection module 4 is used to be based on the NDVI and the NDVI coenvelope line, using giving
Determine decision condition, cloud detection is carried out to the synthesis earth's surface reflectivity data, remove the data influenced by cloud, acquisition meets quality
The Reflectivity for Growing Season data of class requirement；Reflectivity for Growing Season is rebuild module 5 and is used for based on the ground for meeting credit rating requirement
Table reflectivity data and the NDVI coenvelope line obtain any time calculating reflection in specified time by Function Fitting
Rate data, the continuous Reflectivity for Growing Season of reconstruction time.
It is to be understood that the handler module of group cost implementation Reflectivity for Growing Season reconstructing system is pre- including at least data
Processing module 1, valid data synthesis module 2, NDVI coenvelope line are rebuild module 3, cloud detection module 4 and Reflectivity for Growing Season and are rebuild
Module 5, each program module realize the weight of Reflectivity for Growing Season by the calculation processing of mutual data transmitting and program module
It builds.It embodies are as follows:
Due to there are the various factors such as interference, there can be some invalid values in the reflectivity data of original ground surface.In view of each
Kind disturbing factor sets corresponding invalid value judgment rule by data preprocessing module 1, and goes out original according to the setting Rules Filtering
Invalid value in beginning Reflectivity for Growing Season data, obtaining in remaining original ground surface reflectivity data is effective original ground surface reflection
Rate data.
Since data preprocessing module 1 can not eliminate the interference of the cloud in effective original ground surface reflectivity data.In order to the greatest extent
The influence of cloud and atmosphere to AVHRR Reflectivity for Growing Season may be reduced, valid data synthesis module 2 is by daily temporal resolution
AVHRR Reflectivity for Growing Season is synthesized.In order to reach corresponding resolution requirements, valid data synthesis module 2 sets data and closes
At temporal resolution, and polymerization addition is carried out to effective original ground surface reflectivity data according to the temporal resolution, after synthesis
Data be synthesize earth's surface reflectivity data.
Since the Reflectivity for Growing Season that valid data synthesis module 2 synthesizes still includes the information of a large amount of clouds, according to synthetically
It is discontinuous in the NDVI time series that table reflectivity data is calculated.In view of the Reflectivity for Growing Season influenced by cloud is calculated
NDVI value it is relatively low, NDVI coenvelope line rebuilds module 3 and screens the Reflectivity for Growing Season that is influenced by cloud using correlation method.Specific root
According to the synthesis earth's surface reflectivity data that valid data synthesis module 2 obtains, it is corresponding that NDVI coenvelope line rebuilds the calculating data of module 3
Normalized differential vegetation index NDVI.Filtering out for convenience is wherein influenced data that are smaller or not influenced by cloud by cloud, according to meter
The NDVI obtained is calculated, NDVI coenvelope line is rebuild using certain data re-establishing method, as based on Three-dimensional DCT
The penalized least-squares Return Law.
Cloud detection module 4 examines the reflectivity influenced by remaining cloud using the NDVI and its coenvelope line of time series
It surveys.By detect one by one synthesis earth's surface reflectivity data in any time corresponding NDVI and NDVI coenvelope line whether meet to
Determine Rule of judgment, cloud detection module 4 judge the moment synthesis earth's surface reflectivity data whether the influence by cloud.Then cloud is examined
The data influenced by cloud filtered out in the removal synthesis earth's surface reflectivity data of module 4 by this method are surveyed, what is got is surplus
Remainder is according to the Reflectivity for Growing Season data for as meeting credit rating requirement.
After above procedure module eliminates invalid data and the data influenced by cloud, Reflectivity for Growing Season rebuilds module 5
It is quasi- using certain data according to the Reflectivity for Growing Season data and NDVI coenvelope line number evidence for meeting credit rating requirement of acquisition
Conjunction method is fitted the Reflectivity for Growing Season data for meeting credit rating requirement in designated time period.Minimized by interative computation
Second cost function calculates the reflectivity data for obtaining any time in the designated time period, i.e. calculating reflectivity data.Finally
Reflectivity for Growing Season rebuilds module 5 according to the calculating reflectivity data reconstruction time at all moment in the designated time period continuously
Table reflectivity.
A kind of AVHRR Reflectivity for Growing Season reconstructing system provided in an embodiment of the present invention, can effectively remove Reflectivity for Growing Season
Cloud in reconstruction interferes and can effectively carry out Missing Data Filling, simultaneously because the present invention is independent of any auxiliary information, equally
Can be versatile effective for the reconstruction of the different sensing data such as MODIS, VIIRS, FY, Landsat, there is wide answer
Use prospect.
As the another aspect of the embodiment of the present invention, the present embodiment provides a kind of AVHRR Reflectivity for Growing Season reconstructing device,
It is a kind of structural block diagram of AVHRR Reflectivity for Growing Season reconstructing device of the embodiment of the present invention with reference to Fig. 7, comprising: at least one storage
Device 701, at least one processor 702, communication interface 703 and bus 704.
Wherein, memory 701, processor 702 and communication interface 703 complete mutual communication by bus 704, communicate
Information of the interface 703 between the Reflectivity for Growing Season reconstructing device and original ground surface reflectivity data storage equipment is transmitted；
The computer program that can be run on processor 702 is stored in memory 701, processor 702 is realized when executing described program
Reflectivity for Growing Season method for reconstructing as described in above-described embodiment.
It is to be understood that including at least memory 701, processor 702, communication in the Reflectivity for Growing Season reconstructing device
Interface 703 and bus 704, and memory 701, processor 702 and communication interface 703 by bus 704 formed it is mutual
Communication connection, and achievable mutual communication.
Communication interface 703 is realized logical between Reflectivity for Growing Season reconstructing device and original ground surface reflectivity data storage equipment
Letter connection, and achievable mutual information transmission, such as realize the reading of original ground surface reflectivity data by communication interface 703
Deng.
When device is run, processor 702 calls the program instruction in memory 701, to execute above-mentioned each method embodiment
Provided method, for example, the NDVI and the NDVI coenvelope line are based on, using given decision condition, to described
It synthesizes earth's surface reflectivity data and carries out cloud detection, remove the data influenced by cloud, the earth's surface that acquisition meets credit rating requirement is anti-
Penetrate rate data etc..
In another embodiment of the present invention, a kind of non-transient computer readable storage medium, the non-transient calculating are provided
Machine readable storage medium storing program for executing stores computer instruction, and the computer instruction executes the computer as described in above-described embodiment
Reflectivity for Growing Season method for reconstructing.
It is to be understood that realizing that all or part of the steps of above method embodiment can be relevant hard by program instruction
Part is completed, and program above-mentioned can be stored in a computer readable storage medium, when being executed, execution includes the program
The step of above method embodiment；And storage medium above-mentioned includes: that ROM, RAM, magnetic or disk etc. are various can store
The medium of program code.
The embodiment of Reflectivity for Growing Season method for reconstructing described above is only schematical, wherein being used as separation unit
The unit of explanation may or may not be physically separated, and both can be located in one place, or can also be distributed
Onto heterogeneous networks unit.Some or all of the modules therein can be selected to realize this embodiment scheme according to actual needs
Purpose.Those of ordinary skill in the art are without paying creative labor, it can understand and implement.
By the description of embodiment of above, those skilled in the art is it will be clearly understood that each embodiment can borrow
Help software that the mode of required general hardware platform is added to realize, naturally it is also possible to pass through hardware.Based on this understanding, above-mentioned
Substantially the part that contributes to existing technology can be embodied in the form of software products technical solution in other words, the meter
Calculation machine software product may be stored in a computer readable storage medium, such as ROM/RAM, magnetic disk, CD, including several fingers
It enables, with so that a computer equipment (such as personal computer, server or network equipment etc.) executes above-mentioned each method reality
Apply method described in certain parts of example or embodiment of the method.
A kind of AVHRR Reflectivity for Growing Season reconstructing device provided in an embodiment of the present invention and a kind of non-transient computer is readable deposits
Storage media, the cloud that can be effectively removed in Reflectivity for Growing Season reconstruction interfere and can effectively carry out Missing Data Filling, simultaneously because this
Invention, equally can be effective for the different sensing datas such as MODIS, VIIRS, FY, Landsat independent of any auxiliary information
Reconstruction, it is versatile, have broad application prospects.
Illustrate that technical solution of the present invention and beneficial effect, the embodiment of the present invention have carried out emulation examination in order to clearer
It tests, simulation process and simulation result are as follows:
It is the l-G simulation test flow chart that AVHRR NDVI and Reflectivity for Growing Season are rebuild according to the embodiment of the present invention with reference to Fig. 8,
In figure on the basis of the AVHRR Reflectivity for Growing Season data to daily temporal resolution carry out temporal resolution polymerization in 8 days, rebuild
The NDVI coenvelope line of continuously smooth in time series, and based on the NDVI coenvelope line and the NDVI of time series detection by cloud
The reflectivity data of influence is finally constraint with the NDVI coenvelope line of continuously smooth in time series, carries out based on high quality
Reflectivity for Growing Season Time Continuous Reflectivity for Growing Season reconstruction.
The method provided according to embodiments of the present invention in l-G simulation test rebuilds the global NDVI and ground of nineteen eighty-two to 2015
Table reflectivity.For convenience, the NDVI of reconstruction and Reflectivity for Growing Season are denoted as GLASS AVHRR, by AVHRR primary reflection rate
Data are denoted as LTDR AVHRR.On different vegetation types website, by GLASS AVHRR NDVI and Reflectivity for Growing Season and LTDR
AVHRR NDVI and Reflectivity for Growing Season are compared, while considering the most widely used SG filtering method, by GLASS
AVHRR NDVI is compared with the NDVI (being denoted as SG AVHRR) rebuild using SG filtering.In addition, spatially by GLASS
AVHRR Reflectivity for Growing Season is compared with LTDR AVHRR Reflectivity for Growing Season.In l-G simulation test, filtering setting size to SG is 5
Smooth window, Fig. 9 and Figure 10 are the simulation result schematic diagram of the embodiment of the present invention.
With reference to Fig. 9, for 1992 to the 2005 different vegetation types website LTDR rebuild according to the embodiment of the present invention
The NDVI and Reflectivity for Growing Season time series simulation curve of AVHRR and GLASS AVHRR and the time sequence of SG AVHRR NDVI
Column simulation curve.Fig. 9 (a) to Fig. 9 (f) is respectively 6 different type websites, 1992 to 2005 years GLASS AVHRR
The emulation of the time series of NDVI and Reflectivity for Growing Season, LTDR AVHRR NDVI and Reflectivity for Growing Season and SG AVHRR NDVI is bent
Line, wherein curve 1 indicates that GLASS AVHRR, curve 2 indicate that LTDR AVHRR, curve 3 indicate SG AVHRR.
As seen from Figure 9,2000 and the second half year in 1994, LTDR AVHRR Reflectivity for Growing Season shortage of data, and according to
Method for reconstructing provided in an embodiment of the present invention is all provided in the period of these websites LTDR AVHRR Reflectivity for Growing Season missing
Reasonable NDVI and Reflectivity for Growing Season data.In these websites, most of LTDR AVHRR red spectral band reflectance values all exist
0.2 or more, for corresponding NDVI value all close to 0, this is mainly due to the pollutions such as cloud to cause.The weight provided according to embodiments of the present invention
Construction method successfully eliminates these Reflectivity for Growing Season influenced by cloud, and has rebuild continuous NDVI and earth's surface in time series
Reflectivity data.
Meanwhile the coenvelope line of GLASS AVHRR NDVI and LTDR the AVHRR NDVI of reconstruction have extraordinary one
Cause property, and the lower envelope line for the GLASS AVHRR Reflectivity for Growing Season and LTDR AVHRR Reflectivity for Growing Season rebuild has well
Consistency；In addition to Yucheng website, it is very good that the time-serial position of GLASS AVHRRNDVI and SG AVHRR NDVI has
Consistency.SG is filtered in Zhangbei, Puechabon, Larose, Wankama and Turco website can obtain well
NDVI rebuilds effect.But since the vegetation pattern of Yucheng website is that there are two the crops of the season of growth for tool, it is clear that SG filter
The window setting of wave is excessive, causes to rebuild well in website SG AVHRR NDVI smaller between two seasons of growth
NDVI value.
Different from SG filter method it needs to be determined that suitable smooth window, method, system and equipment provided by the invention, are not necessarily to
Any parameter is set, therefore the process for rebuilding Reflectivity for Growing Season is stable, quick and full-automatic, is very suitable to the complete of long-term sequence
The processing of ball data.This method can be used for MODIS, VIIRS, FY, Landsat etc. independent of any auxiliary information simultaneously
The reconstruction of different sensing datas, has broad application prospects.In addition, method provided by the invention, system and equipment, Ke Yitong
The Reflectivity for Growing Season data of Shi Chongjian different-waveband can effectively avoid different-waveband data caused physics meaning when rebuilding respectively
Inconsistency in justice.
With reference to Figure 10, for the complete of 9 days January in 2010 construct according to the embodiment of the present invention and Reflectivity for Growing Season on July 12
Ball emulates distribution map.Wherein, Figure 10 (a) and Figure 10 (b) is respectively GLASS AVHRR and the LDTR AVHRR on January 9th, 2010
Reflectivity for Growing Season RGB image, Figure 10 (c) and Figure 10 (d) are respectively the GLASS AVHRR and LDTR on July 12nd, 2010
AVHRR Reflectivity for Growing Season RGB image.
By Figure 10 (b) as it can be seen that since LDTR AVHRR Reflectivity for Growing Season is polluted by cloud, most of region is all covered by cloud in figure
Lid.The method for reconstructing of the application embodiment of the present invention in 10 (a) effectively eliminates these remaining clouds, obtains spatially complete
GLASS AVHRR Reflectivity for Growing Season.Likewise, existing since LDTR AVHRR Reflectivity for Growing Season is polluted by cloud, in 10 (d) large stretch of
Cloud, the method for reconstructing of the application embodiment of the present invention, effectively eliminate all reflectance values influenced by cloud, lay equal stress in 10 (c)
Reasonable Reflectivity for Growing Season value is built.
To sum up, a kind of AVHRR Reflectivity for Growing Season method for reconstructing, system and device provided by the invention, to the daily time
On the basis of the AVHRR Reflectivity for Growing Season data of resolution ratio are polymerize, wrapped on the NDVI of continuously smooth in reconstruction time sequence
Winding thread, and the NDVI based on time series and its coenvelope line detect the reflectivity influenced by cloud, finally to connect in time series
Continue smooth NDVI coenvelope line for constraint, carries out the weight of the Reflectivity for Growing Season of the Reflectivity for Growing Season Time Continuous based on high quality
It builds, the cloud that can be effectively removed in Reflectivity for Growing Season reconstruction interferes and can effectively carry out Missing Data Filling.Simultaneously because of the invention
It, equally can be effective for the weight of the different sensing datas such as MODIS, VIIRS, FY, Landsat independent of any auxiliary information
It builds, it is versatile, it has broad application prospects.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, and those skilled in the art is it is understood that it still can be right
Technical solution documented by foregoing embodiments is modified or equivalent replacement of some of the technical features；And this
It modifies or replaces, the spirit and model of technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution
It encloses.
Claims (10)
1. a kind of AVHRR Reflectivity for Growing Season method for reconstructing characterized by comprising
S1 is removed invalid value processing to original ground surface reflectivity data, it is anti-to be obtained effective original ground surface based on setting rule
Penetrate rate data；
S2, the synthesis for carrying out specified time resolution ratio to effective original ground surface reflectivity data are handled, and obtain synthesis earth's surface
Reflectivity data；
S3 is based on the synthesis earth's surface reflectivity data, calculates normalized differential vegetation index NDVI, and be based on the NDVI, utilizes
Given algorithm rebuilds NDVI coenvelope line；
S4 is based on the NDVI and the NDVI coenvelope line, using given decision condition, to the synthesis Reflectivity for Growing Season number
According to cloud detection is carried out, the data influenced by cloud are removed, obtain the Reflectivity for Growing Season data for meeting credit rating requirement；
S5 passes through function based on the Reflectivity for Growing Season data for meeting credit rating requirement and the NDVI coenvelope line
Fitting obtains the calculating reflectivity data of any time in specified time, the continuous Reflectivity for Growing Season of reconstruction time.
2. the method according to claim 1, wherein setting rule described in step S1 includes:
If the red spectral band reflectivity of any pixel point is greater than the near infrared band reflectivity of the pixel point, the pixel point is determined
Reflectivity for Growing Season be invalid value；
And/or if red spectral band and near infrared band the enhancing vegetation index of any pixel point are greater than given NDVI, determining should
The Reflectivity for Growing Season of pixel point is invalid value.
3. the method according to claim 1, wherein the step of S2, further comprises:
If there are at least two effective original ground surface reflectivity numbers in the synthesis window of the specified time resolution ratio
According to then using the NDVI maximum value synthetic method of observation angle constraint, synthesis effective original ground surface reflectivity data；
Alternatively, if there are effective original ground surface reflectivity numbers in the synthesis window of the specified time resolution ratio
According to then as the synthesis earth's surface reflectivity data；
Alternatively, if effective original ground surface reflectivity data is not present in the synthesis window of the specified time resolution ratio,
Then to specify the mean value of effective original ground surface reflectivity data in the time limit as the synthesis earth's surface reflectivity data.
4. according to the method described in claim 3, it is characterized in that, the NDVI maximum value using observation angle constraint synthesizes
The step of method, synthesis effective original ground surface reflectivity data, further comprises:
In the synthesis window of the specified time resolution ratio, to the view zenith angle of effective original ground surface reflectivity data
It is arranged by sequence from small to large；
Based on the corresponding effective original ground surface reflectivity data of two view zenith angles the smallest in the sequence, point
Corresponding NDVI is not calculated；
The corresponding effective original ground surface reflectivity data of the biggish corresponding NDVI in the two is chosen, as the conjunction
At Reflectivity for Growing Season data.
5. the method according to claim 1, wherein based on the NDVI described in step S3, using given
The step of algorithm reconstruction NDVI coenvelope line, further comprises:
Given packet is minimized by interative computation using the penalized least-squares Return Law based on Three-dimensional DCT
First cost function of the vector of value containing time series of NDVI obtains the estimation of optimal time sequence NDVI value vector；
Estimated based on the optimal time sequence NDVI value vector, constructs the NDVI coenvelope line.
6. the method according to claim 1, wherein the step of S4, further comprises:
Based on the corresponding NDVI of the synthesis earth's surface reflectivity data, it is following given successively to judge whether any moment NDVI meets
Decision condition:
|NDVIi-NDVI_Envi| > α × NDVI_Envi；
In formula, NDVIiIndicate the NDVI value at the i-th moment, NDVI_EnviIndicate the NDVI value at the i-th moment of NDVI coenvelope line, α table
Show given threshold；
If judgement knows that the i-th moment NDVI meets the given decision condition, the corresponding synthesis of the i-th moment NDVI is determined
Reflectivity for Growing Season data are the data influenced by cloud；
The data influenced by cloud in the synthesis earth's surface reflectivity data are removed, meet credit rating requirement described in acquisition
Reflectivity for Growing Season data.
7. the method according to claim 1, wherein the step of S5, further comprises:
Based on the Reflectivity for Growing Season data for meeting credit rating requirement, acquisition time sequence infrared and near infrared band reflection
Rate point set；
Based on described infrared and near infrared band reflectivity point set and the NDVI coenvelope line, quadratic polynomial letter is utilized
Number minimizes the second cost function by interative computation, is fitted the ground for meeting credit rating requirement in given time window
Table reflectivity data obtains the calculating reflectivity data of any time in specified time；
The calculating reflectivity data based on any time, rebuilds the Reflectivity for Growing Season of Time Continuous in the specified time.
8. according to the method described in claim 3, it is characterized in that, the specified time resolution ratio is 8 days resolution ratio.
9. a kind of AVHRR Reflectivity for Growing Season reconstructing system characterized by comprising
Data preprocessing module, for being removed invalid value processing to original ground surface reflectivity data, obtaining based on setting rule
Take effective original ground surface reflectivity data；
Valid data synthesis module, for carrying out the synthesis of specified time resolution ratio to effective original ground surface reflectivity data
Processing obtains synthesis earth's surface reflectivity data；
NDVI coenvelope line rebuilds module, for being based on the synthesis earth's surface reflectivity data, calculates normalized differential vegetation index
NDVI, and it is based on the NDVI, NDVI coenvelope line is rebuild using given algorithm；
Cloud detection module, for being based on the NDVI and the NDVI coenvelope line, using given decision condition, to the synthesis
Reflectivity for Growing Season data carry out cloud detection, remove the data influenced by cloud, obtain the Reflectivity for Growing Season for meeting credit rating requirement
Data；
Reflectivity for Growing Season rebuilds module, for based on the Reflectivity for Growing Season data and described for meeting credit rating requirement
NDVI coenvelope line obtains the calculating reflectivity data of any time in specified time by Function Fitting, and reconstruction time is continuous
Reflectivity for Growing Season.
10. a kind of AVHRR Reflectivity for Growing Season reconstructing device characterized by comprising at least one processor, at least one
Manage device, communication interface and bus；
The memory, the processor and the communication interface complete mutual communication, the communication by the bus
Information of the interface between the AVHRR Reflectivity for Growing Season reconstructing device and original ground surface reflectivity data storage equipment passes
It is defeated；
The computer program that can be run on the processor is stored in the memory, the processor executes described program
Method of the Shi Shixian as described in any in claim 1 to 8.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5612901A (en) * | 1994-05-17 | 1997-03-18 | Gallegos; Sonia C. | Apparatus and method for cloud masking |
| CN102831310A (en) * | 2012-08-17 | 2012-12-19 | 北京师范大学 | Method for building high-spatial resolution NDVI (normalized difference vegetation index) time series data |
| CN105654050A (en) * | 2015-12-29 | 2016-06-08 | 南京信息工程大学 | Invalid value correction-based NDVI data reconstruction method |
-
2017
- 2017-09-07 CN CN201710800321.3A patent/CN107782700B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5612901A (en) * | 1994-05-17 | 1997-03-18 | Gallegos; Sonia C. | Apparatus and method for cloud masking |
| CN102831310A (en) * | 2012-08-17 | 2012-12-19 | 北京师范大学 | Method for building high-spatial resolution NDVI (normalized difference vegetation index) time series data |
| CN105654050A (en) * | 2015-12-29 | 2016-06-08 | 南京信息工程大学 | Invalid value correction-based NDVI data reconstruction method |
Non-Patent Citations (1)
| Title |
|---|
| 时空信息协同的地表反射率时域重建方法研究;杨刚;《浙江省地理学会2016年学术年会暨浙江省第三届地理名师名校长联盟高峰论坛:论文摘要集》;20161231;第14页 |
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