CN117571658B - VBFP-based plateau Gao Hancao ground object waiting period monitoring method and device - Google Patents
VBFP-based plateau Gao Hancao ground object waiting period monitoring method and device Download PDFInfo
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Abstract
The invention provides a VBFP-based plateau Gao Hancao land climatic period monitoring method and device, which relate to the technical field of climatic period monitoring and comprise the following steps: acquiring surface reflectivity data of the plateau alpine grasslands; computing enhanced weatherable index based on surface reflectance dataNEVIThe method comprises the steps of carrying out a first treatment on the surface of the Enhanced type weatherometer based on double-filtering mean value methodNEVIReconstructing; based on reconstructed enhanced weatherometerNEVIAnd constructing a vegetation index background field of the plateau Gao Hancao land in the climatic period, inverting the climatic period based on the vegetation index background field, and judging whether the plateau alpine grassland enters the green-turning period or the yellow-withered period. The method and the device solve the problem that the weather period of the alpine grassland of the plateau cannot be estimated rapidly and accurately in the prior art.
Description
Technical Field
The invention relates to the technical field of climatic period monitoring, in particular to a method and a device for monitoring the climatic period of a plateau Gao Hancao land based on VBFP.
Background
The surface vegetation is taken as a primary producer in the ecological system, is an important component part of the land ecological system, is also the most sensitive component part to climate change, is a product developed for a long time under the combined action of environment components (air temperature, moisture and other elements), and plays an extremely important role in the material and energy exchange process. The interaction relationship between vegetation climate and atmosphere is one of the research focuses of various subjects such as hydrology, meteorology and ecology in recent years, and vegetation climate parameters are closely related to the season distribution dynamics of the underlying atmosphere, so that the climate signals changing year by year are extremely important to climate and even global environment changes. The plateau alpine region is a sensitive region of global climate change due to the unusual natural geographic conditions and fragile and sensitive environment, and the unique vegetation climate information and the response thereof to the climate change in the plateau alpine environment are hot spots of attention of global change researchers.
The satellite images based on the long-time sequence have natural advantages, are suitable for observation in a wide area, can acquire information about seasonal vegetation development, and are used for extracting and analyzing seasonal weather parameters. At present, various methods for performing vegetation weathers inversion on remote sensing data of a long time sequence include a threshold method, an absolute value method, a slope method and a curve fitting method. The slope method is used for identifying the turning green and withered time of vegetation growth by carrying out first-order derivation on a vegetation index curve, is suitable for extracting the weather which has stable growth state and is less influenced by external environment, but the accuracy is reduced when the weather is influenced by external condition change. The curve fitting method is used for fitting vegetation growth process based on a mathematical model, is suitable for areas with small changes and good vegetation conditions, has low accuracy for low vegetation coverage areas, and is not suitable for grasslands in high and cold areas of the plateau. The absolute value method takes a certain absolute value as the beginning or ending of growth, and the difference between the growth of the annual plants and the actual situation is larger. The threshold method is to set a fixed threshold or a dynamic threshold to obtain the vegetation starting time and the vegetation ending time, and the selection of the threshold in the method is greatly influenced by different areas and artificial subjective factors.
In summary, although there are various methods of estimating vegetation period, most are only applicable to a wide area where vegetation growth is good. The curve fitting method with higher calculation complexity has the problem of low running speed, so the method is not suitable for rapid monitoring in a large-scale area in the climatic period, and most of the monitoring in the climatic period is based on a single vegetation index, however, the single vegetation index cannot well represent the growth condition of the alpine grasslands of the plateau under the influence of high-sea waves and high-cold characteristics. Therefore, the current weathered period estimation method cannot rapidly and accurately estimate the weathered period of the plateau alpine grassland.
Disclosure of Invention
Accordingly, the present invention is directed to a VBFP-based method and apparatus for monitoring the climatic period of a plateau Gao Hancao, so as to alleviate the problem that the climatic period of a plateau alpine grassland cannot be estimated rapidly and accurately in the prior art.
In order to achieve the above object, the technical scheme adopted by the embodiment of the invention is as follows:
in a first aspect, an embodiment of the present invention provides a VBFP-based method for monitoring a plateau Gao Hancao land feature, including: acquiring surface reflectivity data of the plateau alpine grasslands; computing enhanced weatherable index based on surface reflectance dataNEVIThe method comprises the steps of carrying out a first treatment on the surface of the Enhanced type weatherometer based on double-filtering mean value methodNEVIReconstructing; based on reconstructed enhanced weatherometerNEVIAnd constructing a vegetation index background field of the plateau Gao Hancao land in the climatic period, inverting the climatic period based on the vegetation index background field, and judging whether the plateau alpine grassland enters the green-turning period or the yellow-withered period.
In one embodiment, the surface reflectance data includes at least: short wave infrared band reflectivity, near infrared band reflectivity, red band reflectivity and blue band reflectivity; computing enhanced weatherable index based on surface reflectance dataNEVIComprising: carrying out weighted calculation on the reflectivity of the short wave infrared band and the reflectivity of the red wave band to obtain weighted reflectivity; the enhanced type weatherindex is calculated based on the weighted reflectivity, the near infrared band reflectivity and the blue band reflectivityNEVI。
In one embodiment, the weighted reflectivity obtained by weighting the reflectivity of the short-wave infrared band and the reflectivity of the red light band includes: the weighted reflectivity is calculated according to the following formula:
wherein,representing weighted reflectivity, +.>Indicating red band reflectivity +.>Representing the reflectivity of the short-wave infrared band +.>Representing the weighting coefficients.
In one embodiment, the enhanced weatherometer is calculated based on weighted reflectivity, near infrared band reflectivity, and blue band reflectivityNEVIComprising: calculating the enhanced weatherometer according to the following formulaNEVI：
Wherein,Bthe gain factor is represented by a gain factor,indicating the reflectivity of the blue band, ">Indicating the reflectivity of the near-infrared band,and->A weight parameter indicating the effect of atmosphere on the red band reflectivity by the blue band reflectivity correction,lrepresenting soil background conditioning parameters.
In one embodiment, the enhanced weatherometer is based on a double filtered mean methodNEVIPerforming reconstruction, comprising:
enhancement type weatherometer according to Savizky-Golay filter model and Whittaker filter model respectivelyNEVIReconstructing;
the Savizky-Golay filtering model is as follows:
wherein,Yrepresenting an original time sequenceNEVI，Representing time seriesNEVIData fitting values->Representing time seriesNEVIMiddle (f)jThe coefficients of the filtering of the individual data values,Nrepresenting the number of convolutions that are present,jrepresenting an original time sequenceNEVIM represents the filter window size;
the Whittaker filter model is:
wherein,nrepresenting an original time sequenceNEVIIs provided for the length of (a),Sthe vector after the smoothing is represented as such,representing smoothed data points +.>Representing Savizky-Golay filtered data,/A>Lambda represents the smoothness parameter.
In one embodiment, the vegetation index background field comprises at least: a bluing period background; based on reconstructed enhanced weatherometerNEVIConstructing a vegetation index background field of a plateau Gao Hancao land in a climatic period, performing a climatic period inversion based on the vegetation index background field, and judging whether the plateau alpine grassland enters a turning green period or not, wherein the method comprises the following steps: reconstructed enhanced weatherometer with preset long time sequenceNEVIThe mean value of (2) is determined as the background of the turning green period; obtaining a current enhanced weatherometerNEVIDelta value from the blushing background if the current enhanced weatherindexNEVIAnd if the increment value of the background in the turning green period is larger than the preset increment, determining that the plateau alpine grassland enters the turning green period.
In one embodiment, the vegetation index background field comprises at least: a background in the dark; based on weightPost-construction enhanced weatherometerNEVIConstructing a vegetation index background field of a plateau Gao Hancao land in a climatic period, performing a climatic period inversion based on the vegetation index background field, and judging whether the plateau alpine grassland enters a dry period or not, wherein the method comprises the following steps: reconstructed enhanced weatherometer with preset long time sequenceNEVIIs determined as the background in the dark yellow period; obtaining a current enhanced weatherometerNEVIDecrement value against background in dry-off period, if current enhanced weatherindexNEVIAnd if the decrement value of the background in the dry-off period is larger than the preset decrement value, determining that the highland alpine grasslands enter the dry-off period.
In a second aspect, an embodiment of the present invention provides a VBFP-based plateau Gao Hancao terrain weather monitoring apparatus, including: the data acquisition module is used for acquiring the surface reflectivity data of the highland alpine grasslands;NEVIa calculation module for calculating an enhanced weatherometer based on the surface reflectivity dataNEVI；NEVIThe reconstruction module is used for carrying out the method of filtering the enhanced type weatherindex based on the double-filtering mean valueNEVIReconstructing; an inversion module for reconstructing the enhanced weatherometerNEVIAnd constructing a vegetation index background field of the plateau Gao Hancao land in the climatic period, inverting the climatic period based on the vegetation index background field, and judging whether the plateau alpine grassland enters the green-turning period or the yellow-withered period.
In a third aspect, an embodiment of the present invention provides an electronic device comprising a processor and a memory storing computer executable instructions executable by the processor to perform the steps of the method of any one of the first aspects described above.
In a fourth aspect, embodiments of the present invention provide a computer readable storage medium having a computer program stored thereon, which when executed by a processor performs the steps of the method of any of the first aspects provided above.
The embodiment of the invention has the following beneficial effects:
the VBFP-based plateau Gao Hancao land weather monitoring method and device provided by the embodiment of the present invention firstly, obtain the surface of the plateau alpine grasslandReflectance data; second, calculate an enhanced weatherometer based on the surface reflectance dataNEVIThe method comprises the steps of carrying out a first treatment on the surface of the Then, the enhanced type weatherometer is subjected to the method based on the double-filtering mean valueNEVIReconstructing; finally, based on the reconstructed enhanced weatherometerNEVIAnd constructing a vegetation index background field of the plateau Gao Hancao land in the climatic period, inverting the climatic period based on the vegetation index background field, and judging whether the plateau alpine grassland enters the green-turning period or the yellow-withered period. According to the growth characteristics of the highland and alpine grasslands, the method utilizes satellite earth surface reflectivity data of a long-time sequence to construct the enhanced type weatherometer suitable for monitoring the weatherometer of the highland alpine grasslandsNEVIAnd using long time sequencesNEVIAnd the historical climatic information is used for establishing a model for estimating the bluing period and the withering period of the plateau alpine grasslands, so that the rapid monitoring of the climatic period of the plateau Gao Hancao is realized, and the problem that the climatic period of the plateau alpine grasslands cannot be estimated rapidly and accurately in the prior art is solved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for monitoring the weather period of a plateau Gao Hancao based on VBFP according to an embodiment of the present invention;
FIG. 2 shows the present inventionThe embodiment provides a dual-filter front-back filterNEVIA vegetation index visual effect contrast diagram;
FIG. 3 is a diagram showing a comparison of the filtering front and back of a long time series according to an embodiment of the present invention;
FIG. 4 is a flowchart of another VBFP-based method for monitoring the weather period of the plateau Gao Hancao according to the embodiment of the present invention;
FIG. 5 is a diagram showing a contrast verification of a satellite inversion green-turning period result and a ground pasturing station result provided by an embodiment of the present invention;
FIG. 6 is a diagram showing a comparison verification of satellite inversion withered and yellow period results and ground pasture test point station results provided by an embodiment of the invention;
FIG. 7 is a schematic structural diagram of a VBFP-based plateau Gao Hancao weatherometer according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, although various vegetation period estimation methods exist, most are only applicable to wide areas with good vegetation growth conditions. The curve fitting method with higher calculation complexity has the problem of low running speed, so the method is not suitable for rapid monitoring in a large-scale area in the climatic period, and most of the monitoring in the climatic period is based on a single vegetation index, however, the single vegetation index cannot well represent the growth condition of the alpine grasslands of the plateau under the influence of high-sea waves and high-cold characteristics. Therefore, the current weathered period estimation method cannot rapidly and accurately estimate the weathered period of the plateau alpine grassland.
Based on the method and the device for monitoring the climatic period of the plateau Gao Hancao based on the VBFP, provided by the embodiment of the invention, the problem that the climatic period of the plateau alpine grassland cannot be estimated rapidly and accurately in the prior art is solved.
For the sake of understanding the present embodiment, a method for monitoring the weather of the plateau Gao Hancao based on VBFP (Vegetation Index Background Field Phenological Monitoring Method, vegetation index background field) disclosed in the present embodiment is described in detail, and the method may be executed by an electronic device, such as a smart phone, a computer, a tablet computer, or the like. Referring to the flowchart of a VBFP-based plateau Gao Hancao terrain weathering monitoring method shown in fig. 1, the method mainly includes the following steps S101 to S104:
step S101: and obtaining the surface reflectivity data of the highland alpine grasslands.
In one embodiment, the surface reflectivity product with the resolution of MOD09A1 500 can be obtained from the NASA website, the product information is shown in table 1, and the preprocessing such as projection conversion, data stitching, boundary clipping and the like is performed by using the data obtained by the Gdal tool.
Step S102: computing enhanced weatherable index based on surface reflectance dataNEVI。
In one embodiment, the normalized vegetation index (Normalized Difference Vegetation Index, NDVI) and the enhanced vegetation index (Enhanced Vegetation Index, EVI) are complemented by each other, are commonly used among the numerous vegetation indexes at present, and play a positive role in the extraction of physiological parameters of vegetation. However, the plateau alpine grasslands are affected by high altitude and alpine, and the snow coverage area is higher than other areas, so that the accuracy of vegetation growth conditions is affected to a certain extent. Based on the above, the application introduces a short wave infrared band sensitive to snow, and constructs an enhanced type weather index suitable for monitoring the weather period of the plateau alpine grasslandsNEVIThe method is used for inversion of the altitude information of the plateau Gao Hancao.
Table 1 surface reflectivity product information
In particular implementations, the surface reflectance data includes at least: short wave infrared band reflectivity, near infrared band reflectivity, red band reflectivity, and blue band reflectivity. In this embodiment, the enhanced weatherometer is calculated based on the surface reflectance dataNEVIWhen used, the following means may be employed including but not limited to:
firstly, the short wave infrared band reflectivity and the red light band reflectivity are subjected to weighted calculation to obtain weighted reflectivity.
Specifically, the weighted reflectivity can be calculated according to the following formula:
wherein,representing weighted reflectivity, +.>Indicating red band reflectivity +.>Representing the reflectivity of the short-wave infrared band +.>Representing a weighting coefficient whose expected value is +.>Can approach the respective->。
Then, the enhanced weatherometer is calculated based on the weighted reflectivity, the near infrared band reflectivity and the blue band reflectivityNEVI。
Specifically, the enhanced weatherometer may be calculated according to the following formulaNEVI：
Wherein,Brepresenting the gain factor, the value may be 2.5 in this embodiment,indicating the reflectivity of the blue band of light,indicating the reflectivity of the near infrared band, ">And->The weight parameters indicating the influence of the atmosphere on the reflectivity of the red light wave band by the reflectivity correction of the blue light wave band can be respectively 6 and 7.5,lthe value of the soil background regulating parameter is 1.
Step S103: enhanced type weatherometer based on double-filtering mean value methodNEVIReconstruction is performed.
In one embodiment, the existing long-time sequence vegetation index data is subjected to strict pretreatment, so that the influence of solar altitude angle, atmosphere, cloud, aerosol and other data is eliminated, and the situation is closest to the real situation in a period, but still residual cloud, long-time cloud, cloud haze and other 'noise' exists. Therefore, there is a need for a time-series enhanced weatherometer obtained after pretreatmentNEVIReconstructing the data to remove noise in the image to the greatest extent possible while retaining the original enhancement weatherindex to the greatest extentNEVIAuthenticity of the data. The traditional single filtering method has insufficient prior feature consideration of the long-time sequence and has limitation on the reconstruction of the long-time sequence vegetation index, and based on the prior feature consideration, the embodiment of the invention integrates the Savizky-Golay local window filtering method and the Whittaker filtering method and enhances the long-time sequence vegetation index based on the double-filtering mean value methodNEVIReconstruction is performed, thereby greatly reducing reconstruction errors.
In specific implementation, the double-filter mean method is formed by adding Whittaker spectrum variation analysis to Savizky-Golay local window filter information. Specifically, the original time sequence is firstly subjected to a Savizky-Golay filtering modelNEVIPerforming filtering treatment, and then performing data fitting and smoothing on the filtered data through a Whittaker filtering model to obtain a reconstructed time sequenceNEVIThe method comprises the steps of carrying out a first treatment on the surface of the The Savizky-Golay filtering model is as follows:
wherein,Yrepresenting an original time sequenceNEVI，Representing time seriesNEVIData fitting values->Representing time seriesNEVIMiddle (f)jThe coefficients of the filtering of the individual data values,Nrepresenting the number of convolutions that are present,jrepresenting an original time sequenceNEVIM represents the filter window size, which together with the degree of the smoothing polynomial controls the smoothing effect.
The Whittaker filter model is:
wherein the Whittaker filtering model takes the original length asnIs of the original time series of (a)NEVIThe data is expressed as，nRepresenting an original time sequenceNEVII.e., the number of data points in the data set y,Srepresenting smoothed vectors, ++>Representing smoothed data points +.>Representing Savizky-Golay filtered data, the first term in the formula is a data fitting term, the second term is a smoothness term, lambda represents a smoothness parameter, and the trade-off between the two terms is controlled.
See fig. 2 for a dual filter front-to-back filterNEVICompared with the original data, the vegetation index visual effect contrast diagram and the long-time sequence filtering front-back contrast diagram shown in fig. 3 have the advantages that the abnormal noise randomly appearing in the image is correspondingly removed, the data quality is improved to a certain extent, the original ground feature is well reserved, and the vegetation index visual effect contrast diagram can be used for various information extraction and trend analysis.
Step S104: based on reconstructed enhanced weatherometerNEVIAnd constructing a vegetation index background field of the plateau Gao Hancao land in the climatic period, inverting the climatic period based on the vegetation index background field, and judging whether the plateau alpine grassland enters the green-turning period or the yellow-withered period.
In one embodiment, the reconstructed enhanced weatherometer with long time sequence can be utilized according to vegetation growth rules and historic weatherometer information of the target areaNEVIConstructing a vegetation index background field (Vegetation Index Background Field Phenological Monitoring Method, VBFP) of the plateau Gao Hancao land in the climatic period, and finally based on the synthesized vegetation index background field of the plateau and a certain day in the areaNEVIComparative analysis, if at a certain momentNEVIIf the increment or decrement of (a) reaches a certain proportion, the time is considered to enter the green-turning period or the yellow-withered period.
According to the VBFP-based plateau Gao Hancao land weather monitoring method provided by the embodiment of the present invention, according to the growth characteristics of the plateau alpine grassland, the satellite earth surface reflectivity data of the long-time sequence is utilized to construct an enhanced type weather index suitable for plateau alpine grassland weather monitoringNEVIAnd using long time sequencesNEVIEstablishing a model for estimating the bluing period and the withered period of the plateau alpine grasslands with the historical climatic information, and realizing the rapid monitoring of the climatic period of the plateau Gao Hancao land, thereby relieving the problem that the climatic period of the plateau alpine grasslands cannot be estimated rapidly and accurately in the prior artThe questions are given.
In one embodiment, the vegetation index background field comprises at least: a bluish background and a withered yellow background. The method specifically comprises the following steps of:
firstly, reconstructing the reconstructed enhanced weatherometer with a preset long time sequenceNEVIThe mean value of (2) is determined as the background of the blushing period.
In specific implementation, the enhanced weatherometer of the long time sequence 2012-2021 in 108 days (late 4 months) to 190 days (early 7 months) can be selected according to the vegetation growth rule of the research areaNEVIThe rolling average value synthesis is carried out, and the generated vegetation turning-green period background field can be calculated according to the following formula:
wherein,indicating the background of the turning green period,NEVI 1 ，NEVI 2 ，…，NEVI n enhanced weatherometer for long time sequenceNEVIThe value of the sum of the values,nrepresenting the selectionNEVINumber of values.
Then, the current enhanced weatherometer is obtainedNEVIDelta value from the blushing background if the current enhanced weatherindexNEVIAnd if the increment value of the background in the turning green period is larger than the preset increment, determining that the plateau alpine grassland enters the turning green period.
In particular, the current long time sequence can be based on the synthesized blushing period backgroundNEVIComparing with the background of the blushing period, when at a certain momentNEVIBefore the increment reaches the turning greenNEVIAbove a certain proportion P, the general stool is considered to be turned green, and the general stool can be specifically expressed by the following formula:
wherein,NEVI(currently) representing the current enhancementWeather indexNEVI，NEVI(background) refers to syntheticNEVIThe background value of the turning green period, P refers to the currentNEVIThe vegetation coverage difference of the research area is larger relative to the increment of the background in the blushing period, and the vegetation coverage difference can be set to be different values according to different areas, and is generally about 10% -30%.
The method specifically comprises the following steps of:
firstly, reconstructing the reconstructed enhanced weatherometer with a preset long time sequenceNEVIIs determined as the background in the dark yellow period.
In practice, since the grasses in the plateau area generally reach the highest yield in the period from the last ten days of 7 months to the last ten days of 8 months, the grasses can be planted in the period from the last ten days of 7 months to the last ten days of 8 monthsNEVIThe maximum value synthesis value is taken as a withered and yellow period background field, and specifically, the withered and yellow period background can be calculated according to the following formula:
wherein,indicating a background in the dark.
Then, the current enhanced weatherometer is obtainedNEVIDecrement value against background in dry-off period, if current enhanced weatherindexNEVIAnd if the decrement value of the background in the dry-off period is larger than the preset decrement value, determining that the highland alpine grasslands enter the dry-off period.
In particular, the current long time sequence can be based on the synthesized withered and yellow period backgroundNEVIThe data are compared with the background in the dark yellow period, and when the data are analyzed at a certain momentNEVIBefore the decrement of (2) reaches the withered yellowNEVIIf the proportion P of the total is above a certain level, the general excrement is considered to be withered and yellow, and the general excrement can be expressed by the following formula:
in the method, in the process of the invention,NEVI(currently) is currentNEVIThe data set is used to determine, based on the data,NEVIbackground) refers to 7 months to 8 monthsNEVIMaximum, P means when the grassland is in the dry periodNEVIThe vegetation coverage difference of the investigation region is large relative to the decrement of the background in the dark yellow period, and the vegetation coverage difference can be set to be different values according to different regions, and is generally about 10% -30%.
In order to facilitate understanding, the embodiment of the invention also provides a VBFP plateau Gao Hancao-based weathered period monitoring method, which is shown in fig. 4, and mainly comprises the following steps:
step 1: data collection and preprocessing.
Specifically, the surface reflectivity data with the resolution of MOD09A1 500 can be obtained, and preprocessing such as projection conversion, data stitching, boundary clipping and the like can be performed by using the data obtained by the Gdal tool.
Step 2: enhanced weatherometer indexNEVIIs a construction of (3).
Step 3: enhanced weatherability of long time sequenceNEVIIs performed in the reconstruction of (a).
Step 4: inversion of vegetation waiting period of plateau alpine grasslands.
Step 5: and outputting results, namely inverting the results in the green-turning period and the yellow-withering period.
In the embodiment of the invention, the average turning green period prediction result of the research area 2012-2021 is obtained through calculation by the method, the obvious tendency of early east, early west and late green period of the grassland in the research area can be found, the starting time of the turning green period is gradually delayed from southeast to northwest, the time of the average turning green period of the plateau alpine grassland in the research area is concentrated in the middle ten days to the next ten days of the five months, the eastern turning green period is mainly in 4 months to 5 months, the western part is mainly in 6 months, the influence of sea waves is mainly caused, and the turning green period of the grassland is later in the area with higher latitude or altitude.
Similarly, average withered and yellow period prediction results of the research areas 2012-2021 are calculated according to the method, the withered and yellow periods are obviously different in space, the withered and yellow periods are gradually delayed from northeast to southwest, the pasture withered and yellow periods in northeast areas are mainly concentrated in the period of 9 months-10 months in the last ten days, and the withered and yellow periods in southwest areas are mainly concentrated in the middle and late ten days of 10 months. Under the combined action of the green returning period and the yellow withering period, the growing season length of the pasture is gradually shortened from southwest to northeast, and the trend accords with the topography and climate characteristics of a research area.
According to the embodiment of the invention, the observation data of the forage grass weathers in the research area provided by 3 pasturing point stations are obtained, 30 sample points in 2012-2021 are selected by taking the test point data as true values, and the accuracy of the weathers of satellite inversion is verified by adopting a correlation coefficient R2, an absolute error (Bias) and a Root Mean Square Error (RMSE). The results are shown in fig. 5 and 6: the result of the satellite inversion in the green-turning period and the result of the satellite inversion in the yellow-turning period are consistent with the data of the ground station, and the correlation coefficient is larger than 0.7, so that the satellite inversion in the green-turning period and the satellite inversion in the yellow-turning period have good correlation, and the characteristic of the space-time change of the weather period of the alpine grasslands on the plateau can be accurately inverted based on the weather period extracted by the method.
According to the VBFP-based plateau Gao Hancao land weather monitoring method provided by the embodiment of the invention, the enhanced type weatherometer suitable for monitoring the plateau alpine grasslands in the weather is constructed by utilizing satellite earth surface reflectivity data of long-time sequence according to the growth characteristics of the plateau alpine grasslandsNEVIData, using long time sequencesNEVIAnd establishing an estimation model of the blushing period and the withered period of the alpine grassland of the plateau according to the historical climatic information of the research area, and realizing rapid monitoring of the climatic period of the plateau Gao Hancao. Compared with the traditional complex function fitting method, the method has the advantages that the calculation process is simple and efficient, and the problem that the weather period of the plateau alpine grassland cannot be estimated rapidly and accurately in the prior art is solved.
For the VBFP-based plateau Gao Hancao terrain weathering monitoring method provided in the foregoing embodiment, the embodiment of the present invention further provides a VBFP-based plateau Gao Hancao terrain weathering monitoring device, see a structural schematic diagram of the VBFP-based plateau Gao Hancao terrain weathering monitoring device shown in fig. 7, which illustrates that the device mainly includes the following parts:
the data acquisition module 701 is used for acquiring the surface reflectivity data of the highland alpine grassland.
NEVIA calculation module 702 for calculating an enhanced weatherindex based on the surface reflectivity dataNEVI。
NEVIA reconstruction module 703 for performing an enhancement of the weatherometer based on a double-filter mean methodNEVIReconstruction is performed.
An inversion module 704 for reconstructing the enhanced weatherometer based on the reconstructed enhanced weatherometerNEVIAnd constructing a vegetation index background field of the plateau Gao Hancao land in the climatic period, inverting the climatic period based on the vegetation index background field, and judging whether the plateau alpine grassland enters the green-turning period or the yellow-withered period.
According to the VBFP-based plateau Gao Hancao land weather monitoring device provided by the embodiment of the invention, the satellite earth surface reflectivity data of a long-time sequence is utilized to construct an enhanced type weather index suitable for monitoring the plateau alpine grasslands according to the growth characteristics of the plateau alpine grasslandsNEVIAnd using long time sequencesNEVIAnd the historical climatic information is used for establishing a model for estimating the bluing period and the withering period of the plateau alpine grasslands, so that the rapid monitoring of the climatic period of the plateau Gao Hancao is realized, and the problem that the climatic period of the plateau alpine grasslands cannot be estimated rapidly and accurately in the prior art is solved.
In one embodiment, the surface reflectance data includes at least: short wave infrared band reflectivity, near infrared band reflectivity, red band reflectivity and blue band reflectivity; above-mentionedNEVIThe computing module 702 is further configured to: carrying out weighted calculation on the reflectivity of the short wave infrared band and the reflectivity of the red wave band to obtain weighted reflectivity; the enhanced type weatherindex is calculated based on the weighted reflectivity, the near infrared band reflectivity and the blue band reflectivityNEVI。
In one embodiment, the aboveNEVIThe computing module 702 is further configured to: the weighted reflectivity is calculated according to the following formula:
wherein,representing weighted reflectivity, +.>Indicating red band reflectivity +.>Representing the reflectivity of the short-wave infrared band +.>Representing the weighting coefficients.
In one embodiment, the aboveNEVIThe computing module 702 is further configured to: calculating the enhanced weatherometer according to the following formulaNEVI：
Wherein,Bthe gain factor is represented by a gain factor,indicating the reflectivity of the blue band, ">Indicating the reflectivity of the near-infrared band,and->A weight parameter indicating the effect of atmosphere on the red band reflectivity by the blue band reflectivity correction,lrepresenting soil background conditioning parameters.
In one embodiment, the aboveNEVIThe reconstruction module 703 is further configured to:
enhancement type weatherometer according to Savizky-Golay filter model and Whittaker filter model respectivelyNEVIReconstructing;
the Savizky-Golay filtering model is as follows:
wherein,Yrepresenting an original time sequenceNEVI，Representing time seriesNEVIData fitting values->Representing time seriesNEVIMiddle (f)jThe coefficients of the filtering of the individual data values,Nrepresenting the number of convolutions that are present,jrepresenting an original time sequenceNEVIM represents the filter window size;
the Whittaker filter model is:
wherein,nrepresenting an original time sequenceNEVIIs provided for the length of (a),Sthe vector after the smoothing is represented as such,representing smoothed data points +.>Representing Savizky-Golay filtered data,/A>Lambda represents the smoothness parameter.
In one embodiment, the vegetation index background field comprises at least: a bluing period background; the inversion module 704 further functions to: reconstructed enhanced weatherometer with preset long time sequenceNEVIThe mean value of (2) is determined as the background of the turning green period; obtaining a current enhanced weatherometerNEVIDelta value from the blushing background if the current enhanced weatherindexNEVIAnd if the increment value of the background in the turning green period is larger than the preset increment, determining that the plateau alpine grassland enters the turning green period.
In one embodiment, the vegetation index background field comprises at least: a background in the dark; the inversion module 704 further functions to: reconstructed enhanced weatherometer with preset long time sequenceNEVIIs determined as the background in the dark yellow period; obtaining the timePre-enhancement type weather indexNEVIDecrement value against background in dry-off period, if current enhanced weatherindexNEVIAnd if the decrement value of the background in the dry-off period is larger than the preset decrement value, determining that the highland alpine grasslands enter the dry-off period.
It should be noted that, for the sake of brevity, reference may be made to the corresponding contents of the foregoing method embodiments for the description of the device embodiment, where the principles and technical effects of the device provided in the embodiment are the same as those of the foregoing method embodiments. The particular values provided in the practice of the present invention are exemplary only and are not limiting herein.
The embodiment of the invention also provides electronic equipment, which comprises a processor and a storage device; the storage means has stored thereon a computer program which, when run by a processor, performs the method according to any of the above embodiments.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device 100 includes: a processor 80, a memory 81, a bus 82 and a communication interface 83, the processor 80, the communication interface 83 and the memory 81 being connected by the bus 82; the processor 80 is arranged to execute executable modules, such as computer programs, stored in the memory 81.
The memory 81 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and at least one other network element is implemented via at least one communication interface 83 (which may be wired or wireless), and may use the internet, a wide area network, a local network, a metropolitan area network, etc.
Bus 82 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 8, but not only one bus or type of bus.
The memory 81 is configured to store a program, and the processor 80 executes the program after receiving an execution instruction, and the method executed by the apparatus for flow defining disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 80 or implemented by the processor 80.
The processor 80 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in processor 80. The processor 80 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a digital signal processor (Digital Signal Processing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 81 and the processor 80 reads the information in the memory 81 and in combination with its hardware performs the steps of the method described above.
The computer program product of the readable storage medium provided by the embodiment of the present invention includes a computer readable storage medium storing a program code, where the program code includes instructions for executing the method described in the foregoing method embodiment, and the specific implementation may refer to the foregoing method embodiment and will not be described herein.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A VBFP-based plateau Gao Hancao terrain weathering monitoring method, comprising:
acquiring surface reflectivity data of the plateau alpine grasslands;
calculating an enhanced weatherometer based on the surface reflectance dataNEVI；
Based on a double-filtering mean method, the enhanced type weatherometer is subjected toNEVIReconstructing;
enhanced reconstruction-basedIndex of physical conditionNEVIAnd constructing a vegetation index background field of the plateau Gao Hancao land in a climatic period, and performing climatic period inversion based on the vegetation index background field to judge whether the plateau alpine grassland enters a green-turning period or a dry-yellow period.
2. The method of claim 1, wherein the surface reflectivity data comprises at least: short wave infrared band reflectivity, near infrared band reflectivity, red band reflectivity and blue band reflectivity;
calculating an enhanced weatherometer based on the surface reflectance dataNEVIComprising:
carrying out weighted calculation on the short wave infrared band reflectivity and the red light band reflectivity to obtain weighted reflectivity;
calculating an enhanced weatherometer based on the weighted reflectivity, the near infrared band reflectivity and the blue band reflectivityNEVI。
3. The method of claim 2, wherein weighting the short wave infrared band reflectivity and the red light band reflectivity to obtain weighted reflectivity comprises:
the weighted reflectivity is calculated according to the following formula:
wherein,representing weighted reflectivity, +.>Indicating red band reflectivity +.>Representing the reflectivity of the short-wave infrared band +.>Representing the weighting coefficients.
4. A method according to claim 3, wherein calculating an enhanced weatherability index NEVI based on the weighted reflectivity, the near infrared band reflectivity and the blue band reflectivity comprises:
calculating the enhanced weatherometer according to the following formulaNEVI：
Wherein,Bthe gain factor is represented by a gain factor,indicating the reflectivity of the blue band, ">Indicating the reflectivity of the near infrared band, ">Anda weight parameter indicating the effect of atmosphere on the red band reflectivity by the blue band reflectivity correction,lrepresenting soil background conditioning parameters.
5. The method of claim 1, wherein the enhanced weatherometer according to the double filtered mean methodNEVIPerforming reconstruction, comprising:
the enhancement type weatherometer is respectively subjected to a Savizky-Golay filtering model and a Whittaker filtering modelNEVIReconstructing;
the Savizky-Golay filtering model comprises the following steps:
wherein,Yrepresenting an original time sequenceNEVI，Representing time seriesNEVIData fitting values->Representing time seriesNEVIMiddle (f)jThe coefficients of the filtering of the individual data values,Nrepresenting the number of convolutions that are present,jrepresenting an original time sequenceNEVIM represents the filter window size;
the Whittaker filter model is as follows:
wherein,nrepresenting an original time sequenceNEVIIs provided for the length of (a),Sthe vector after the smoothing is represented as such,representing smoothed data points +.>Representing Savizky-Golay filtered data,/A>Lambda represents the smoothness parameter.
6. The method of claim 1, wherein the vegetation index background field comprises at least: a bluing period background;
based on reconstructed enhanced weatherometerNEVIConstructing a vegetation index background field of the plateau Gao Hancao land in a climatic period, performing a climatic period inversion based on the vegetation index background field, and judging whether the plateau alpine grassland enters a green-turning period or not, and packagingThe method comprises the following steps:
reconstructed enhanced weatherometer with preset long time sequenceNEVIThe mean value of (2) is determined as the background of the turning green period;
obtaining a current enhanced weatherometerNEVIDelta value with the green-turning background if current enhanced weatherindexNEVIAnd if the increment value of the background in the turning green period is larger than a preset increment, determining that the plateau alpine grassland enters the turning green period.
7. The method of claim 1, wherein the vegetation index background field comprises at least: a background in the dark;
based on reconstructed enhanced weatherometerNEVIConstructing a vegetation index background field of the plateau Gao Hancao land in a climatic period, performing a climatic period inversion based on the vegetation index background field, and judging whether the plateau alpine grassland enters a withered and yellow period or not, wherein the method comprises the following steps:
reconstructed enhanced weatherometer with preset long time sequenceNEVIIs determined as the background in the dark yellow period;
obtaining a current enhanced weatherometerNEVIDecrement value against the dry-off period background, if current enhanced weatherable indexNEVIAnd if the decrement value of the plateau alpine grassland and the background in the dry-off period is larger than the preset decrement value, determining that the plateau alpine grassland enters the dry-off period.
8. VBFP-based plateau Gao Hancao ground object weather monitoring device, characterized by comprising:
the data acquisition module is used for acquiring the surface reflectivity data of the highland alpine grasslands;
NEVIa calculation module for calculating an enhanced weatherometer based on the surface reflectance dataNEVI；
NEVIA reconstruction module for performing a double-filter mean method on the enhanced weatherometerNEVIReconstructing;
an inversion module for reconstructing the enhanced weatherometerNEVIConstructing a vegetation index back of the plateau Gao Hancao land feature waiting periodAnd (3) performing a climatic period inversion based on the vegetation index background field, and judging whether the plateau alpine grassland enters a green-turning period or a withered period.
9. An electronic device comprising a processor and a memory, the memory storing computer executable instructions executable by the processor, the processor executing the computer executable instructions to implement the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, performs the steps of the method of any of the preceding claims 1 to 7.
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