CN106485345A - Cotton Gossypii time of infertility canopy SPAD value remote sensing appraising and appraising model construction method - Google Patents
Cotton Gossypii time of infertility canopy SPAD value remote sensing appraising and appraising model construction method Download PDFInfo
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Abstract
Embodiment of the invention discloses that one grows cotton time of infertility canopy SPAD value remote sensing appraising and appraising model construction method.With the Cotton Gossypii of Wei Beihanyuan area plantation as test material, measurement time of infertility Cotton Canopy SPAD value and canopy reflectance spectrum spectrum, the Remote Spectra parameter of original hyper spectral reflectance, the first derivative spectra reflectance, different-waveband combination is done correlation analysiss with SPAD value respectively, set up the SPAD forecast model of five kinds of important spectrum parameters, set up the appraising model of full spectrum SPAD using PLSR simultaneously, and test, finally filter out precision highest model.The PLSR model of the full spectrum set up based on important spectral variables is monitored to Cotton Gossypii SPAD value using hyperspectral technique, and prediction effect is notable, can provide foundation for time of infertility Cotton growth remote sensing monitoring, has positive directive function to instructing cotton planting and production.
Description
Technical field
The present invention relates to Cotton Gossypii detection field, more particularly it relates to Cotton Gossypii time of infertility canopy SPAD (" soil
The abbreviation of earth crop analysis instrument development ", Soil and Plant Analyzer Development) value remote sensing appraising and estimating
Calculate model building method.
Background technology
Chlorophyll is topmost pigment in photosynthesis of plant, is also the important thing that plant and the external world carry out energy exchange
Matter.Chlorophyll content is closely related with plant photosynthetic capacity, stage of development and Nitrogen Status, has become as and evaluates plant growing way
A kind of effective means, has great significance to the real-time monitoring of chlorophyll content of plant[1].SPAD value is that a leaf relatively is green
Cellulose content reading, can be used as the chlorophyll content of plant units area[2].SPAD-502 chlorophyll meter is generally adopted to measure plant
SPAD value, this instrument passes through to measure leaf to the absorbance in two wavelength period, to assess the chlorophyllous phase in current leaf
To content, it has become the current whole world and has measured chlorophyllous common method[3].Research shows, chlorophyll content is reflected with blade
There is high correlation between rate.Therefore, in recent years, at home and abroad obtained based on the research that EO-1 hyperion predicts chlorophyll content
Widely launch.
High-spectrum remote-sensing have spectral resolution high (<10nm), the features such as wave band seriality is strong, spectral information amount is big, its
Resolution is less than the semi-absorbing width (about 20--40nm) of general terrestrial materials.And progressively ripe vegetation hyperspectral analysis are calculated
Method, for more accurately detecting the fine spectral information of vegetation, the spectrum change feature of description each key growthdevelopmental stage, quantitative inversion cotton
Flower SPAD value, set up cotton growth information quantitative model and provide possibility.
There are some researches show, in the near-infrared spectrum analysis of crop, the prediction effect of partial least squares algorithm method is excellent
In general linear model, and there is obvious advantage to continuous spectrum analysis[4,5].Offset minimum binary (PLS) regression analysis are
Integrate a kind of new multicomponent statistics of the basic function of multiple linear regression analysis, canonical correlation analysis and principal component analysiss
Data analysing method, can effectively overcome the insurmountable difficult problem of multiple linear analysis method.The present invention uses PLSR
Construct the SPAD forecast model of Cotton Gossypii time of infertility canopy spectra.
Vegetation hyperspectral analysis algorithm research has focused largely on Oryza sativa L. both at home and abroad at present[6], Semen Tritici aestivi[6], Brassica campestris L[3,8]Deng grain and oil
Crop, relatively fewer to Cotton Gossypii research.The domestic research area to Cotton Gossypii is concentrated mainly on the Arid Area in Xinjiang of China[9-11],
And the research for Wei Beihanyuan area Cotton Canopy chlorophyll content in leaf blades is seldom seen.Wei Beihanyuan area is located in northern Shensi hills ditch
The south in gully area, the north of the central Shaanxi plain, are the important agricultural bases in Shaanxi Province, therefore choose the important warp in Wei Beihanyuan area
Ji crop Cotton Gossypii is that object conducts a research work, and this is to solving local food problem, increasing peasant income and quickening rural economic development
There is important strategic importance.Meanwhile, research chlorophyllous to Cotton Canopy in the past is due to weather condition restriction and experiment condition
The factor such as limited, is often directed to the estimation of key developmental stages, not yet has the estimation in the time of infertility, therefore the present invention is with the time of infertility
Full and accurate field Cotton Gossypii basic data modeling, to improve the reliability of estimation models further, to be that the EO-1 hyperion of Cotton growth is distant
Sense monitoring provides foundation.
List of references
[1] Yao Xia, Wu Huabing, Zhu Yan, Tian Yongchao, Zhou Zhiguo, Cao Weixing. Cotton Gossypii functional leaf pigment content and EO-1 hyperion
The correlation research [J] of parameter. Cotton Science, 2007,19 (4):267～272.
[2] Zhao Yanru, Yu Keqiang, Li Xiaoli, He Yong. the Fructus Cucurbitae moschatae leaf chlorophyll distribution visualization based on high light spectrum image-forming
Research [J]. spectroscopy and spectrum analyses, 2014,34 (5):1378～1382
[3] Ding Xibin, Liu Fei, at the beginning of, He Yong. the rape leaf SPAD value based on high light spectrum image-forming technology detects [J]. light
Spectroscopy and spectrum analyses, 2015, (2):486～491
[4] Yang Guodong. the partial least-square regression method based on Variable Selection and its application [D]. Central South University, 2013.
[5] Wang Jihua, Huang Wenjiang, Lao Cailian, Zhang Luda, Luo Changbing, Wang Tao, Liu Liangyun, Song Xiaoyu, Ma Zhihong. use
PLS algorithm is by wheat canopy reflectance spectrum inverting Vertical nitrogen distribution [J]. spectroscopy and spectrum analyses, 2007,27 (7):1319
～1322
[6] Chen Junying, Tian Qingjiu, Shi Runhe. spectra inversion research [J] of rice leaf chlorophyll content. remote sensing information,
2005,(6):12～16.
[7] He Kexun, Zhao Shuhe, to build refined, Luo Yunxiao, Qin Zhihao. and water stress is to Semen Tritici aestivi spectrum Red-edge parameter and product
The impact [J] of amount change. spectroscopy and spectrum analyses, 2013,33 (8):2143～2147.
[8] Li Lantao, Ma Yi, Wei Quanquan, Wang Shanqin, Ren Tao, Li little Kun, Cong Huan, Wang Zhen, Wang Shaohua, Lu Jianwei. base
Winter rape plant nitrogen accumulation monitoring model [J] in EO-1 hyperion. Transactions of the Chinese Society of Agricultural Engineering, 2015,31 (20):147～156
[9] Jiang Guiying. the EO-1 hyperion dose of cotton in Xinjiang Main Cultivation physical signs and applied research [D]. Hunan
Agriculture university, 2004.
[10] Huang Chunyan. the Cotton Leaves in North Xinjiang Remote sensing monitoring study [D] based on high-spectral data. Shihezi Univ, 2005.
[11] Wang Keru, Pan Wenchao, Li Shaokun, etc. difference applies ammonia amount Cotton Canopy EO-1 hyperion properties study [J]. spectrum
Learn and spectrum analyses .2011,31 (7):1868-1872.
[12] Cheng Guofeng, Dou Shen, Xu Wei. the response [J] of Wei Beihanyuan area temperature Change and winter wheat phenology. arid area
Agricultural research .2014 (05):112-115.
[13] Qi Yaqin, Lv Xin, Chen Guanwen, vast stretch of wooded country is flourish, Chen Yan, Yang Kun. Cotton Canopy is extracted based on high-spectral data special
The research [J] of reference breath. Cotton Science, 2011,23 (2):167～171
[14] Li Fenling, Wang Li, Liu Jing, Chang Qingrui. the Wheat Leavess SPAD value based on a number satellite data of high score is distant
Sense estimation [J]. agricultural mechanical journal, 2015,46 (9):273～281
[15] Lu Hongtao. PLS mathematical model and its algorithm research [D]. North China Electric Power University, 2014.
[16] Qin Zhanfei, Chang Qingrui, Shen Jian, etc. irrigation areas Oryza sativa L. red side feature and SPAD EO-1 hyperion forecast model
[J]. Wuhan University Journal (information science version) .2016:1-8.
[17] Yuan Jie. the research [D] based on EO-1 hyperion Red-edge parameter dose Cotton Canopy characteristic information. Shihezi is big
Learn, 2007.
Content of the invention
In consideration of it, the invention provides one grows cotton time of infertility canopy SPAD value remote sensing appraising model construction method, bag
Include following steps：Select multiple hillslope processes, select multiple sampling points in each hillslope processes；Close respectively at different growth of Cotton Gossypii
Key period of duration carries out canopy spectra measurement；Each sampling point surveys a plurality of complete curve, finally takes its average average as this sampling point
Reflectance spectrum, each cell takes the reflectance spectrum as this cell for the reflectance spectrum meansigma methodss of multiple sampling points；Measuring spectrum
At sampling point, second and third piece blade that Cotton Canopy launches is selected to measure, each sampling point random measurement multiple SPAD value, take
Its meansigma methods is as the canopy chlorophyll test value of this sampling point；Original for Cotton Gossypii canopy spectra reflectance and blade SPAD value are carried out single-phase
Close analysis；Cotton Canopy spectral reflectivity is made to carry out correlation analysiss with blade SPAD value after first differential；Multiple by choose
Remote Spectra parameter and SPAD value carry out correlation analysiss, and the Remote Spectra parameter choosing correlation maximum is modeled.
Preferably, obtain the smooth complete curve of spectrum after the original spectrum obtaining being processed, then to reflectance spectrum
Do first differential to process to eliminate influence of noise, to reduce error.
Preferably, avoid vein part during measurement, SPAD time of measuring is synchronous with spectrum data gathering.
Preferably, to SPAD value dependency, the most significant characteristic spectrum parameter is independent variable, to time of infertility SPAD for selection
Value makees linear fit, builds model.
Preferably, the spectrum of all test samples to the time of infertility for the applied forecasting model partial least-squares regression method PLSR
Characteristic parameter sets up the SPAD forecast model of Cotton Canopy blade.
Preferably, described growth key developmental stages include：Seedling stage, Sheng flower bud phase, full-bloom stage, Shengjing Town, the term of opening bolls.
Preferably, described Cotton Gossypii time of infertility canopy SPAD value remote sensing appraising model construction method includes：Using inspection sample
This is tested to the model accuracy of different input variables, using coefficient of determination R2, root-mean-square error RMSE and regression equation oblique
Three indexs of rate are checking the predictive ability of time of infertility model, coefficient of determination R2With slope absolute value closer to 1, RMSE value is got over
Little, then precision of forecasting model is higher.
Present invention also offers one grows cotton time of infertility canopy SPAD value remote sensing estimation method, including using according to above-mentioned
The model that method builds is estimating Cotton Gossypii time of infertility canopy SPAD value.
According to the drawings and Examples being described below, these and other aspects of the invention will be apparent from understanding
, and will be elucidated with reference to the embodiment being described below.
Brief description
Illustrated preferred embodiment in refer to the attached drawing is explained the present invention more fully below.
Fig. 1 shows the dependency of cotton leaf SPAD according to embodiments of the present invention and canopy original spectrum.
Fig. 2 shows the dependency of cotton leaf SPAD according to embodiments of the present invention and canopy the first derivative spectra.
Fig. 3 shows blade SPAD predictive value according to embodiments of the present invention and actual measurement Distribution value.
Specific embodiment
Describe the preferred embodiments of the present invention below in conjunction with accompanying drawing in detail.
1 materials and methods
1.1 research area overviews
Test San He village of Qian County Liangshan township (108 ° of 00 ' 13 " E～108 ° 24 ' in Wei Beihanyuan area in 2014-2015
18 " E, 34 ° 19 ' 36 " N～34 ° 45 ' 05 " N) carry out, locality belongs to that warm temperate zone is semiarid, the continental monsoon climate of semi-moist, year
Precipitation is 550-730mm, rain heat same season, and arid threatens big.Because of severe water and soil erosion, lead to soil leanness, make agriculture base
Plinth is especially weak, seriously restricts agricultural sustainable development.Research area preceding crop Cotton Gossypii, experimental cultivar grinds No. 28 for Shandong cotton.This
Invention 46 hillslope processes of design, cell size is 5m*6m.Cotton planting mode is covering with ground sheeting ridge kind.
1.2 data acquisition
1.2.1 the measurement of Cotton Canopy high-spectral data
Using the SVCHR1024i of the U.S. portable all band field spectroradiometer, spectral region 350-2500nm, wherein
350-1000nm interval spectral resolution is 1.4nm, and 1000-1850nm interval spectral resolution is 3.8nm, 1850-2500nm
For 2.4nm, select the 10 of ceiling unlimited calm weather:00-14:00, each cell choose 3 representative, uniformly
No disease pest harm sampling point, respectively Cotton Gossypii growth key developmental stages (seedling stage, contain flower bud phase, full-bloom stage, Shengjing Town, blow-of-cottons
Phase) carry out canopy spectra measurement.Every time mensure all carries out the demarcation of reference white plate, sensor probe vertically downward, apart from Cotton Gossypii
Canopy top about 50cm, the spectral scan time is set to 3s, and every sampling point surveys 3-5 bar complete curve, finally takes its average as this sample
The average reflectance spectra of point, each cell takes the reflectance spectrum as this cell for the reflectance spectrum meansigma methodss of three sampling points.
1.2.2 the measurement of SPAD value
Carry out nondestructive field using SPAD instrument immediately to measure, measure spectrum corresponding canopy chlorophyll.Measuring
At the sampling point of spectrum, second and third piece blade that Cotton Canopy launches is selected to measure, 10 SPAD of each sampling point random measurement
Value, takes its meansigma methods as the canopy chlorophyll test value of this sampling point.In order to reduce error, choose at the middle part of every leaf and uniformly divide
10 points of cloth, avoid vein part during measurement.SPAD time of measuring is synchronous with spectrum data gathering.
1.3 data processing
1.3.1 high spectrum image information selects
In order to reject background, the impact of atmospheric scattering and the contrast improving different Absorption Characteristics, process in actual analysis
It is often necessary to various conversion are carried out to original high-spectral data during high-spectral data[13].Basic variation is main
It is the differential transform of differential transform, logarithmic transformation and logarithm.
The original spectrum obtaining is done Overlap/Matching process with SVC HR-1024i software first, obtains smooth
The complete curve of spectrum, then adopt origin reflectance spectrum to be done with first differential process to eliminate influence of noise, to reduce error, its
Principle：
λ in formulaiFor the wavelength value at passage i, R (λi) it is wavelength XiThe spectral reflectance value at place, Δ λ is adjacent wavelength interval.
1.3.2 Remote Spectra parameter selects
Remote sensing vegetation spectrum parameter passes through the linearly or nonlinearly combination and variation of different-waveband reflectance, weakens background information
Interference to vegetation spectral features, is favorably improved the precision that remotely-sensed data expresses chlorophyll content.The present invention is extracted 22 kinds
Cotton Canopy blade SPAD value estimation mould is built to the sensitive wide-band spectrum index of chlorophyll content and 7 kinds of Red-edge parameter
Type.Spectrum parameter calculation is shown in Table 1.
Table 1 Remote Spectra parameter and its computing formula
Note：R is the reflectance of original spectrum, and NIR is the corresponding wavelength of first flex point near infrared range.
1.3.3 characteristic spectrum modeling and forecasting
Above-mentioned 29 kinds of spectrum parameters and SPAD value are carried out correlation analysiss, the Remote Spectra parameter choosing correlation maximum is entered
Row modeling.Time of infertility observation obtains 920 samples, wherein 800 as test sample, 120 give over to test samples.
2 results and analysis
2.1 SPAD values and the dependency of spectral reflectivity
2.1.1 SPAD value and original spectrum dependency
Original for Cotton Gossypii canopy spectra reflectance and blade SPAD value are carried out Correlation analysis (sample number n=800), result
As shown in Figure 1.As seen from the figure, cotton leaf SPAD and the positive infrared band on red side to 1250nm for the canopy spectra reflectance are in pole
Notable positive correlation, is in extremely significantly negatively correlated in the green-red wave band of 500-715nm and the near infrared band of 1340-2500nm, this master
If chlorophyll is determined in the special convergence reflecting properties of this spectrum range.Wherein, the sensitive band of SPAD value occurs in
At 708.2nm, corresponding r=-0.533, reach 99% confidence level significantly correlated.
2.1.2 SPAD and the first derivative spectra dependency
Cotton Canopy spectral reflectivity is made to carry out correlation analysiss with blade SPAD value after first differential, result such as Fig. 2 institute
Show.Figure it is seen that the dependency of SPAD value and spectrum first differential is better than the dependency of original spectrum on the whole.Wavelength
The correlation coefficient of 500-760nm is more than 0.6, wherein reflects the sensitive band of SPAD content at 734.7nm, r=
0.6992.
2.2 cotton leaf spectrum parameters and SPAD dependency
Various spectrum parameters are calculated according to table 1 and carries out correlation analysiss with SPAD value, obtain table 2.29 spectrum parameters
In only 6, not up to significantly correlated levels poor with SPAD value dependency, up to 21 and SPAD value are in extremely significantly correlated water
Flat.
The table 2 Cotton Gossypii time of infertility each spectral variables and the dependency of SPAD
Note：1.** represents significantly correlated in 0.01 level；2.* represents significantly correlated in 0.05 level.
As can be seen from Table 2, best with time of infertility cotton leaf SPAD dependency its phase relation of several spectral variables
Number is followed successively by improved Chlorophyll absorption reflection index MCARI, composite plant cover index M CARI/OSAVI, anti-air from high to low
Vegetation index VARI, illustrates that with SPAD value be all notable negative correlation, and the wherein correlation coefficient highest of MCARI has reached -0.679；
The red side of R, MERIS land chlorophyll index M TCI and SPAD are in notable positive correlation.The calculating of these spectral variables all with HONGGUANG
Wave band is relevant, and the exactly chlorophyllous strong absorption bandses of red spectral band.In addition, MCARI, MCARI/OSAVI, MTCI, VARI, R
Red side passed the significance test of 99% confidence level, shows that this five spectral variables have preferably to the change of SPAD value
Sign acts on.
2.3 Cotton Canopy SPAD value appraising models build
When SPAD value being estimated using canopy spectra data, using two methods modeling.1) choose to SPAD value phase
The most significant five characteristic spectrum parameters (the red side of MCARI, MCARI/OSAVI, MTCI, VARI and R) of closing property are independent variable, to complete
Period of duration SPAD value makees linear fit, and the model of structure is shown in Table 3.
The regressive prediction model of table 3 Cotton Gossypii time of infertility blade SPAD value
As can be seen from Table 3, the regression equation correlation coefficient that five kinds of selected variables are set up with SPAD value all reaches extremely notable
Level, the absolute coefficient R of the equation of linear regression matching wherein with MCARI as independent variable2With correlation coefficient r all highests, difference
For 0.461 and -0.6789.
2) partial least-squares regression method (Partial least squares regression, PLSR) is a kind of new
Multivariate statistics data analysing method, what it was mainly studied is the regression modeling to many independent variables for the multivariate response, especially works as each variable
During internal height linear correlation, more effective with partial least-squares regression method.PLSR collection main constituent, canonical correlation and multiple linear return
The advantage returning three kinds of analysis methods of analysis is integrated, and can build model using all effective spectrum parameters, extract reflection
The maximum information of data variation, has good forecast function[4].Application PLSR[15]Spectrum to 800 samples of the time of infertility
Characteristic parameter sets up the SPAD forecast model of Cotton Canopy blade, the R of model2=0.733, RMSEC=4.546, each spectrum becomes
Amount is shown in Table 4 with the regression coefficient of SPAD value.
The each spectral variables of table 4 Cotton Gossypii and the regression coefficient of SPAD
2.4 model testing
For testing model effect, using 120 test samples, the model accuracy of different input variables is tested, adopt
Use coefficient of determination R2, root-mean-square error RMSE and three indexs of regression equation slope to be checking the prediction energy of time of infertility model
Power, coefficient of determination R2With slope absolute value closer to 1, RMSE value is less, illustrates that precision of forecasting model is higher.Model testing result
It is shown in Table 5 and Fig. 3.
Table 5 SPAD appraising model accuracy test
As shown in Table 5, estimated by the SPAD that the red side of spectral signature variable MCARI, MCARI/OSAVI, MTCI, VARI, R is set up
The precision calculating model prediction time of infertility Cotton Canopy SPAD value is relatively low, in addition to MTCI, the appraising model of four additional parameter
Checking R2All 0.53 about, all there is no the checking R of SPAD-PLSR model2Greatly (0.7370).In all models, SPAD-
The checking R of PLSR model2Maximum, RMSE is minimum, and respectively 0.737 and 4.135, so SPAD-PLSR model is compared to other
Model has obvious advantage, can effectively SPAD value be estimated.Relatively first five model, the R of SPAD-VARI (700)2?
Greatly, but its root-mean-square error RMSE is also maximum, regression equation slope only 0.553 simultaneously, illustrate that this model prediction accuracy is not high；
The R of SPAD-MCARI model2It is only second to SPAD-VARI (700), root-mean-square error is minimum in five models, returns simultaneously
Return equation slope closest to 1, illustrate that SPAD-MCARI precision highest, predictive ability in first five model are best.
From the figure 3, it may be seen that the cotton in the regression equation set up by independent variable with spectral variables, with MCARI as independent variable
Corolla layer SPAD value estimated value and actual measurement Distribution value are closest to 1:1 line, demonstrates above-mentioned SPAD-MCARI further at first five
Precision highest in individual model, best to the estimation ability of time of infertility SPAD value.And pass through SPAD-PLSR model actual measurement value with pre-
The comparison of measured value scattergram and SPAD-MCARI model actual measurement value and calculating value distribution Butut is it can be seen that SPAD-PLSR model is excellent
Gesture becomes apparent from, and the distribution between its predictive value and measured value more concentrates, closer to 1:1 line, it is thus determined that SPAD-PLSR model is
The best model of estimation Cotton Gossypii time of infertility canopy SPAD value.
3 conclusions and discussion
The dependency of Cotton Canopy original spectrum reflectivity data, the first derivative spectra data and SPAD is all higher, permissible
It is used for estimating SPAD value.The dependency that the dependency of the first derivative spectra and SPAD does than original spectrum reflectivity data on the whole
More preferably, this is because differential eliminates the impact of background, atmospheric scattering to result, and improves the contrast of different Absorption Characteristics.
For Primitive reflex spectrum, the sensitive band of SPAD value occurs at 708.2nm, corresponding r=-0.533；For first differential light
Spectrum, the sensitive band of SPAD content occurs at 734.7nm, r=0.6992.
When SPAD value being estimated using canopy spectra data, generally with original spectrum and the first derivative spectra as data
Source, extracts Remote Spectra characteristic parameter, makees linear regression analyses with spectroscopic data variation to time of infertility SPAD value, thus
Set up the SPAD forecast model based on spectrum parameter[16], this is consistent with the first modeling method of the present invention, and adopts PLSR pair
Important spectral variables modeled and checked the time of infertility, and the distribution between its predictive value and measured value more concentrates, closer to 1:1 line,
Illustrate that its forecast result of model is more preferably more accurate, illustrate that SPAD-PLSR appraising model is estimated to time of infertility Cotton Canopy SPAD value
Survey more applicable, this, to instructing cotton planting and production to have positive directive function, can provide foundation for Cotton Gossypii remote sensing monitoring.?
SPAD value prediction model parameter selection aspect, scholar's application before is most to be the Red-edge parameter being extracted by first differential[17],
And best with SPAD value dependency spectral variables in the present invention are the red sides of MCARI, MCARI/OSAVI and R, cause this species diversity
The reason be probably that region is different, illumination condition is different or background complex situations are different.The present invention becomes to important Remote Spectra
Amount does the conventional linear regression model of SPAD value, wherein prediction effect most preferably SPAD-MCARI model：Y=-64.33x+
61.822, R2=0.461, proof-tested in model precision result compared with other, R2Maximum, RMSE is minimum, so SPAD-MCARI mould
Type has certain advantage compared to other models, may apply to the not high platform of required precision.
The time of infertility SPAD-PLSR model sample quantity that the present invention uses is enriched, precision of prediction is high, detailed with the time of infertility
Real field Cotton Gossypii basic data modeling, improves the reliability of estimation models, is that Wei Beihanyuan area prediction Cotton Canopy leaf is green
Element provides reference method, and the high-spectrum remote-sensing monitoring for time of infertility Cotton growth provides foundation, asks for solving local grain
Topic, increasing peasant income and quickening rural economic development have important strategic importance.
Above in conjunction with drawings and Examples, the present invention is described in detail.It is understood, however, that the enforcement of the present invention
Example is not limited to disclosed specific embodiment, and the modification to this embodiment and other embodiment are also intended to be comprised in institute
In the range of attached claims.Although being used here particular term, they only make in general and descriptive sense
With, rather than the purpose in order to limit.
Claims (8)
1. one grow cotton time of infertility canopy SPAD value remote sensing appraising model construction method it is characterised in that comprising the following steps：
Select multiple hillslope processes, select multiple sampling points in each hillslope processes；
Carry out canopy spectra measurement respectively at the different growth key developmental stages of Cotton Gossypii；
Each sampling point surveys a plurality of complete curve, finally takes its average as the average reflectance spectra of this sampling point, each cell takes many
The reflectance spectrum meansigma methodss of individual sampling point are as the reflectance spectrum of this cell；
At the sampling point measuring spectrum, second and third piece blade that Cotton Canopy launches is selected to measure, each sampling point is surveyed at random
Measure multiple SPAD values, take its meansigma methods as the canopy chlorophyll test value of this sampling point；
Original for Cotton Gossypii canopy spectra reflectance and blade SPAD value are carried out Correlation analysis；
Cotton Canopy spectral reflectivity is made to carry out correlation analysiss with blade SPAD value after first differential；
The multiple Remote Spectra parameters chosen and SPAD value are carried out correlation analysiss, chooses the Remote Spectra parameter of correlation maximum
It is modeled.
2. Cotton Gossypii time of infertility canopy SPAD value remote sensing appraising model construction method according to claim 1, its feature exists
In also including：
Obtain the smooth complete curve of spectrum after the original spectrum obtaining is processed, then reflectance spectrum is done at first differential
Reason is to eliminate influence of noise, to reduce error.
3. Cotton Gossypii time of infertility canopy SPAD value remote sensing appraising model construction method according to claim 1, its feature exists
In avoiding vein part during measurement, SPAD time of measuring is synchronous with spectrum data gathering.
4. Cotton Gossypii time of infertility canopy SPAD value remote sensing appraising model construction method according to claim 1, its feature exists
In, including：
Choosing the most significant characteristic spectrum parameter to SPAD value dependency is independent variable, makees Linear Quasi to time of infertility SPAD value
Close, build model.
5. Cotton Gossypii time of infertility canopy SPAD value remote sensing appraising model construction method according to claim 1, its feature exists
In, including：
The spectral signature parameter of all test samples to the time of infertility for the applied forecasting model partial least-squares regression method PLSR is built
The SPAD forecast model of vertical Cotton Canopy blade.
6. Cotton Gossypii time of infertility canopy SPAD value remote sensing appraising model construction method according to claim 1, its feature exists
In described growth key developmental stages include：Seedling stage, Sheng flower bud phase, full-bloom stage, Shengjing Town, the term of opening bolls.
7. built according to the Cotton Gossypii time of infertility canopy SPAD value remote sensing appraising model that in claim 1-6, any one is described
Method is it is characterised in that include：
Using test samples, the model accuracy of different input variables is tested, using coefficient of determination R2, root-mean-square error RMSE
To check the predictive ability of time of infertility model, coefficient of determination R with three indexs of regression equation slope2More connect with slope absolute value
Nearly 1, RMSE value is less, then precision of forecasting model is higher.
8. one grow cotton time of infertility canopy SPAD value remote sensing estimation method it is characterised in that including using according to claim
The model that method that in 1-6, any one is described builds is estimating Cotton Gossypii time of infertility canopy SPAD value.
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| CN111275567A (en) * | 2020-01-15 | 2020-06-12 | 新疆疆天航空科技有限公司 | SENP cotton yield estimation method based on unmanned aerial vehicle image and estimation model construction method |
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| CN109752487A (en) * | 2018-11-29 | 2019-05-14 | 北京农业信息技术研究中心 | Wheat Leavess nitrogen content predictor method and device |
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| CN111275567A (en) * | 2020-01-15 | 2020-06-12 | 新疆疆天航空科技有限公司 | SENP cotton yield estimation method based on unmanned aerial vehicle image and estimation model construction method |
| CN111275567B (en) * | 2020-01-15 | 2022-04-29 | 新疆疆天航空科技有限公司 | SENP cotton yield estimation method based on unmanned aerial vehicle image and estimation model construction method |
| CN111507197A (en) * | 2020-03-23 | 2020-08-07 | 中国科学院空天信息创新研究院 | Cotton defoliant drug application prescription chart generation method and device |
| CN113884444A (en) * | 2020-07-03 | 2022-01-04 | 上海市农业科学院 | Model establishing method, SPAD value predicting method and device and electronic equipment |
| CN111781183A (en) * | 2020-07-30 | 2020-10-16 | 河南省农业科学院小麦研究所 | Method for estimating chlorophyll content of plant leaf by using chlorophyll fluorescence |
| CN112881327A (en) * | 2021-01-25 | 2021-06-01 | 安徽皖南烟叶有限责任公司 | Tobacco leaf SPAD value estimation method based on novel vegetation index |
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