CN106525731A - Canopy-leaf-nitrogen vertical distribution detection method and device based on remote sensing and agronomy knowledge - Google Patents
Canopy-leaf-nitrogen vertical distribution detection method and device based on remote sensing and agronomy knowledge Download PDFInfo
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- CN106525731A CN106525731A CN201610856308.5A CN201610856308A CN106525731A CN 106525731 A CN106525731 A CN 106525731A CN 201610856308 A CN201610856308 A CN 201610856308A CN 106525731 A CN106525731 A CN 106525731A
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N2021/1793—Remote sensing
- G01N2021/1797—Remote sensing in landscape, e.g. crops
Abstract
The invention provides a canopy-leaf-nitrogen vertical distribution detection method and device based on remote sensing and agronomy knowledge. The method includes the steps that the remote sensing reflection information of red light, green light and near-infrared bands of a crop canopy is obtained; according to the agronomy knowledge, a crop-canopy-leaf-nitrogen vertical distribution mathematical model is established; according to the remote sensing reflection information of the red light, green light and near-infrared bands of the crop canopy, an empirical statistic method is adopted, and estimation values of the canopy-nitrogen vertical distribution model parameter K (namely, the vertical distribution coefficient) and N <0> (namely, the nitrogen content of canopy top leaves) are obtained; according to the canopy-nitrogen vertical distribution model and the estimation values of the parameter K and the N <0> obtained through remote sensing, crop-canopy-leaf-nitrogen vertical distribution information is obtained. According to the canopy-leaf-nitrogen vertical distribution detection method and device, the rapid non-destructive monitoring advantages of the remote sensing technology and the advantages of the mechanism performance and the universality of an agronomy knowledge model are fully used, and high-accuracy remote sensing detection of the different-level leaf-nitrogen concentration of crops is achieved; in other words, high-accuracy remote sensing detection of crop-leaf-nitrogen vertical distribution is achieved.
Description
Technical field
The present invention relates to agricultural technology field, and in particular to a kind of canopy leaf nitrogen based on remote sensing information with agricultural knowledge hangs down
Straight distribution detection method and device.
Background technology
Land resource is seriously in short supply at present, and weather conditions are complicated and changeable, improves existing fertility of ploughing to maintaining grain
Food safety is most important.Nitrogen is the indispensable important nutrient of crop.Plant growth and production depend not only upon plant from
The quantity of nitrogen is drawn in soil, and largely additionally depends on vertical distribution form of the nitrogen in canopy.Improve and
Adjusting vertical distribution of the nitrogen in canopy can be used as a kind of feasible way for improving crop-producing power, and which acts on following big
Become more important under the continuous elevated weather conditions of air carbon dioxide concentration.Using remote sensing technology monitoring crop Nitrogen Status,
With the advantage such as quick, lossless, scope is big, for the importance and necessity of modern agricultural production is commonly recognized.At present
Existing crop nitrogen remote-sensing monitoring method is essentially all the pin with the average leaf nitrogen concentration of canopy or canopy Nitrogen Accumulation amount as target
The remote sensing estimation method of canopy leaf nitrogen vertical distribution is also extremely lacked.Meanwhile, in view of crop different levels Leaf nitrogen concentration
The sensitivity that difference distribution and different levels blade are coerced to nitrogen is different, builds canopy leaf nitrogen vertical distribution remote sensing technique pair
Improve crop nitrogen remote sensing monitoring precision and its actual application value is also extremely important.
At present, the remote detecting method of crop canopies different levels leaf N content is very limited.Wherein, based on crop canopies
The evaluation method of reflectance spectrum and partial least squares algorithm, in view of contribution of the lower leave to canopy reflectance spectra is relatively small,
There is larger uncertainty using the method estimation lower floor leaf N content.It is photosynthetic based on crop canopies reflectance spectrum and different levels
The evaluation method of Net long wave radiation intercepting and capturing amount, as the luminous energy acquisition of information for obtaining large area crop different levels is relatively difficult, limits
The practical application of the method is made.The leaf N content of different levels is extracted using multi-angle canopy reflectance spectra, in view of multi-angle is seen
What is surveyed is still the mixed spectra of different leaf layers, and its estimation precision is restricted.Using different levels single blade reflectance spectrum or glimmering
Light characteristic estimates the nitrogen content of each level blade, is faced with large area remote sensing monitoring and is difficult to obtain the reflection of crop different levels blade
The predicament of spectrum and fluorescence information, practical application.
The content of the invention
For defect of the prior art, the present invention provides a kind of canopy leaf nitrogen based on remote sensing information with agricultural knowledge and hangs down
Straight distribution detection method and device, the mechanism for making full use of remote sensing technology quick nondestructive monitoring advantage and agricultural knowledge model to have
Property and universality advantage, realize the high accuracy remote sensing of crop different levels leaf nitrogen concentration, that is, realize crop leaf nitrogen hang down
The high accuracy remote sensing of straight distribution.
In a first aspect, a kind of the invention provides canopy leaf nitrogen detecting vertical distribution based on remote sensing information and agricultural knowledge
Method, including：
Obtain the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
Crop canopies leaf nitrogen vertical distribution mathematical model is set up according to agricultural knowledge：
N=N0·exp(-K·LAI)
Wherein, N is dependent variable, i.e. nitrogen content at canopy depth location；LAI is independent variable, i.e., to hat at the top of canopy
Accumulation leaf area index at a certain depth location of layer；K is Vertical nitrogen distribution coefficient, and its value is bigger, represents that nitrogen vertically divides
Cloth section is steeper, and different levels nitrogen content difference is bigger；Coefficient N0Nitrogen content when being 0 for LAI, the i.e. nitrogen of canopy top vane
Content；
According to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band, using the method for empirical statistics, obtain
Take the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K；
According to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band, using the method for empirical statistics, obtain
Take the nitrogen content N of canopy top vane0Estimated value；
According to model parameter K, N that canopy leaf nitrogen vertical distribution mathematical model and remote sensing are obtained0Estimated value, obtain crop
Canopy leaf nitrogen vertical distribution information.
Further, the remote sensing reflective information for obtaining crop canopies HONGGUANG, green glow and near infrared band, including：
According to preset need, crop canopies HONGGUANG, green glow and near-infrared ripple are obtained based on existing remote sensing platform and sensor
The remote sensing reflective information of section.
Further, the remote sensing reflective information according to crop canopies HONGGUANG, green glow and near infrared band, using experience
The method of statistics, obtains the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K, including：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
According to the canopy spectra vegetation index for obtaining, and canopy spectra vegetation index and canopy Vertical nitrogen distribution coefficient
Empirical statistics relation between K, obtains the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K.
Further, the remote sensing reflective information according to crop canopies HONGGUANG, green glow and near infrared band, using experience
The method of statistics, obtains the nitrogen content N of canopy top vane0Estimated value, including：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
According to the canopy spectra vegetation index for obtaining, and the nitrogen content of canopy spectra vegetation index and canopy top vane
N0Between empirical statistics relation, obtain the nitrogen content N of canopy top vane0Estimated value.
Further, the canopy spectra vegetation index includes：Normalized site attenuation NDVI, red green refer to than vegetation
Number RGVI, ratio vegetation index RVI and/or wide dynamic range vegetation index WDRVI.
Further, described K, N obtained according to canopy leaf nitrogen vertical distribution mathematical model and remote sensing0Estimates of parameters,
Crop canopies leaf nitrogen vertical distribution information is obtained, including：
According to canopy leaf nitrogen vertical distribution mathematical model N=N0K, N that exp (- K LAI) and remote sensing are obtained0Parameter is estimated
Evaluation, obtains crop canopies leaf nitrogen vertical distribution information.
Second aspect, present invention also offers a kind of canopy leaf nitrogen vertical distribution based on remote sensing information with agricultural knowledge is visited
Device is surveyed, including：
First acquisition module, for obtaining the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
Module is set up, for crop canopies leaf nitrogen vertical distribution mathematical model being set up according to agricultural knowledge：
N=N0·exp(-K·LAI)
Wherein, N is dependent variable, i.e. nitrogen content at canopy depth location；LAI is independent variable, i.e., to hat at the top of canopy
Accumulation leaf area index at a certain depth location of layer；K is Vertical nitrogen distribution coefficient, and its value is bigger, represents that nitrogen vertically divides
Cloth section is steeper, and different levels nitrogen content difference is bigger；Coefficient N0Nitrogen content when being 0 for LAI, the i.e. nitrogen of canopy top vane
Content；
Second acquisition module, for the remote sensing reflective information according to crop canopies HONGGUANG, green glow and near infrared band, adopts
The method of empirical statistics, obtains the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K；
3rd acquisition module, for the remote sensing reflective information according to crop canopies HONGGUANG, green glow and near infrared band, adopts
The method of empirical statistics, obtains the nitrogen content N of canopy top vane0Estimated value；
4th acquisition module, for model parameter K, N obtained according to canopy leaf nitrogen vertical distribution mathematical model and remote sensing0
Estimated value, obtain crop canopies leaf nitrogen vertical distribution information.
Further, first acquisition module specifically for：
According to preset need, crop canopies HONGGUANG, green glow and near-infrared ripple are obtained based on existing remote sensing platform and sensor
The remote sensing reflective information of section.
Further, second acquisition module specifically for：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
According to the canopy spectra vegetation index for obtaining, and canopy spectra vegetation index and canopy Vertical nitrogen distribution coefficient
Empirical statistics relation between K, obtains the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K.
Further, the 3rd acquisition module specifically for：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
According to the canopy spectra vegetation index for obtaining, and the nitrogen content of canopy spectra vegetation index and canopy top vane
N0Between empirical statistics relation, obtain the nitrogen content N of canopy top vane0Estimated value.
Further, the canopy spectra vegetation index includes：Normalized site attenuation NDVI, red green refer to than vegetation
Number RGVI, ratio vegetation index RVI and/or wide dynamic range vegetation index WDRVI.
Further, the 4th acquisition module specifically for：
According to canopy leaf nitrogen vertical distribution mathematical model N=N0K, N that exp (- K LAI) and remote sensing are obtained0Parameter is estimated
Evaluation, obtains crop canopies leaf nitrogen vertical distribution information.
As shown from the above technical solution, what the present invention was provided divides based on remote sensing information is vertical with the canopy leaf nitrogen of agricultural knowledge
Cloth detection method, the mechanistic and universality for making full use of remote sensing technology quick nondestructive monitoring advantage and agricultural knowledge model to have
Advantage, obtains with remote sensing technology and makees information on object plane, using the vertical extension of agronomy model realization canopy, establishes mechanistic strong
And reliable crop canopies leaf nitrogen vertical distribution remote detecting method, realize the high accuracy of crop different levels leaf nitrogen concentration
Remote sensing.
Description of the drawings
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
Accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are the present invention
Some embodiments, for those of ordinary skill in the art, on the premise of not paying creative work, can be with basis
These accompanying drawings obtain other accompanying drawings.
Fig. 1 is one embodiment of the invention offer based on remote sensing information and the canopy leaf nitrogen detecting vertical distribution of agricultural knowledge
The flow chart of method；
Fig. 2 is a preferred embodiment of the present invention offer based on remote sensing information and the canopy leaf nitrogen vertical distribution of agricultural knowledge
The flow chart of detection method；
Fig. 3 a- Fig. 3 c are under different water and fertilizer conditions, different times canopy of winter wheat leaf nitrogen vertical distribution and mathematical model are retouched
State schematic diagram；
Fig. 4 a- Fig. 4 d are canopy of winter wheat leaf nitrogen vertical distribution COEFFICIENT K and vegetation index NDVI, RVI, RGVI, WDRVI
Relationship description schematic diagram；
Fig. 5 is the K value precision analysis schematic diagrams that canopy of winter wheat is estimated based on spectral vegetation indexes RGVI；
Fig. 6 a- Fig. 6 d are canopy of winter wheat leaf nitrogen vertical distribution model parameters N0With vegetation index NDVI, RVI, RGVI,
The relationship description schematic diagram of WDRVI；
Fig. 7 is the N that canopy of winter wheat is estimated based on spectral vegetation indexes RVI0Value precision analysis schematic diagram；
Fig. 8 a- Fig. 8 c are the canopy of winter wheat different levels of the method estimation combined with agricultural knowledge based on remote sensing information
The precision analysis schematic diagram of leaf nitrogen concentration；
Fig. 9 is that the canopy leaf nitrogen vertical distribution based on remote sensing information with agricultural knowledge that another embodiment of the present invention is provided is visited
Survey the structural representation of device.
Specific embodiment
For making purpose, technical scheme and the advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, clear, complete description is carried out to the technical scheme in the embodiment of the present invention, it is clear that described embodiment is
The a part of embodiment of the present invention, rather than the embodiment of whole.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
For the scheme that background section is mentioned, the major defect for existing is：1st, based on crop canopies reflectance spectrum and
Partial least squares algorithm estimates the leaf N content of different levels, due to lower leave it is relatively small to the contribution that canopy reflect, it is sharp
There is larger uncertainty with the method estimation lower floor leaf N content.2nd, it is photosynthetic based on crop canopies reflectance spectrum and different levels
Net long wave radiation intercepting and capturing amount estimates the leaf N content of different levels, due to the light for obtaining large area crop different levels in practical application
Energy acquisition of information is relatively difficult, limits the practicality of the method.3rd, different levels are extracted using multi-angle canopy reflectance spectra
Leaf N content, in view of multi-angle observation be still different leaf layers mixed spectra, its estimation precision be limited.4th, based on different levels
Single blade reflectance spectrum or fluorescent characteristic estimate the nitrogen content of each level blade, obtain big face due to being difficult to remote sensing in practical application
The reflection of product crop different layers position blade and fluorescence information, practicality are weaker.5th, lack suitable for different scale and different remote sensing
The crop canopies leaf nitrogen vertical distribution remote sensing technique of platform.
For the defect of background technology scheme, the purpose of the present invention is to consider crop canopies leaf nitrogen vertical distribution form
Feature and obtain the factor such as complexity of desired data, by link crop remote sensing information (i.e. crop canopies spectral reflectance) with
Agricultural knowledge (i.e. crop canopies leaf nitrogen vertical distribution mathematical model), sets up mechanistic strong and reliable crop canopies leaf nitrogen and hangs down
Straight distribution remote detecting method, so that extract the nitrogen of crop different levels blade based on the Remote Spectra data for being easier to obtain
Content, realizes the high accuracy remote sensing of crop canopies leaf nitrogen vertical distribution, while being easy in different remote sensing platforms (star-machine-ground
Deng) and different spaces yardstick on (field-region etc.) practice, with stronger practicality and universality.The present invention is based on
Remote sensing information is combined with agronomy model, by the two mutual supplement with each other's advantages, sets up mechanistic strong and reliable crop canopies leaf nitrogen
Vertical distribution remote-sensing monitoring method.Obtained using remote sensing technology and make information on object plane, using agronomy model realization Crop Information
Extension in canopy vertical direction.Explanation will be explained in detail to the present invention by specific embodiment below.
Fig. 1 shows the canopy leaf nitrogen vertical distribution based on remote sensing information and agricultural knowledge that one embodiment of the invention is provided
The flow chart of detection method.Referring to Fig. 1, the canopy leaf nitrogen based on remote sensing information with agricultural knowledge provided in an embodiment of the present invention hangs down
Straight distribution detection method, comprises the steps：
Step 101：Obtain the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band.
Step 102：Crop canopies leaf nitrogen vertical distribution mathematical model is set up according to agricultural knowledge.
In this step, following crop canopies leaf nitrogen vertical distribution mathematical model is set up according to agricultural knowledge：
N=N0·exp(-K·LAI)
Wherein, N is dependent variable, i.e. nitrogen content at canopy depth location；LAI is independent variable, i.e., to hat at the top of canopy
Accumulation leaf area index at a certain depth location of layer；K is Vertical nitrogen distribution coefficient, and its value is bigger, represents that nitrogen vertically divides
Cloth section is steeper, and different levels nitrogen content difference is bigger；Coefficient N0Nitrogen content when being 0 for LAI, the i.e. nitrogen of canopy top vane
Content.
Step 103：According to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band, using empirical statistics
Method, obtain canopy Vertical nitrogen distribution COEFFICIENT K estimated value.
Step 104：According to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band, using empirical statistics
Method, obtain canopy top vane nitrogen content N0Estimated value.
Step 105：According to model parameter K, N that canopy leaf Vertical nitrogen distribution mathematical model and remote sensing are obtained0Estimation
Value, obtains crop canopies leaf nitrogen vertical distribution information.
Understand from the description above, it is provided in an embodiment of the present invention vertical with the canopy leaf nitrogen of agricultural knowledge based on remote sensing information
Distribution detection method, make full use of remote sensing technology quick nondestructive monitoring advantage and agricultural knowledge model have it is mechanistic and pervasive
Property advantage, with remote sensing technology obtain make information on object plane, using the vertical extension of agronomy model realization canopy, establish mechanistic
Strong and reliable crop canopies leaf nitrogen vertical distribution remote detecting method, realizes the high-precision of crop different levels leaf nitrogen concentration
Degree remote sensing.
With reference to Fig. 2 and by a preferred embodiment present invention is provided based on remote sensing information and agricultural knowledge
Canopy leaf nitrogen detecting vertical distribution method is explained in detail explanation.
The image data developed rapidly there is provided abundant different spatial and temporal resolutions and spectral resolution of remote sensing technology, together
When make data acquisition and using more easy.In modern agricultural production, using remote sensing technology monitoring crop nitrogen nutritional status
Importance is widely recognized as.But the crop canopies leaf nitrogen vertical distribution for still lacking with stronger universality and stability at present is distant
Sense detection method.For this problem, the embodiment of the present invention is intended to：Make full use of remote sensing technology quick nondestructive monitoring advantage and agriculture
The mechanistic and universality advantage that model of gaining knowledge has, obtains with remote sensing technology and makees information on object plane, using agronomy model
The vertical extension of canopy is realized, mechanistic strong and reliable crop canopies leaf nitrogen vertical distribution remote detecting method is set up, is realized
The high accuracy remote sensing of crop different levels leaf nitrogen concentration, while the method is easy in different remote sensing platforms and different spaces yardstick
Upper application, with stronger practicality and universality.
Canopy leaf nitrogen detecting vertical distribution method based on remote sensing information and agricultural knowledge provided in an embodiment of the present invention, bag
Include following process：
Step 101：Obtain the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band.
In this step, according to preset need, crop canopies HONGGUANG, green glow are obtained based on existing remote sensing platform and sensor
With the remote sensing reflective information of near infrared band.
Here, the preset need includes：The crop area of monitoring is needed, needing the period of monitoring, and/or, to monitoring
The requirement of spatial resolution as a result.Such as, a certain preset need is：Need to monitor winter wheat crop, 100 hectares of area is needed
Growth period to be monitored is jointing to blooming, and time interval is less than 5 days, to the spatial resolution requirements of monitoring result is
Below 20m, then can obtain crop canopies HONGGUANG, green glow and near red based on existing remote sensing platform and sensor according to the demand
The remote sensing reflective information of wave section.
Such as the optical image of domestic and international various space satellite observation platforms, the visible ray near-infrared of aviation UAV observation
Remote sensing image, the observation of ground tower, car platform and man portable's spectral reflectance etc..In practical application, according to crop monitoring face
Product, forecasting stage and the spatial resolution demand to monitoring result etc., it is determined that the spatial and temporal resolution of required remote sensing information it
Afterwards, you can collect the data message for meeting needs based on above-mentioned remote sensing platform.
Step 102：Crop canopies leaf nitrogen vertical distribution mathematical model is set up according to agricultural knowledge.
In this step, need to set up crop canopies leaf nitrogen vertical distribution mathematical model according to agricultural knowledge.Specifically, by
It is to regulate and control one of most effective factor of plant leaf blade photosynthetic capacity in nitrogen.On canopy scale, plant leaf blade nitrogen content vertical distribution
Difference is relevant with light distribution difference in canopy；On leaf scale, and maintain what diphosphoribulose carboxylase (Rubisco) was limited
Balance between the carbonation efficiency that carbonation efficiency and electric transmission are limited is relevant.Plant canopy Vertical nitrogen distribution can using with light
Form quantitative description as distributional class, that is, follow Beer law from canopy top down by exponential decrease form with accumulation blade face
The increase of product index (LAI) is gradually lowered.It is specific as follows：
N=N0·exp(-K·LAI)
Wherein, N is dependent variable, i.e. nitrogen content at canopy depth location；LAI is independent variable, i.e., to hat at the top of canopy
Accumulation leaf area index at a certain depth location of layer；K is Vertical nitrogen distribution coefficient, and its value is bigger, represents that nitrogen vertically divides
Cloth section is steeper, and different levels nitrogen content difference is bigger；Coefficient N0Nitrogen content when being 0 for LAI, the i.e. nitrogen of canopy top vane
Content.Under different water and fertilizer conditions, different times canopy of winter wheat leaf nitrogen vertical distribution and model are described as shown in Fig. 3 a- Fig. 3 c.Inspection
Testing and showing, it is feasible canopy leaf nitrogen vertical distribution to be described using above-mentioned exponential decrease pattern, and with the high precision of comparison.
Step 103：According to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band, using empirical statistics
Method, obtain canopy Vertical nitrogen distribution COEFFICIENT K estimated value.
In this step, obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band first and be preced with
Layer spectral vegetation indexes, then according to the canopy spectra vegetation index for obtaining, and canopy spectra vegetation index and canopy nitrogen
Empirical statistics relation between vertical distribution COEFFICIENT K, obtains the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K.
It can be seen that, this step employs the estimated value that the method for empirical statistics obtains canopy Vertical nitrogen distribution COEFFICIENT K.Wherein
Empirical model is widely used method in current Crop Information Remotely sensed acquisition.The method Main Basiss crop parameter and canopy
Empirical statistics relation between spectral vegetation indexes (i.e. the mathematical combination of sensitive band reflectance), with simple structure, precision
It is higher, be easy to the advantages of applying.By canopy near-infrared, HONGGUANG and spectral vegetation indexes and canopy derived from green light band reflectance
Dependency relation with highly significant, such as normalized site attenuation (NDVI), red green ratio between Vertical nitrogen distribution COEFFICIENT K
(vegetation index definition sees below for vegetation index (RGVI), ratio vegetation index (RVI), wide dynamic range vegetation index (WDRVI) etc.
Table is 1).The statistical relationship of winter wheat nitrogen content vertical distribution COEFFICIENT K and above-mentioned vegetation index is as shown in Figure 4 a- shown in Figure 4 d.It is based on
Above-mentioned statistical relationship can be with Remotely sensed acquisition parameter K information.Fig. 5 shows that the winter wheat nitrogen content extracted using RGVI is vertically divided
Cloth values of factor K and measured value comparative result.Inspection shows, is feasible based on canopy spectra index Remotely sensed acquisition K values, and has
Higher precision.
1 spectral vegetation indexes of table are defined
In formula, Rnir、Rred、RgreenRepresent crop canopies in the anti-of near infrared band, red spectral band and green light band respectively
Radiance rate value.
Step 104：According to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band, using empirical statistics
Method, obtain canopy top vane nitrogen content N0Estimated value.
In this step, obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band first and be preced with
Layer spectral vegetation indexes, at the top of the then canopy spectra vegetation index according to acquisition, and canopy spectra vegetation index and canopy
The nitrogen content N of blade0Between empirical statistics relation, obtain the nitrogen content N of canopy top vane0Estimated value.
It can be seen that, similar with above-mentioned steps, this step also uses the nitrogen that the method for empirical statistics obtains canopy top vane
Content N0Estimated value.Wherein canopy Vertical nitrogen distribution model parameter N0Canopy top vane nitrogen content is represented, which is near with canopy
Also have between infrared, HONGGUANG and spectral vegetation indexes derived from green light band reflectance (such as NDVI, RVI, WDRVI, RGVI etc.)
There is the dependency of highly significant.The nitrogen content N of canopy of winter wheat top vane0With the statistical relationship such as figure of above-mentioned vegetation index
Shown in 6a- Fig. 6 d.Can be with Remotely sensed acquisition parameter N based on above-mentioned statistical relationship0Information.Fig. 7 shows little using the winter of RVI extractions
The nitrogen content N of wheat canopy top vane0Value and measured value comparative result.Inspection shows, based on canopy spectra index Remotely sensed acquisition N0
Value is feasible, and with higher precision.
Step 105：According to parameter K, N that canopy leaf nitrogen vertical distribution mathematical model and remote sensing are obtained0Estimated value, obtain
Crop canopies leaf nitrogen vertical distribution information.
In this step, canopy leaf nitrogen vertical distribution mathematical model parameter K and N are extracted using remote sensing reflective information0It
Afterwards, canopy leaf nitrogen vertical distribution section is determined, in other words above-mentioned model N=N0The relation of exp (- K LAI) is i.e. true
It is fixed, then the leaf N content information of crop different levels is obtained.Using under the conditions of the different disposal that the method is obtained, it is different
The estimation result of period of duration canopy of winter wheat different levels leaf nitrogen concentration is as shown in Fig. 8 a- Fig. 8 c.Inspection shows, with measured value ratio
More consistent, precision comparison is high.
By being described above, the present invention passes through on the basis of technical scheme feasibility and practicality is taken into full account
Link remote sensing information and agronomy model, it is proposed that crop canopies leaf nitrogen vertical distribution remote detecting method, with stronger mechanism
Property and reliability, so as to can based on be easier to obtain remotely-sensed data extract crop different levels blade nitrogen content.Inspection knot
Fruit shows (see Fig. 8 a- Fig. 8 c), can extract the leaf of the crop canopies different levels under different times, different condition using the method
Nitrogen concentration information, and with higher precision, universality and stability are stronger.Meanwhile, the method is applicable to different remote sensing platforms
(star-machine-ground etc.) and different spaces yardstick (field-region etc.), should be according to crop monitoring area and concrete need in practical application
Ask, it is determined that the spatial and temporal resolution and collection mode of required remotely-sensed data.As current China's nitrogenous fertilizer has excessive administration, make
Into huge waste and environmental pollution, and carry out the nitrogen vertical distribution remote sensing of crop canopies leaf for raising crop nitrogen remote sensing
Diagnostic accuracy, improves crop production and management level, promotes Sustainable Development of Modern Agriculture, safeguards national food and ecological safety
It is significant.
Another embodiment of the present invention provides a kind of canopy leaf nitrogen vertical distribution based on remote sensing information with agricultural knowledge and visits
Device is surveyed, referring to Fig. 9, the device includes：First acquisition module 91, set up module 92, the second acquisition module the 93, the 3rd obtain mould
Block 94 and the 4th acquisition module 95；Wherein：
First acquisition module 91, for obtaining the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
Module 92 is set up, for crop canopies leaf nitrogen vertical distribution mathematical model being set up according to agricultural knowledge：
N=N0·exp(-K·LAI)
Wherein, N is dependent variable, i.e. nitrogen content at canopy depth location；LAI is independent variable, i.e., to hat at the top of canopy
Accumulation leaf area index at a certain depth location of layer；K is Vertical nitrogen distribution coefficient, and its value is bigger, represents that nitrogen vertically divides
Cloth section is steeper, and different levels nitrogen content difference is bigger；Coefficient N0Nitrogen content when being 0 for LAI, the i.e. nitrogen of canopy top vane
Content；
Second acquisition module 93, for the remote sensing reflective information according to crop canopies HONGGUANG, green glow and near infrared band, adopts
With the method for empirical statistics, the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K is obtained；
3rd acquisition module 94, for the remote sensing reflective information according to crop canopies HONGGUANG, green glow and near infrared band, adopts
With the method for empirical statistics, the nitrogen content N of canopy top vane is obtained0Estimated value；
4th acquisition module 95, for parameter K, N obtained according to canopy leaf nitrogen vertical distribution mathematical model and remote sensing0's
Estimated value, obtains crop canopies leaf nitrogen vertical distribution information.
Further, first acquisition module 91 specifically for：
According to preset need, crop canopies HONGGUANG, green glow and near-infrared ripple are obtained based on existing remote sensing platform and sensor
The remote sensing reflective information of section.
Further, second acquisition module 93 specifically for：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
And, according to the canopy spectra vegetation index for obtaining, and canopy spectra vegetation index and canopy Vertical nitrogen distribution COEFFICIENT K it
Between empirical statistics relation, obtain the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K.
Further, the 3rd acquisition module 94 specifically for：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
And, according to the canopy spectra vegetation index for obtaining, and the nitrogen content N of canopy spectra vegetation index and canopy top vane0
Between empirical statistics relation, obtain the nitrogen content N of canopy top vane0Estimated value.
Further, the canopy spectra vegetation index includes：Normalized site attenuation NDVI, red green refer to than vegetation
Number RGVI, ratio vegetation index RVI and/or wide dynamic range vegetation index WDRVI.
Further, the 4th acquisition module 95 specifically for：
According to canopy leaf nitrogen vertical distribution mathematical model N=N0K, N that exp (- K LAI) and remote sensing are obtained0Parameter is estimated
Evaluation, obtains crop canopies leaf nitrogen vertical distribution information.
Canopy leaf nitrogen detecting vertical distribution device based on remote sensing information and agricultural knowledge provided in an embodiment of the present invention can
For performing the canopy leaf nitrogen detecting vertical distribution side based on remote sensing information and agricultural knowledge described in any of the above-described embodiment
Method, its know-why are similar with technique effect, and here is omitted.
In describing the invention, it should be noted that term " on ", the orientation of the instruction such as D score or position relationship be base
In orientation shown in the drawings or position relationship, it is for only for ease of the description present invention and simplifies description, rather than indicate or imply
The device or element of indication must have specific orientation, with specific azimuth configuration and operation, therefore it is not intended that to this
The restriction of invention.Unless otherwise clearly defined and limited, term " installation ", " being connected ", " connection " should be interpreted broadly, example
Such as, can be fixedly connected, or be detachably connected, or be integrally connected；Can be mechanically connected, or be electrically connected
Connect；Can be joined directly together, it is also possible to be indirectly connected to by intermediary, can be the connection of two element internals.For this
For the those of ordinary skill in field, above-mentioned term concrete meaning in the present invention can be understood as the case may be.
Also, it should be noted that herein, such as first and second or the like relational terms are used merely to one
Entity or operation are made a distinction with another entity or operation, and are not necessarily required or implied between these entities or operation
There is any this actual relation or order.And, term " including ", "comprising" or its any other variant are intended to contain
Lid nonexcludability is included, so that a series of process, method, article or equipment including key elements not only will including those
Element, but also including other key elements being not expressly set out, or also include for this process, method, article or equipment
Intrinsic key element.In the absence of more restrictions, the key element for being limited by sentence "including a ...", it is not excluded that
Also there is other identical element in process, method, article or equipment including the key element.
Above example is merely to illustrate technical scheme, rather than a limitation；Although with reference to the foregoing embodiments
The present invention has been described in detail, it will be understood by those within the art that：Which still can be to aforementioned each enforcement
Technical scheme described in example is modified, or carries out equivalent to which part technical characteristic；And these are changed or replace
Change, do not make the essence of appropriate technical solution depart from the spirit and scope of various embodiments of the present invention technical scheme.
Claims (10)
1. a kind of canopy leaf nitrogen detecting vertical distribution method based on remote sensing information and agricultural knowledge, it is characterised in that include：
Obtain the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
Crop canopies leaf nitrogen vertical distribution mathematical model is set up according to agricultural knowledge：
N=N0·exp(-K·LAI)
Wherein, N is dependent variable, i.e. nitrogen content at canopy depth location；LAI is independent variable, i.e., to canopy at the top of canopy
Accumulation leaf area index at one depth location；K is Vertical nitrogen distribution coefficient；Coefficient N0Nitrogen content when being 0 for LAI, i.e.,
The nitrogen content of canopy top vane；
According to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band, using the method for empirical statistics, hat is obtained
The estimated value of layer Vertical nitrogen distribution COEFFICIENT K；
According to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band, using the method for empirical statistics, hat is obtained
The nitrogen content N of layer top vane0Estimated value；
According to K, N that canopy leaf nitrogen vertical distribution mathematical model and remote sensing are obtained0Estimates of parameters, obtains crop canopies leaf nitrogen and hangs down
Straight distributed intelligence.
2. method according to claim 1, it is characterised in that the acquisition crop canopies HONGGUANG, green glow and near-infrared ripple
The remote sensing reflective information of section, including：
According to preset need, crop canopies HONGGUANG, green glow and near infrared band are obtained based on existing remote sensing platform and sensor
Remote sensing reflective information.
3. method according to claim 1, it is characterised in that described according to crop canopies HONGGUANG, green glow and near-infrared ripple
The remote sensing reflective information of section, using the method for empirical statistics, obtains the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K, including：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
According to the canopy spectra vegetation index for obtaining, and canopy spectra vegetation index and canopy Vertical nitrogen distribution COEFFICIENT K it
Between empirical statistics relation, obtain the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K.
4. method according to claim 1, it is characterised in that described according to crop canopies HONGGUANG, green glow and near-infrared ripple
The remote sensing reflective information of section, using the method for empirical statistics, obtains the nitrogen content N of canopy top vane0Estimated value, including：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
According to the canopy spectra vegetation index for obtaining, and the nitrogen content N of canopy spectra vegetation index and canopy top vane0It
Between empirical statistics relation, obtain the nitrogen content N of canopy top vane0Estimated value.
5. the method according to any one of Claims 1 to 4, it is characterised in that described according to canopy leaf nitrogen vertical distribution number
Learn K, N that model and remote sensing are obtained0Estimates of parameters, obtains crop canopies leaf nitrogen vertical distribution information, including：
According to canopy leaf nitrogen vertical distribution mathematical model N=N0K, N that exp (- K LAI) and remote sensing are obtained0Estimates of parameters,
Obtain crop canopies leaf nitrogen vertical distribution information.
6. a kind of canopy leaf nitrogen detecting vertical distribution device based on remote sensing information and agricultural knowledge, it is characterised in that include：
First acquisition module, for obtaining the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
Module is set up, for crop canopies leaf nitrogen vertical distribution mathematical model being set up according to agricultural knowledge：
N=N0·exp(-K·LAI)
Wherein, N is dependent variable, i.e. nitrogen content at canopy depth location；LAI is independent variable, i.e., to canopy at the top of canopy
Accumulation leaf area index at one depth location；K is Vertical nitrogen distribution coefficient；Coefficient N0Nitrogen content when being 0 for LAI, i.e.,
The nitrogen content of canopy top vane；
Second acquisition module, for the remote sensing reflective information according to crop canopies HONGGUANG, green glow and near infrared band, using experience
The method of statistics, obtains the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K；
3rd acquisition module, for the remote sensing reflective information according to crop canopies HONGGUANG, green glow and near infrared band, using experience
The method of statistics, obtains the nitrogen content N of canopy top vane0Estimated value；
4th acquisition module, for K, N for being obtained according to canopy leaf nitrogen vertical distribution mathematical model and remote sensing0Estimates of parameters, obtains
To crop canopies leaf nitrogen vertical distribution information.
7. device according to claim 6, it is characterised in that first acquisition module specifically for：
According to preset need, crop canopies HONGGUANG, green glow and near infrared band are obtained based on existing remote sensing platform and sensor
Remote sensing reflective information.
8. device according to claim 6, it is characterised in that second acquisition module specifically for：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
According to the canopy spectra vegetation index for obtaining, and canopy spectra vegetation index and canopy Vertical nitrogen distribution COEFFICIENT K it
Between empirical statistics relation, obtain the estimated value of canopy Vertical nitrogen distribution COEFFICIENT K.
9. device according to claim 6, it is characterised in that the 3rd acquisition module specifically for：
Canopy spectra vegetation index is obtained according to the remote sensing reflective information of crop canopies HONGGUANG, green glow and near infrared band；
According to the canopy spectra vegetation index for obtaining, and the nitrogen content N of canopy spectra vegetation index and canopy top vane0It
Between empirical statistics relation, obtain the nitrogen content N of canopy top vane0Estimated value.
10. the device according to any one of claim 6～9, it is characterised in that the 4th acquisition module specifically for：
According to canopy leaf nitrogen vertical distribution mathematical model N=N0K, N that exp (- K LAI) and remote sensing are obtained0Estimates of parameters,
Obtain crop canopies leaf nitrogen vertical distribution information.
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| CN112785590A (en) * | 2021-02-09 | 2021-05-11 | 河北地质大学 | Vegetation index calculation method based on double-difference normalization |
| CN113075251A (en) * | 2021-03-04 | 2021-07-06 | 山西省农业科学院经济作物研究所 | Sorghum waterlogging detection method |
| CN113125356A (en) * | 2021-03-26 | 2021-07-16 | 塔里木大学 | Red date tree canopy leaf nitrogen vertical distribution detection method based on remote sensing information and agronomic knowledge |
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