CN113311449B - Hyperspectral laser radar vegetation blade incident angle effect correction method - Google Patents

Hyperspectral laser radar vegetation blade incident angle effect correction method Download PDF

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CN113311449B
CN113311449B CN202110558253.0A CN202110558253A CN113311449B CN 113311449 B CN113311449 B CN 113311449B CN 202110558253 A CN202110558253 A CN 202110558253A CN 113311449 B CN113311449 B CN 113311449B
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vegetation
surface roughness
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CN113311449A (en
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白杰
牛铮
高帅
毕恺艺
黄滟茹
张昌赛
孙刚
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Aerospace Information Research Institute of CAS
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section

Abstract

The invention discloses a method for correcting the incidence angle effect of a hyperspectral laser radar vegetation blade, which comprises the steps of measuring echo intensity data of a measured vegetation blade sample under different wavelengths and different incidence angles by using a hyperspectral laser radar; on the premise of simultaneously considering the influence of the wavelength and the incidence angle on the diffuse reflection scale factor and the surface roughness, correcting an original incidence angle effect formula; calculating by adopting a least square method to obtain two parameters in the corrected incidence angle effect formula; sequentially and iteratively calculating diffuse reflection scale factors and surface roughness parameters under all wavelengths and incidence angles, and constructing a lookup table; establishing a corrected hyperspectral laser radar vegetation blade incident angle effect correction formula; and correcting the echo intensity of the same vegetation blade at other wavelengths and incidence angles based on the lookup table and the incidence angle effect correction formula. The method simultaneously considers the influence of the wavelength and the incident angle of the hyperspectral laser radar on the diffuse reflection scale factor and the surface roughness, and improves the correction effect.

Description

Hyperspectral laser radar vegetation blade incident angle effect correction method
Technical Field
The invention relates to the technical field of hyperspectral laser radars, in particular to a method for correcting the incidence angle effect of vegetation blades of a hyperspectral laser radar.
Background
The traditional single-waveband laser radar can only acquire echo information of a single waveband, the existing hyperspectral imager can only acquire hyperspectral radiation signal values on a two-dimensional plane, and the algorithm is more although the three-dimensional hyperspectral point cloud acquired by the method based on data fusion of the single-waveband laser radar and the hyperspectral imager is developed for a period of time, but a certain matching error which cannot be eliminated exists in the data fusion process. The hyperspectral lidar solves the problems, hyperspectral lidar can be used for directly acquiring hyperspectral three-dimensional point cloud data, but the hyperspectral lidar also faces the problem of an incident angle effect, when the three-dimensional point cloud data is acquired, the echo intensities of the same leaf acquired under different incident angles are different, certain errors can be brought when inversion of vegetation biochemical parameters, and the capability of accurately estimating the vertical distribution of vegetation biochemical components by using the hyperspectral lidar is greatly limited.
The elimination method aiming at the single-waveband laser radar incident angle effect is not few, but most of the elimination methods are based on the assumption that the object surface follows the scattering characteristic of the Lambert cosine law, and part of parameters in the rest few physical correction methods are difficult to estimate, and are time-consuming and labor-consuming.
The prior art has three methods of Lambert body hypothesis, vegetation index method and polynomial fitting method aiming at the correction of the incidence angle effect of the hyperspectral laser radar. The lambertian hypothesis assumes that the surface of the vegetation blade is lambertian, and the backward scattering follows the cosine law, however, the true lambertian body is almost absent in the natural world, and the law cannot truly represent the complex reflection characteristics of the vegetation blade; the vegetation index method considers that similar incident angle effects exist in adjacent wave bands, the incident angle effects can be eliminated to a certain extent by constructing the vegetation index, the defect is that a user cannot directly obtain the echo intensity after the correction of a certain wave band, but only can obtain the result of one vegetation index, and if the index is not suitable for the subsequent biochemical component estimation, the index cannot be used continuously; the polynomial fitting rule is to simply combine various related variables to obtain a polynomial fitting mathematical relation for a specific example, and has no physical significance and low practicability.
Disclosure of Invention
The invention aims to provide a hyperspectral lidar vegetation blade incident angle effect correction method, which considers the influences of the wavelength and the incident angle of a hyperspectral lidar, improves the correction effect, is not limited by a vegetation index method, and can obtain the corrected echo intensity of any wavelength and any incident angle.
The purpose of the invention is realized by the following technical scheme:
a method for hyperspectral lidar vegetation blade angle of incidence effect correction, the method comprising:
step 1, measuring echo intensity data of a measured vegetation blade sample under different wavelengths and different incidence angles by using a hyperspectral laser radar;
step 2, for the hyperspectral lidar, on the premise of simultaneously considering the influence of the wavelength and the incidence angle on the diffuse reflection scale factor and the surface roughness, correcting an original incidence angle effect formula, wherein the corrected incidence angle effect formula is expressed as:
Figure BDA0003078116160000021
wherein, I l,λ (alpha) is the intensity of the back scattering echo of the blade under a certain wavelength lambda and an incidence angle alpha of the hyperspectral lidar; I.C. A l , λ (0) Is the backscattering echo intensity of the blade in a certain wavelength lambda and normal direction; k is a radical of formula d,λ (. Alpha.) and m λ (α) diffuse reflectance scale factor and surface roughness, respectively, under simultaneous consideration of wavelength and angle of incidence;
step 3, calculating diffuse reflection scale factor k in the incidence angle effect formula corrected in the step 2 by adopting a least square method according to echo intensity data measured by all blade samples under a certain wavelength and incidence angle d,λ (alpha) and surface roughness m λ (α)；
Step 4, adopting the mode of the step 3, sequentially and iteratively calculating diffuse reflection scale factors and surface roughness parameters under all wavelengths and incidence angles so as to construct a corresponding lookup table;
step 5, establishing a corrected hyperspectral lidar vegetation blade incident angle effect correction formula according to the corrected incident angle effect formula in the step 2, wherein the hyperspectral lidar vegetation blade incident angle effect correction formula specifically comprises the following steps:
Figure BDA0003078116160000022
wherein, I l,λ,cor (α) is the echo intensity of the vegetation leaf sample after correction at wavelength λ and incident angle α;
and 6, correcting the echo intensities of the vegetation blades under other wavelengths and incidence angles based on the lookup table constructed in the step 4 and the incidence angle effect correction formula established in the step 5, and obtaining the corrected echo intensities.
According to the technical scheme provided by the invention, the influence of the wavelength and the incident angle of the hyperspectral laser radar is considered, the correction effect is improved, the method is not limited by a vegetation index method, the corrected echo intensity of any wavelength and any incident angle can be obtained, and a foundation is laid for the vertical estimation of subsequent biochemical parameters.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for correcting the effect of the incidence angle of a hyperspectral lidar vegetation blade according to an embodiment of the invention;
FIG. 2 is a schematic diagram of the variation of the original echo intensity with angle for three vegetation leaf samples according to the present invention;
FIG. 3 is a graph showing the echo intensities of three leaf samples corrected using a prior art raw correction model;
FIG. 4 is a graph showing the echo intensities of three leaf samples after being corrected by the method according to the embodiment of the invention;
FIG. 5 is a standard deviation diagram comparing the calibration method of the embodiment of the present invention with the original calibration model of the one-band lidar.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
In the following, embodiments of the present invention will be described in further detail with reference to the accompanying drawings, and as shown in fig. 1, a schematic flow chart of a method for correcting an incident angle effect of a hyperspectral lidar vegetation blade provided by the embodiments of the present invention is shown, where the method includes:
step 1, measuring echo intensity data of a measured vegetation blade sample under different wavelengths and different incidence angles by using a hyperspectral laser radar;
in this step, the incident angle is set in such a manner that: the laser incidence direction of the hyperspectral laser radar is fixed, and a compass on which a vegetation leaf sample to be detected is supported is rotated in each experiment, so that the included angle between the normal of the vegetation leaf sample to be detected and the laser incidence direction is changed;
wherein, the laser incidence angle is set to be 0-70 degrees; step length is 10 degrees; the wavelength range is 540nm-840nm.
In specific implementation, the reason why the embodiment does not set a larger incident angle is that experiments show that an excessively large incident angle causes very weak and almost no echo intensity. The wavelength range of the instrument used in the experiment of the embodiment is 540nm-840nm, the spectral resolution is 16nm, and after the experiment is completed, the echo intensities of the vegetation blade sample to be measured under different wavelengths and incidence angles are obtained.
Step 2, correcting an original incidence angle effect formula on the premise of simultaneously considering the influence of the wavelength and the incidence angle on a diffuse reflection scale factor and the surface roughness for the hyperspectral laser radar;
when using a traditional single-band laser radar to characterize the backscattering intensity distribution of an object surface, the following model (i.e. the original incidence angle effect formula) can be used:
I＝f[k d cosα+(1-k d )exp(-(tan 2 α)/m 2 )/cos 5 α]
wherein I is the backscattering intensity under a given incidence angle and is used for representing the complex reflection characteristics of the surface of the vegetation blade; f is the echo intensity with the incident angle in the normal direction of the blade; k is a radical of d Is a diffuse reflectance scale factor; α is the angle of incidence; m is the object surface roughness; k is a radical of d And m can be estimated by using a least square method based on a curve of intensity changing along with the angle, and the value range is 0-1.
It is noted that the diffuse reflectance scale factor k is assumed in the original model d And the surface roughness m is only wavelength dependent, the corresponding original angle of incidence effect correction formula should be expressed as:
I cor ＝I/[k d cosα+(1-k d )exp(-(tan 2 α)/m 2 )/cos 5 α]
wherein, I cor Is the corrected backscatter intensity at a given angle of incidence;
however, the surface of the object is considered to be a smooth surface, and the following conditions need to be satisfied:
Δh＜λ/(8cosα)
in the experiment, the Δ h is generally difficult to directly acquire and is a physical quantity on a microscopic scale. When measuring the surface roughness parameter of an object and the reflection factor affected by the surface roughness parameter, two factors of the incident angle and the wavelength have to be considered.
The embodiment of the invention represents and calculates the diffuse reflection scale factor k d And when the surface roughness m is obtained, the influence of the wavelength and the incidence angle is considered at the same time, and for the hyperspectral laser radar, the corrected incidence angle effect formula is expressed as follows:
Figure BDA0003078116160000041
wherein, I l,λ (alpha) is the intensity of the back scattering echo of the blade under a certain wavelength lambda and an incidence angle alpha of the hyperspectral lidar; I.C. A l,λ (0) Is the backscattering echo intensity of the blade at a certain wavelength lambda and normal direction; k is a radical of d,λ (. Alpha.) and m λ And (alpha) is a diffuse reflectance scale factor and a surface roughness, respectively, under the influence of both the wavelength and the incident angle.
From the above original angle of incidence effect formula and the corrected angle of incidence effect formula, it can be known that: two parameters on the right side of equal sign in the original incidence angle effect formula-diffuse reflection scale factor k d And the surface roughness m does not change with the incident angle, but only with the wavelength; and the corrected incidence angle effect formula, k d,λ (. Alpha.) and m λ The (α) varies with both wavelength and angle of incidence, and thus the results are very different.
Step 3, calculating diffuse reflection scale factor k in the incidence angle effect formula corrected in the step 2 by adopting a least square method according to echo intensity data measured by all blade samples under a certain wavelength and incidence angle d,λ (. Alpha.) and surface roughness m λ (α)；
In this step, in particular, the echo intensity data obtained in step 1 and the correction of step 2 are usedFormula for the effect of the rear angle of incidence, at I l,λ (. Alpha.) and I l,λ (0) Under the known premise, a diffuse reflection scale factor k of the blade sample under a certain wavelength lambda and an incidence angle alpha is estimated through a least square method d,λ (alpha) and surface roughness m λ (α)。
For example, if 10 samples are used for each type of vegetation leaf in the experiment, the echo intensity at 10 ° incidence angle is corrected to 0 ° for a certain wavelength, such as 540nm, as follows:
the echo intensity I at an angle of incidence of 0 DEG has been measured l,540 (0 deg.), according to step 2, its theoretical echo intensity at an angle of incidence of 10 deg. can be expressed as I l,540 (0) multiplied by the second right-hand portion of the modified angle of incidence effect equation, and the actual I l,540 (10 deg.) has also been measured and by means of least squares, an optimal set of k can be found d,540 (10 ℃) and m 540 (10 °), minimizing a variance between an echo intensity of a theoretical 10 ° incident angle and an echo intensity of an actually measured 10 ° incident angle; thus, the diffuse reflectance scale factor k of the leaf-like sample at a wavelength of 540nm and an incident angle of 10 ° d,λ (alpha) and surface roughness m λ (alpha) can be obtained.
Step 4, adopting the mode of the step 3, sequentially and iteratively calculating diffuse reflection scale factors and surface roughness parameters under all wavelengths and incidence angles, and accordingly constructing a corresponding lookup table;
in the step, specifically, the mode of step 3 is adopted, and the diffuse reflection scale factor k of the blade sample under all wavelengths of the hyperspectral lidar and all incident angles set in the experiment are sequentially calculated in an iterative manner d,λ (alpha) and surface roughness m λ (α) and establishing a wavelength λ, an angle of incidence α, a diffuse reflectance scale factor k d,λ (alpha) and surface roughness m λ (α) a look-up table. Wherein the lookup table is composed of a plurality of rows, each row comprising 4 parameters, respectively wavelength λ, incident angle α, diffuse reflectance scale factor k d,λ (. Alpha.) and surface roughness m λ (α)。
Step 5, establishing a corrected hyperspectral lidar vegetation blade incident angle effect correction formula according to the corrected incident angle effect formula in the step 2, wherein the hyperspectral lidar vegetation blade incident angle effect correction formula specifically comprises the following steps:
Figure BDA0003078116160000051
wherein, I l,λ,cor And (alpha) is the echo intensity of the vegetation blade sample after correction at the wavelength lambda and the incidence angle alpha.
And 6, correcting the echo intensities of the vegetation blades under other wavelengths and incidence angles based on the lookup table constructed in the step 4 and the incidence angle effect correction formula established in the step 5, and obtaining the corrected echo intensities.
In the step, the specific process is as follows:
firstly, according to the lookup table constructed in the step 4, estimating corresponding diffuse reflection scale factor k by adopting an inverse distance weighting method for echo intensities under other wavelengths and incidence angles d,λ (. Alpha.) and surface roughness m λ (alpha); the distance in the inverse distance weighting method refers to the absolute value of the difference between the wavelength of the waveband to be estimated and the wavelengths of two corresponding adjacent wavebands in the lookup table;
for example, if one wants to calculate the diffuse reflectance scale factor k at a wavelength of 541nm and an incident angle of 12 ° d,λ (. Alpha.) and surface roughness m λ (α), the procedure is as follows:
first find the diffuse reflectance scale factor k at a wavelength of 540nm and angles of incidence of 10 ° and 20 °, respectively, in a look-up table d,540 (10 ℃) and k d,540 (20 °), calculating the diffuse reflectance scale factor k at a wavelength of 540nm and an incident angle of 12 ° d,540 (12°)。
Figure BDA0003078116160000061
The diffuse reflectance scale factor k was then found at a wavelength of 556nm at incidence angles of 10 ° and 20 °, respectively d,556 (10 ℃) and k d,556 (20 °), calculating the diffuse reflectance scale factor k at a wavelength of 556nm and an incident angle of 12 ° d,556 (12°)。
Figure BDA0003078116160000062
Finally calculating the diffuse reflectance scale factor k when the wavelength is 541nm and the incidence angle is 12 DEG d,541 (12°)。
Figure BDA0003078116160000063
The same principle for calculating the surface roughness is that first the surface roughness m is found in the look-up table at a wavelength of 540nm and at angles of incidence of 10 and 20, respectively 540 (10°)、m 540 (20 ℃ C.), the surface roughness m at a wavelength of 540nm and an incident angle of 12 ℃ was calculated 540 (12°)。
Figure BDA0003078116160000064
Then, the surface roughness m was found at a wavelength of 556nm and incident angles of 10 ° and 20 °, respectively 556 (10 ℃) and m 556 (20 ℃ C.), the surface roughness m at a wavelength of 556nm and an incident angle of 12 ℃ was calculated 556 (12°)。
Figure BDA0003078116160000065
Finally calculating the surface roughness m at the wavelength of 541nm and the incidence angle of 12 DEG 541 (12°)。
Figure BDA0003078116160000071
And then the estimated diffuse reflectance scale factor k d,λ (. Alpha.) and surface roughness m λ (alpha) is substituted into the incidence angle effect correction formula established in the step 5, the echo intensity is corrected to the echo intensity in the normal direction (under the incidence angle of 0 degrees), and the corrected blade with the wavelength lambda and the incidence angle alpha is obtainedThe echo intensity of (2).
The following is a study of the effects and errors of the calibration method according to the embodiment of the present invention:
fig. 2 is a schematic diagram showing the variation of the original echo intensity with the angle of three vegetation leaf samples according to the embodiment of the present invention, where the three vegetation leaf samples are: a. magnolia denudata; b. walnut; c. and (4) macaranga tanarius. The raw echo intensity drops slowly at 0 deg. -30 deg. incidence, drops rapidly at 40 deg. and 50 deg., and finally at larger incidence this trend becomes less. At angles of incidence greater than 50 deg., almost no intensity values are recorded, the larger the angle of incidence, the smaller the backscatter intensity measured, and the intensity trend is almost flat at larger angles of incidence. From the wavelength, the intensity variation flattens out at wavelengths less than 670nm and greater than 751nm, indicating overall: the intensity decreases with increasing angle of incidence. There is a significant incidence angle effect in the intensity, which is usually mainly due to the surface roughness and diffuse reflectance scale factor of the blade at different incidence angles and different wavelengths.
As shown in fig. 3, which is a schematic diagram of the echo intensities of three leaf samples corrected by using the original correction model of the prior art, the correction effect is not ideal in general, and the echo intensities corrected by magnolia delavayi, walnut and macaranga tanarius show large fluctuation when the angles are more than 40 degrees; the walnut has a greater tendency to fluctuate at 540nm and 686nm compared to magnolia delavayi; furthermore, the intensity of the macaranga tanarius fluctuates most with the change of the incident angle, so the correction effect is poor.
Fig. 4 is a schematic diagram showing the echo intensities of three leaf samples corrected by the method according to the embodiment of the present invention, and no significant fluctuation is found compared with the correction result of fig. 3. For walnuts and macaranga tanarius, the corrected intensities have small fluctuations at 653nm and 670nm, probably due to systematic errors in the acquisition of the intensity data by the hyperspectral lidar, and overall, the intensities of other incident angles after correction are close to the intensities in the normal direction.
The above results show that: the correction method of the present invention, which considers both the incident angle and the wavelength, is better than the correction effect of the original model, and the incident angle effect is eliminated overall.
In addition, error analysis was performed for quantitative comparison and analysis of the correction effect. The echo intensity under the incident angle of 0 is taken as a standard value, the standard deviation of the echo intensity after the correction of the original correction model and the correction method of the embodiment of the invention is counted, as shown in fig. 5, the standard deviation intention of the correction method of the embodiment of the invention and the standard deviation intention of the echo intensity after the correction of the original correction model of the single-band laser radar are compared, and it can be clearly seen from the figure that: the standard deviation of the correction method provided by the embodiment of the invention is smaller than that of the original correction model, so that the superiority of the correction method provided by the embodiment of the invention is shown.
It is noted that those skilled in the art will recognize that embodiments of the present invention are not described in detail herein.
In summary, the correction method provided by the embodiment of the invention does not adopt an ideal lambertian body hypothesis, when the complex reflection characteristics of the blade surface are represented, the blade surface is regarded as a combination of diffuse reflection and specular reflection, and when diffuse reflection scale factors and roughness calculation are considered, the influence of the wavelength and the incidence angle of the hyperspectral lidar is considered for the first time, so that the correction effect is improved; meanwhile, in the using process, the correction method is not limited by a vegetation index method, and the corrected echo intensity of any wavelength and any incidence angle can be obtained, so that a foundation is laid for the vertical estimation of subsequent biochemical parameters.
The above description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are also within 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 (5)

1. A hyperspectral lidar vegetation blade incident angle effect correction method is characterized by comprising the following steps of:
step 1, measuring echo intensity data of a measured vegetation blade sample under different wavelengths and different incidence angles by using a hyperspectral laser radar;
step 2, for the hyperspectral lidar, on the premise of simultaneously considering the influence of the wavelength and the incidence angle on the diffuse reflection scale factor and the surface roughness, correcting an original incidence angle effect formula, wherein the corrected incidence angle effect formula is expressed as:
Figure FDA0003078116150000011
wherein, I l,λ (alpha) is the intensity of the back scattering echo of the blade under a certain wavelength lambda and an incidence angle alpha of the hyperspectral lidar; i is l , λ (0) Is the backscattering echo intensity of the blade in a certain wavelength lambda and normal direction; k is a radical of d,λ (. Alpha.) and m λ (α) diffuse reflectance scale factor and surface roughness, respectively, under consideration of both wavelength and angle of incidence;
step 3, calculating the diffuse reflection scale factor k in the incidence angle effect formula corrected in the step 2 by adopting a least square method according to the echo intensity data measured by all the blade samples under a certain wavelength and an incidence angle d,λ (alpha) and surface roughness m λ (α)；
Step 4, adopting the mode of the step 3, sequentially and iteratively calculating diffuse reflection scale factors and surface roughness parameters under all wavelengths and incidence angles, and accordingly constructing a corresponding lookup table;
step 5, establishing a corrected hyperspectral lidar vegetation blade incident angle effect correction formula according to the corrected incident angle effect formula in the step 2, wherein the hyperspectral lidar vegetation blade incident angle effect correction formula specifically comprises the following steps:
Figure FDA0003078116150000012
wherein, I l,λ,cor (α) is the echo intensity of the vegetation blade sample after correction at wavelength λ and incidence angle α;
and 6, correcting the echo intensities of the vegetation blades under other wavelengths and incidence angles based on the lookup table constructed in the step 4 and the incidence angle effect correction formula established in the step 5, and obtaining the corrected echo intensities.
2. The method for correcting the effect of the incidence angles of the hyperspectral lidar vegetation blades according to claim 1 is characterized in that in step 1, the incidence angles are set in a manner that:
the laser incidence direction of the hyperspectral laser radar is fixed, and a compass on which a vegetation leaf sample to be detected is supported is rotated in each experiment, so that the included angle between the normal of the vegetation leaf sample to be detected and the laser incidence direction is changed;
wherein, the laser incidence angle is set to be 0-70 degrees; step size is 10 °; the wavelength range is 540nm-840nm.
3. The method for correcting the effect of the hyperspectral lidar vegetation blade incidence angle according to claim 1, wherein in step 3, in particular according to the echo intensity data obtained in step 1 and the formula of the incidence angle effect corrected in step 2, in step I l,λ (. Alpha.) and I l,λ (0) On the premise of known conditions, a diffuse reflection scale factor k of the blade sample under a certain wavelength lambda and an incidence angle alpha is estimated through a least square method d,λ (alpha) and surface roughness m λ (α)。
4. The method for correcting the effect of the incidence angles of the vegetation blades of the hyperspectral lidar according to claim 1, wherein in step 4, specifically in the manner of step 3, the diffuse reflectance scale factor k of the blade samples at all wavelengths of the hyperspectral lidar and at all incidence angles set in the experiment is sequentially calculated in an iterative manner d,λ (. Alpha.) and surface roughness m λ (α) and establishing a wavelength λ, an angle of incidence α, a diffuse reflectance scale factor k d,λ (. Alpha.) and surface roughness m λ (α) a look-up table.
5. The method for correcting the effect of the hyperspectral lidar vegetation blade incidence angle according to claim 1, wherein the process of step 6 specifically comprises:
constructed first according to step 4A lookup table for estimating corresponding diffuse reflectance scale factor k by inverse distance weighting method for echo intensities at other wavelengths and incidence angles d,λ (. Alpha.) and surface roughness m λ (alpha); the distance in the inverse distance weighting method refers to an absolute value of a difference between the wavelength of the waveband to be estimated and the wavelengths of two corresponding adjacent wavebands in the lookup table;
and then the estimated diffuse reflectance scale factor k d,λ (. Alpha.) and surface roughness m λ And (alpha) substituting the incidence angle effect correction formula established in the step 5 to obtain the echo intensity of the vegetation blade sample after correction under the wavelength lambda and the incidence angle alpha.
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