CN113945927A - Forest canopy height inversion method through volume scattering optimization - Google Patents
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Abstract
The invention relates to the technical field of forest canopy height inversion, in particular to a method for inverting forest canopy height by a three-stage algorithm optimized through volume scattering, which comprises the following steps: step one, performing polarized complex phase dry line fitting based on an RVoG model; step two, the reaction is carried out by gammaPDlowEstimating a ground phase phig；γPDlowAnd gammaPDhighThe polarization interference complex coherence with the maximum polarization space phase difference; step three, determining volume scattering; screening out a volume scattering complex coherence observation value from each polarized complex phase trunk and carrying out volume scattering estimation by adopting a mode value invariant projection method; step four, passing the thickness h of the vegetationvAnd estimating the height of the canopy by using a lookup table LUT constructed by the extinction coefficient sigma. According to the forest canopy height estimation method, the ground phase and the volume scattering in the classic three-stage algorithm are optimized, and the accuracy of forest canopy height estimation can be improved.
Description
Technical Field
The invention relates to the technical field of forest canopy height inversion, in particular to a forest canopy height inversion method through volume scattering optimization.
Background
The forest occupies about 30% of the land area, is the most complete and largest land ecosystem on the earth, and is the most important maintainer of the land ecosystem. The forest height is one of basic structural parameters of the forest and is an important forest stand arbor measurement factor. However, due to the restriction of factors such as forest distribution, complex terrain conditions, weather conditions and the like, large-scale continuous forest height measurement is always a technical problem of forest investigation. Synthetic Aperture Radar (SAR) is widely used for forest structure and biophysical parameter inversion due to its ability to acquire vegetation surface polarization and interference pattern data. InSAR (Interferometric Synthetic Aperture radar) and PolInSAR (polar and Interferometric Synthetic Aperture radar) are sensitive to the shape, direction and vertical structure of forest body scattering, and can obtain different polarization interference complex coherence under different vegetation heights for monitoring forest structures.
The PolInSAR technology integrates the measurement of the InSAR technology on the vertical structure of a scatterer and the sensitivity of the PolSAR technology on the shape and the direction of the scatterer, can generate a complex phase dry image under any polarization scattering mechanism, and lays a physical foundation for extracting forest structure information, wherein various polarization scattering mechanisms correspond to forest structure characteristics. In 1998, cloude estimates forest height for the first time by using different scattering mechanism interference optimization algorithms. The RVoG model proposed by Treuhaft et al is the basis of a model for estimating the height mechanism of a forest canopy by the current PolInSAR technology. In 2001, the Papathanassiou combines a polarization interference coherence optimization algorithm with an RVoG model, provides a single-baseline RVoG complex phase dry model tree height inversion 6-parameter method, and adopts nonlinear iterative optimization solution. In 2003, Cloude and Papathanassou propose a classic three-stage algorithm of RVoG complex coherence model based on the geometrical distribution characteristics of complex coherence, and simplify the complexity of forest canopy height estimation. The typical three-stage algorithm is influenced by terrain phase estimation error and bulk coherence estimation error, and the vegetation height inversion has an underestimation phenomenon. Khati adopts a classical three-stage inversion algorithm and TanDEM-X data to invert the forest canopy height of tropical forest areas in India, and an underestimation phenomenon (-7 to-10 m) occurs. The solution is subjected to SAR data simulation, and an underestimation phenomenon exists in the classical three stages when no terrain influence exists; in the forest with larger canopy density, the phase centers of all polarization channels are relatively concentrated, the ground phase center is higher, and the vegetation height estimation value is lower. The RVoG model is a mechanism model for estimating the height of the forest canopy by using a polarization interference technology PolInSAR, and the model estimates the height of the forest canopy by solving the distance between a ground phase center and a bulk scattering phase center and the bulk scattering amplitude.
The classical three-stage algorithm of the RVoG model is to solve for the ground phase and bulk scattering from the polarization scattering features of L, P long wavelengths. Most of data of the current on-orbit satellite-borne SAR system needs to be acquired in a heavy orbit mode, and the influence of time losing coherence is serious during forest height estimation. And the TanDEM-X satellite-borne data adopts a one-sending and two-receiving mode to observe the ground objects, and the time base line is zero. If the X-band data and the classical three-stage algorithm are used for jointly inverting the forest canopy height, the ground phase and the body scattering complex phase interference estimation are inaccurate, and the forest canopy estimated height is underestimated or overestimated. Therefore, the RVoG model classical three-stage inverse algorithm solution aiming at the X-band data needs to be optimized.
Disclosure of Invention
It is an object of the present invention to provide a method for inverting forest canopy height by volume scattering optimization that overcomes some or all of the disadvantages of the prior art.
The method for inverting the forest canopy height through the volume scattering optimization comprises the following steps:
step one, performing polarized complex phase dry line fitting based on an RVoG model;
step two, the reaction is carried out by gammaPDlowEstimating a ground phase phig；γPDlowAnd gammaPDhighIs most different in polarization space phaseLarge polarization interference complex coherence;
step three, determining volume scattering; screening out a volume scattering complex coherence observation value from each polarized complex phase trunk and carrying out volume scattering estimation by adopting a mode value invariant projection method;
step four, passing the thickness h of the vegetationvAnd estimating the height of the canopy by using a lookup table LUT constructed by the extinction coefficient sigma.
Preferably, in the first step, the track of each polarization complex coherence on the plurality of unit circles CUC will be in a linear form; fitting parameters of a complex phase dry fitting straight line by adopting a total least square method; and the phases of two intersection points of the complex coherent fitting straight line and the complex unit circle CUC are used as candidate ground phases.
Preferably, in step two, the composition is prepared from gammaPDlowThe specific steps for estimating the ground phase are as follows:
2.1, calculating the phase difference between each observed complex coherent value and two intersection points, and respectively sorting according to the small to large phase difference delta phii,ωThe following formula is calculated:
wherein gamma (omega) is the total complex coherence of polarization interference of ground and vegetation two-layer models and is changed along with a polarization scattering mechanism omega; i represents an intersection; j is an imaginary number unit, abs () is an absolute value function, and arg () is a phase value function;
2.2, sequencing: if gamma isPDlowWhen the first 3 bits are ordered in Rank1, then the ground phase isg＝φ1(ii) a If gamma isPDlowWhen the first 3 bits are ordered in Rank2, then the ground phase isg＝φ2(ii) a If neither of the two sets of ranks exceeds the first 3 bits, then φ1And phi2Then, the two estimated canopy height values are estimated as candidate ground phases; selecting an estimate of the height of the canopy within a reasonable rangeCandidate ground phase as phigAnd (6) outputting.
Preferably, in step three, the specific steps for determining the volume scattering are as follows:
3.1 observed value of gamma (omega) from scatteringobserve) Selecting a volume-coherent observation
Will gammaPDhigh、γopt3And gammaPDlowExcluding from γHH、γHV、γVH、γVV、γHH-VV、γHH+VV、γOPT1、 γOPT2、γLL、γRRSelecting the complex phase stem which is farthest away from the ground phase as an effective value for observing the body coherence; HH. HV, VH, VV, HH + VV, HH-VV, LL, RR, OPT1, OPT2, OPT3, PDhigh, PDlow are polarization interference complex coherence of 13 polarization scattering mechanisms;
3.2 estimating the volume scatter gamma (omega) by a mode-invariant projection methodv)；
Firstly, using the origin of the coordinate system as the center of a circle and the effective observed value gamma (omega) of the volume scatteringobserve) The module value of (A) is a radius of a circle; then calculating the intersection point P of the circle and the fitting straight line1And P2(ii) a Taking the intersection point P with smaller distance from the vertical projection point P1Scatter gamma (omega) as volumev) As shown in the following formula:
wherein x is gamma (omega)v) Y is gamma (ω)v) K is the slope of the fitted line, b is the intercept of the fitted line, and m is the modulus of the bulk scattering observation
If the volume scatter observation value gamma (omega)observe) The distance to the fitted straight line is very close, P1Not very different from p'; if a circle andif the fitted straight line has no intersection point, the perpendicular projection point p' is used instead.
Preferably, in step four, the canopy height estimation method specifically includes: after the LUT is constructed, a plurality of groups (h) are calculated according to the RVoG modelvσ) theory γvComparison theory of gammavAnd estimating gammavThe canopy height of the effective area can be estimated using the minimization function F, as shown in the following equation:
γvis interference complex coherence, k, caused by vegetation layer body scatteringzIs the vertical effective wave number, and theta is the incident angle of the radar wave.
According to the forest canopy height estimation method, the ground phase and the volume scattering in the classic three-stage algorithm are optimized, and the accuracy of forest canopy height estimation can be improved.
Drawings
FIG. 1 is a flow chart of a method for inverting forest canopy height by volume scattering optimization in example 1;
FIG. 2 is a schematic diagram of the RVoG model in example 1;
FIG. 3 is a schematic representation of the geometric representation of the internal phase trunks in a complex planar unit circle of example 1;
fig. 4 is a schematic diagram of the mode projection of example 1 in which the mode value is unchanged.
Detailed Description
For a further understanding of the invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings and examples. It should be understood that the examples are illustrative of the invention only and not limiting.
Example 1
RVoG model
Treuhaft proposes a forest height inversion method of a random azimuth volume layer model (RVoG) with ground echo, and a forest is a random volume particle layer which is regarded as covering the ground surface and contains a large number of randomly distributed and mutually independent volume particles.
Incident on radar wavesIn the two-layer RVoG model (see fig. 2) with angle θ: the earth surface is considered as a surface scattering layer which cannot be penetrated by radar waves and has a height Z0Causing the ground phase phigThickness of vegetation is hvThe height of the forest canopy is Z0+hv. Assuming that the scattering energy of the vegetation layer changes exponentially with the increase of the height, after eliminating the effects of registration error, atmospheric decoherence and the like, the polarization interference complex coherence gamma (omega) based on the RVoG model is expressed as formula (1):
wherein gamma (omega) is the total complex coherence of polarization interference of ground and vegetation two-layer models and is changed along with a polarization scattering mechanism (omega); phi is ag(＝kzz0) For the surface elevation z0The resulting ground phase. μ (ω) is the effective volume scattering amplitude ratio, see equation (2); t isg(omega) is a reflection symmetric ground scattering coherence matrix, TvAnd (omega) is a diagonal coherence matrix of the volume scattering. f (z) is the radar reflectivity vertical profile,
p2＝p1+ikz(ii) a Theta is the incident angle of the radar wave; sigma is a vegetation layer extinction coefficient; gamma rayvThe interference complex coherence caused by the scattering of the vegetation layer body is shown in a theoretical model of formula (3); k is a radical ofzIs a vertical effective wavenumber, and in the formula (4), a plurality of the interference conditions are Monostand tic, then m is 2; if the interference condition is Bistatic, m is 1. Delta theta is the incident angle difference of the main image and the auxiliary image; λ is the radar wave operating wavelength.
In the RVoG complex coherence model, theta, lambda, delta theta, kzAll can be obtained by bringing in parameters of an SAR platform system; four quantities to be estimated: phi is ag、μ(ω)、hvσ, the forest canopy height can be estimated by solving the RVoG complex coherence model.
As shown in fig. 1, the present embodiment provides a method for inverting forest canopy height by volume scattering optimization, which includes the following steps:
step one, performing polarized complex phase dry line fitting based on an RVoG model;
according to formula (1) in the RVoG model, the trajectory of each polarization Complex coherence (in this embodiment, polarization interference Complex coherence employing 13 polarization scattering mechanisms of HH, HV, VH, VV, HH + VV, HH-VV, LL, RR, OPT1, OPT2, OPT3, PDhigh, and PDlow) in the Complex Unit Circle (CUC) will be in a linear form. The first step of the present embodiment is the same as the classic three-stage algorithm, and the classic three-stage algorithm adopts the overall least square method to fit the parameters of the complex coherent fitting straight line. The phases of two intersections of the Complex Fitting Line (CFL) and the CUC are used as candidate ground phases, as shown in fig. 3.
Step two, the reaction is carried out by gammaPDlowEstimating a ground phase phig；γPDlowAnd gammaPDhighThe polarization interference complex coherence with the maximum polarization space phase difference;
in the classical three-stage algorithm, the ground phase is the comparison γHVThe distance to the candidate intersection is estimated. Under the influence of the uncertainty of the terrain fluctuation and the growth direction of branches and leaves, an X-band HV polarization channel is not necessarily arranged at the top of a forest crown and is possibly close to the ground; meanwhile, the polarized complex coherence distribution of the X wave band is relatively concentrated and tends to a certain intersection point. In both cases, the classical three-stage algorithm may incorrectly estimate the phase. Therefore, this embodiment is constructed from γPDlowThe ground phase is estimated. Gamma rayPDlowAnd gammaPDhighPolarization interference with maximum polarization space phase differenceComplex coherence, gammaPDlowThe phase center is close to the bottom of the forest, and the intersection point on the same side is the ground floor intersection point.
By gammaPDlowThe specific steps for estimating the ground phase are as follows:
2.1, calculating the phase difference between each observed complex coherent value and two intersection points, and respectively sorting according to the small to large phase difference delta phii,ωThe following formula is calculated:
wherein gamma (omega) is the total complex coherence of polarization interference of ground and vegetation two-layer models and is changed along with a polarization scattering mechanism omega; i represents an intersection; j is an imaginary number unit, abs () is an absolute value function, and arg () is a phase value function;
2.2, sequencing: if gamma isPDlowWhen the first 3 bits are ordered in Rank1, then the ground phase isg＝φ1(ii) a If gamma isPDlowWhen the first 3 bits are ordered in Rank2, then the ground phase isg＝φ2(ii) a If neither of the two sets of ranks exceeds the first 3 bits, then φ1And phi2Then, the two estimated canopy height values are estimated as candidate ground phases; selecting the candidate ground phase with the estimated value of the height of the canopy in a reasonable range as phigAnd (6) outputting.
Step three, determining volume scattering; screening out a volume scattering complex coherence observation value from each polarized complex phase trunk and carrying out volume scattering estimation by adopting a mode value invariant projection method;
in the classical three-stage algorithm, γHVAs a volume scattering complex coherence observation, its vertical projection on the fitted straight line is used as an estimate of the volume scattering complex coherence, in which case μHVA value close to 0, gammaHVTo the ground
With the furthest distance. Under the influence of terrain fluctuation and uncertainty of the growth direction of branches and leaves, the HV polarization channel in the X wave band may contain other scattering contributions besides bulk scattering, and the phase of the HV polarization channel is not necessarily at the top of a canopy and may be close to the ground. The classical three-stage algorithm directly selects the scattering complex coherence of the HV polarization channel as a bulk scattering complex coherence observed value. The vertical projection changes the modulus and phase of the effective observed value of the volume scattering complex phase interference, and errors are easily introduced, as shown in fig. 4. Therefore, the embodiment proposes optimized estimation of volume scattering, that is, screening out the observed value of complex coherence of volume scattering from each polarization complex coherence and performing volume scattering estimation by using a module-invariant projection method, which includes the following specific steps:
3.1 observed value of gamma (omega) from scatteringobserve) Selecting a volume-coherent observation
The wavelength of the X wave band is shorter, the penetrability is poorer, and the echo mainly comes from branches and leaves on the upper part of the forest canopy. According to the existing polarization complex phase dry algorithm principle and earlier research results (Chawan autumn, 2018), gamma isPDhighAnd gammaopt3May be higher than the forest canopy. Thus, gamma will bePDhigh、γopt3And gammaPDlowExcluding from γHH、γHV、γVH、γVV、 γHH-VV、γHH+VV、γOPT1、γOPT2、γLL、γRRSelecting the complex phase trunk farthest from the ground phase as an effective value of body coherent observation; HH. HV, VH, VV, HH + VV, HH-VV, LL, RR, OPT1, OPT2, OPT3, PDhigh, PDlow are polarization interference complex coherence of 13 polarization scattering mechanisms;
3.2 estimating the volume scatter gamma (omega) by a mode-invariant projection methodv)；
Firstly, using the origin of the coordinate system as the center of a circle and the effective observed value gamma (omega) of the volume scatteringobserve) The module value of (A) is a radius of a circle; then calculating the intersection point P of the circle and the fitting straight line1And P2(ii) a Get away from perpendicularIntersection point P with smaller projection point P' distance1Scatter gamma (omega) as volumev) As shown in the following formula:
wherein x is gamma (omega)v) Y is gamma (ω)v) K is the slope of the fitted line, b is the intercept of the fitted line, and m is the modulus of the bulk scattering observation
If the volume scatter observation value gamma (omega)observe) The distance to the fitted straight line is very close, P1Not very different from p'; if the circle does not intersect the fitted straight line, the vertical projection point p' is substituted.
Step four, passing the thickness h of the vegetationvAnd estimating the height of the canopy by using a lookup table LUT constructed by the extinction coefficient sigma.
The canopy height estimation method specifically comprises the following steps: after constructing the LUT, according to the RVoG model, calculating a plurality of groups (h)vσ) theory γvComparison theory of gammavAnd estimating gammavThe height of the canopy of the active area can be estimated using a minimization function F, as shown in the following equation:
γvis interference complex coherence, k, caused by vegetation layer body scatteringzIs the vertical effective wave number, and theta is the incident angle of the radar wave. Step four is the same as the existing classical three-stage algorithm.
In this embodiment, a fixed extinction coefficient σ is used in order to be able to examine the performance gain of the optimization method in terms of a high degree of estimation. It has been found that the extinction coefficients of tropical broad-leaved forests and coniferous forests are mainly between 0.1-0.9 dB/m. When a scholars inverts the forest height, the extinction coefficient of the conifer forest is fixed to be 0.2dB/m, and the extinction coefficient of the tropical forest is eliminatedThe optical coefficients are fixed at 0.3dB/m and 0.4 dB/m. In this example, the extinction coefficients of Sipalene in the study area were all 0.2 dB/m. In addition, hvThe values are limited to 5-30 m.
The present invention and its embodiments have been described above schematically, and the description is not intended to be limiting, and what is shown in the drawings is only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, if the person skilled in the art receives the teaching, without departing from the spirit of the invention, the person skilled in the art shall not inventively design the similar structural modes and embodiments to the technical solution, but shall fall within the scope of the invention.
Claims (5)
1. A method for inverting forest canopy height through volume scattering optimization is characterized by comprising the following steps: the method comprises the following steps:
step one, performing polarized complex phase dry line fitting based on an RVoG model;
step two, the reaction is carried out by gammaPDlowEstimating a ground phase phig；γPDlowAnd gammaPDhighThe polarization interference complex coherence with the maximum polarization space phase difference;
step three, determining volume scattering; screening out a volume scattering complex coherence observation value from each polarized complex phase trunk and carrying out volume scattering estimation by adopting a mode value invariant projection method;
step four, passing the thickness h of the vegetationvAnd estimating the height of the canopy by using a lookup table LUT constructed by the extinction coefficient sigma.
2. The method for inverting forest canopy heights optimized by volume scattering according to claim 1, wherein: in the first step, the track of each polarized complex coherence in the complex unit circle CUC is in a linear form; fitting parameters of a complex phase dry fitting straight line by adopting a total least square method; and the phases of two intersection points of the complex coherent fitting straight line and the complex unit circle CUC are used as candidate ground phases.
3. Inversion forest canopy height square optimized by volume scattering as claimed in claim 1The method is characterized in that: in the second step, the reaction is carried out by gammaPDlowThe specific steps for estimating the ground phase are as follows:
2.1, calculating the phase difference between each observed complex coherent value and two intersection points, and respectively sorting according to the sequence from small to large, wherein the phase difference is delta phii,ωThe following formula is calculated:
wherein gamma (omega) is the total complex coherence of polarization interference of ground and vegetation two-layer models and is changed along with a polarization scattering mechanism omega; i represents an intersection; j is an imaginary number unit, abs () is an absolute value function, and arg () is a phase value function;
2.2, sequencing: if gamma isPDlowWhen the first 3 bits are ordered in Rank1, then the ground phase isg＝φ1(ii) a If gamma isPDlowWhen the first 3 bits are ordered in Rank2, then the ground phase isg＝φ2(ii) a If neither of the two sets of ranks exceeds the first 3 bits, then φ1And phi2Then, the two estimated canopy height values are estimated as candidate ground phases; selecting as phi a candidate ground phase for which the canopy height estimate is within a reasonable rangegAnd (6) outputting.
4. A method for inverting forest canopy heights optimized by volume scattering according to claim 3, characterized in that: in the third step, the specific steps for determining the volume scattering are as follows:
3.1 observed value of gamma (omega) from scatteringobserve) Selecting a volume-coherent observation
Will gammaPDhigh、γopt3And gammaPDlowExclusionFrom γHH、γHV、γVH、γVV、γHH-VV、γHH+VV、γOPT1、γOPT2、γLL、γRRSelecting the complex phase stem which is farthest away from the ground phase as an effective value for observing the body coherence; HH. HV, VH, VV, HH + VV, HH-VV, LL, RR, OPT1, OPT2, OPT3, PDhigh, PDlow are polarization interference complex coherence of 13 polarization scattering mechanisms;
3.2 estimating the volume scatter gamma (omega) by a mode-invariant projection methodv)；
Firstly, using the origin of the coordinate system as the center of a circle and the effective observed value gamma (omega) of the volume scatteringobserve) The module value of (A) is a radius of a circle; then calculating the intersection point P of the circle and the fitting straight line1And P2(ii) a Taking the intersection point P with smaller distance from the vertical projection point P1Scatter gamma (omega) as volumev) As shown in the following formula:
wherein x is gamma (omega)v) Y is gamma (ω)v) K is the slope of the fitted line, b is the intercept of the fitted line, and m is the modulus of the bulk scattering observation
If the volume scatter observation value gamma (omega)observe) The distance to the fitted straight line is very close, P1Not very different from p'; if the circle does not intersect the fitted straight line, the vertical projection point p' is substituted.
5. The method for inverting forest canopy heights optimized by volume scattering according to claim 4, wherein: in the fourth step, the canopy height estimation method specifically comprises the following steps: after constructing the LUT, according to the RVoG model, calculating a plurality of groups (h)vσ) theory γvComparison theory of gammavAnd estimating gammavThe minimization function F can be used to estimateThe canopy height of the active area was measured as follows:
γvis interference complex coherence, k, caused by vegetation layer body scatteringzIs the vertical effective wave number, and theta is the radar wave incidence angle.
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| CN117434517A (en) * | 2023-12-21 | 2024-01-23 | 西南林业大学 | Forest canopy height estimation method based on extinction coefficient optimization |
| CN117452432A (en) * | 2023-12-21 | 2024-01-26 | 西南林业大学 | Forest canopy height estimation method based on forest penetration compensation |
| CN117665809A (en) * | 2023-12-21 | 2024-03-08 | 西南林业大学 | Method for inverting forest canopy height |
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| CN117665809B (en) * | 2023-12-21 | 2024-06-21 | 西南林业大学 | Method for inverting forest canopy height |
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