A method and apparatus for inverting forest leaf area index

Abstract

This application provides a method and apparatus for inverting the leaf area index (LAI) of a forest. The method first acquires information about the tree height and the total attenuation coefficient of each component in the forest to electromagnetic waves. The total attenuation coefficient includes the attenuation coefficients of leaves and branches. Then, based on the tree height and the total attenuation coefficients of each component, the product of the total attenuation coefficients is calculated. Finally, the LAI is inverted using the relationship between the product of the total attenuation coefficients and the LAI. This method utilizes the attenuation characteristics of the forest to electromagnetic waves to invert the LAI. Since the attenuation of electromagnetic waves is not affected by tree species, region, complex meteorological conditions, or the chosen mathematical model, it can more accurately reflect the attenuation of electromagnetic waves by the leaf area. Therefore, the accuracy of the LAI inversion using this method is higher.

Description

Technical Field

[0001] This application relates to the field of ecological research technology, and in particular to a method and apparatus for inverting forest leaf area index. Background Technology

[0002] Forests are large, widely distributed, complex, and highly productive terrestrial ecosystems that play a vital role in maintaining ecological balance. Forest leaf area index (FIA) is an important parameter representing the interaction between forests and the atmosphere, and a key factor in ecosystem and global climate change research. In global forest ecology research, FIA has been recognized as an important reference indicator for describing the state of global forests and their energy and material cycles with the external environment.

[0003] Existing technologies typically utilize optical remote sensing to retrieve forest leaf area index (LAI). This retrieval usually employs empirical methods based on vegetation indices. These methods establish a correlation between LAI and vegetation indices, allowing the vegetation index to be calculated from remotely sensed surface reflectance, which in turn estimates the LAI. However, optical remote sensing cannot be implemented in cloud- and rain-affected areas, limiting its application.

[0004] Empirical models are simple and widely used in practice. However, the accuracy of leaf area index estimated by empirical methods is often affected by tree species, region, and the chosen mathematical model, resulting in low inversion accuracy. Summary of the Invention

[0005] In view of this, the present application provides a method and apparatus for retrieving forest leaf area index, which aims to solve the problems of low accuracy in retrieving forest leaf area index and limitations imposed by complex meteorological conditions in the prior art.

[0006] In a first aspect, embodiments of this application provide a method for retrieving forest leaf area index, the method comprising:

[0007] The tree height information of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves are obtained; the total attenuation coefficient includes the attenuation coefficient of the leaves in the forest to electromagnetic waves and the attenuation coefficient of the branches in the forest to electromagnetic waves.

[0008] Based on the tree height information of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves, calculate the total attenuation coefficient product of tree height;

[0009] The leaf area index is inverted based on the relationship between the total tree height attenuation coefficient product and the leaf area index.

[0010] Optionally, the step of calculating the total attenuation coefficient product based on the tree height information of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves specifically includes:

[0011] Based on the heterogeneity of the attenuation coefficient characteristics of leaves and branches in horizontal and vertical polarization, the attenuation coefficients of leaves and branches are separated.

[0012] Based on the tree height information of the forest and the attenuation coefficient of the leaves in the forest to attenuate electromagnetic waves, calculate the product of tree height and leaf attenuation coefficient;

[0013] Based on the tree height information of the forest and the attenuation coefficient of the branches in the forest to electromagnetic waves, calculate the product of tree height and branch attenuation coefficient.

[0014] Optionally, the step of inverting the leaf area index based on the relationship between the total tree height attenuation coefficient product and the leaf area index specifically includes:

[0015] Construct the relationship between the total tree height attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index;

[0016] The leaf area index is inverted based on the relationship between the total tree height attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index.

[0017] Optionally, the construction of the relationship between the total tree height attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index specifically includes:

[0018] Based on the product of forest tree height and the attenuation coefficients of horizontal and vertical polarization, the relationship between the total attenuation coefficient product of tree height and the leaf area index is constructed.

[0019] Optionally, the method further includes:

[0020] Using a ground-direction volume two-layer model, the parameters of the total tree height attenuation coefficient product in the horizontal polarization and in the relationship between vertical polarization and leaf area index are inverted.

[0021] Secondly, embodiments of this application provide a forest leaf area index inversion device, the device including an acquisition module, a calculation module and an inversion module;

[0022] The acquisition module is used to acquire information about the tree height of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves; the total attenuation coefficient includes the attenuation coefficient of the leaves in the forest to electromagnetic waves and the attenuation coefficient of the branches in the forest to electromagnetic waves.

[0023] The calculation module is used to calculate the total attenuation coefficient product of tree height based on the tree height information of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves.

[0024] The inversion module is specifically used to invert the leaf area index based on the relationship between the total tree height attenuation coefficient product and the leaf area index.

[0025] Optionally, the computing module is specifically used for:

[0026] Based on the heterogeneity of the attenuation coefficient characteristics of leaves and branches in horizontal and vertical polarization, the attenuation coefficients of leaves and branches are separated.

[0027] Based on the tree height information of the forest and the attenuation coefficient of the leaves in the forest to attenuate electromagnetic waves, calculate the product of tree height and leaf attenuation coefficient;

[0028] Based on the tree height information of the forest and the attenuation coefficient of the branches in the forest to electromagnetic waves, calculate the product of tree height and branch attenuation coefficient.

[0029] Optionally, the inversion module specifically includes a construction unit and a calculation unit;

[0030] The construction unit is specifically used to construct the relationship between the total tree height attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index.

[0031] The inversion unit is specifically used to invert the leaf area index based on the relationship between the total tree height attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index.

[0032] Optionally, the building unit is specifically used for:

[0033] Based on the product of forest tree height and the attenuation coefficients of horizontal and vertical polarization, the relationship between the total attenuation coefficient product of tree height and the leaf area index is constructed.

[0034] Optionally, the inversion module is specifically used for:

[0035] Using a ground-direction volume two-layer model, the parameters of the total tree height attenuation coefficient product in the horizontal polarization and in the relationship between vertical polarization and leaf area index are inverted.

[0036] This application provides a method and apparatus for inverting the leaf area index (LAI) of a forest. When executing the method, firstly, the tree height information of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves are obtained. The total attenuation coefficient includes the attenuation coefficient of leaves and branches to electromagnetic waves. Then, based on the tree height information and the total attenuation coefficient of each component, the product of the total attenuation coefficients of the tree height is calculated. Finally, the LAI is inverted based on the relationship between the product of the total attenuation coefficients of the tree height and the LAI. Thus, by inverting the LAI through the relationship between the product of the total attenuation coefficients of the tree height and the LAI, that is, by utilizing the attenuation characteristics of the forest to electromagnetic waves, the LAI is inverted. Since the attenuation of electromagnetic waves is not affected by tree species, region, complex meteorological conditions, or the selected mathematical model, it can more accurately reflect the attenuation of electromagnetic waves by the leaf area. Therefore, the accuracy of inverting the LAI using the above method is higher. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings used in the description of the embodiment or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 A framework diagram of a method for retrieving leaf area index provided in an embodiment of this application;

[0039] Figure 2 A flowchart illustrating a leaf area index inversion method provided in this application embodiment;

[0040] Figure 3 A flowchart illustrating the scattering and attenuation of electromagnetic waves in a forest, provided as an embodiment of this application;

[0041] Figure 4 A flowchart illustrating the physical relationship model between leaf area index and polarimetric synthetic aperture radar parameters is provided in this application embodiment.

[0042] Figure 5 This application provides an embodiment of a parameter inversion method using the OVoG model. and h v Flowchart;

[0043] Figure 6 This is a schematic diagram of a forest leaf area index inversion device provided in an embodiment of this application. Detailed Implementation

[0044] Forests are large, widely distributed, complex, and highly productive terrestrial ecosystems that play a vital role in maintaining ecological balance. Forest leaf area index (FIA) is an important parameter representing the interaction between forests and the atmosphere, and a key factor in ecosystem and global climate change research. In global forest ecology research, FIA has been recognized as an important reference indicator for describing the state of global forests and their energy and material cycles with the external environment.

[0045] Currently, remote sensing inversion techniques for forest leaf area index include:

[0046] (1) Inversion techniques based on optical data

[0047] There are generally two methods for retrieving forest leaf area index (LAI) using optical remote sensing: one is an empirical method based on vegetation indices, and the other is a physical model method based on the theory of canopy light transmission. The empirical method establishes a correlation between LAI and vegetation indices, calculates the vegetation index from remotely sensed surface reflectance, and then estimates the LAI. While the empirical model is simple, the accuracy of the empirical relationship is often affected by tree species, region, and the chosen mathematical model, resulting in uncertain accuracy and lack of portability. Furthermore, an empirical model obtained in one region is often difficult to reliably apply to another. The second method is based on physical models, which establish models of surface spectral reflectance and biophysical parameters of leaves, canopy, and background, such as LAI. Using remotely sensed surface reflectance combined with known surface information, the inverted model can estimate the key spectral contribution parameter, LAI. However, physical models are complex, with numerous parameters, some of which are difficult to obtain. Simplified assumptions based on vegetation type are often required, making practical applications very challenging.

[0048] (2) Inversion technology based on lidar data

[0049] LiDAR technology has developed rapidly in recent years, especially airborne LiDAR, which can effectively acquire high-precision horizontal and vertical forest structure parameters. Currently, there are two main methods for acquiring forest area density (LAI) using LiDAR data: one is to use LiDAR point cloud data to obtain statistical variable information and construct a regression analysis model to estimate forest LAI. Commonly used LiDAR statistical variables can be roughly divided into two categories: density quantiles and density-related variables, and height quantiles and height-related variables. Currently, the LiDAR statistical variables used for LAI estimation mainly include average height, canopy closure, and height quantiles. The other method is based on the Beer-Lambert law, constructing a semi-physical, semi-empirical model to invert forest LAI. This method has a certain degree of universality and is often used in forest LAI inversion studies. However, airborne LiDAR data cannot meet the needs of large-scale forest LAI inversion, and the accuracy of point cloud filtering and classification needs improvement. Meanwhile, spaceborne LiDAR data analysis is greatly affected by terrain and has low spatial resolution, making it unable to accurately invert forest LAI.

[0050] (3) Inversion techniques based on polarimetric synthetic aperture radar (SAR) data

[0051] Numerous studies have been conducted on retrieving forest leaf area index based on SAR spatial observation technology, but most of these studies have established models based on the empirical correlation between SAR backscattering coefficient and leaf area index.

[0052] In summary, current remote sensing inversion methods for forest leaf surface index have some insurmountable drawbacks:

[0053] (1) Optical remote sensing is affected by climate conditions and has low accuracy in retrieving forest leaf area index;

[0054] (2) The spaceborne lidar waveform data resources are lacking and the spatial resolution is low, making it impossible to achieve a fine inversion of the forest leaf area index.

[0055] (3) The models for retrieving forest leaf area index using SAR spatial observation technology are all empirical models based on backscattering coefficient. The establishment of these models lacks explanation of physical mechanisms, lacks robustness, and contains uncertainties.

[0056] In view of this, and in response to the above-mentioned deficiencies of existing technologies, this invention establishes an empirical and physical model relationship between microwave remote sensing amplitude method and polarimetric interferometric coherence and forest leaf area index, proposes a technical route for microwave remote sensing inversion of forest leaf area index, makes full use of the penetration capability of SAR, establishes a polarimetric interferometric SAR inversion method for complex forest structures, and establishes a leaf area index inversion technical method with all-weather and all-day inversion capability under complex meteorological conditions in tropical rainforests, providing a more ideal remote sensing inversion means for inverting leaf area index in tropical rainforests under complex meteorological conditions.

[0057] See Figure 1 , Figure 1 This is a framework diagram of a method for retrieving leaf area index provided in an embodiment of this application. The specific process is as follows:

[0058] (1) Using the generalized Rayleigh-Gans (GRG) approximation model and the infinite-length loss medium cylinder scattering model, the internal field of leaves and branches is estimated, the scattering and attenuation process of electromagnetic waves by leaves, branches and trunks in the forest is simulated, the loss difference of horizontal and vertical polarized waves in each component is analyzed, and the isotropic or anisotropic information of leaves and branches in the forest is obtained.

[0059] (2) Based on forward scattering theory, using the isotropic characteristics of leaves and branches, and with the attenuation coefficient as an intermediate parameter, the attenuation contribution of leaves is separated under horizontal and vertical polarization, and a physical relationship model between the tree height attenuation coefficient product and the leaf area index is obtained.

[0060] (3) Using fully polarimetric radar images, based on polarimetric interferometric SAR (PolInSAR) technology, the forest tree height and the attenuation coefficients of horizontal and vertical polarimetric waves are calculated through the Oriented Volume over Ground (OVoG) model, and the product of tree height and attenuation coefficient is obtained.

[0061] (4) Combining the relationship model in step (2) with the LAI sample values ​​measured in the field, construct a semi-empirical model for LAI inversion, and use the semi-empirical model for LAI inversion to invert the forest leaf area index.

[0062] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0063] See Figure 2 , Figure 2A flowchart of a leaf area index inversion method provided in this application embodiment includes:

[0064] S201. Obtain information on tree height in the forest and the total attenuation coefficient of electromagnetic waves by each component in the forest; the total attenuation coefficient includes the attenuation coefficient of electromagnetic waves by leaves in the forest and the attenuation coefficient of electromagnetic waves by branches in the forest.

[0065] Before calculating the attenuation coefficient, it is necessary to obtain the formula for calculating the attenuation coefficient of electromagnetic waves by the scatterer. It is necessary to simulate the scattering and attenuation process of electromagnetic waves in the forest in order to calculate the attenuation coefficient.

[0066] See Figure 3 , Figure 3 A flowchart illustrating the scattering and attenuation of electromagnetic waves in a forest is provided for embodiments of this application. Specifically, the flowchart includes the following steps:

[0067] (1) Forest volume stratification

[0068] A forest is a complex system. To facilitate the simulation of scattering decomposition of each component, the forest volume layer is modeled as a discrete collection of leaves and branches. Leaves are simulated as lossy dielectric disks, and branches are simulated as finite-length dielectric cylinders. The internal field is estimated using the GRG approximation model and the scattering model of an infinite-length lossy dielectric cylinder, respectively, to obtain the scattering amplitude in the incident direction.

[0069] (2) Construction of forward scattering amplitude model

[0070] Based on forward scattering theory, the statistical characteristics of electromagnetic wave forward scattering within the forest volume layer are obtained, and the attenuation coefficient of the scatterer is expressed as:

[0071]

[0072] In the formula, n is the number density of the scattering body, and k0 is the free space propagation constant. It is a unit vector in the direction of propagation. Corresponding to the horizontal and vertical polarization unit vectors, It is the imaginary part of the average forward scattering amplitude, specifically expressed as:

[0073]

[0074] In the formula, p(θ, φ) is the joint probability density function of the tilt angle θ and the azimuth angle φ.

[0075] (3) Electromagnetic wave attenuation simulation

[0076] Based on forward scattering theory, this study simulates the scattering and attenuation processes of electromagnetic waves at different frequencies in individual scatterers and scatterer sets within leaves and branches. By setting different geometric dimensions of elliptical disks and cylinders, and electromagnetic wave incident angles, the variation of the attenuation coefficient of the scatterer set under different parameters is investigated. Assuming that leaves are isotropic within the forest and branches are oriented media, the attenuation loss characteristics of polarized waves by various forest components are analyzed under horizontal and vertical polarization.

[0077] To obtain the attenuation coefficients of electromagnetic waves attenuated by leaves and branches in a forest, it is necessary to obtain the physical relationship between the leaf area index and the parameters of the polarization synthetic aperture radar.

[0078] See Figure 4 , Figure 4 This application provides a flowchart for constructing a physical relationship model between leaf area index and polarimetric synthetic aperture radar parameters. Specifically, the flowchart includes the following steps:

[0079] (1) Assuming the leaves in the forest are elliptical in shape, with major and minor axes a and b respectively, the leaf number density is N, and the tree height is h, then:

[0080] LAI (Forest Leaf Area Index) = N × π × a × b × h

[0081] The forest volumetric layer comprises discrete leaves and branches. Based on the isotropic information of leaves and branches, it can be seen that leaves are randomly distributed within the volumetric layer, exhibiting isotropy, and their attenuation coefficient is independent of polarization. Branches, however, are a collection with a directional distribution, exhibiting anisotropy, and their attenuation coefficient for polarized waves differs between horizontal and vertical polarization. (Forest total attenuation coefficient) It can be written as σ, which is independent of polarization (leaf). l polarization-related (branch) The sum is as follows:

[0082]

[0083] That is, the total attenuation coefficient of electromagnetic waves by all components in the forest includes the attenuation coefficient of electromagnetic waves by the leaves and the attenuation coefficient of electromagnetic waves by the branches.

[0084] S202. Calculate the total attenuation coefficient product of tree height based on the tree height information of the forest and the total attenuation coefficient of each component in the forest for electromagnetic wave attenuation.

[0085] Based on the tree height information of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves, calculate the total attenuation coefficient product of tree height, that is, calculate the product of tree height and leaf attenuation coefficient based on the tree height information of the forest and the attenuation coefficient of leaves to electromagnetic waves; calculate the product of tree height and trunk attenuation coefficient based on the tree height information of the forest and the attenuation coefficient of branches to electromagnetic waves.

[0086] Specifically, the attenuation coefficients of leaves and branches can be separated based on the heterogeneity of the attenuation coefficient characteristics of electromagnetic wave attenuation in horizontal and vertical polarization; then, based on the tree height information of the forest and the attenuation coefficient of leaves in the forest, the product of tree height and leaf attenuation coefficient can be calculated; and based on the tree height information of the forest and the attenuation coefficient of branches in the forest, the product of tree height and branch attenuation coefficient can be calculated.

[0087] (2) Since the leaves are randomly distributed in position and direction, the attenuation coefficient σ l It can be written as:

[0088]

[0089] in The average forward scattering amplitude, independent of polarization, is represented by a disk simulating the blade with radius a. l The height of the forest volume layer is h. v Number density of leaves n l It can be written as:

[0090]

[0091] Combining the two formulas above, we can obtain the leaf attenuation coefficient σ. l and tree height h v The product of:

[0092]

[0093] in, It is related to leaf size and relative permittivity, and is a constant in a relatively uniform forest area. Therefore, it can be seen that the leaf area index (LAI) and tree height (h) are related. v With attenuation coefficient σ l The product is linearly dependent;

[0094] (3) Similarly, due to the anisotropic characteristics of branches and trunks in a forest, the forward scattering coefficients of horizontal and vertical polarization are expressed as follows:

[0095]

[0096]

[0097] In the formula, θ i It is the angle of the incident direction of the electromagnetic wave, a b Let χ″ be the radius of the branch, l be the length of the branch, and χ″ be the length of the branch. r This represents the imaginary part of the relative permittivity. Substituting the attenuation coefficient formula for the scatterer into the formula, we obtain the attenuation coefficients of horizontally and vertically polarized waves in the branch, expressed as:

[0098]

[0099]

[0100] Where, m=k0χ″ r n b π(a b ) 2 l, n b I1 represents the number density of tree branches. Branches are randomly distributed in the forest within a certain angle range [θ1, θ2]. I1 and I2 are functions of the branch angle distribution, expressed as... l2 = 1 - I1.

[0101] (4) Based on the attenuation coefficients of leaves and branches obtained above, the relationship between total forest extinction and LAI under horizontal and vertical polarization waves can be derived. That is, based on the product of forest tree height and attenuation coefficients of horizontal and vertical polarization, the relationship between the product of the total attenuation coefficient of tree height and leaf area index under horizontal and vertical polarization waves can be constructed. The relationship between the product of the total attenuation coefficient of tree height and leaf area index under horizontal and vertical polarization waves is expressed as follows:

[0102]

[0103]

[0104] in Combining the above two formulas, the distribution range of branch inclination angle and ( represent and ) and h v Given the information, a linear LAI estimation model can be established.

[0105] S203. Based on the relationship between the total tree height attenuation coefficient product and the leaf area index, the leaf area index is inverted.

[0106] If a linear LAI estimation model is obtained, the leaf area index (LAI) can be inverted using the relationship between the total attenuation coefficient product of tree height and the LAI. This relationship includes the relationship between the total attenuation coefficient product of tree height and the LAI under both horizontal and vertical polarization. This means that the parameters need to be determined. and hv .

[0107] Specifically, the parameters of the total tree height attenuation coefficient product in the horizontal polarization and the relationship between the vertical polarization and leaf area index can be retrieved using the Oriented Volume over Ground (OVoG) two-layer model. and h v .

[0108] This application provides a method for inverting the leaf area index (LAI) of a forest. When executing the method, firstly, the tree height information of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves are obtained. The total attenuation coefficient includes the attenuation coefficient of leaves and branches to electromagnetic waves. Then, based on the tree height information and the total attenuation coefficient of each component, the product of the total attenuation coefficients of the tree height is calculated. Finally, the LAI is inverted based on the relationship between the product of the total attenuation coefficients of the tree height and the LAI. Thus, by inverting the LAI through the relationship between the product of the total attenuation coefficients of the tree height and the LAI, that is, by utilizing the attenuation characteristics of the forest to electromagnetic waves, the LAI is inverted. Since the attenuation of electromagnetic waves is not affected by tree species, region, complex meteorological conditions, or the selected mathematical model, it can more accurately reflect the attenuation of electromagnetic waves by the leaf area. Therefore, the accuracy of inverting the LAI using the above method is higher.

[0109] See Figure 5 , Figure 5 This application provides an embodiment of a parameter inversion method using the OVoG model. and h v The flowchart is as follows.

[0110] (1) The OVoG model is a two-layer model that includes the interaction between the incident wave and the ground located at the bottom of the volume layer. In the combination of the ground and forest volume layers, the scattering ratio between the ground and the volume is... The complex interference coherence coefficient in the OVoG model changes with polarization. It can be represented as:

[0111]

[0112]

[0113] Among them, K z This represents the actual vertical wavenumber. The vector is the normalized projection vector, where σ represents the attenuation coefficient, corresponding to the co-polarization and cross-polarization in the eigenpolarization basis. This indicates volumetric decoherence. θ is the angle of incidence.

[0114] (2) There are 7 unknowns in the OVoG model, namely the volumetric layer height h. v Terrain phase φ0, extinction of two characteristic polarizations and and the ground volume ratio μ of the three polarization channels HH μ HV μ VV The attenuation of cross-polarization can be obtained by considering it as the mean of the attenuation of co-polarization, expressed as: The polarimetric interferometry data provides the complex coherence coefficients (HH, HV, and VV) for three channels, with a total of six known conditions (Re represents the real part of the complex number, and Im represents the imaginary part of the complex number), which are as follows: Let represent the real and imaginary parts of the complex coherence coefficients for each polarization, respectively. Then, the complete inversion problem can be formulated as a minimization problem:

[0115]

[0116] in It is the complex interference coherence coefficient The expression for the coherence phase φ0 requires linear fitting of the coherence coefficients in the first stage because there is one more unknown than known condition. First, the complex coherence coefficients of the three polarization channels and the complex coherence under other polarization states are calculated. Then, linear fitting is performed based on the distribution of these coherence coefficients within the complex unit circle to estimate the terrain phase φ0.

[0117] (3) Based on the extracted terrain phase φ0, there are 6 known and 6 unknowns. A numerical optimization algorithm can be used to solve for the 6 remaining unknowns. In this embodiment, the attenuation coefficient can be obtained by solving the OVoG model based on fully polarimetric radar imagery. and Attenuation coefficient With height h v The product and attenuation coefficient With height h v The product of.

[0118] Based on the inversion of the above OVoG model, the following was obtained: and h v By combining the LAI sample values ​​obtained from field measurements with the LAI linear estimation model, the correlation between the product of theoretical K and LAI and the measured LAI values ​​is calculated, and a complete LAI inversion semi-empirical model is constructed, thereby inverting the forest leaf area index (LAI) in this embodiment.

[0119] See Figure 6 , Figure 6 This is a schematic diagram of a forest leaf area index inversion device provided in an embodiment of this application. The device includes:

[0120] The module comprises 601 for acquisition, 602 for calculation, and 603 for inversion.

[0121] The acquisition module 601 is used to acquire information on the tree height of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves; the total attenuation coefficient includes the attenuation coefficient of leaves in the forest to electromagnetic waves and the attenuation coefficient of branches in the forest to electromagnetic waves.

[0122] The calculation module 602 is used to calculate the total attenuation coefficient product of tree height based on the tree height information of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves.

[0123] The inversion module 603 is specifically used to invert the leaf area index based on the relationship between the total tree height attenuation coefficient product and the leaf area index.

[0124] This application provides a forest leaf area index (LAI) inversion device for executing a corresponding method. First, it acquires the tree height information of the forest and the total attenuation coefficient of each component in the forest to electromagnetic waves. The total attenuation coefficient includes the attenuation coefficient of leaves and branches to electromagnetic waves. Then, based on the tree height information and the total attenuation coefficient of each component, it calculates the product of the total attenuation coefficients of tree height. Finally, it inverts the LAI based on the relationship between the product of the total attenuation coefficients of tree height and the LAI. Thus, by using the relationship between the product of the total attenuation coefficients of tree height and the LAI, the LAI is inverted, utilizing the attenuation characteristics of the forest to electromagnetic waves. Since the attenuation of electromagnetic waves is not affected by tree species, region, complex meteorological conditions, or the selected mathematical model, it can more accurately reflect the attenuation of electromagnetic waves by the leaf area. Therefore, the accuracy of the LAI inversion using the above method is higher.

[0125] In an optional embodiment of this application, the computing module 602 is specifically used for:

[0126] Based on the heterogeneity of the attenuation coefficient characteristics of leaves and branches in horizontal and vertical polarization, the attenuation coefficients of leaves and branches are separated.

[0127] Based on the tree height information of the forest and the attenuation coefficient of the leaves in the forest to attenuate electromagnetic waves, calculate the product of tree height and leaf attenuation coefficient;

[0128] Based on the tree height information of the forest and the attenuation coefficient of the branches in the forest to electromagnetic waves, calculate the product of tree height and branch attenuation coefficient.

[0129] In an optional embodiment of this application, the inversion module 603 specifically includes a construction unit and a calculation unit;

[0130] The construction unit is specifically used to construct the relationship between the total tree height attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index.

[0131] The inversion unit is specifically used to invert the leaf area index based on the relationship between the total tree height attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index.

[0132] In an optional embodiment of this application, the building unit is specifically used for:

[0133] Based on the product of forest tree height and the attenuation coefficients of horizontal and vertical polarization, the relationship between the total attenuation coefficient product of tree height and the leaf area index is constructed.

[0134] In an optional embodiment of this application, the inversion module 603 is specifically used for:

[0135] Using a ground-direction volume two-layer model, the parameters of the total tree height attenuation coefficient product in the horizontal polarization and in the relationship between vertical polarization and leaf area index are inverted.

[0136] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that all or part of the steps in the methods of the above embodiments can be implemented by means of software plus a general-purpose hardware platform. Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as a read-only memory (ROM) / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, a server, or a network communication device such as a router) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0137] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0138] The above description is merely an exemplary implementation of this application and is not intended to limit the scope of protection of this application.

Claims

1. A leaf area index inversion method, characterized in that, The method comprises: obtaining tree height information of a forest, and total attenuation coefficients of each component in the forest to electromagnetic wave attenuation; the total attenuation coefficients comprise attenuation coefficients of leaves in the forest to electromagnetic wave attenuation and attenuation coefficients of branches and stems in the forest to electromagnetic wave attenuation; calculating a tree height total attenuation coefficient product according to the tree height information of the forest and the total attenuation coefficients of each component in the forest to electromagnetic wave attenuation; inverting a leaf area index according to a relationship between the tree height total attenuation coefficient product and the leaf area index; the calculation of the tree height total attenuation coefficient product according to the tree height information of the forest and the total attenuation coefficients of each component in the forest to electromagnetic wave attenuation specifically comprises: separating attenuation coefficients of leaves and branches and stems according to heterogeneity of the attenuation coefficients of leaves and branches and stems to electromagnetic wave attenuation in horizontal polarization and vertical polarization; calculating a tree height and leaf attenuation coefficient product according to the tree height information of the forest and the attenuation coefficients of leaves in the forest to electromagnetic wave attenuation; calculating a tree height and branch and stem attenuation coefficient product according to the tree height information of the forest and the attenuation coefficients of branches and stems in the forest to electromagnetic wave attenuation; the inversion of the leaf area index according to the relationship between the tree height total attenuation coefficient product and the leaf area index specifically comprises: constructing a relationship between the tree height total attenuation coefficient product in horizontal polarization and vertical polarization and the leaf area index; inverting the leaf area index according to the relationship between the tree height total attenuation coefficient product in horizontal polarization and vertical polarization and the leaf area index; the construction of the relationship between the tree height total attenuation coefficient product in horizontal polarization and vertical polarization and the leaf area index specifically comprises: constructing the relationship between the tree height total attenuation coefficient product in horizontal polarization and vertical polarization and the leaf area index according to tree height and horizontal polarization and vertical polarization attenuation coefficient products; the method further comprises: inverting parameters in the relationship between the tree height total attenuation coefficient product in horizontal polarization and vertical polarization and the leaf area index by using a ground-direction volume two-layer model.

2. A leaf area index calculating device characterized by comprising: The device comprises an acquisition module, a calculation module and an inversion module; the acquisition module is used to obtain tree height information of a forest, and total attenuation coefficients of each component in the forest to electromagnetic wave attenuation; the total attenuation coefficients comprise attenuation coefficients of leaves in the forest to electromagnetic wave attenuation and attenuation coefficients of branches and stems in the forest to electromagnetic wave attenuation; the calculation module is used to calculate a tree height total attenuation coefficient product according to the tree height information of the forest and the total attenuation coefficients of each component in the forest to electromagnetic wave attenuation; the inversion module is specifically used to invert a leaf area index according to a relationship between the tree height total attenuation coefficient product and the leaf area index; the calculation module is specifically used to: separate attenuation coefficients of leaves and branches and stems according to heterogeneity of the attenuation coefficients of leaves and branches and stems to electromagnetic wave attenuation in horizontal polarization and vertical polarization; calculate a tree height and leaf attenuation coefficient product according to the tree height information of the forest and the attenuation coefficients of leaves in the forest to electromagnetic wave attenuation; calculate a tree height and branch and stem attenuation coefficient product according to the tree height information of the forest and the attenuation coefficients of branches and stems in the forest to electromagnetic wave attenuation; the inversion module specifically comprises a construction unit and a calculation unit; The construction unit is specifically configured for constructing a relationship between a tree height total attenuation coefficient product in horizontal polarization and in vertical polarization and a leaf area index; The calculation unit is specifically configured for inverting the leaf area index according to the relationship between the tree height total attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index; The construction unit is specifically configured for: constructing the relationship between the tree height total attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index according to forest tree height and horizontal polarization and vertical polarization attenuation coefficient products; The inversion module is specifically configured for: inverting parameters in the relationship between the tree height total attenuation coefficient product in horizontal polarization and in vertical polarization and the leaf area index by using a ground-direction volume two-layer model.

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