CN116881609B - Calculation method for gap rate of forest canopy in universality - Google Patents
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Abstract
The application relates to the technical field of calculation of forest canopy gap rate, solves the technical problem that the computed canopy gap rate GF error of the Nilson model in the non-zenith direction is large at present, and particularly relates to a method for computing the forest canopy gap rate in universality, which comprises the following steps: s1, obtaining partial canopy structure parameters after filtering treatment through forestry ground surface investigation, observation or using an airborne laser radar method; s2, expanding calculation of crown overlap OAC and crown distribution parameters GI from the nadir direction to the whole hemisphere space based on the Nilson model, and constructing a New-Nilson model with universality. The New-Nilson model provided by the application has higher universality, is suitable for all forest stands with different tree distribution patterns, azimuth angle effects, scale effects and gradient effects, and can accurately calculate the crown interlayer reflectivity GF, so that the model has important significance for building a general crown reflectivity model.
Description
Technical Field
The application relates to the technical field of forest canopy gap rate calculation, in particular to a method for calculating the forest canopy gap rate in universality.
Background
The canopy gap ratio (GF) is defined as the probability of transmission of a light beam through the vegetation canopy, and accurately calculating the canopy gap ratio GF of a forest is a prerequisite for forest remote sensing forward modeling and inversion.
The existing forest canopy gap rate GF calculation model is based on various tree distribution models, and is only suitable for specific situations. For example, the Neyman-A model, the Poisson model, and the super geometric model are applicable to forests with aggregated, random, and regular tree distributions, respectively. The GF model of Nilson is considered applicable to general forests and any tree distribution.
When observing the gap ratio GF of the canopy of the forests with different tree distributions in the nadir direction in the Nilson model, the gap ratio GF of the canopy calculated in the non-nadir direction is underestimated for forests with aggregated distribution; for a regularly distributed forest, the calculated canopy gap ratio GF in the non-nadir direction is overestimated, especially in forests with azimuthal and slope effects. This is due to the simplification of the calculation of the canopy overlap (overlaps among crowns, OAC) links in other directions than the nadir direction. Therefore, the Nilson model calculates a greater margin GF error for forests that are clustered and forests that are regularly distributed in a direction other than the nadir direction.
Disclosure of Invention
Aiming at the defects of the prior art, the application provides a method for calculating the gap rate of a forest canopy in universality, which solves the technical problem that the gap rate GF error of the canopy calculated in the non-zenith direction of the current Nilson model is large.
In order to solve the technical problems, the application provides the following technical scheme: a method for calculating the gap rate of a universal forest canopy comprises the following steps:
s1, obtaining partial canopy structure parameters after filtering treatment through forestry ground surface investigation, observation or using an airborne laser radar method;
s2, expanding calculation of crown overlap OAC and crown distribution parameters GI from the nadir direction to the whole hemisphere space based on a Nilson model, and constructing a New-Nilson model with universality;
s3, inputting partial canopy structure parameters into a New-Nilson model to calculate to obtain the accurately calculated canopy gap rate GF.
Further, in step S1, the partial canopy structure parameters include:
blade area of individual crowns；
Single tree crownCrown projection area in the direction +.>；
Projection of unit leaf area onto viewing vertical plane；
Crown closureDefining the sum of crown projections of a unit ground area;
the observation direction in the hemispherical space isWhen a single tree is projected area +.>Relative variance of number of internally contained trees。
Further, in step S1,crown closure in the direction +.>The method directly carries out approximate calculation through a formula, and the approximate calculation formula is as follows:
；
in the above formula, the superscript "" indicates a direction parameter corresponding to the same parameter in the Nilson model, but the parameter is added with directivity unlike the Nilson model;for tree density->Is->Crown projected area in the direction.
Further, in step S2, the formula of the constructed New-Nilson modelThe method comprises the following steps:
；
in the above formula, the superscript "" indicates the direction parameter corresponding to the same parameter in the Nilson model,from relative variancesDeriving as +.>Time formula->Characteristic parameters of->Crown closure is defined as the sum of crown projections per unit ground area.
Further, the method comprises the steps of,from the relative variance->Deriving as +.>Time formulaCharacteristic parameters of->The expression of (2) is:
；
in the above formula, the superscript "" indicates the direction parameter corresponding to the same parameter in the Nilson model,is the observation direction in the hemispherical space is +.>When a single tree is projected area +.>The relative variance of the number of the inner containing trees, +.>Is a single crown->The cap gap ratio GF in the direction.
The expression of (2) is:
；
in the above-mentioned method, the step of,projection of the unit leaf area onto the viewing vertical plane, < >>Leaf area for a single crown +.>Is a single crown->Crown projected area in the direction.
Further, the closure of the canopyDefined as 1 minus the intercalant clearance (considered crown opaque), expressed as:
；
in the above formula, the superscript "" indicates the direction parameter corresponding to the same parameter in the Nilson model,is->Crown closure in the direction ++>，/>Is the rate of the gap between crowns.
By means of the technical scheme, the application provides a method for calculating the gap rate of the forest canopy in universality, which has the following beneficial effects:
the calculation model for the gap rate of the canopy of the forest, which is suitable for different tree distributions, can consider the New-Nilson model with overlapping canopy in all directions, has high consistency between the simulation result of the gap rate GF of the canopy and the ray tracing result in all directions, ensures that the New-Nilson model has high universality, is suitable for all forest stands with different tree distribution patterns, azimuth angle effects, scale effects and gradient effects, and has important significance for establishing a general canopy reflectivity model.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a method for calculating the gap rate of a forest canopy according to the present application;
FIG. 2 is a graph of different tree distribution patterns corresponding to the same tree density in accordance with the present application;
FIG. 3 is a graph of simulated crown gap ratio GF versus different zenith angles and different forests for the present application.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will become more readily apparent, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. Therefore, the realization process of how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented.
Those of ordinary skill in the art will appreciate that all or a portion of the steps in a method of implementing an embodiment described above may be implemented by a program to instruct related hardware, and thus, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Referring to fig. 1-3, a specific implementation manner of the present embodiment is shown, and the present embodiment provides a forest canopy gap rate calculation model suitable for different tree distributions, which can consider a New-Nilson model with overlapping crowns in all directions, and the canopy gap rate GF simulation result and the ray tracing result show very high consistency in all directions, so that the New-Nilson model has relatively high universality, and is suitable for all forest stands with different tree distribution patterns, azimuth angle effects, scale effects and gradient effects, thereby having important significance in establishing a general canopy reflectivity model.
Referring to fig. 1, the present embodiment provides a method for calculating a gap rate of a forest canopy, which is applied to an actual remote sensing inversion field, and specifically includes the following steps:
s1, acquiring partial canopy structure parameters, in this embodiment, the partial canopy structure parameters may be obtained through forestry ground surface investigation, observation and other means or through data filtering by using methods such as an airborne laser radar, so that the acquisition of the partial canopy structure parameters may be obtained by adopting conventional technical means in the art, and will not be described in detail herein.
The partial canopy structure parameters include:
area of (single-sided) leaves (leaves, flowers, branches, etc.) of a single crown；
Single tree crownCrown projection area in the direction +.>；
Projection of unit leaf area onto viewing vertical plane；
Crown closureDefining the sum of crown projections of a unit ground area;
the observation direction in the hemispherical space isWhen a single tree is projected area +.>Relative variance of number of internally contained trees。
In this embodiment, the crown closure in the partial crown structure parametersDegree of coincidenceIn other words, several different acquisition methods are proposed, specifically as follows:
wherein the crown closure is related toAccording to the Nilson model report, a simple hand-held device consists of a straight tube fixed on a universal joint and a mirror under the straight tube, which can help an observer to see vertically upwards through the straight tube, so as to perform point-to-point sampling. In addition, crown closure->Can be measured by average overlapping times, and the closure degree of the canopyThen the zero overlap probability is calculated as 1 minus.
Measuring crown closure with previous Nilson modelAnd canopy closure->The only difference in the method of (2) is that the straight tube is held in multiple directions, not just in the vertical or nadir direction. The input parameters of the New Nilson model are similar to the previous Nilson model, and the measurement of tree distribution or crown-to-crown overlap OAC in the zenith direction of the stand can be extended to the non-zenith direction. If the structure of the trees in the stand is similar (e.g. artificial forest Lin Fen), the plant is +.>Crown closure in the direction +.>The method can be directly calculated through the approximate calculation formula, wherein the approximate calculation formula is as follows:
；
in the above formula, the superscript' indicates the direction parameter corresponding to the same parameter in the Nilson model, and the parameter is added with directivity unlike the Nilson model;for tree density (number of trees/forest land),>is->Crown projected area in the direction.
Image classification is another method for calculating directional crown closure degree from top to bottomAnd canopy closure->Is a method of (2). Recently, airborne LiDAR (ALS) or ground laser scanning (terrestrial laser scanning, TLS) has been demonstrated to be able to accurately measure directional canopy and canopy closure. These new techniques have been reported to perform well in the segmentation of individual crowns. The crown projection area can be easily calculated by dividing the single crown projection area in all directions by the ground projection area. In the virtual forest scene with more point clouds, the directional inter-canopy gap can be easily calculated, and the directional canopy closure degree is +.>The calculation may be performed by subtracting the directional inter-crown gap rate from 1, but in the present embodiment, it is obtained by directly performing the formula approximation calculation.
S2, expanding calculation of crown overlap OAC and crown distribution parameters GI from the nadir direction to the whole hemisphere space based on a Nilson model, and constructing a New-Nilson model with universality;
in step S2, the New-Nilson model of the directional crown-to-crown overlap OAC is different from the conventional Nilson model, which describes the crown-to-crown overlap by only considering the distribution parameters of the tree in the nadir direction, that is, crown closure and canopy closure, but the New-Nilson model with universality, which is improved again in this embodiment, introduces the directional attribute for the New-Nilson model parameters compared with the conventional Nilson model, so that the New-Nilson model is still available for the entire hemispherical space.
Specifically, the New-Nilson model, which correctly considers the directional crown-to-crown overlap OAC, is as follows:
crown closure calculation using key crown distribution parameters GI in Nilson series modelAnd canopy closure->Wherein crown closure->And canopy closure->The crown overlap OAC of the nadir can be accurately calculated by the crown distribution parameter GI only in relation to the crown overlap OAC of the nadir. However, the crown-to-crown overlap OAC in other directions may not be accurately calculated.
The New-Nilson model of directional crown-to-crown overlap OAC is different from the Nilson crown gap rate GF model, the traditional Nilson model only considers the distribution parameters of the tree in the direction of the nadir to describe the overlapping among the crowns, namely the crown closure degree and the crown closure degree, and the improved New-Nilson model is still available for the whole hemispherical space. Therefore, the formula of the cap layer gap rate GF of the Nilson model is modified to obtain the formula of the New-Nilson modelThe method comprises the following steps:
；
in the above-mentioned method, the step of,representing the natural logarithm as a constant +.>Logarithmic base>The prime difference between the New-Nilson model and the Nilson model is that the crown overlap OAC calculation using crown distribution parameters GI extends from the nadir direction to the entire hemispherical space.
Is the observation direction in the hemispherical space is +.>When a single tree is projected area +.>The relative variance of the number of the inner containing trees, +.>Can be defined by the relative variance->Export (I)>Is in the formula->For the characteristic parameters in the calculation process, +.>Crown closure is defined as the sum of crown projections per unit ground area.
Single tree crownCrown gap ratio in the direction ++>Can be expressed as:
；
in the above-mentioned method, the step of,projection of the unit leaf area onto the viewing vertical plane, < >>For the (single-sided) leaf (leaf, flower, branch, etc.) area of a single crown, +.>Is a single crown->Crown projected area in the direction.
For canopy closure, 1 minus the intercalary gap ratio (considered crown opaque) is defined +.>Is a tree-shaped distribution mode parameter in a poisson distribution-based GF formula proposed by a Nilson (1999) model, is a correction factor and defines possible deviation between a crown distribution mode and poisson distribution, and the possible deviation is->The calculation formula of (2) is as follows:
；
crown closureThe calculation formula of (2) is as follows:
；
the superscript "" indicates the direction parameter corresponding to the same parameter in the Nilson model,is the rate of the gap between crowns.
In the embodiment, on the basis of a Nilson model, the calculation of overlapping OACs and tree distribution among crowns is expanded to the whole hemispherical space from the direction of the nadir, and a New general New-Nilson model is provided for accurately calculating the crown clearance GF. The result shows that all canopy gap rate GF simulation results and ray tracing results of the New-Nilson model show very high consistency in all directions, and the New-Nilson model is a real general GF model and is suitable for all forest stands with different tree distribution patterns, azimuth angle effects and gradient effects, and the New-Nilson model of the general GF provided by the embodiment has great significance for building the general canopy reflectivity model.
S3, inputting partial canopy structure parameters into a New-Nilson model to calculate to obtain the accurately calculated canopy gap rate GF.
Specifically, partial canopy structure parameters are substituted into the formula of the New-Nilson modelCalculated as +.>Crown gap ratio GF and crown closure in the direction +.>It follows from the above that:
the calculation formula of the canopy gap ratio GF is:
；
the embodiment can accurately estimate the canopy gap rate GF, has important influence on the fields of vegetation remote sensing, ecological remote sensing, environment and forestation, is a key parameter in remote sensing application, and provides necessary preconditions for canopy reflectivity modeling and inversion of a plurality of vegetation parameters.
New-Nilson model formulaResults and verification:
in general, tree-type distribution patterns in reality can be divided into three major categories: cluster, random, and regular. According to the theory of a Neyman-a model, a Poisson model and a super geometric model (super geometric distribution model, hypergeometric model, HG), 6 forest stands with tree distribution of cluster type, random type and regular type are generated on the basis of the three models, as shown in fig. 2, wherein one forest stand with tree distribution of cluster type (Neyman-a type distribution m2=3), 1 forest stand with Poisson distribution and 3 forest stands with regular distribution are included: super geometric distribution, RASD (shortest exclusion distance, relative allowable shortest distance) is 0.5, 1, 1.15 and 1.25, with forest names HG1, HG2, HG3 and HG4, respectively.
Fig. 2 corresponds to forests (from aggregate to random to regular) with the same tree density but different tree distribution patterns, respectively:
fig. 2 (a): neyman-a (m2=3); fig. 2 (b): poisson; fig. 2 (c): HG1 (rasd=0.5); fig. 2 (d): HG2 (rasd=1); fig. 2 (e): HG3 (rasd=1.15); fig. 2 (f): HG4 (rasd=1.25).
The results of the verification are as follows, (Nilson and Peterson, 1991) and (Nilson, 1999), referred to herein as Nilson91 model and Nilson99 model, compare the results of the cap gap ratio GF of the Nilson91 model, the Nilson99 model, and the added directionality Nilson91 model with the results of the cap gap ratio GF of the newly constructed New-Nilson99 model.
Simulation results of the New-Nilson model were verified by Ray Tracing (RT) method, and FIG. 3 shows the effect of four methods on the crown clearance GF in different forests of different tree distributions. The Nilson91 model and the Nilson99 model have higher consistency with RT simulation results in crown-to-crown gap rate GF values in the nadir direction in all forests. Furthermore, for forests with poisson and HGl tree distributions, there was no significant difference in canopy gap ratio GF results from RT model results for both models. This means that all these models can simulate the canopy gap ratio GF of all considered forests in the nadir direction, as well as canopy gap ratios GF with completely random tree distribution or small exclusion distances in any direction.
In the non-nadir direction, the Nilson91 model and Nilson99 model underestimate the canopy gap ratio GF for forests with Neyman-a tree distributions, as shown in fig. 3, while the canopy gap ratio GF is overestimated for forests with the larger RASD super-geometric tree distributions. In contrast, the results of the cap gap ratio GF simulation in the New-Nilson model are relatively consistent with the RT results. In most directions of all stand, new-Nilson model and RT have no difference in GF results. Therefore, it is necessary to consider the crown-to-crown overlap OAC in all directions in the New-Nilson model.
Fig. 3 shows simulated canopy gap ratios GF comparisons for different zenith angles and different forests, respectively:
fig. 3 (a): neyman-a (m2=3); fig. 3 (b): poisson; fig. 3 (c): HG1 (rasd=0.5); fig. 3 (d): HG2 (rasd=1); fig. 3 (e): HG3 (rasd=1.15); fig. 3 (f): HG4 (rasd=1.25).
In addition, the simulation accuracy is described using the relative error RE, which is calculated as follows:
；
wherein,the results of the cap gap ratio GF simulation of three Nilson models, two previous Nilson91 and Nilson99 models, respectively, and a New New Nilson model, +.>Is the GF result in RT simulation.
Table I shows the relative error RE in GF results between the GF model and RT for three Nilson in forests with different tree distribution patterns. For forests with poisson and HG1 distributions, the relative error RE in all directions in the GF model of these three Nilson is less than 10%, i.e. by calculation of the relative error RE in all directions.
In other words, this means that all these models can model the canopy gap ratio GF under vertical observation of all forests considered with completely random tree distribution, or small exclusion distances, as well as canopy gap ratios GF in any direction. However, as shown in Table I, as the zenith angle of observation increases, the relative error RE of other forests increases in the non-zenith direction in the first two Nilson models. Typically, the results of the Nilson91 and Nilson99 models underestimate the canopy gap ratio GF for forests with a Neyman-a tree distribution, as shown in fig. 3, overestimating the canopy gap ratio GF for forests with a super-geometric tree distribution with a large RASD.
In the HG4 stand with a large zenith angle, the average relative error RE of the Nilson99 and Nilson91 models reached 46% and 37%, respectively.
；
In summary, the method for calculating the gap rate of the forest canopy with universality provided by the embodiment expands the calculation of the crown overlap OAC and the crown distribution parameter GI from the nadir direction to the whole hemisphere space based on the Nilson model, and constructs a New-Nilson model with universality, which has the following advantages:
the accurate estimation of the canopy gap ratio GF has important influence on the fields of vegetation remote sensing, ecological remote sensing, environment and forestry. Light, when transmitted through the vegetation canopy, interacts with vegetation and other media, resulting in light absorption and scattering phenomena. The light energy absorbed by the canopy is utilized by the vegetation tissue for photosynthesis and biochemical processes, while the scattered light energy is reflected back to the atmosphere or propagates to other directions.
Many optical instruments in the fields of vegetation remote sensing and forestry rely on accurately estimated canopy gap rates GF. Remote sensing technology can provide information interpretation and analysis of vegetation structure and function by acquiring vegetation reflection and radiation data. Therefore, accurate estimation of the cap gap rate GF is critical to ensure reliability and interpretation of the telemetry data.
The reliability and accuracy of the canopy reflectivity model is also affected by the canopy gap ratio GF. These models can estimate reflectivity and infer vegetation parameters by modeling the light absorption and multiple scattering processes within the canopy. Accurate estimation of the coronary gap rate GF may improve the accuracy of these models, thereby improving the interpretation ability of vegetation structure and function.
In addition, in ecological and environmental studies, canopy gap rate GF is a key indicator for assessing vegetation growth and ecosystem function. For example, accurate estimation of biophysical variables such as leaf area light absorption ratio, leaf area index, and aggregation index depends on accurate calculation of the canopy gap ratio GF. These variables are important for understanding vegetation growth process, productivity assessment, carbon cycling, etc.
In summary, accurate estimation of the canopy gap ratio GF has an important impact on vegetation, environmental, ecological and forestry fields. The method is a key parameter in remote sensing application, and provides necessary preconditions for canopy reflectivity modeling and inversion of a plurality of vegetation parameters.
The foregoing embodiments have been presented in a detail description of the application, and are presented herein with a particular application to the understanding of the principles and embodiments of the application, the foregoing embodiments being merely intended to facilitate an understanding of the method of the application and its core concepts; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Claims (6)
1. The method for calculating the gap rate of the forest canopy is characterized by comprising the following steps of:
s1, obtaining partial canopy structure parameters after filtering treatment through forestry ground surface investigation, observation or using an airborne laser radar method;
s2, expanding calculation of crown overlap OAC and crown distribution parameters GI from the nadir direction to the whole hemisphere space based on a Nilson model, and constructing a New-Nilson model with universality;
formula of constructed New-Nilson modelThe method comprises the following steps:
；
in the above formula, the superscript "" indicates the direction parameter corresponding to the same parameter in the Nilson model,from relative variancesDeriving as +.>Time formula->Characteristic parameters of->The crown closure degree is defined as the sum of crown projections of unit ground area;
s3, inputting partial canopy structure parameters into a New-Nilson model to calculate to obtain the accurately calculated canopy gap rate GF.
2. The computing method according to claim 1, wherein in step S1, the partial canopy structure parameters include:
blade area of individual crowns；
Single tree crownCrown projection area in the direction +.>；
Projection of unit leaf area onto viewing vertical plane；
Crown closureDefining the sum of crown projections of a unit ground area;
the observation direction in the hemispherical space isWhen a single tree is projected area +.>Relative variance of number of internally contained trees。
3. The method according to claim 2, wherein, in step S1,crown closure in directionThe method directly carries out approximate calculation through a formula, and the approximate calculation formula is as follows:
；
in the above formula, the superscript' indicates the direction parameter corresponding to the same parameter in the Nilson model, and the parameter is added with directivity unlike the Nilson model;for tree density->Is->Crown projected area in the direction.
4. The method of computing as recited in claim 1, wherein,from the relative variance->Deriving as +.>Time formula->Characteristic parameters of->The expression of (2) is:
；
in the above formula, the superscript "" indicates the direction parameter corresponding to the same parameter in the Nilson model,is the observation direction in the hemispherical space is +.>When a single tree is projected area +.>The relative variance of the number of the inner containing trees, +.>Is a single crown->The cap gap ratio GF in the direction.
5. The method of computing as claimed in claim 4, wherein,the expression of (2) is:
；
in the above-mentioned method, the step of,projection of the unit leaf area onto the viewing vertical plane, < >>For the leaf area of a single crown,is a single crown->Crown projected area in the direction.
6. According to claim 1The calculation method is characterized in that the closure degree of the canopyDefined as 1 minus the crown gap ratio, the crown is considered opaque, and the expression is:
；
in the above formula, the superscript "" indicates the direction parameter corresponding to the same parameter in the Nilson model,is->Crown closure in the direction ++>Is the gap rate between crowns; />The tree-shaped distribution mode parameter in the poisson distribution-based GF formula proposed by a Nilson (1999) model is a correction factor and defines possible deviation of a tree crown distribution mode and poisson distribution.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104778693A (en) * | 2015-04-08 | 2015-07-15 | 云挺 | Leaf area index calculation method based on projection algorithm and active contour model |
| CN110703277A (en) * | 2019-10-21 | 2020-01-17 | 北京师范大学 | Method for inverting forest canopy aggregation index based on full-waveform laser radar data |
| CN112254820A (en) * | 2020-10-14 | 2021-01-22 | 中国科学院空天信息创新研究院 | Discrete forest scene thermal infrared radiation transmission simulation method |
| CN114066966A (en) * | 2021-11-16 | 2022-02-18 | 南京林业大学 | Crown porosity estimation method based on porous medium theory and computer graphics |
| WO2022067598A1 (en) * | 2020-09-30 | 2022-04-07 | Nanjing Maoting Information Technology Co., Ltd. | Method of individual tree crown segmentation from airborne lidar data using novel gaussian filter and energy function minimization |
| CN116503727A (en) * | 2023-03-09 | 2023-07-28 | 电子科技大学 | Vegetation aggregation index estimation method based on Poisson distribution and point cloud clustering |
-
2023
- 2023-09-06 CN CN202311143062.3A patent/CN116881609B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104778693A (en) * | 2015-04-08 | 2015-07-15 | 云挺 | Leaf area index calculation method based on projection algorithm and active contour model |
| CN110703277A (en) * | 2019-10-21 | 2020-01-17 | 北京师范大学 | Method for inverting forest canopy aggregation index based on full-waveform laser radar data |
| WO2022067598A1 (en) * | 2020-09-30 | 2022-04-07 | Nanjing Maoting Information Technology Co., Ltd. | Method of individual tree crown segmentation from airborne lidar data using novel gaussian filter and energy function minimization |
| CN112254820A (en) * | 2020-10-14 | 2021-01-22 | 中国科学院空天信息创新研究院 | Discrete forest scene thermal infrared radiation transmission simulation method |
| CN114066966A (en) * | 2021-11-16 | 2022-02-18 | 南京林业大学 | Crown porosity estimation method based on porous medium theory and computer graphics |
| CN116503727A (en) * | 2023-03-09 | 2023-07-28 | 电子科技大学 | Vegetation aggregation index estimation method based on Poisson distribution and point cloud clustering |
Non-Patent Citations (1)
| Title |
|---|
| 树冠尺寸对冠层间隙率和聚集度指数的影响;耿君;田庆久;涂丽丽;范渭亮;王晓菲;;遥感学报(06);1319-1327 * |
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