CN112946669A - Moso bamboo forest quantity identification method and device based on foundation laser radar - Google Patents
Moso bamboo forest quantity identification method and device based on foundation laser radar Download PDFInfo
- Publication number
- CN112946669A CN112946669A CN202110159604.0A CN202110159604A CN112946669A CN 112946669 A CN112946669 A CN 112946669A CN 202110159604 A CN202110159604 A CN 202110159604A CN 112946669 A CN112946669 A CN 112946669A
- Authority
- CN
- China
- Prior art keywords
- point cloud
- cloud data
- laser radar
- data
- voxel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Electromagnetism (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Optical Radar Systems And Details Thereof (AREA)
Abstract
The invention discloses a method and a device for identifying the number of moso bamboo forests based on a foundation laser radar, wherein the method comprises the following steps: acquiring foundation laser radar point cloud data of the moso bamboo forest through a foundation laser radar; obtaining a point cloud data file according to the point cloud data of the foundation laser radar; intercepting the point cloud data file according to a preset interception upper limit and an interception lower limit to generate a section of horizontal strip only containing bamboo stalks; voxel generation of the horizontal strips in a three-dimensional space into a voxel space, wherein the voxel space contains voxels of ground-based lidar point cloud data; and taking the voxel group with continuity in the vertical direction of the whole horizontal strip as a stem, traversing the voxel space and acquiring the number of the moso bamboo groves. By adopting the embodiment of the invention, the field workload of sample plot investigation can be reduced, and meanwhile, according to the special morphological characteristics of the moso bamboos, the provided new method can improve the identification rate of the moso bamboo veneer and provide reference for bamboo forest investigation.
Description
Technical Field
The invention relates to the technical field of forest resource monitoring, in particular to a moso bamboo forest quantity identification method and device based on a foundation laser radar.
Background
The bamboo forest is an important component of forest resources in China, has excellent carbon sequestration capacity, and plays an important role in promoting industrial and regional economic development. Therefore, it is important to conduct the bamboo forest resource investigation regularly and to grasp the current situation and growth change. Traditional bamboo forest resource investigation is time-consuming, labor-consuming and cost-intensive. As an active remote sensing technology, the ground-based laser radar can directly, quickly and accurately acquire the three-dimensional geographic coordinates of a research object, provides accurate information about forest structure parameters such as tree positions, tree numbers, breast height and tree heights, and is more suitable for ground forest investigation. At present, three-dimensional laser point cloud data is rapidly developed in the field of forestry, and how to rapidly and effectively extract forest structure parameters is of great importance, and before extracting the forest structure parameters, a single forest position needs to be determined firstly. Currently, TLS technology is used for single-tree identification, which is mainly focused on tall and large broad-leaved trees, single-tree identification is mostly carried out on the basis of breast-height diameter fitting, the center of a fitted two-dimensional curve is used as a single-tree position, the number of breast-height diameters can be fitted, the single-tree detection precision is determined, and the TLS technology is rarely applied to moso bamboo research.
Disclosure of Invention
The invention aims to provide a moso bamboo forest quantity identification method based on a foundation laser radar, and aims to solve the problem that no method for rapidly and accurately researching the moso bamboo forest quantity exists in the prior art.
The invention provides a method for identifying the number of moso bamboo forests based on a foundation laser radar, which comprises the following steps:
s101, data acquisition: acquiring foundation laser radar point cloud data of the moso bamboo forest through a foundation laser radar;
s102, data processing: obtaining a point cloud data file according to the point cloud data of the foundation laser radar;
s103, intercepting data: intercepting the point cloud data file according to a preset interception upper limit and an interception lower limit to generate a section of horizontal strip only containing bamboo stalks;
s104, data voxel formation: voxel generation of the horizontal strips in a three-dimensional space into a voxel space, wherein the voxel space contains voxels of ground-based lidar point cloud data;
s105, traversing data: and taking the voxel group with continuity in the vertical direction of the whole horizontal strip as a stem, traversing the voxel space and acquiring the number of the moso bamboo groves.
The invention provides a moso bamboo forest quantity recognition device based on a foundation laser radar, which comprises:
the data acquisition module 501: acquiring foundation laser radar point cloud data of the moso bamboo forest through a foundation laser radar;
the data processing module 502: obtaining a point cloud data file according to the point cloud data of the foundation laser radar;
intercept data module 503: intercepting the point cloud data file according to a preset interception upper limit and an interception lower limit to generate a section of horizontal strip only containing bamboo stalks;
data voxelization module 504: voxel generation of the horizontal strips in a three-dimensional space into a voxel space, wherein the voxel space contains voxels of ground-based lidar point cloud data;
the traverse data module 505: and taking the voxel group with continuity in the vertical direction of the whole horizontal strip as a stem, traversing the voxel space and acquiring the number of the moso bamboo groves.
The embodiment of the invention also provides a device for identifying the number of moso bamboo forests based on the foundation laser radar, which comprises: the system comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the computer program realizes the steps of the bamboo forest quantity identification method based on the foundation laser radar when being executed by the processor.
The embodiment of the invention also provides a computer readable storage medium, wherein an implementation program for information transmission is stored on the computer readable storage medium, and the program is executed by a processor to realize the steps of the method for identifying the number of the moso bamboo forests based on the foundation laser radar.
By adopting the embodiment of the invention, the acquisition and processing of the three-dimensional point cloud data of the moso bamboo forest in the sample plot can reduce the field workload of sample plot investigation, and meanwhile, according to the special morphological characteristics of moso bamboos, the invention provides a novel stem identification method, which can improve the single bamboo identification rate of the moso bamboos and provide reference for the bamboo forest investigation work.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a method for identifying the number of moso bamboo forests based on a ground-based laser radar according to an embodiment of the invention;
FIG. 2 is a schematic diagram of ground-based lidar point cloud data of an embodiment of the method of the invention;
FIG. 3 is a schematic view of a horizontal strip of an embodiment of the method of the present invention;
FIG. 4 is a schematic voxel space diagram of a method embodiment of the present invention;
FIG. 5 is a schematic view of a first embodiment of the device according to the present invention, illustrating a device for recognizing the number of moso bamboo forests based on a ground-based lidar;
fig. 6 is a schematic view of a bamboo forest quantity recognition device based on a ground-based laser radar according to a second embodiment of the device.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise. Furthermore, the terms "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Method embodiment
According to an embodiment of the present invention, a method for identifying the number of moso bamboo stands based on a foundation laser radar is provided, fig. 1 is a flowchart of the method for identifying the number of moso bamboo stands based on a foundation laser radar according to the embodiment of the present invention, and as shown in fig. 1, the method for identifying the number of moso bamboo stands based on a foundation laser radar according to the embodiment of the present invention specifically includes:
s101, data acquisition: and acquiring foundation laser radar point cloud data of the phyllostachys pubescens forest through a foundation laser radar.
Specifically, a forest farm is taken as an example, and the geographical position of the forest farm is 31 degrees 15 '1 "N, 119 degrees 43' 52" E, the ground belongs to the Tianmu mountain afternoon, the south is a hilly area, and the north is a plain area. In subtropical monsoon climate, precipitation is abundant, but precipitation amount is not uniform in space-time distribution, precipitation in spring and summer is concentrated, annual precipitation amount is more than 1177mm, annual average temperature is 13-22 ℃, annual average frost-free period is more than 240 days, and good growing environment is provided for vegetation. The forest land is 80% of moso bamboo forest, and the forest coverage rate is 97.5%. 3 20m bamboo pure forest plots (P1, P2 and P3) with a population density of 5500 plants/hm are set in the research area26200 strain/hm25875 strains/hm2In the same field, the vegetation is less under the forest and the terrain is flatter. The ground-based lidar device used in this study was Trimble TX8, which has a 360 ° × 317 ° field of view and a data acquisition rate of one million points per second, in steps of 0.036 ° in both the horizontal and vertical directions. And (3) data acquisition is carried out, 5 stations are scanned in each block, and the stations are distributed by adopting a corner setting method. And 6 reference balls are distributed in each sample plot, all the reference balls are not on the same horizontal plane, and at the same time, at least more than 3 reference balls can be seen at each station, so that the data splicing processing at a later period can be realized. The measured data was obtained by positioning all bamboos in the sample plot using a total station, and a total of 703 moso bamboos were investigated in the sample plot.
S102, data processing: and obtaining a point cloud data file according to the point cloud data of the foundation laser radar.
Further, obtaining the point cloud data file according to the point cloud data of the foundation lidar specifically comprises: preprocessing the foundation laser radar point cloud data to generate corrected point cloud data; and exporting the corrected point cloud data into a point cloud data file with a fixed format.
Further, the preprocessing of the foundation lidar point cloud data to generate corrected point cloud data specifically comprises: and carrying out point cloud splicing, point cloud denoising and terrain correction on the point cloud data of the foundation laser radar to generate corrected point cloud data.
In this embodiment, based on sample plot three-dimensional laser point cloud data obtained by a foundation laser radar, preprocessing such as point cloud creation, point cloud denoising, splicing, terrain correction and the like is performed according to a 'Trimble real works 10.1' software matched with an instrument, fig. 2 is a schematic diagram of the foundation laser radar point cloud data of the method embodiment of the present invention, the three-dimensional laser point cloud data of the sample plot obtained by the above steps is shown in fig. 2, and the three-dimensional laser point cloud data is exported to a data format of las so as to perform subsequent processing.
S103, intercepting data: and intercepting the point cloud data file according to a preset interception upper limit and an interception lower limit to generate a section of horizontal strip only containing bamboo stalks.
In the embodiment of the present invention, a section of horizontal stripe only containing bamboo stalks is firstly intercepted, the upper limit of the stripe is mainly to avoid the interference of bamboo branches and bamboo leaves on the stem identification, the lower limit is mainly to avoid the influence of ground points and low vegetation on the stem identification, and fig. 3 is a schematic diagram of the horizontal stripe of the embodiment of the method of the present invention, as shown in fig. 3.
S104, data voxel formation: the horizontal strips are voxelized in three-dimensional space into a voxel space, wherein the voxel space contains voxels of ground-based lidar point cloud data.
In the embodiment of the invention, the intercepted horizontal strip point cloud is subjected to voxel transformation in a three-dimensional space, and only the voxel containing the original point cloud is recorded; and finally traversing the voxel space, and taking the voxel group with continuity in the vertical direction of the whole strip as a stem, wherein fig. 4 is a schematic diagram of the voxel space of the embodiment of the method of the invention, as shown in fig. 4.
S105, traversing data: and taking the voxel group with continuity in the vertical direction of the whole horizontal strip as a stem, traversing the voxel space and acquiring the number of the moso bamboo groves.
In the present example, Table 1 shows comparative data obtained by estimating the number of plants and actually measured plants using the method for three plots, as shown in Table 1: the correctness is that the estimated data is the correctness of the actual phyllostachys edulis forest, and the integrity of single wood detection of three plots is 89.09%, 91.93% and 90.12%, respectively.
TABLE 1
Apparatus embodiment one
According to an embodiment of the present invention, there is provided a device for identifying the number of moso bamboo stands based on a foundation lidar, fig. 5 is a schematic diagram of the device for identifying the number of moso bamboo stands based on a foundation lidar according to an embodiment of the present invention, and as shown in fig. 5, the device for identifying the number of moso bamboo stands based on a foundation lidar according to an embodiment of the present invention specifically includes:
the data acquisition module 501: acquiring foundation laser radar point cloud data of the moso bamboo forest through a foundation laser radar;
the data processing module 502: obtaining a point cloud data file according to the point cloud data of the foundation laser radar;
further, obtaining the point cloud data file according to the point cloud data of the foundation lidar specifically comprises: preprocessing the foundation laser radar point cloud data to generate corrected point cloud data; and exporting the corrected point cloud data into a point cloud data file with a fixed format.
Further, the preprocessing of the foundation lidar point cloud data to generate corrected point cloud data specifically comprises: and carrying out point cloud splicing, point cloud denoising and terrain correction on the point cloud data of the foundation laser radar to generate corrected point cloud data.
Intercept data module 503: intercepting the point cloud data file according to a preset interception upper limit and an interception lower limit to generate a section of horizontal strip only containing bamboo stalks;
data voxelization module 504: voxel generation of the horizontal strips in a three-dimensional space into a voxel space, wherein the voxel space contains voxels of ground-based lidar point cloud data;
the traverse data module 505: and taking the voxel group with continuity in the vertical direction of the whole horizontal strip as a stem, traversing the voxel space and acquiring the number of the moso bamboo groves.
The embodiment of the present invention is a system embodiment corresponding to the above method embodiment, and specific operations of each module may be understood with reference to the description of the method embodiment, which is not described herein again.
Device embodiment II
The embodiment of the invention provides a moso bamboo forest quantity recognition device based on a foundation laser radar, as shown in fig. 6, comprising: a memory 601, a processor 602 and a computer program stored on the memory 601 and executable on the processor 602, the computer program realizing the following method steps when executed by the processor 602:
s101, data acquisition: acquiring foundation laser radar point cloud data of the moso bamboo forest through a foundation laser radar;
s102, data processing: obtaining a point cloud data file according to the point cloud data of the foundation laser radar;
s103, intercepting data: intercepting the point cloud data file according to a preset interception upper limit and an interception lower limit to generate a section of horizontal strip only containing bamboo stalks;
further, obtaining the point cloud data file according to the point cloud data of the foundation lidar specifically comprises: preprocessing the foundation laser radar point cloud data to generate corrected point cloud data; and exporting the corrected point cloud data into a point cloud data file with a fixed format.
Further, the preprocessing of the foundation lidar point cloud data to generate corrected point cloud data specifically comprises: and carrying out point cloud splicing, point cloud denoising and terrain correction on the point cloud data of the foundation laser radar to generate corrected point cloud data.
S104, data voxel formation: voxel generation of the horizontal strips in a three-dimensional space into a voxel space, wherein the voxel space contains voxels of ground-based lidar point cloud data;
s105, traversing data: and taking the voxel group with continuity in the vertical direction of the whole horizontal strip as a stem, traversing the voxel space and acquiring the number of the moso bamboo groves.
Device embodiment III
The embodiment of the invention provides a computer readable storage medium, on which an implementation program of information transmission is stored, and when being executed by a processor 602, the implementation program implements the following method steps:
s101, data acquisition: acquiring foundation laser radar point cloud data of the moso bamboo forest through a foundation laser radar;
s102, data processing: obtaining a point cloud data file according to the point cloud data of the foundation laser radar;
s103, intercepting data: intercepting the point cloud data file according to a preset interception upper limit and an interception lower limit to generate a section of horizontal strip only containing bamboo stalks;
further, obtaining the point cloud data file according to the point cloud data of the foundation lidar specifically comprises: preprocessing the foundation laser radar point cloud data to generate corrected point cloud data; and exporting the corrected point cloud data into a point cloud data file with a fixed format.
Further, the preprocessing of the foundation lidar point cloud data to generate corrected point cloud data specifically comprises: and carrying out point cloud splicing, point cloud denoising and terrain correction on the point cloud data of the foundation laser radar to generate corrected point cloud data.
S104, data voxel formation: voxel generation of the horizontal strips in a three-dimensional space into a voxel space, wherein the voxel space contains voxels of ground-based lidar point cloud data;
s105, traversing data: and taking the voxel group with continuity in the vertical direction of the whole horizontal strip as a stem, traversing the voxel space and acquiring the number of the moso bamboo groves.
The computer-readable storage medium of this embodiment includes, but is not limited to: ROM, RAM, magnetic or optical disks, and the like.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A moso bamboo forest quantity identification method based on a foundation laser radar is characterized by comprising the following steps:
s1, data acquisition: acquiring foundation laser radar point cloud data of the moso bamboo forest through a foundation laser radar;
s2, data processing: obtaining a point cloud data file according to the point cloud data of the foundation laser radar;
s3, intercepting data: intercepting the point cloud data file according to a preset interception upper limit and an interception lower limit to generate a section of horizontal strip only containing bamboo stalks;
s4, data voxel formation: voxel-wise generating the horizontal strip in three-dimensional space into a voxel space, wherein the voxel space contains voxels of the ground-based lidar point cloud data;
s5, traversing data: and taking a voxel group with continuity in the vertical direction of the whole horizontal strip as a stem, traversing the voxel space, and acquiring the number of the moso bamboo groves.
2. The method of claim 1, wherein obtaining a point cloud data file from the ground-based lidar point cloud data specifically comprises:
preprocessing the foundation laser radar point cloud data to generate corrected point cloud data;
and exporting the corrected point cloud data into a point cloud data file with a fixed format.
3. The method of claim 2, wherein preprocessing the ground-based lidar point cloud data to generate corrected point cloud data specifically comprises:
and carrying out point cloud splicing, point cloud denoising and terrain correction on the foundation laser radar point cloud data to generate corrected point cloud data.
4. A mao bamboo forest quantity recognition device based on ground laser radar is characterized by comprising:
a data acquisition module: acquiring foundation laser radar point cloud data of the moso bamboo forest through a foundation laser radar;
a data processing module: obtaining a point cloud data file according to the point cloud data of the foundation laser radar;
a data intercepting module: intercepting the point cloud data file according to a preset interception upper limit and an interception lower limit to generate a section of horizontal strip only containing bamboo stalks;
a data voxelization module: voxel-wise generating the horizontal strip in three-dimensional space into a voxel space, wherein the voxel space contains voxels of the ground-based lidar point cloud data;
and a traversal data module: and taking a voxel group with continuity in the vertical direction of the whole horizontal strip as a stem, traversing the voxel space, and acquiring the number of the moso bamboo groves.
5. The apparatus of claim 4, wherein the data processing module is specifically configured to:
preprocessing the foundation laser radar point cloud data to generate corrected point cloud data;
and exporting the corrected point cloud data into a point cloud data file with a fixed format.
6. The apparatus of claim 5, wherein the data processing module is specifically configured to:
and carrying out point cloud splicing, point cloud denoising and terrain correction on the foundation laser radar point cloud data to generate corrected point cloud data.
7. The utility model provides a mao bamboo forest quantity recognition device based on ground laser radar which characterized in that includes: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the ground based lidar based bamboo forest number identification method according to any one of claims 1 to 3.
8. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon an implementation program of information transfer, which when executed by a processor implements the steps of the foundation lidar based bamboo forest quantity identification method according to any one of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110159604.0A CN112946669B (en) | 2021-02-05 | 2021-02-05 | Moso bamboo forest quantity identification method and device based on foundation laser radar |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110159604.0A CN112946669B (en) | 2021-02-05 | 2021-02-05 | Moso bamboo forest quantity identification method and device based on foundation laser radar |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112946669A true CN112946669A (en) | 2021-06-11 |
| CN112946669B CN112946669B (en) | 2023-04-25 |
Family
ID=76242460
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110159604.0A Active CN112946669B (en) | 2021-02-05 | 2021-02-05 | Moso bamboo forest quantity identification method and device based on foundation laser radar |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112946669B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114998729A (en) * | 2022-05-25 | 2022-09-02 | 浙江圣海亚诺信息技术有限责任公司 | Single-tree identification method fusing optical image and laser radar data |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101488226A (en) * | 2008-01-16 | 2009-07-22 | 中国科学院自动化研究所 | Tree measurement and reconstruction method based on single three-dimensional laser scanning |
| CN102914501A (en) * | 2012-07-26 | 2013-02-06 | 南京大学 | Method for calculating extinction coefficients of three-dimensional forest canopy by using laser-point cloud |
| CN107705309A (en) * | 2017-10-15 | 2018-02-16 | 南京林业大学 | Forest parameter evaluation method in laser point cloud |
| CN109002418A (en) * | 2018-06-20 | 2018-12-14 | 厦门大学 | Tree breast-height diameter automatic calculating method based on Voxels growing and ground laser point cloud |
| WO2020109666A1 (en) * | 2018-11-30 | 2020-06-04 | Prefor Oy | Method and system for generating forestry data |
-
2021
- 2021-02-05 CN CN202110159604.0A patent/CN112946669B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101488226A (en) * | 2008-01-16 | 2009-07-22 | 中国科学院自动化研究所 | Tree measurement and reconstruction method based on single three-dimensional laser scanning |
| CN102914501A (en) * | 2012-07-26 | 2013-02-06 | 南京大学 | Method for calculating extinction coefficients of three-dimensional forest canopy by using laser-point cloud |
| CN107705309A (en) * | 2017-10-15 | 2018-02-16 | 南京林业大学 | Forest parameter evaluation method in laser point cloud |
| CN109002418A (en) * | 2018-06-20 | 2018-12-14 | 厦门大学 | Tree breast-height diameter automatic calculating method based on Voxels growing and ground laser point cloud |
| WO2020109666A1 (en) * | 2018-11-30 | 2020-06-04 | Prefor Oy | Method and system for generating forestry data |
Non-Patent Citations (4)
| Title |
|---|
| TIAN YAO,XIAOYUAN YANG: "Measuring forest structure and biomass in New England forest stands using Echidna ground-based lidar", 《REMOTE SENSING OF ENVIRONMENT》 * |
| XINLIAN LIANG，VILLE KANKARE: "Terrestrial laser scanning in forest inventories", 《ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING》 * |
| 夏明鹏等: "TLS技术在森林资源调查中的应用现状与展望", 《西北林学院学报》 * |
| 晏颖杰等: "地基激光雷达技术在森林调查中的应用研究进展", 《世界林业研究》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114998729A (en) * | 2022-05-25 | 2022-09-02 | 浙江圣海亚诺信息技术有限责任公司 | Single-tree identification method fusing optical image and laser radar data |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112946669B (en) | 2023-04-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Escolà et al. | Mobile terrestrial laser scanner applications in precision fruticulture/horticulture and tools to extract information from canopy point clouds | |
| CN103914786A (en) | Field agricultural production scene perceptual computing method and device | |
| CN111091079B (en) | TLS-based method for measuring vegetation advantage single plant structural parameters in friable region | |
| CN106950573B (en) | A kind of corn waterlogged disaster appraisal procedure and system based on unmanned plane laser radar | |
| CN111345214A (en) | Xinjiang cotton region identification method and system based on satellite image data | |
| Lowe et al. | Canopy density estimation in perennial horticulture crops using 3D spinning lidar SLAM | |
| CN110909933A (en) | Agricultural drought rapid diagnosis and evaluation method coupling crop model and machine learning language | |
| CN113269825B (en) | Forest breast diameter value extraction method based on foundation laser radar technology | |
| CN111539473A (en) | Orchard inter-row leading line extraction method based on 3D Lidar | |
| CN112946669B (en) | Moso bamboo forest quantity identification method and device based on foundation laser radar | |
| Jin et al. | Exploring seasonal and circadian rhythms in structural traits of field maize from LiDAR time series | |
| CN204461325U (en) | A kind of cover degree for herbaceous plant sample ground measures equipment | |
| CN114548277B (en) | Method and system for ground point fitting and crop height extraction based on point cloud data | |
| CN103020595A (en) | Crop-weed identification and positioning method based on three-dimensional flight time method imaging | |
| Zou et al. | Density estimation method of mature wheat based on point cloud segmentation and clustering | |
| Liu et al. | Estimating the impact of shelterbelt structure on corn yield at a large scale using Google Earth and Sentinel 2 data | |
| CN117409322A (en) | Regional forest natural resource ecological estimation method and system based on air-ground remote sensing combination | |
| CN113487636B (en) | Laser radar-based automatic extraction method for plant height and row spacing of wide-ridge crops | |
| CN116739739A (en) | Loan amount evaluation method and device, electronic equipment and storage medium | |
| CN116402879A (en) | Corn ear position measuring method, device, system and storage medium | |
| CN113156082B (en) | Method and system for identifying depth of active layer of crop root system | |
| CN111913185B (en) | TLS (TLS (visual inspection) measuring method for low shrub pattern investigation of severe cold fragile region | |
| Xiao et al. | The Importance of Using Realistic 3D Canopy Models to Calculate Light Interception in the Field | |
| Guang et al. | Preliminary Study on Data Fusion Based on Internet of Things of Eucalyptus Plantation | |
| CN117281016B (en) | Irrigation decision-making method, device and system of intercropping system based on unmanned aerial vehicle remote sensing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |