CN117036944A - Tree carbon sink amount calculating method and system based on point cloud data and image recognition - Google Patents
Tree carbon sink amount calculating method and system based on point cloud data and image recognition Download PDFInfo
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- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 35
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Abstract
The invention discloses a tree carbon sink amount calculating method and system based on point cloud data and image recognition, wherein the method comprises the following steps: s1, acquiring tree data of a region to be detected, wherein the tree data comprises: three-dimensional point cloud data and image data; the three-dimensional point cloud data are used for acquiring point cloud data; the image data is used for carrying out image recognition to obtain tree information; s2, obtaining first measurement data based on the point cloud data; obtaining second measurement data based on the tree information; and S3, setting a threshold value, and calculating carbon transfer amount based on the threshold value, the first measurement data and the second measurement data to obtain a calculation result. According to the invention, the three-dimensional laser scanning technology and the image recognition technology are adopted to respectively calculate the carbon quantity of the same region to be measured, and the measurement data obtained by calculation are mutually checked by setting the threshold value, so that a relatively accurate calculation result is obtained.
Description
Technical Field
The invention belongs to the technical field of carbon sink calculation, and particularly relates to a tree carbon sink calculation method and system based on point cloud data and image recognition.
Background
Carbon sequestration refers to the ability of forests to absorb carbon dioxide, a greenhouse gas in the atmosphere, by photosynthesis and store it in biomass form in plants and in soil. In the conventional tree measurement process, a tape measure or a wheel ruler is often used for measuring the trunk diameter of the tree, the cloth Lu Laisi height finder is used for measuring the tree height of the tree according to a trigonometric function and a similar triangle principle, the method is used for measuring the tree volume, time and labor are wasted, and the precision is obviously influenced by errors caused by human factors.
The three-dimensional laser scanning technology can expand the point measurement of the traditional measurement system to the surface measurement, can go deep into complex field environment and space to carry out scanning operation, directly collect three-dimensional data of various large and complex entities into a computer completely, further reconstruct three-dimensional models of targets and various geometric data such as points, lines, surfaces and bodies rapidly, and carry out various post-processing work on the collected three-dimensional laser point cloud data. The point cloud data needs to extract and separate objects such as buildings, extracts and classifies trees, and the accuracy of a subsequent algorithm influences the final processing result. And therefore, the processing result thereof needs to be checked.
Disclosure of Invention
The invention aims to solve the defects of the prior art, and provides a tree carbon sink amount calculation method based on point cloud data and image recognition.
In order to achieve the above object, the present invention provides the following solutions:
the tree carbon sink amount calculating method based on the point cloud data and the image identification comprises the following steps:
s1, acquiring tree data of a region to be detected, wherein the tree data comprises: three-dimensional point cloud data and image data; the three-dimensional point cloud data are used for acquiring point cloud data; the image data is used for carrying out image recognition to obtain tree information;
s2, obtaining first measurement data based on the point cloud data; obtaining second measurement data based on the tree information;
and S3, setting a threshold value, and calculating carbon transfer amount based on the threshold value, the first measurement data and the second measurement data to obtain a calculation result.
Preferably, the method for obtaining the first measurement data comprises:
three-dimensional point cloud data are obtained, and coordinate registration, point cloud splicing and point cloud denoising processing are carried out on the three-dimensional point cloud data to obtain first processed point cloud data;
non-tree point cloud data segmentation is carried out on the first processing point cloud data, and the non-tree point cloud data are deleted to obtain tree point cloud data;
extracting tree measurement factors from the tree point cloud data to obtain the point cloud data; the point cloud data includes: tree height, breast diameter and crown;
the first measurement data is obtained based on the point cloud data.
Preferably, the method of obtaining the second measurement data comprises:
acquiring image data and acquiring height information for acquiring the image data;
performing height unification on the image data based on the height information to obtain first processed image data;
dividing the first processed image data to obtain rectangular image data;
performing image recognition and information extraction on the rectangular image data to obtain tree information; the tree information includes: tree species, biomass;
and acquiring the second measurement data based on the tree information.
Preferably, the S3 includes:
setting the threshold value of the difference value of the first measurement data and the second measurement data, and taking the average value of the first measurement data and the second measurement data as a calculation result when the difference value is in the range of the threshold value;
and when the difference value is not in the range of the threshold value, reporting an error, and reminding to re-acquire the tree data.
The invention also provides a tree carbon sink calculating system based on the point cloud data and the image recognition, which comprises:
the system comprises an acquisition system, an analysis system and a computing system;
the acquisition system is used for acquiring tree data of an area to be detected, and the tree data comprise: three-dimensional point cloud data and image data; the three-dimensional point cloud data are used for acquiring point cloud data; the image data is used for carrying out image recognition to obtain tree information;
the analysis system is used for obtaining first measurement data based on the point cloud data; obtaining second measurement data based on the tree information;
the computing system is used for setting a threshold value, and performing carbon sequestration calculation based on the threshold value, the first measurement data and the second measurement data to obtain a calculation result.
Preferably, the analysis system comprises: a first analysis module and a second analysis module;
the first analysis module is used for obtaining first measurement data based on the point cloud data;
the second analysis module is used for obtaining second measurement data based on the tree information.
Preferably, the working method of the first analysis module includes:
three-dimensional point cloud data are obtained, and coordinate registration, point cloud splicing and point cloud denoising processing are carried out on the three-dimensional point cloud data to obtain first processed point cloud data;
non-tree point cloud data segmentation is carried out on the first processing point cloud data, and the non-tree point cloud data are deleted to obtain tree point cloud data;
extracting tree measurement factors from the tree point cloud data to obtain the point cloud data; the point cloud data includes: tree height, breast diameter and crown;
the first measurement data is obtained based on the point cloud data.
Preferably, the working method of the second analysis module includes:
acquiring image data and acquiring height information for acquiring the image data;
performing height unification on the image data based on the height information to obtain first processed image data;
dividing the first processed image data to obtain rectangular image data;
performing image recognition and information extraction on the rectangular image data to obtain tree information; the tree information includes: tree species, biomass;
and acquiring the second measurement data based on the tree information.
Preferably, the working method of the computing system comprises the following steps:
setting the threshold value of the difference value of the first measurement data and the second measurement data, and taking the average value of the first measurement data and the second measurement data as a calculation result when the difference value is in the range of the threshold value;
and when the difference value is not in the range of the threshold value, reporting an error, and reminding to re-acquire the tree data.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the three-dimensional laser scanning technology and the image recognition technology are adopted to respectively calculate the carbon quantity of the same region to be measured, and the measurement data obtained by calculation are mutually checked by setting the threshold value, so that a relatively accurate calculation result is obtained.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the drawings that are needed in the embodiments are briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a tree carbon sink calculating method based on point cloud data and image recognition according to an embodiment of the invention;
fig. 2 is a schematic diagram of a tree carbon sink calculation system based on point cloud data and image recognition according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
As shown in fig. 1, the present embodiment provides a method for calculating carbon sink of a tree based on point cloud data and image recognition, including the steps of:
s1, collecting tree data of a region to be detected, wherein the tree data comprise: three-dimensional point cloud data and image data; the three-dimensional point cloud data are used for acquiring point cloud data; the image data is used for carrying out image recognition to obtain tree information;
in the embodiment, tree data acquisition is performed on the area to be detected through the three-dimensional laser scanning equipment and the image acquisition equipment respectively. The tree data in this embodiment includes: three-dimensional point cloud data and image data; and after the acquisition is completed, respectively analyzing the data to obtain measurement data.
S2, obtaining first measurement data based on the point cloud data; obtaining second measurement data based on the tree information;
in this embodiment, the method for obtaining the first measurement data includes:
1. the three-dimensional point cloud data are subjected to coordinate registration, point cloud splicing and point cloud denoising processing to obtain first processed point cloud data;
the method for registering coordinates comprises the following steps: dividing the acquired three-dimensional point cloud data into an original point set and a mapping point set, and respectively extracting features of the original point set and the mapping point set to obtain original features and mapping features. Splicing the original features and the mapping features to obtain spliced features; performing convolution calculation on the spliced features to obtain convolution features; and performing attention calculation on the convolution characteristics to obtain attention characteristics, and obtaining point cloud registration data based on the attention characteristics.
The method for point cloud splicing comprises the following steps: and (3) splicing all three-dimensional point cloud data into a complete point cloud by adopting a point cloud splicing function of the Cyclonr software, and discarding points with too small predicted distances of repeated points to eliminate redundancy of the data.
The point cloud denoising process is used for removing noise points and isolated points in the three-dimensional point cloud data. And finally obtaining first processing point cloud data.
2. The first processing point cloud data is used for carrying out non-tree point cloud data segmentation, and deleting the non-tree point cloud data to obtain tree point cloud data;
3. extracting tree measurement factors from the tree point cloud data to obtain point cloud data; the point cloud data includes: tree height, breast diameter, crown, etc.;
in this embodiment, the elevation histogram is established by using the tree point cloud data, and the tree height information is extracted based on the elevation histogram. The crown is obtained by manually judging the start position of the crown and the tree height information. And the chest diameter is extracted after fitting the slice point cloud with the chest height and the thickness of 2cm by adopting a least square circle fitting algorithm.
4. The point cloud data obtains first measurement data.
Firstly, calculating the volume V of the standing tree through the chest diameter and the tree height; then, calculating first measurement data based on the stumpage volume; the method for calculating the volume V of the standing tree comprises the following steps:
V＝6.745×10 -5 D 1.96 H 0.8144
wherein D represents the chest diameter and H represents the tree height.
The calculation side of the first measurement data C includes:
C＝V×P×0.48
wherein V represents the volume of the standing tree, and P represents the biomass per unit volume of the trunk.
The method for obtaining the second measurement data comprises the following steps:
1. acquiring image data and acquiring height information of the acquired image data;
2. the image data are subjected to height unification based on the height information, and first processed image data are obtained;
3. dividing the first processed image data to obtain rectangular image data;
and carrying out grid division on the first processed image data according to the size of the detected area to obtain rectangular image data.
4. Performing image recognition and information extraction on the rectangular image data to obtain tree information; the tree information includes: tree species, biomass;
in the embodiment, species identification and quantity statistics are carried out on each piece of rectangular image data to obtain tree species and tree quantity information; biomass is calculated based on tree species and tree data information.
The biomass B calculating method comprises the following steps:
B＝L×(1+R)×V×A
wherein L represents the biomass of a single plant of a tree, R represents the ratio of the underground biomass to the overground biomass of tree species, V represents the number of tree species, and A represents the actual space area of a rectangular image.
5. Second measurement data is acquired based on the tree information.
In the present embodiment, the second measurement data C 1 The calculation method of (1) comprises the following steps:
wherein C is t2 Representing t 2 Carbon reserves of biomass at time, C t1 Representing t 1 Biomass carbon reserves over time.
And S3, setting a threshold value, and calculating the carbon sink amount based on the threshold value, the first measurement data and the second measurement data to obtain a calculation result.
In this embodiment, S3 includes:
setting a threshold value of a difference value between the first measurement data and the second measurement data, and taking the average value of the first measurement data and the second measurement data as a calculation result when the difference value is in the range of the threshold value;
when the difference value is not in the range of the threshold value, reporting errors, and reminding to collect tree data again.
The threshold value can be set by the results obtained when testing different areas, and can also be set according to experience and actual precision requirements.
Example two
As shown in fig. 2, the present embodiment provides a tree carbon sink calculating system based on point cloud data and image recognition, including: acquisition system, analysis system and computing system.
The collection system is used for gathering the trees data in the district that awaits measuring, and trees data include: three-dimensional point cloud data and image data; the three-dimensional point cloud data are used for acquiring point cloud data; the image data is used for carrying out image recognition to obtain tree information.
In this embodiment, the acquisition system includes: a three-dimensional laser scanning device and an image acquisition device; and respectively acquiring tree data of the region to be detected through the three-dimensional laser scanning equipment and the image acquisition equipment. The tree data in this embodiment includes: three-dimensional point cloud data and image data; and after the acquisition is completed, respectively analyzing the data to obtain measurement data.
The analysis system is used for obtaining first measurement data based on the point cloud data; second measurement data is obtained based on the tree information.
The analysis system includes: a first analysis module and a second analysis module; the first analysis module is used for obtaining first measurement data based on the point cloud data; the second analysis module is used for obtaining second measurement data based on tree information.
The working method of the first analysis module comprises the following steps:
three-dimensional point cloud data are obtained, coordinate registration, point cloud splicing and point cloud denoising processing are carried out on the three-dimensional point cloud data, and first processing point cloud data are obtained;
the method for registering coordinates comprises the following steps: dividing the acquired three-dimensional point cloud data into an original point set and a mapping point set, and respectively extracting features of the original point set and the mapping point set to obtain original features and mapping features. Splicing the original features and the mapping features to obtain spliced features; performing convolution calculation on the spliced features to obtain convolution features; and performing attention calculation on the convolution characteristics to obtain attention characteristics, and obtaining point cloud registration data based on the attention characteristics.
The method for point cloud splicing comprises the following steps: and (3) splicing all three-dimensional point cloud data into a complete point cloud by adopting a point cloud splicing function of the Cyclonr software, and discarding points with too small predicted distances of repeated points to eliminate redundancy of the data.
The point cloud denoising process is used for removing noise points and isolated points in the three-dimensional point cloud data. And finally obtaining first processing point cloud data.
Non-tree point cloud data segmentation is carried out on the first processing point cloud data, and the non-tree point cloud data are deleted to obtain tree point cloud data;
extracting tree measurement factors from the tree point cloud data to obtain point cloud data; the point cloud data includes: tree height, breast diameter and crown;
in this embodiment, the elevation histogram is established by using the tree point cloud data, and the tree height information is extracted based on the elevation histogram. The crown is obtained by manually judging the start position of the crown and the tree height information. And the chest diameter is extracted after fitting the slice point cloud with the chest height and the thickness of 2cm by adopting a least square circle fitting algorithm.
First measurement data is obtained based on the point cloud data.
Firstly, calculating the volume V of the standing tree through the chest diameter and the tree height; then, calculating first measurement data based on the stumpage volume; the method for calculating the volume V of the standing tree comprises the following steps:
V＝6.745×10 -5 D 1.96 H 0.8144
wherein D represents the chest diameter and H represents the tree height.
The calculation side of the first measurement data C includes:
C＝V×P×0.48
wherein V represents the volume of the standing tree, and P represents the biomass per unit volume of the trunk.
The working method of the second analysis module comprises the following steps:
acquiring image data and acquiring height information of the acquired image data;
the image data are subjected to height unification based on the height information, and first processed image data are obtained;
dividing the first processed image data to obtain rectangular image data;
in this embodiment, the first processed image data is grid-divided according to the size of the measured area, so as to obtain rectangular image data.
Performing image recognition and information extraction on the rectangular image data to obtain tree information; the tree information includes: tree species, biomass.
In the embodiment, species identification and quantity statistics are carried out on each piece of rectangular image data to obtain tree species and tree quantity information; biomass is calculated based on tree species and tree data information.
The biomass B calculating method comprises the following steps:
B＝L×(1+R)×V×A
wherein L represents the biomass of a single plant of a tree, R represents the ratio of the underground biomass to the overground biomass of tree species, V represents the number of tree species, and A represents the actual space area of a rectangular image.
Second measurement data is acquired based on the tree information.
In the present embodiment, the second measurement data C 1 The calculation method of (1) comprises the following steps:
wherein C is t2 Representing t 2 Carbon reserves of biomass at time, C t1 Representing t 1 Biomass carbon reserves over time.
The computing system is used for setting a threshold value, and performing carbon sink calculation based on the threshold value, the first measurement data and the second measurement data to obtain a calculation result.
The working method of the computing system comprises the following steps:
setting a threshold value of a difference value between the first measurement data and the second measurement data, and taking the average value of the first measurement data and the second measurement data as a calculation result when the difference value is in the range of the threshold value;
when the difference value is not in the range of the threshold value, reporting errors, and reminding to collect tree data again.
The threshold value can be set by the results obtained when testing different areas, and can also be set according to experience and actual precision requirements.
The above embodiments are merely illustrative of the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, but various modifications and improvements made by those skilled in the art to which the present invention pertains are made without departing from the spirit of the present invention, and all modifications and improvements fall within the scope of the present invention as defined in the appended claims.
Claims (9)
1. The tree carbon sink calculating method based on the point cloud data and the image identification is characterized by comprising the following steps of:
s1, acquiring tree data of a region to be detected, wherein the tree data comprises: three-dimensional point cloud data and image data; the three-dimensional point cloud data are used for acquiring point cloud data; the image data is used for carrying out image recognition to obtain tree information;
s2, obtaining first measurement data based on the point cloud data; obtaining second measurement data based on the tree information;
and S3, setting a threshold value, and calculating carbon transfer amount based on the threshold value, the first measurement data and the second measurement data to obtain a calculation result.
2. The method for calculating the carbon sink of the tree based on the point cloud data and the image recognition according to claim 1, wherein the method for obtaining the first measurement data comprises:
three-dimensional point cloud data are obtained, and coordinate registration, point cloud splicing and point cloud denoising processing are carried out on the three-dimensional point cloud data to obtain first processed point cloud data;
non-tree point cloud data segmentation is carried out on the first processing point cloud data, and the non-tree point cloud data are deleted to obtain tree point cloud data;
extracting tree measurement factors from the tree point cloud data to obtain the point cloud data; the point cloud data includes: tree height, breast diameter and crown;
the first measurement data is obtained based on the point cloud data.
3. The method for calculating the carbon sink of the tree based on the point cloud data and the image recognition according to claim 1, wherein the method for obtaining the second measurement data comprises:
acquiring image data and acquiring height information for acquiring the image data;
performing height unification on the image data based on the height information to obtain first processed image data;
dividing the first processed image data to obtain rectangular image data;
performing image recognition and information extraction on the rectangular image data to obtain tree information; the tree information includes: tree species, biomass;
and acquiring the second measurement data based on the tree information.
4. The method for calculating the carbon sink of the tree based on the point cloud data and the image recognition according to claim 1, wherein the step S3 comprises:
setting the threshold value of the difference value of the first measurement data and the second measurement data, and taking the average value of the first measurement data and the second measurement data as a calculation result when the difference value is in the range of the threshold value;
and when the difference value is not in the range of the threshold value, reporting an error, and reminding to re-acquire the tree data.
5. The tree carbon sink calculating system based on the point cloud data and the image recognition is characterized by comprising:
the system comprises an acquisition system, an analysis system and a computing system;
the acquisition system is used for acquiring tree data of an area to be detected, and the tree data comprise: three-dimensional point cloud data and image data; the three-dimensional point cloud data are used for acquiring point cloud data; the image data is used for carrying out image recognition to obtain tree information;
the analysis system is used for obtaining first measurement data based on the point cloud data; obtaining second measurement data based on the tree information;
the computing system is used for setting a threshold value, and performing carbon sequestration calculation based on the threshold value, the first measurement data and the second measurement data to obtain a calculation result.
6. The tree carbon sink calculation system based on point cloud data and image recognition of claim 5, wherein the analysis system comprises: a first analysis module and a second analysis module;
the first analysis module is used for obtaining first measurement data based on the point cloud data;
the second analysis module is used for obtaining second measurement data based on the tree information.
7. The tree carbon sink calculation system based on point cloud data and image recognition of claim 6, wherein the first analysis module operates by:
three-dimensional point cloud data are obtained, and coordinate registration, point cloud splicing and point cloud denoising processing are carried out on the three-dimensional point cloud data to obtain first processed point cloud data;
non-tree point cloud data segmentation is carried out on the first processing point cloud data, and the non-tree point cloud data are deleted to obtain tree point cloud data;
extracting tree measurement factors from the tree point cloud data to obtain the point cloud data; the point cloud data includes: tree height, breast diameter and crown;
the first measurement data is obtained based on the point cloud data.
8. The tree carbon sink calculation system based on point cloud data and image recognition of claim 6, wherein the second analysis module operates by:
acquiring image data and acquiring height information for acquiring the image data;
performing height unification on the image data based on the height information to obtain first processed image data;
dividing the first processed image data to obtain rectangular image data;
performing image recognition and information extraction on the rectangular image data to obtain tree information; the tree information includes: tree species, biomass;
and acquiring the second measurement data based on the tree information.
9. The tree carbon sink calculation system based on point cloud data and image recognition of claim 5, wherein the method of operation of the calculation system comprises:
setting the threshold value of the difference value of the first measurement data and the second measurement data, and taking the average value of the first measurement data and the second measurement data as a calculation result when the difference value is in the range of the threshold value;
and when the difference value is not in the range of the threshold value, reporting an error, and reminding to re-acquire the tree data.
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