A carbon storage monitoring method and system based on UAV-LS

Abstract

The present invention discloses a carbon reserve monitoring method and system based on UAV-LS, which relates to the technical field of forest resource monitoring. It includes: obtaining the basic density b of wood samples of plants in the sample plot to be tested; obtaining the laser radar point cloud data and the plant carbon content coefficient C of the sample plot to be tested; s The lidar point cloud data is input into the DSM model to obtain the aboveground vegetation volume V. The aboveground biomass M is obtained by multiplying the basic density b of the wood sample with the aboveground vegetation volume V. The aboveground biomass M is related to the plant carbon content coefficient C. s Multiply to get the aboveground carbon storage C at the plot scale t ; Calculate plant biomass based on growth data, input plant biomass into biomass model to obtain historical carbon storage; compare aboveground carbon storage with historical carbon storage, and obtain carbon storage type of the sample plot to be tested based on changes in carbon storage. The present invention can avoid the negative effects of unreasonable sample selection on carbon storage monitoring, and obtain changes in carbon storage more accurately and intuitively.

Description

Technical Field

[0001] The present invention relates to the technical field of forest resource monitoring, and in particular to a carbon reserve monitoring method and system based on UAV-LS. Background Art

[0002] Since the Industrial Revolution, the content of greenhouse gases such as CO2 in the atmosphere has gradually increased due to human factors such as the burning of fossil fuels and the destruction of forest vegetation. In order to mitigate global climate change, afforestation and reforestation have become indicators to offset greenhouse gas emission reduction. In view of this, the carbon storage of forest ecosystems has gradually become a hot topic in current ecological research.

[0003] In the prior art, when monitoring the carbon storage of forest ecosystems, the main method is the biomass inventory method, and its steps include: first, it is necessary to determine the research area and target, that is, the scope of the forest to be investigated and the carbon storage to be estimated. Conventional tree measurement methods such as clear-cutting method, average tree method, random sampling method, diameter class selection method, volume conversion method, dimensional analysis method, etc. are used to measure the biomass of each component in the forest ecosystem. Generally, soil profile survey sampling method or soil drilling method is used to collect soil samples, and dry burning method or potassium dichromate oxidation method is used indoors to determine the soil carbon content, so as to obtain the organic carbon content in the soil. Based on the survey results of biomass and soil carbon content, the carbon storage of the forest ecosystem is calculated.

[0004] The defects of the above-mentioned prior art are: the accuracy of the biomass inventory method depends on the selection of sample collection. If the sample selection is unreasonable, it will lead to inaccurate detection of carbon storage changes. Summary of the invention

[0005] Based on this, it is necessary to provide a carbon reserve monitoring method and system based on UAV-LS to address the above technical problems.

[0006] The embodiment of the present invention provides a carbon storage monitoring method based on UAV-LS, comprising:

[0007] Obtain the basic density b of the wood samples of the plants in the sample plot to be tested;

[0008] Obtain the laser radar point cloud data and plant carbon content coefficient C of the sample site to be tested s The lidar point cloud data is input into the DSM model to obtain the aboveground vegetation volume V. The aboveground biomass M is obtained by multiplying the basic density b of the wood sample with the aboveground vegetation volume V. The aboveground biomass M is related to the plant carbon content coefficient C. s Multiply to get the aboveground carbon storage C at the plot scale t ;

[0009] Obtain the growth data of each plant in the sample plot to be tested, calculate the plant biomass based on the growth data, and input the plant biomass into the biomass model to obtain the historical carbon storage;

[0010] Aboveground carbon storage C t By comparing with historical carbon storage, the change of carbon storage in the sample site to be tested is inferred, and the carbon storage type of the sample site to be tested is obtained based on the change of carbon storage.

[0011] In addition, the plant growth data includes tree height h and tree breast diameter D.

[0012] Additionally, calculating the plant biomass based on the growth data includes:

[0013] Calculate the biomass of the plant trunk B t :

[0014] lg B t =lg 0.0382+0.8837lg(D 2 h)

[0015] Among them, B t is the trunk biomass, D is the tree diameter at breast height, and h is the tree height;

[0016] Calculate the biomass of plant branches B b :

[0017] lg B b =lg 0.1070+0.6350lg(D 2 h)

[0018] Among them, B b is the branch biomass, D is the tree diameter at breast height, and h is the tree height;

[0019] Calculate the biomass of plant leaves B l :

[0020] lg B l =lg 0.00141+0.8134lg(D 2 h)

[0021] Among them, B l is leaf biomass, D is tree diameter at breast height, and h is tree height;

[0022] Calculate the biomass of the plant root system B r :

[0023] lg B r =lg 0.10+0.6185lg(D 2 h)

[0024] Among them, B r is the root biomass, D is the tree diameter at breast height, and h is the tree height;

[0025] Plant trunk biomass Bt , plant branch biomass B b , plant leaf biomass B l , plant root biomass B r Add them together to get the plant biomass.

[0026] In addition, the carbon storage type of the sample site to be tested obtained according to the change of carbon storage includes:

[0027] The local carbon storage C t If it is greater than the historical carbon storage, the carbon storage has increased, and the carbon storage type of the sample site to be tested is carbon sink;

[0028] The local carbon storage C t It is less than the historical carbon storage, the carbon storage is reduced, and the carbon storage type of the sample site to be tested is carbon source.

[0029] In addition, a carbon storage monitoring system based on UAV-LS includes:

[0030] A collection module, used to obtain the basic density b of the wood samples of the plants in the sample plot to be tested;

[0031] The first detection module is used to obtain the laser radar point cloud data and plant carbon content coefficient C of the sample site to be tested. s The lidar point cloud data is input into the DSM model to obtain the aboveground vegetation volume V. The aboveground biomass M is obtained by multiplying the basic density b of the wood sample with the aboveground vegetation volume V. The aboveground biomass M is related to the plant carbon content coefficient C. s Multiply to get the aboveground carbon storage C at the plot scale t ;

[0032] The second detection module is used to obtain the growth data of each plant in the sample plot to be tested, calculate the plant biomass according to the growth data, and input the plant biomass into the biomass model to obtain the historical carbon storage;

[0033] Comparison module for converting aboveground carbon stocks C t By comparing with historical carbon storage, the change of carbon storage in the sample site to be tested is inferred, and the carbon storage type of the sample site to be tested is obtained based on the change of carbon storage.

[0034] Compared with the prior art, the carbon storage monitoring method and system based on UAV-LS provided in the embodiment of the present invention have the following beneficial effects:

[0035] The present invention obtains the basic density b of the wood samples of the plants in the sample plot to be tested; obtains the laser radar point cloud data and the plant carbon content coefficient C of the sample plot to be tested; sThe lidar point cloud data is input into the DSM model to obtain the aboveground vegetation volume V. The aboveground biomass M is obtained by multiplying the basic density b of the wood sample with the aboveground vegetation volume V. The aboveground biomass M is related to the plant carbon content coefficient C. s Multiply to get the aboveground carbon storage C at the plot scale t ; Obtain the growth data of each plant in the sample plot to be tested, calculate the plant biomass based on the growth data, input the plant biomass into the biomass model to obtain the historical carbon storage; convert the aboveground carbon storage C t By comparing with historical carbon storage, the change of carbon storage in the sample site to be tested is inferred, and the carbon storage type of the sample site to be tested is obtained based on the change of carbon storage.

[0036] Compared with the existing technology, the above-mentioned technical solution calculates the basic density b of the wood sample and combines the lidar point cloud data and plant growth data to avoid the negative effects of unreasonable sample selection on carbon storage monitoring. t By comparing with historical carbon reserves, changes in carbon reserves can be obtained more accurately and intuitively. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A schematic flow chart of a carbon storage monitoring method based on UAV-LS provided in an embodiment. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0039] In one embodiment, a carbon storage monitoring method based on UAV-LS is provided, such as Figure 1 As shown, the method includes:

[0040] Collect wood samples from plants in the sample plot to be tested, measure the volume and dry weight of the wood samples, and divide the dry weight of the samples by the sample volume to obtain the basic density b of the wood samples.

[0041] Obtaining LiDAR point cloud data and plant carbon content coefficient C s , the lidar point cloud data is input into the aboveground vegetation volume V determined by the DSM model, and the aboveground biomass M is obtained by multiplying the basic density b of the wood sample by the aboveground vegetation volume V. The formula for calculating the aboveground biomass M is:

[0042] M=bV

[0043] Where b is the basic density of the wood sample and V is the aboveground vegetation volume.

[0044] Aboveground biomass M and plant carbon content coefficient Cs Multiply to get the aboveground carbon storage C at the plot scale t , calculate the aboveground carbon storage C t The formula is:

[0045] C t =M×C s

[0046] Where M is the aboveground biomass, C s is the carbon content coefficient of plants.

[0047] The growth data of each plant in the sample plot to be tested, including tree height h and tree diameter at breast height D, are measured, and the plant biomass is calculated based on the growth data. The calculation formula is:

[0048] Calculate the biomass of the plant trunk B t :

[0049] lg B t =lg 0.0382+0.8837lg(D 2 h)

[0050] Among them, B t is the trunk biomass, D is the tree diameter at breast height, and h is the tree height;

[0051] Calculate the biomass of plant branches B b :

[0052] lg B b =lg 0.1070+0.6350lg(D 2 h)

[0053] Among them, B b is the branch biomass, D is the tree diameter at breast height, and h is the tree height;

[0054] Calculate the biomass of plant leaves B l :

[0055] lg B l =lg 0.00141+0.8134lg(D 2 h)

[0056] Among them, B l is leaf biomass, D is tree diameter at breast height, and h is tree height;

[0057] Calculate the biomass of the plant root system B r :

[0058] lg B r =lg 0.10+0.6185lg(D 2 h)

[0059] Among them, Br is the root biomass, D is the tree diameter at breast height, and h is the tree height;

[0060] Plant trunk biomass B t , plant branch biomass B b , plant leaf biomass B l , plant root biomass B r Add them together to get the plant biomass.

[0061] The plant biomass is input into the biomass model to obtain the historical carbon storage, the aboveground carbon storage C t Compare with the historical carbon storage to infer the change of carbon storage in the sample site to be tested, and obtain the carbon storage type of the sample site to be tested based on the change of carbon storage:

[0062] The local carbon storage C t If it is greater than the historical carbon storage, the carbon storage has increased and the carbon storage type of the sample site to be tested is carbon sink.

[0063] The local carbon storage C t It is less than the historical carbon storage, the carbon storage is reduced, and the carbon storage type of the sample site to be tested is carbon source.

[0064] In one embodiment, a carbon storage monitoring system based on UAV-LS is provided, the system comprising:

[0065] A collection module, used to obtain the basic density b of the wood samples of the plants in the sample plot to be tested;

[0066] The first detection module is used to obtain the laser radar point cloud data and plant carbon content coefficient C of the sample site to be tested. s The lidar point cloud data is input into the DSM model to obtain the aboveground vegetation volume V. The aboveground biomass M is obtained by multiplying the basic density b of the wood sample with the aboveground vegetation volume V. The aboveground biomass M is related to the plant carbon content coefficient C. s Multiply to get the aboveground carbon storage C at the plot scale t ;

[0067] The second detection module is used to obtain the growth data of each plant in the sample plot to be tested, calculate the plant biomass according to the growth data, and input the plant biomass into the biomass model to obtain the historical carbon storage;

[0068] Comparison module for converting aboveground carbon stocks C t By comparing with historical carbon storage, the change of carbon storage in the sample site to be tested is inferred, and the carbon storage type of the sample site to be tested is obtained based on the change of carbon storage.

[0069] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A carbon storage monitoring method based on UAV-LS, characterized in that: include: Obtain the basic density b of the wood samples of the plants in the sample plot to be tested; Obtain the laser radar point cloud data and plant carbon content coefficient C of the sample site to be tested s The lidar point cloud data is input into the DSM model to obtain the aboveground vegetation volume V. The aboveground biomass M is obtained by multiplying the basic density b of the wood sample with the aboveground vegetation volume V. The aboveground biomass M is related to the plant carbon content coefficient C. s Multiply to get the aboveground carbon storage C at the plot scale t ; Obtain the growth data of each plant in the sample plot to be tested, calculate the plant biomass based on the growth data, and input the plant biomass into the biomass model to obtain the historical carbon storage; Aboveground carbon storage C t By comparing with historical carbon storage, the change of carbon storage in the sample site to be tested is inferred, and the carbon storage type of the sample site to be tested is obtained based on the change of carbon storage.

2. A carbon storage monitoring method based on UAV-LS as claimed in claim 1, characterized in that: The plant growth data includes tree height h and tree diameter at breast height D.

3. A carbon storage monitoring method based on UAV-LS as claimed in claim 2, characterized in that: Calculating the plant biomass according to the growth data comprises: Calculate the biomass of the plant trunk B t : lg B t =lg 0.0382+0.8837lg(D 2 h) Among them, B t is the trunk biomass, D is the tree diameter at breast height, and h is the tree height; Calculate the biomass of plant branches B b : lg B b =lg 0.1070+0.6350lg(D 2 h) Among them, B b is the branch biomass, D is the tree diameter at breast height, and h is the tree height; Calculate the biomass of plant leaves B l : lg B l =lg 0.00141+0.8134lg(D 2 h) Among them, B l is leaf biomass, D is tree diameter at breast height, and h is tree height; Calculate the biomass of the plant root system B r : lg B r =lg 0.10+0.6185lg(D 2 h) Among them, B r is the root biomass, D is the tree diameter at breast height, and h is the tree height; Plant trunk biomass B t , plant branch biomass B b , plant leaf biomass B l , plant root biomass B r Add them together to get the plant biomass.

4. A carbon storage monitoring method based on UAV-LS as claimed in claim 1, characterized in that: The carbon storage type of the sample site to be tested obtained according to the change of carbon storage includes: The local carbon storage C t If it is greater than the historical carbon storage, the carbon storage has increased, and the carbon storage type of the sample site to be tested is carbon sink; The local carbon storage C t It is less than the historical carbon storage, the carbon storage is reduced, and the carbon storage type of the sample site to be tested is carbon source.

5. A carbon storage monitoring system based on UAV-LS, characterized in that: include: A collection module, used to obtain the basic density b of the wood samples of the plants in the sample plot to be tested; The first detection module is used to obtain the laser radar point cloud data and plant carbon content coefficient C of the sample site to be tested. s The lidar point cloud data is input into the DSM model to obtain the aboveground vegetation volume V. The aboveground biomass M is obtained by multiplying the basic density b of the wood sample with the aboveground vegetation volume V. The aboveground biomass M is related to the plant carbon content coefficient C. s Multiply to get the aboveground carbon storage C at the plot scale t ; The second detection module is used to obtain the growth data of each plant in the sample plot to be tested, calculate the plant biomass according to the growth data, and input the plant biomass into the biomass model to obtain the historical carbon storage; Comparison module for converting aboveground carbon stocks C t By comparing with historical carbon storage, the change of carbon storage in the sample site to be tested is inferred, and the carbon storage type of the sample site to be tested is obtained based on the change of carbon storage.

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