CN116433748B - Forest land multisource data fusion forest carbon reserve determination method and system - Google Patents
Forest land multisource data fusion forest carbon reserve determination method and system Download PDFInfo
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Abstract
The invention discloses a forest carbon reserve determining method and system based on forest land multisource data fusion, and relates to the field of carbon reserve detection, wherein the method comprises the following steps: acquiring a shooting forest image based on a remote sensing imaging and positioning technology, and performing grid division on the shooting forest based on the shooting forest area to acquire a first-order grid sample land; dividing the first-order grid pattern into a first second-order grid, a second-order grid and a third-order second-order grid according to the order of the forest stand canopy density from low to high; the first, second and third layers of second-order grids form a second-order three-layer grid pattern; respectively taking the central point of each grid in the processed second-order three-layer grid sample plot as the center, and expanding the set area outwards to obtain a field monitoring sample plot corresponding to each grid, thereby obtaining a third-order three-layer field monitoring sample plot; determining carbon reserves of all the field monitoring sample areas based on the three-order three-layer field monitoring sample areas so as to determine the carbon reserves of the whole forest; the carbon reserves of each field monitoring sample area are the carbon reserves after the multi-source data are fused. The invention improves the accuracy of forest carbon reserve calculation.
Description
Technical Field
The invention relates to the technical field of carbon reserve detection, in particular to a forest carbon reserve determination method and system for forest multisource data fusion.
Background
Forest is taken as the main body of photosynthesis of the land ecological system, the annual fixed carbon quantity accounts for about 2/3 of the whole land ecological system, and plays a very important role in relieving and preventing climate change. Research shows that the carbon stored in the unit area of the forest ecosystem is 20-100 times of that of the farmland, and the proportion of the carbon stored in the forest area of 30% of the whole world is up to 77% of the total amount of the land ecosystem. Therefore, increasing carbon sequestration by increasing forest areas and improving forest quality has become a major measure of climate change for international society. Fixing CO in forests 2 In the process of (2), the carbon absorbed from the atmosphere is divided into three categories of overground vegetation carbon libraries, soil carbon libraries and dead organic carbon libraries according to storage mediums. In order to more comprehensively understand the relation between forest carbon fixation and climate change, scientific and comprehensive data are needed to be used as support, and a metering system with scientific method, accurate model and reasonable parameters is needed to be established so as to better serve the work of the forestry on the climate change.
At present, forest carbon reserves and dynamic monitoring calculation thereof are mainly concentrated in a single carbon reservoir, existing research results related to a plurality of carbon reservoirs are relatively few, research on a certain area simultaneously comprising a plurality of carbon reservoirs is almost none, and comprehensive and complete estimation of forest total carbon reserves cannot be performed. In addition, in order to obtain the data of forest resources, a method commonly used is a full-forest survey method, which is limited by huge field investigation workload and opportunity cost of destructiveness to forest ecosystems, and is time-consuming and labor-consuming.
Disclosure of Invention
The invention aims to provide a forest carbon reserve determining method and system for forest land multisource data fusion, and accuracy of forest carbon reserve calculation is improved.
In order to achieve the above object, the present invention provides the following solutions:
a forest land multisource data fusion forest carbon reserve determining method comprises the following steps:
acquiring a photographed forest image based on a remote sensing imaging and positioning technology, determining a photographed forest area according to the photographed forest image, and performing grid division on the photographed forest image based on the photographed forest area to obtain a first-order grid sample plot;
processing boundary grids of the first-order grid sample plot, and determining the forest stand canopy density of each grid in the first-order grid sample plot after processing;
dividing the processed first-order grid pattern into a first-layer second-order grid, a second-layer second-order grid and a third-layer second-order grid according to the sequence of the forest stand canopy density from low to high; the first layer second-order grid, the second layer second-order grid and the third layer second-order grid form a second-order three-layer grid sample plot;
removing the grids in the second-order three-layer grid sample plot, wherein the central points of the grids in the second-order three-layer grid sample plot do not fall on the second-order three-layer grid sample plot, so as to obtain a processed second-order three-layer grid sample plot;
respectively taking the central point of each grid in the processed second-order three-layer grid sample plot as the center, and expanding the set area outwards to obtain a field monitoring sample plot corresponding to each grid, wherein each field monitoring sample plot forms a third-order three-layer field monitoring sample plot;
determining carbon reserves of all the field monitoring sample lands based on the three-level three-layer field monitoring sample lands, and determining the carbon reserves of the whole forest where the forest area corresponding to the shot forest image is located according to the carbon reserves of all the field monitoring sample lands; the carbon reserves of each field monitoring sample area are the carbon reserves after the multi-source data are fused.
Optionally, the carbon reserves of each field monitoring sample plot include a vegetation carbon reservoir, a soil carbon reservoir, and a dead organic carbon reservoir.
Optionally, determining the carbon reserves of each field monitoring sample plot based on the three-level three-layer field monitoring sample plot, and determining the carbon reserves of the whole forest where the forest area corresponding to the photographed forest image is located according to the carbon reserves of each field monitoring sample plot, which specifically includes:
and calculating the carbon reserves of the whole forest where the photographed forest is positioned according to a hierarchical sampling calculation formula.
Optionally, the hierarchical sampling calculation formula is expressed as:
；
；
C n1 =C D(n1) + C S(n1) + C P(n1) ；
C n2 =C D(n2) + C S(n2) + C P(n2) ；
C n3 =C D(n3) + C S(n3) + C P(n3) ；
wherein C is Total (S) For the carbon reserves of the entire forest,is the carbon reserve of the unit area of the whole forest, S is the area of the whole forest, C n1 Monitoring the total carbon reserves of the sample plot for the first layer in situ, C n2 Monitoring the total carbon reserves of the sample plot for the second layer in situ, C n3 Monitoring the total carbon reserves of the sample plot for the third layer in the field S 1 Representing the area of the first layer of field monitoring sample area S 2 Representing the area of the second layer of field monitoring sample area S 3 Representing the area of the third layer of field monitoring sample area C D(n1) Represents a first layer of dead organic carbon library, C S(n1) Represents a first layer of soil carbon reservoir, C P(n1) Representing a first layer of overground vegetation carbon library C D(n2) Represents a second layer of dead organic carbon library, C S(n2) Represents a second layer of soil carbon reservoir, C P(n2) Representing a second layer of overground vegetation carbon library C D(n3) Representing a third layer of dead organic carbon library，C S(n3) Represents a third layer of soil carbon reservoir, C P(n3) Representing a third layer of above-ground vegetation carbon reservoirs.
Optionally, processing the boundary grids of the first-order grid pattern, and determining the stand canopy density of each grid in the first-order grid pattern after processing, which specifically comprises:
and removing grids with the area smaller than 50% of the grid area in the boundary grids of the first-order grid sample plot to obtain the first-order grid sample plot after processing.
Optionally, the processed first-order grid pattern is divided into a first-layer second-order grid, a second-layer second-order grid and a third-layer second-order grid according to the order of the forest stand canopy density from low to high, and specifically comprises the following steps:
in the processed first-order grid sample plot, grids with the forest stand canopy density less than 0.2 are marked as first-layer second-order grids, grids with the forest stand canopy density greater than or equal to 0.2 and less than or equal to 0.69 are marked as second-layer second-order grids, and grids with the forest stand canopy density less than 0.69 are marked as third-layer second-order grids.
Optionally, the set area is a× a m 2 A=1/200 a, a is the side length of the shot forest image, and the interval of the grid number of the first-order grid pattern is 200-210.
The invention discloses a forest carbon reserve determining system for forest land multisource data fusion, which comprises the following components:
the first-order grid pattern determining module is used for obtaining a photographed forest image based on remote sensing imaging and positioning technology; determining a shooting forest area according to the shot forest image, and carrying out grid division on the shot forest image based on the shooting forest area to obtain a first-order grid sample;
the stand canopy closure degree determining module is used for processing the boundary grids of the first-order grid sample plot and determining stand canopy closure degree of each grid in the first-order grid sample plot after processing;
the second-order three-layer grid pattern determining module is used for dividing the processed first-order grid pattern into a first-layer second-order grid, a second-layer second-order grid and a third-layer second-order grid according to the sequence from low to high of the canopy density of the forest stand; the first layer second-order grid, the second layer second-order grid and the third layer second-order grid form a second-order three-layer grid sample plot;
the second-order three-layer grid sample processing module is used for removing grids of the second-order three-layer grid sample plot, wherein the central points of the grids in the second-order three-layer grid sample plot do not fall on the second-order three-layer grid sample plot, so as to obtain a processed second-order three-layer grid sample plot;
the third-order three-layer field monitoring sample area determining module is used for respectively taking the central point of each grid in the processed second-order three-layer grid sample areas as the center, expanding the set area outwards to obtain the field monitoring sample areas corresponding to each grid, and forming the third-order three-layer field monitoring sample areas by the field monitoring sample areas;
the carbon reserves determining module of the whole forest is used for determining the carbon reserves of all the field monitoring sample lands based on the three-level three-layer field monitoring sample lands and determining the carbon reserves of the whole forest where the forest area corresponding to the shot forest image is located according to the carbon reserves of all the field monitoring sample lands; the carbon reserves of each field monitoring sample area are the carbon reserves after the multi-source data are fused.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the invention, shooting forest areas are divided into three layers according to the canopy density of the forest stand, carbon reserves of all the field monitoring sample areas are determined based on three-order three-layer field monitoring sample areas, and the carbon reserves of the whole forest where a shot forest image is located are determined according to the carbon reserves of all the field monitoring sample areas; the carbon reserves of all the field monitoring sample areas are the carbon reserves after the multi-source data are fused, so that the integrity and the accuracy of the forest carbon reserve monitoring calculation result are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of a forest carbon reserve determining method for forest land multisource data fusion according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a forest carbon reserve determining method based on forest land multisource data fusion provided by the embodiment of the invention;
fig. 3 is a schematic structural diagram of a forest carbon reserve determining system with forest land multisource data fusion 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.
The invention aims to provide a forest carbon reserve determining method and system for forest land multisource data fusion, and accuracy of forest carbon reserve calculation is improved.
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 embodiment provides a forest carbon reserve determining method for forest land multisource data fusion, which specifically includes the following steps:
step 101: and acquiring a photographed forest image based on a remote sensing imaging and positioning technology, determining a photographed forest area according to the photographed forest image, and performing grid division on the photographed forest image based on the photographed forest area to obtain a first-order grid pattern.
The step 101 specifically includes: according to the actual coverage area of the forest in the estimated area, the shot forest map is divided into a certain number of first-order grid patterns by remote sensing imaging and aerial satellite positioning technology, and the grid number of the first-order grid patterns is controlled to be 200-210 (the grid number is 200< N <210, and the grid specification is A multiplied by A m).
Step 102: and processing the boundary grids of the first-order grid pattern, and determining the forest stand canopy density of each grid in the first-order grid pattern after processing.
The step 102 specifically includes:
and removing grids with the area smaller than 50% of the grid area in the boundary grids of the first-order grid sample plot to obtain the first-order grid sample plot after processing.
And obtaining the stand canopy closure degree of each sample area (grid) by using the second-class data, and carrying out layering treatment on the sample areas according to the stand canopy closure degree, wherein the three layers are formed.
Step 103: dividing the processed first-order grid pattern into a first-layer second-order grid, a second-layer second-order grid and a third-layer second-order grid according to the sequence of the forest stand canopy density from low to high; the first layer second order grid, the second layer second order grid and the third layer second order grid form a second order three-layer grid sample.
Step 103 specifically includes:
in the processed first-order grid pattern, the grid with the forest stand canopy density less than 0.2 is marked as a first-layer second-order grid, and the total area of the first-layer second-order grid is marked as S 1 Obtaining N1 second-order grid patterns; the grids with the forest stand canopy density being greater than or equal to 0.2 and less than or equal to 0.69 are marked as second-layer second-order grids, and the total area of the second-layer second-order grids is marked as S 2 Obtaining N2 second-order grid patterns; the grid with the forest stand canopy density less than 0.69 is marked as a third layer second-order grid, and the total area of the third layer second-order grid is marked as S 1 The number of second-order lattice patterns obtained is N3.
And then, based on the proportion of each layer in the obtained second-order three-layer grid sample plot to the total area of the forest, layering calculation is carried out to obtain the carbon reserve of the whole forest in unit area.
Step 104: and removing the grids in the second-order three-layer grid sample plot, wherein the central points of the grids in the second-order three-layer grid sample plot do not fall on the second-order three-layer grid sample plot, so as to obtain the processed second-order three-layer grid sample plot.
Step 104 specifically includes: and removing the grids of the second-order three-layer grid sample plot, wherein the central points of the grids in the second-order three-layer grid sample plot do not fall on the second-order three-layer grid sample plot after high-definition grinding and judging, so as to obtain the processed second-order three-layer grid sample plot.
Step 105: and respectively taking the central point of each grid in the processed second-order three-layer grid sample plot as the center, and expanding the set area outwards to obtain the field monitoring sample plot corresponding to each grid, wherein each field monitoring sample plot forms a third-order three-layer field monitoring sample plot.
Step 106: determining carbon reserves of all the field monitoring sample lands based on the three-level three-layer field monitoring sample lands, and determining the carbon reserves of the whole forest where the forest area corresponding to the shot forest image is located according to the carbon reserves of all the field monitoring sample lands; the carbon reserves of each field monitoring sample area are the carbon reserves after the multi-source data are fused.
The number of the field monitoring sites in the third-order three-layer field monitoring sites (the third-order field monitoring sites in fig. 2) is n, wherein the number of the first field monitoring sites, the second field monitoring sites and the third field monitoring sites is n1, n2 and n3 respectively. And carrying out field monitoring on the n field monitoring samples to obtain the carbon reserves of each field monitoring sample.
The carbon reserves of each field monitoring sample area are the sum of vegetation carbon libraries, soil carbon libraries and dead organic matter carbon libraries of the field monitoring sample area.
The set area is a multiplied by a m 2 A=1/200 a, a being the side length of the captured forest image.
Forest fixing CO 2 In the process of (2), the carbon absorbed from the atmosphere is divided into three categories of vegetation carbon libraries, soil carbon libraries and dead organic carbon libraries according to storage mediums, and the carbon libraries jointly complete the distribution of substances and energy of the forest ecosystem in a mutually independent and mutually connected mode. In order to more accurately calculate the total carbon reserves of the forest, a carbon reserve metering model established by special investigation of a forest carbon reservoir is utilized, and the total carbon reserves of the forest are calculated based on different carbon reservoirs.
(1) The vegetation carbon reserves (vegetation carbon libraries) on the field monitoring sample lands are obtained by adopting a biomass expansion factor method.
(2) And measuring and calculating the soil carbon library of the field monitoring sample area by adopting a carbon density method.
(3) The method is characterized in that the underground litters of the sample plot and dead wood carbon reserves (dead organic carbon libraries) are monitored in the field, and the biomass relation model method is adopted for estimation.
Step 105 specifically includes:
and calculating the carbon reserves of the whole forest where the photographed forest is positioned according to a hierarchical sampling calculation formula.
The hierarchical sampling calculation formula is expressed as:
；
；
C n1 =C D(n1) + C S(n1) + C P(n1) ；
C n2 =C D(n2) + C S(n2) + C P(n2) ；
C n3 =C D(n3) + C S(n3) + C P(n3) ；
wherein C is Total (S) For the carbon reserves of the entire forest,is the carbon reserve of the unit area of the whole forest, S is the area of the whole forest, C n1 Monitoring the total carbon reserves of the sample plot for the first layer in situ, C n2 Monitoring the total carbon reserves of the sample plot for the second layer in situ, C n3 Monitoring the total carbon reserves of the sample plot for the third layer in the field S 1 Representing the area of the first layer of field monitoring sample area S 2 Representing the area of the second layer of field monitoring sample area S 3 Representing the area of the third layer of field monitoring sample area C D(n1) Represents a first layer of dead organic carbon library, C S(n1) Represents a first layer of soil carbon reservoir, C P(n1) Representing a first layer of overground vegetation carbon library C D(n2) Represents a second layer of dead organic carbon library, C S(n2) Represents a second layer of soil carbon reservoir, C P(n2) Representing a second layer of overground vegetation carbon reservoirs,C D(n3) represents a third layer of dead organic carbon library, C S(n3) Represents a third layer of soil carbon reservoir, C P(n3) Representing a third layer of above-ground vegetation carbon reservoirs.
The invention adopts biomass method to calculate forest carbon reserve:
a) Dead organic carbon library C D 。
And estimating the carbon reserves of dead forest and litters of the forest by adopting a biomass relation model method. The method comprises the steps of respectively establishing a relation model of biomass per unit area of dead and dead wood and cumulated mass per unit area of arbor layer according to forest types by utilizing special investigation modeling data of a forest carbon library. For a model with poor fitting effect (sparse forest, and canopy density less than 0.2), namely dead organic carbon libraries of the first layer of third-order n1 sample areas are calculated, the average value of biomass ratio of unit area of the corresponding carbon libraries to the unit area of the forest stand is adopted to represent, and the expression is as follows:
C D = C D(n1) +C D(n2) +C D(n3) ；
；
C D(n2) =f(M)×A D1 ×CF；
C D(n3) =f(M)×A D2 ×CF；
wherein C is D Total dead organic carbon library of three layers, C D(n1) For the first layer third-order on-site monitoring of the dead organic carbon library, C D(n2) For the second layer third-order in-situ monitoring of the dead organic carbon library, C D(n3) For third-layer third-order on-site monitoring of dead organic carbon libraries, f (M) is the relation between withered carbon libraries corresponding to forest types of forests to be detected and dead wood carbon library biomass and arbor layer accumulation, M is the arbor layer unit area accumulation (M 3 /hm 2 ）；The average value of biomass per unit area of the withered wood carbon library and the ratio of the biomass on the ground per unit area of the stand is corresponding to the forest type of the forest to be detected;A D1 monitoring the area of the sample site for the first layer third order field (hm 2 ），A D2 Monitoring the area of the sample site for the second layer third order field (hm 2 ），A D3 Monitoring the area of the plot for third-level third-order field (hm 2 ) The method comprises the steps of carrying out a first treatment on the surface of the CF represents the average carbon content, CF is the average carbon content of a certain carbon bank determined according to the forest type (++>Taking forest carbon library special survey actual measurement data 0.42%>The inter-government climate change committee (Intergovernmental Panel on Climate Change, IPCC) was taken as a measurement value of 0.5.
b) Soil carbon reservoir C S -carbon density method.
Calculation of forest soil carbon reserves by utilizing soil carbon bank special investigation to obtain sample data and experimental measurement data of soil volume weight, soil layer thickness and soil organic carbon content of each soil layer corresponding to the field monitoring sample land, obtaining soil organic carbon density of each soil layer corresponding to the field monitoring sample land according to soil class and soil type, and calculating the soil carbon reserves, wherein the expression is as follows:
C S =C S(n1) +C S(n2) +C S(n3) ；
C S(n1) =A S1 ×D；
C S(n2) =A S2 ×D；
C S(n3) =A S3 ×D；
wherein C is S Total soil carbon reservoir of three layers, C S(n1) C, monitoring a soil carbon library of the sample area for the third-order of the first layer in the field S(n2) C, monitoring a soil carbon library of the sample area for the third-order of the second layer in the field S(n3) For third-layer third-order in-situ monitoring of soil carbon library of sample area, A S1 Monitoring land occupation area (hm) of a sample land for a first layer third-order field 2 ），A S2 Monitoring land occupation area (hm) of the sample land for the second layer third-order field 2 ），A S3 Land occupation for third-level third-order field monitoring of sample landFloor area (hm) 2 ) D is the soil type organic carbon-carbon density (Mg/hm) of the forest to be detected 2 ）。
c) Ground vegetation carbon warehouse C P 。
The calculation of the vegetation carbon library on the forest land adopts a biomass expansion factor method.
C P = C P(n1) +C P(n2) +C P(n3) ；
；
Wherein C is P In order to obtain a vegetation carbon library on the forest floor by a biomass expansion factor method, j is 1, 2 or 3, C P(n1) For the first layer third-order on-site monitoring of vegetation carbon libraries on the sample land, C P(n2) For the second layer third-order on-site monitoring of vegetation carbon libraries on the sample land, C P(n3) For third-layer third-order on-site monitoring of vegetation carbon libraries on sample lands, V ji Monitoring the accumulation amount (m) of the ith tree species of the plot for the jth layer third-order field 3 ）；BEF ji Monitoring biomass expansion factors of ith tree species of a sample plot for a j-th layer third-order field; d (D) ji Monitoring the wood basis density (t/m) of the ith tree species of the plot for the j-th layer third-order field 3 ）；R ji Monitoring the root-to-stem ratio of the ith tree species of the sample plot for the j-th layer third-order field; CF (compact flash) ji Monitoring the carbon content (t C/t) of the ith tree species of the sample plot for a third-order field of layer j; for example, the carbon content is 0.4705 when the forest type is bamboo forest, and is 0.465 when the forest type is shrub.
The beneficial effects of the invention are as follows:
1. the multi-order hierarchical sampling reduces the sampling units, reduces the workload and time cost of forest carbon reserve investigation, and improves the efficiency value.
2. Considering the influence of the canopy density on the forest carbon reservoir, the canopy density of the forest stand is layered, so that the sample unit is scientifically concentrated, and the accuracy is improved.
3. In the process of calculating the carbon reserves of the forest dead organic carbon library, corresponding optimal calculation methods are adopted for different layers, so that accuracy of the measuring section result is remarkably improved.
4. Not only is the overground vegetation carbon reservoir estimated, but also the soil carbon reservoir and the dead organic carbon reservoir are included, and the comprehensiveness and the integrity of the estimation result of the total carbon reserves of the forest are obviously improved.
5. By adopting a non-single data fusion calculation mode, the deviation and the contingency of the carbon reserve measuring and calculating process are reduced, and the efficiency and the scientificity of forest carbon reserve calculation are improved.
Example 2
As shown in fig. 3, the present embodiment provides a forest carbon reserve determining system for forest land multisource data fusion, which includes:
a first-order grid pattern determining module 201, configured to obtain a captured forest image based on remote sensing imaging and positioning technologies; and determining a shooting forest area according to the shot forest image, and carrying out grid division on the shot forest image based on the shooting forest area to obtain a first-order grid pattern.
The stand canopy density determining module 202 is configured to process the boundary grids of the first-order grid pattern, and determine stand canopy density of each grid in the first-order grid pattern after processing.
The second-order three-layer grid pattern determining module 203 is configured to divide the processed first-order grid pattern into a first-layer second-order grid, a second-layer second-order grid and a third-layer second-order grid according to the order of the forest stand canopy density from low to high; the first layer second order grid, the second layer second order grid and the third layer second order grid form a second order three-layer grid sample.
And the second-order three-layer grid sample processing module 204 is configured to remove the grid in the second-order three-layer grid sample plot, where the center point of the grid does not fall on the second-order three-layer grid sample plot, so as to obtain a processed second-order three-layer grid sample plot.
And the third-order three-layer field monitoring sample determination module 205 is configured to obtain a field monitoring sample corresponding to each grid by outwards expanding a set area with the center point of each grid in the processed second-order three-layer grid sample as the center, where each field monitoring sample forms a third-order three-layer field monitoring sample.
The carbon reserves determining module 206 of the whole forest is configured to determine the carbon reserves of each field monitoring sample area based on the third-order three-layer field monitoring sample area, and determine the carbon reserves of the whole forest where the forest area corresponding to the photographed forest image is located according to the carbon reserves of each field monitoring sample area; the carbon reserves of each field monitoring sample area are the carbon reserves after the multi-source data are fused.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (6)
1. A method for determining forest carbon reserves by means of forest land multisource data fusion, which is characterized by comprising the following steps:
acquiring a photographed forest image based on a remote sensing imaging and positioning technology, determining a photographed forest area according to the photographed forest image, and performing grid division on the photographed forest image based on the photographed forest area to obtain a first-order grid sample plot;
processing boundary grids of the first-order grid sample plot, and determining the forest stand canopy density of each grid in the first-order grid sample plot after processing;
dividing the processed first-order grid pattern into a first-layer second-order grid, a second-layer second-order grid and a third-layer second-order grid according to the sequence of the forest stand canopy density from low to high; the first layer second-order grid, the second layer second-order grid and the third layer second-order grid form a second-order three-layer grid sample plot;
removing the grids in the second-order three-layer grid sample plot, wherein the central points of the grids in the second-order three-layer grid sample plot do not fall on the second-order three-layer grid sample plot, so as to obtain a processed second-order three-layer grid sample plot;
respectively taking the central point of each grid in the processed second-order three-layer grid sample plot as the center, and expanding the set area outwards to obtain a field monitoring sample plot corresponding to each grid, wherein each field monitoring sample plot forms a third-order three-layer field monitoring sample plot;
determining carbon reserves of all the field monitoring sample lands based on the three-level three-layer field monitoring sample lands, and determining the carbon reserves of the whole forest where the forest area corresponding to the shot forest image is located according to the carbon reserves of all the field monitoring sample lands; the carbon reserves of all the field monitoring sample areas are the carbon reserves after the multi-source data are fused;
determining the carbon reserves of all the field monitoring sample lands based on the three-level three-layer field monitoring sample lands, and determining the carbon reserves of the whole forest where the forest area corresponding to the shot forest image is located according to the carbon reserves of all the field monitoring sample lands, wherein the method specifically comprises the following steps:
calculating the carbon reserves of the whole forest where the photographed forest is located according to a hierarchical sampling calculation formula;
the hierarchical sampling calculation formula is expressed as:
；
；
C n1 =C D(n1) + C S(n1) + C P(n1) ；
C n2 =C D(n2) + C S(n2) + C P(n2) ；
C n3 =C D(n3) + C S(n3) + C P(n3) ；
wherein C is Total (S) For the carbon reserves of the entire forest,is the carbon reserve of the unit area of the whole forest, S is the area of the whole forest, C n1 Monitoring the total carbon reserves of the sample plot for the first layer in situ, C n2 Monitoring the total carbon reserves of the sample plot for the second layer in situ, C n3 Monitoring the total carbon reserves of the sample plot for the third layer in the field S 1 Representing the area of the first layer of field monitoring sample area S 2 Representing the area of the second layer of field monitoring sample area S 3 Representing the area of the third layer of field monitoring sample area C D(n1) Represents a first layer of dead organic carbon library, C S(n1) Represents a first layer of soil carbon reservoir, C P(n1) Representing a first layer of overground vegetation carbon library C D(n2) Represents a second layer of dead organic carbon library, C S(n2) Represents a second layer of soil carbon reservoir, C P(n2) Representing a second layer of overground vegetation carbon library C D(n3) Represents a third layer of dead organic carbon library, C S(n3) Represents a third layer of soil carbon reservoir, C P(n3) Representing a third layer of above-ground vegetation carbon reservoirs.
2. The method for determining forest carbon reserves in a forest land multisource data fusion according to claim 1, wherein the carbon reserves of each field monitoring sample land comprise a vegetation carbon reservoir, a soil carbon reservoir and a dead organic carbon reservoir.
3. The forest land multisource data fusion forest carbon reserve determination method according to claim 1, wherein boundary grids of the first-order grid-like plot are processed, and the forest stand canopy of each grid in the processed first-order grid-like plot is determined, specifically comprising:
and removing grids with the area smaller than 50% of the grid area in the boundary grids of the first-order grid sample plot to obtain the first-order grid sample plot after processing.
4. The forest land multisource data fusion forest carbon reserve determination method according to claim 1, wherein the processed first-order grid pattern is divided into a first-layer second-order grid, a second-layer second-order grid and a third-layer second-order grid according to the order of the canopy density of the forest stand from low to high, and specifically comprises the following steps:
in the processed first-order grid sample plot, grids with the forest stand canopy density less than 0.2 are marked as first-layer second-order grids, grids with the forest stand canopy density greater than or equal to 0.2 and less than or equal to 0.69 are marked as second-layer second-order grids, and grids with the forest stand canopy density less than 0.69 are marked as third-layer second-order grids.
5. The method for determining forest carbon reserves by fusion of forest land multisource data according to claim 1, wherein the set area is a× a m 2 A=1/200 a, a is the side length of the shot forest image, and the interval of the grid number of the first-order grid pattern is 200-210.
6. A forest land multisource data fusion forest carbon reserve determination system, comprising:
the first-order grid pattern determining module is used for obtaining a photographed forest image based on remote sensing imaging and positioning technology; determining a shooting forest area according to the shot forest image, and carrying out grid division on the shot forest image based on the shooting forest area to obtain a first-order grid sample;
the stand canopy closure degree determining module is used for processing the boundary grids of the first-order grid sample plot and determining stand canopy closure degree of each grid in the first-order grid sample plot after processing;
the second-order three-layer grid pattern determining module is used for dividing the processed first-order grid pattern into a first-layer second-order grid, a second-layer second-order grid and a third-layer second-order grid according to the sequence from low to high of the canopy density of the forest stand; the first layer second-order grid, the second layer second-order grid and the third layer second-order grid form a second-order three-layer grid sample plot;
the second-order three-layer grid sample processing module is used for removing grids of the second-order three-layer grid sample plot, wherein the central points of the grids in the second-order three-layer grid sample plot do not fall on the second-order three-layer grid sample plot, so as to obtain a processed second-order three-layer grid sample plot;
the third-order three-layer field monitoring sample area determining module is used for respectively taking the central point of each grid in the processed second-order three-layer grid sample areas as the center, expanding the set area outwards to obtain the field monitoring sample areas corresponding to each grid, and forming the third-order three-layer field monitoring sample areas by the field monitoring sample areas;
the carbon reserves determining module of the whole forest is used for determining the carbon reserves of all the field monitoring sample lands based on the three-level three-layer field monitoring sample lands and determining the carbon reserves of the whole forest where the forest area corresponding to the shot forest image is located according to the carbon reserves of all the field monitoring sample lands; the carbon reserves of all the field monitoring sample areas are the carbon reserves after the multi-source data are fused;
determining the carbon reserves of all the field monitoring sample lands based on the three-level three-layer field monitoring sample lands, and determining the carbon reserves of the whole forest where the forest area corresponding to the shot forest image is located according to the carbon reserves of all the field monitoring sample lands, wherein the method specifically comprises the following steps:
calculating the carbon reserves of the whole forest where the photographed forest is located according to a hierarchical sampling calculation formula;
the hierarchical sampling calculation formula is expressed as:
；
；
C n1 =C D(n1) + C S(n1) + C P(n1) ；
C n2 =C D(n2) + C S(n2) + C P(n2) ；
C n3 =C D(n3) + C S(n3) + C P(n3) ；
wherein C is Total (S) For the carbon reserves of the entire forest,is the carbon reserve of the unit area of the whole forest, S is the area of the whole forest, C n1 Monitoring the total carbon reserves of the sample plot for the first layer in situ, C n2 Monitoring the total carbon reserves of the sample plot for the second layer in situ, C n3 Is the third layerIn-situ monitoring of total carbon reserves in the sample site, S 1 Representing the area of the first layer of field monitoring sample area S 2 Representing the area of the second layer of field monitoring sample area S 3 Representing the area of the third layer of field monitoring sample area C D(n1) Represents a first layer of dead organic carbon library, C S(n1) Represents a first layer of soil carbon reservoir, C P(n1) Representing a first layer of overground vegetation carbon library C D(n2) Represents a second layer of dead organic carbon library, C S(n2) Represents a second layer of soil carbon reservoir, C P(n2) Representing a second layer of overground vegetation carbon library C D(n3) Represents a third layer of dead organic carbon library, C S(n3) Represents a third layer of soil carbon reservoir, C P(n3) Representing a third layer of above-ground vegetation carbon reservoirs. />
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102306299A (en) * | 2011-07-22 | 2012-01-04 | 浙江农林大学 | Distance measuring method based on gradient, intercept and relevant coefficient |
| CN107943885A (en) * | 2017-11-15 | 2018-04-20 | 中国科学院东北地理与农业生态研究所 | A kind of sample investigation method for obtaining the accurate space orientation data of forest community |
| CN109992747A (en) * | 2019-04-03 | 2019-07-09 | 海南省林业科学研究所 | A kind of spatial balance methods of sampling based on GIS platform |
| CN112819066A (en) * | 2021-01-28 | 2021-05-18 | 北京林业大学 | Res-UNet single tree species classification technology |
| CN114091613A (en) * | 2021-11-26 | 2022-02-25 | 安徽师范大学 | Forest biomass estimation method based on high-score joint networking data |
| CN114781011A (en) * | 2022-04-07 | 2022-07-22 | 武汉大学 | High-precision calculation method and system for pixel-level global forest carbon reserves |
| CN116071419A (en) * | 2023-03-06 | 2023-05-05 | 四川省林业和草原调查规划院(四川省林业和草原生态环境监测中心) | Carbon sink dynamic metering method for carbon sink forestation and forest management carbon sink projects |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FI20185930A1 (en) * | 2018-11-02 | 2020-05-03 | Collectivecrunch Oy | Forest stand target attribute prediction |
-
2023
- 2023-06-14 CN CN202310698726.6A patent/CN116433748B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102306299A (en) * | 2011-07-22 | 2012-01-04 | 浙江农林大学 | Distance measuring method based on gradient, intercept and relevant coefficient |
| CN107943885A (en) * | 2017-11-15 | 2018-04-20 | 中国科学院东北地理与农业生态研究所 | A kind of sample investigation method for obtaining the accurate space orientation data of forest community |
| CN109992747A (en) * | 2019-04-03 | 2019-07-09 | 海南省林业科学研究所 | A kind of spatial balance methods of sampling based on GIS platform |
| CN112819066A (en) * | 2021-01-28 | 2021-05-18 | 北京林业大学 | Res-UNet single tree species classification technology |
| CN114091613A (en) * | 2021-11-26 | 2022-02-25 | 安徽师范大学 | Forest biomass estimation method based on high-score joint networking data |
| CN114781011A (en) * | 2022-04-07 | 2022-07-22 | 武汉大学 | High-precision calculation method and system for pixel-level global forest carbon reserves |
| CN116071419A (en) * | 2023-03-06 | 2023-05-05 | 四川省林业和草原调查规划院(四川省林业和草原生态环境监测中心) | Carbon sink dynamic metering method for carbon sink forestation and forest management carbon sink projects |
Non-Patent Citations (1)
| Title |
|---|
| Corrigendum to "Mapping carbon storage in urban trees with multi-source remote sensing data: Relationships between biomass, land use, and demographics in Boston neighborhoods";Steve M. Raciti.etc;《Science of the Total Environment》;全文 * |
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