CN114021371B - Carbon reserve influence estimation method and device, electronic equipment and storage medium - Google Patents
Carbon reserve influence estimation method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application provides a carbon reserve influence estimation method and device, electronic equipment and a storage medium, and relates to the field of carbon reserve estimation. The method comprises the steps of firstly obtaining information to be processed in a preset area, wherein the information to be processed comprises periodic average air temperature/periodic average earth temperature, a digital elevation model, gradient, slope direction, longitude and latitude information, then determining a periodic average air temperature/periodic average earth temperature estimation model according to the information to be processed, then determining periodic average air temperature/periodic average earth temperature of each reference point in the preset area according to the estimation model, and then determining perennial frozen soil areas in the preset area according to the periodic average air temperature/periodic average earth temperature of each reference point so as to determine the contribution rate of the change of the perennial frozen soil areas to the change of the carbon reserve. The method and the device can accurately determine the permafrost region and determine the influence of permafrost degradation on carbon reserve change.
Description
Technical Field
The present disclosure relates to the field of carbon reserve estimation, and in particular, to a method and an apparatus for estimating influence of carbon reserve, an electronic device, and a storage medium.
Background
With global climate change and regional human activity aggravation, permafrost rapidly degrades, a series of ecological environment problems such as forest line moving upwards and wetland atrophy are caused, and regional carbon reserve loss is caused.
However, the current determination scheme for the perennial frozen soil areas is not perfect, and the influence of the change of the perennial frozen soil areas on the change of the carbon reserves cannot be accurately determined.
Disclosure of Invention
The application aims to provide a carbon reserve influence estimation method, a carbon reserve influence estimation device, electronic equipment and a storage medium, and aims to solve the problems that a determination scheme for a perennial frozen soil area is not perfect and influences of changes of the perennial frozen soil area on carbon reserve changes cannot be accurately determined in the prior art.
In order to achieve the above purpose, the embodiments of the present application employ the following technical solutions:
in a first aspect, an embodiment of the present application provides a carbon storage impact estimation method, where the carbon storage impact estimation method includes:
acquiring information to be processed in a preset region, wherein the information to be processed comprises periodic average air temperature/periodic average ground temperature, a digital elevation model, gradient, slope, longitude and latitude information;
determining a periodic average air temperature/periodic average ground temperature estimation model according to the information to be processed;
determining the periodic average air temperature/periodic average ground temperature of each reference point in the preset area according to the estimation model;
and determining the permafrost region in the preset region according to the periodic average air temperature/periodic average ground temperature of each reference point so as to determine the contribution rate of the change of the permafrost region to the change of the carbon reserve.
In a second aspect, an embodiment of the present application provides a carbon storage amount influence estimation device including:
the information acquisition unit is used for acquiring information to be processed in a preset area, wherein the information to be processed comprises cycle average air temperature/cycle average earth temperature, a digital elevation model, a slope, a sloping direction, longitude and latitude information;
the processing unit is used for determining a periodic average air temperature/periodic average ground temperature estimation model according to the information to be processed;
the processing unit is further used for determining the periodic average air temperature/periodic average ground temperature of each reference point in the preset area according to the ground temperature estimation model;
and the processing unit is further used for determining the permafrost region in the preset region according to the periodic average air temperature/periodic average ground temperature of each reference point so as to determine the contribution rate of the change of the permafrost region to the change of the carbon reserve.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory configured to store one or more programs; a processor. The one or more programs, when executed by the processor, implement the carbon reserve impact estimation method described above.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the above-mentioned carbon storage impact estimation method.
Compared with the prior art, the method has the following beneficial effects:
the embodiment of the application provides a method and a device for estimating carbon reserve influence, electronic equipment and a storage medium, and the method comprises the steps of firstly obtaining information to be processed in a preset area, wherein the information to be processed comprises cycle average air temperature/cycle average earth temperature, a digital elevation model, gradient, slope direction, longitude and latitude information, then determining a cycle average air temperature/cycle average earth temperature estimation model according to the information to be processed, then determining cycle average air temperature/cycle average earth temperature of each reference point in the preset area according to the estimation model, and then determining a perennial frozen earth area in the preset area according to the cycle average air temperature/cycle average earth temperature of each reference point. Because this application can be on the basis of obtaining a plurality of pending information, determine comparatively accurate temperature/ground temperature estimation model, then confirm the temperature/ground temperature of different position according to the estimation model to confirm relevant model according to this, the permafrost region that consequently determines is more accurate, and the influence of the change of the permafrost region of confirming that can be accurate to the carbon reserves change.
In order to make the aforementioned objects, features and advantages of the present application comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic block diagram of an electronic device according to an embodiment of the present disclosure.
Fig. 2 is a schematic flow chart of a method for estimating influence of carbon reserves according to an embodiment of the present disclosure.
Fig. 3 is another schematic flow chart of a method for estimating influence of carbon reserve according to an embodiment of the application.
Fig. 4 is a block diagram of a carbon storage influence estimation apparatus according to an embodiment of the present disclosure.
In the figure:
100-an electronic device; 101-a processor; 102-a memory; 103-a communication interface; 200-carbon storage influence estimating means; 210-an information acquisition unit; 220-processing unit.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, as presented in the figures, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not construed as indicating or implying relative importance.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
As described in the background art, the drawing of the permafrost is mainly realized through on-site drilling survey, meteorological data, remote sensing and model simulation, but the drilling and the meteorological data are single-point observation, and the remote sensing data lack high spatial resolution data of a long-time sequence, so that the long-term change drawing of the permafrost has certain restrictions. Meanwhile, with global climate change and regional human activities aggravation, permafrost degrades rapidly, a series of ecological environment problems such as forest line moving upwards, wetland atrophy and the like are caused, and regional carbon reserves are lost.
In view of this, the embodiment of the present application provides a method for estimating influence of carbon reserves, which determines air temperatures/ground temperatures at different points by using a manner of determining an air temperature/ground temperature estimation model first, and determines a permafrost region according to the determined air temperatures/ground temperatures.
It should be noted that the carbon reserve influence estimation method provided by the present application may be applied to an electronic device, and optionally, fig. 1 illustrates a schematic structural block diagram of an electronic device 100 provided by an embodiment of the present application, where the electronic device 100 includes a memory 102, a processor 101, and a communication interface 103, and the memory 102, the processor 101, and the communication interface 103 are electrically connected to each other directly or indirectly to implement data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines.
The memory 102 may be used to store software programs and modules, such as program instructions or modules corresponding to the carbon storage impact estimation apparatus 200 provided in the embodiment of the present application, and the processor 101 executes the software programs and modules stored in the memory 102 to execute various functional applications and data processing, thereby executing the steps of the positioning method provided in the embodiment of the present application. The communication interface 103 may be used for communicating signaling or data with other node devices.
The Memory 102 may be, but is not limited to, a Random Access Memory (RAM) 102, a Read Only Memory (ROM) 102, a Programmable Read Only Memory (PROM) 102, an Erasable Read Only Memory (EPROM) 102, an Electrically Erasable Programmable Read Only Memory (EEPROM) 102, and the like.
The processor 101 may be an integrated circuit chip having signal processing capabilities. The Processor 101 may be a general-purpose Processor 101, including a Central Processing Unit (CPU) 101, a Network Processor 101 (NP), and the like; but may also be a Digital Signal processor 101 (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components.
It will be appreciated that the configuration shown in FIG. 1 is merely illustrative and that electronic device 100 may include more or fewer components than shown in FIG. 1 or have a different configuration than shown in FIG. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.
The carbon reserve influence estimation method provided by the present application is exemplified below:
as an alternative implementation, referring to fig. 2, the carbon storage influence estimation method includes:
and S102, acquiring information to be processed in a preset area, wherein the information to be processed comprises cycle average air temperature/cycle average earth temperature, a digital elevation model, a slope direction, longitude and latitude information.
And S104, determining a periodic average air temperature/periodic average ground temperature estimation model according to the information to be processed.
And S106, determining the periodic average air temperature/periodic average ground temperature of each reference point in the preset area according to the estimation model.
And S108, determining the permafrost region in the preset region according to the periodic average air temperature/periodic average ground temperature of each reference point so as to determine the contribution rate of the change of the permafrost region to the change of the carbon reserve.
The preset area described herein refers to a research area, and generally, the research area is a whole area, for example, a certain basin is used as the preset area, or a certain natural geographic unit is used as the preset area, which is not limited herein.
On the basis, the daily air temperature/ground temperature data of the meteorological sites in the preset area can be collected and processed into the periodic average air temperature/periodic average ground temperature. Namely, a plurality of sampling points are arranged in a preset area, air temperature/ground temperature data are sampled day by day, and then the average air temperature or ground temperature is calculated.
It should be noted that the term average air temperature/term average ground temperature described in the present application means that only air temperature information may be collected and then the term average air temperature is determined, or only ground temperature information may be collected and then the term average ground temperature is determined; or simultaneously collecting the air temperature information or the ground temperature information, and then respectively determining the periodic average air temperature and the periodic average ground temperature.
It should be noted that, the present application is not limited to the size of the period, for example, when the period is one year, the period average air temperature/period average ground temperature refers to the average air temperature/ground temperature within one year; when the period is two years, the average air temperature/ground temperature in two years is determined, but the period may be five years or ten years, and the like, which is not limited herein.
In addition, acquisition of the digital elevation model, the slope, heading, longitude and latitude data may collect a high-precision Digital Elevation Model (DEM) of the area of interest, such as DEM data of 90m spatial resolution, and generate the slope and heading of the area of interest via a terrain analysis tool in ArcGIS. To better distinguish between a shade slope and a sun slope, the slope direction value is converted to a cos value. By generating grid data in ArcGIS, for example, the size of the grid is identical to the spatial resolution of DEM data, and 90m is obtained, longitude and latitude are assigned to the grid, and spatial distribution data of longitude and latitude is generated.
After the relevant information to be processed is obtained, the period average air temperature/period average ground temperature estimation model needs to be determined based on the information to be processed.
It can be understood that the purpose of determining the estimation model is to obtain the cycle average air temperature/cycle average ground temperature at any position in the preset area after obtaining the digital elevation model, the gradient, the slope direction, the longitude and the latitude information parameters after determining the estimation model from the to-be-processed information determined by the plurality of sampling points in the preset area.
As an implementation mode, the periodic average air temperature/periodic average ground temperature estimation model is established through a least square method model. Optionally, the estimation model satisfies the formula:
wherein, T 0 Indicating the position of the sampling point within a predetermined area, Z OLS (T 0 ) Represents T 0 Position cycle average air temperature/cycle average ground temperature value, δ 0 Denotes intercept, Y m (T 0 ) Represents T 0 Variable Y of position m A value of, whereinQuantity Y m Including digital elevation model, slope, longitude and latitude information, delta m (T 0 ) Regression coefficients representing different variables; x is the number of variables,. Epsilon 0 Representing the residual error.
As can be seen from the model formula, the unknowns in the model include delta 0 、ε 0 And a regression coefficient delta corresponding to each variable m (T 0 ) And, in this application, the value of x is 5, the unknown quantity includes 7 in total, and then the information of the sampling point is brought into the model formula, so that the unknown quantity in the model formula can be solved.
Here, it should be noted that, the information of the sampling points is not limited in any way, and for example, the information of the sampling points at different positions in the same year may be used, or the information of the sampling points at different positions in different years may also be used, for example, in 2000 years, when 100 sampling points are included in a preset area, the data of 100 sampling points are substituted into a model formula, and a formula of the estimation model is finally determined.
It will be understood that the formula for determining the estimation model is essentially the value of 7 unknowns, on the basis of which the estimation model is determined according to the information to be processed of the predetermined area, and therefore, differences in the predetermined area will result in differences in the estimation model. For example, for study area a, the estimation model determined is a, and for study area B, the estimation model determined is B.
In addition, in order to ensure the accuracy of the estimation model, the embodiment of the application can also check the co-linearity between the variables through a Variance Inflation Factor (VIF), and if the VIF is greater than 7.5, the co-linearity between the variables is shown, and the co-linearity-existing variables are removed. Significance is judged by a significance level P, if P is larger than 0.5, the variable is not significant, and the non-significant variable is removed. And finally, judging the overall accuracy of the regression model through the correlation coefficient R.
As an alternative implementation manner, in order to further improve the accuracy of the estimation model, after the step of S104, the method further includes:
and S1051, determining a residual interpolation model according to the difference value.
And S1052, determining a target model according to the estimation model and the residual interpolation model.
The step of S106 includes:
and determining the periodic average air temperature/periodic average ground temperature of each reference point in the preset area according to the target model.
Optionally, in the embodiment of the present application, a common kriging method is adopted to perform spatial interpolation on the residual error, so as to determine a residual error interpolation model.
Wherein, the residual interpolation model satisfies the formula:
Z ok (T 0 ) Represents T 0 Residual interpolation of the periodic average air temperature/periodic average ground temperature of the location; z (. Epsilon.) T0 ) Represents the cycle average air temperature/cycle average temperature residual value at position i; lambda i Representing a weight coefficient; n represents the number of stations in the neighborhood that have a significant influence on the estimated cycle average air temperature/cycle average ground temperature residual value.
And the periodic average air temperature/periodic average ground temperature residual value represents the difference between the periodic average air temperature/periodic average ground temperature obtained by the sampling point and the periodic average air temperature/periodic average ground temperature at the same position determined by the estimation model. For example, for a certain location, the periodic average air temperature/periodic average ground temperature determined by an auxiliary device such as a weather station is D, and at the same location, after the digital elevation model, the slope, the direction of slope, the longitude and the latitude information are acquired, the periodic average air temperature/periodic average ground temperature F can be determined by using the above estimation model, the values of D and F are not equal, and Z (epsilon) T0 ) I.e. the value representing D-F.
Since the sampling point has a certain influence on the periodic average air temperature/periodic average ground temperature residual value, the weight coefficient determined for each position is not the same.
In order to ensure the precision of residual interpolation, the optimal parameters in the common kriging can be calculated through GS + software, including a model, a variable range, a lump value, a base value and the like, and the interpolation precision is judged through the sum of squares of the residual errors and a correlation coefficient.
On the basis, the target model satisfies the formula:
Z OLSK (T 0 )＝Z OLS (T 0 )+Z ok (T 0 )
wherein Z is OLSK (T 0 ) Representing the object model, Z OLS (T 0 ) Representing an estimation model, Z ok (T 0 ) Representing a residual interpolation model.
After the target model is determined, the estimated periodic average air temperature/periodic average ground temperature value can be subjected to precision evaluation through measured values of meteorological stations, and the indexes are root mean square error and correlation coefficient.
After the target model corresponding to the preset area is determined, that is, each position in the preset area meets the formula of the target model, the average air temperature ^ in the period of each position can be calculated according to the formula
And (5) periodically averaging the earth temperature.
Optionally, the application uses a target model to determine the cycle average air temperature/cycle average ground temperature of each reference point in the preset region. And classifying and drawing the distribution of the permafrost in the research area by utilizing the existing system for classifying the permafrost through the period average air temperature/period average ground temperature value.
As one implementation, S108 includes:
taking a region with the periodic average temperature of less than-5 ℃ or the periodic average ground temperature of-4-0 ℃ as a first permafrost region;
taking the area with the cycle average temperature of-5 to-3 ℃ or the cycle average ground temperature of 0 to 2 ℃ as a second perennial frozen soil area;
taking the area with the periodic average temperature of-3-0 ℃ or the periodic average ground temperature of 3-4 ℃ as a third permafrost area;
and taking the region except the permafrost region in the preset region as a seasonal permafrost region.
Taking the classification system of permafrost region in northeast China as an example, the classification is shown in table one:
watch 1
That is, the preset area can be divided into four types of frozen earth, including: the permafrost regions are distributed in a large or discontinuous way, the permafrost regions are distributed in a large-island way, the island-shaped permafrost regions and the sparse island-shaped permafrost regions are distributed sporadically, and the seasonal permafrost regions are distributed.
Through the carbon reserve influence estimation method, the distribution situation of the permafrost region in the research region can be determined, the determined permafrost region is relatively accurate, and the contribution rate of the change of the permafrost region to the change of the carbon reserve can be determined after the permafrost region is determined.
As an implementation manner, referring to fig. 3, after S108, the step further includes:
s110, interpreting the land utilization types of the preset area, and acquiring the area of each land utilization type;
and S112, determining the carbon reserve according to the area of each soil utilization type in two adjacent periods and a preset carbon reserve estimation model so as to determine the contribution rate of the change of the permafrost region to the change of the carbon reserve.
After the frozen soil is classified into types, the carbon reserves can be determined according to the areas of the land utilization types in two adjacent periods and a preset carbon reserve estimation model, so that the contribution rate of the change of the frozen soil area to the change of the carbon reserves can be determined.
The carbon reserve estimation adopts a carbon reserve estimation module of an InVEST model, and a preset carbon reserve estimation model meets the formula:
wherein, C Total Represents the total carbon reserve of a predetermined region, A i An area representing a land use type i; n is the number of land utilization typesAmount (the amount is 7 in the examples of the present application); c i_above 、C i_below 、C i_dead And C i_soil Respectively representing above-ground carbon density, underground carbon density, dead organic matter and soil carbon density.
The land utilization in the application is divided into 7 types of woodland, grassland, cultivated land, water area, construction land, wetland and unused land. Wherein the forest land is selected from coniferous forest, broad-leaved forest, coniferous and broad-leaved mixed forest, and shrub forest. In the land use type, the carbon reserves of the land types such as grassland and crops are relatively rare and very unstable, and the carbon density values are fixed values. The carbon reservoir of a forest varies significantly as the forest increases in carbon density. By introducing the vegetation map, the forest land classification in the land utilization is reclassified, such as coniferous forest, broad-leaved forest, coniferous and broad-leaved mixed forest, shrubbery and the like. The relation between different forest ages and carbon density, such as linear relation, exponential relation and the like, is established through field investigation or forest age and carbon density investigation data in documents. And further improving a carbon reserve estimation module of the InVEST model, and improving the estimation precision of the carbon reserve by combining forest age data.
It will be appreciated that changes in permafrost regions will result in changes in the area of one or more land use types, and hence in changes in the total amount of carbon reserves in the area under study. Therefore, the total carbon reserve determined by the land utilization type can reflect the influence of permafrost degradation on the change of the total carbon reserve.
The carbon reserve change of the permafrost region is mainly influenced by two factors, namely, the frozen soil change and the vegetation carbon fixation amount. In order to quantitatively evaluate the influence of the permafrost degradation and vegetation carbon sequestration increase on regional carbon reserves, two schemes are designed for evaluation, wherein the first scheme is used for calculating the influence of the permafrost degradation on the carbon reserves by changing land utilization-fixed carbon density, the second scheme is used for calculating the influence of the vegetation carbon sequestration increase on the carbon reserves by changing carbon density-fixed land utilization, and then the contribution rate is used for calculating the contribution of the permafrost degradation and the vegetation carbon sequestration to the carbon reserves.
The contribution rate of the permafrost region change to the carbon reserve change satisfies the formula:
wherein R is l Representing the rate of contribution of permafrost region changes to the change in carbon reserves; r p Representing the contribution rate of vegetation carbon sequestration to the change of the carbon reserves; delta l represents the variation of carbon reserves under the condition of change of permafrost regions, and delta p represents the variation of carbon reserves under the condition of carbon fixation of vegetation. Further, the influence and contribution of the perennial frozen soil degradation on the carbon reserves can be estimated by comparing the two schemes.
For example, in a research area, in 2000, the total amount of carbon reserves determined according to the above carbon reserve estimation model was X, and in 2001, if it is assumed that the change in carbon reserves was affected only by the change in the area of the frozen soil area, the area per soil utilization type is newly determined, and C is assumed i_above 、C i_below 、C i_dead And C i_soil The value is consistent with the value at 2000 and is substituted into the carbon reserve estimation model to determine that the total carbon reserve is Y. On the other hand, if it is assumed that the change in carbon storage in 2001 is only affected by carbon sequestration by the vegetation, the area of each land utilization type is set to be constant and only C of the current year needs to be acquired again when estimating the carbon storage in 2001 i_above 、C i_below 、C i_dead And C i_soil And substituting the carbon storage estimation model to determine that the total carbon storage is Z. Then in this example, Δ l represents the value of Y-X and Δ p represents the value of Z-X, and the effect of permafrost degradation and vegetation carbon sequestration on carbon reserve changes is determined.
Based on the foregoing implementation, please refer to fig. 4, an embodiment of the present application further provides an apparatus 200 for estimating influence of carbon storage, including:
the information acquiring unit 210 is configured to acquire information to be processed in a preset area, where the information to be processed includes cycle average air temperature/cycle average earth temperature, a digital elevation model, a slope, a longitude, and latitude information.
It is understood that the above S102 may be performed by the information obtaining unit 210.
The processing unit 220 is configured to determine a period average air temperature/period average geothermal estimation model according to the information to be processed.
It is understood that the above S104 may be performed by the processing unit 220.
The processing unit 220 is further configured to determine the cycle average air temperature/the cycle average earth temperature of each reference point in the preset region according to the earth temperature estimation model.
It is understood that the above S106 may be executed by the processing unit 220.
The processing unit 220 is further configured to determine the permafrost region in the preset region according to the cycle average air temperature/cycle average ground temperature of each reference point.
It is understood that the above S108 may be performed by the processing unit 220.
It should be noted that each method flow may correspond to one functional module, which is not described herein.
In summary, the embodiment of the present application provides a method, an apparatus, an electronic device, and a storage medium for estimating influence of carbon reserves, where information to be processed in a preset area is first obtained, where the information to be processed includes cycle average air temperature/cycle average ground temperature, a digital elevation model, a slope direction, longitude, and latitude information, then a cycle average air temperature/cycle average ground temperature estimation model is determined according to the information to be processed, then a cycle average air temperature/cycle average ground temperature of each reference point in the preset area is determined according to the estimation model, and then a permafrost area in the preset area is determined according to the cycle average air temperature/cycle average ground temperature of each reference point. According to the method and the device, on the basis of obtaining a plurality of pieces of information to be processed, a relatively accurate air temperature/ground temperature estimation model can be determined, then the air temperatures/ground temperatures of different point positions are determined according to the estimation model, and the relevant models are determined according to the air temperatures/ground temperatures, so that the determined permafrost region is more accurate, and the influence of the change of the permafrost region on the change of the carbon reserve can be accurately determined.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s).
It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.
It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: u disk, removable hard disk, read only memory, random access memory, magnetic or optical disk, etc. for storing program codes.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected by one skilled in the art without departing from the spirit and scope of the invention, as defined in the appended claims.
Claims (7)
1. A carbon storage amount influence estimation method, characterized by comprising:
acquiring information to be processed in a preset area, wherein the information to be processed comprises periodic average air temperature/periodic average ground temperature, a digital elevation model, a slope, a sloping direction, longitude and latitude information;
determining a periodic average air temperature/periodic average earth temperature estimation model according to the information to be processed, wherein the estimation model represents the relation between the digital elevation model, the gradient, the slope direction, the longitude and latitude information of any position in the preset area and the average air temperature/periodic average earth temperature;
determining the periodic average air temperature/periodic average ground temperature of each reference point in the preset area according to the estimation model;
taking a region with the periodic average temperature of less than-5 ℃ or the periodic average ground temperature of-4-0 ℃ as a first perennial frozen soil region;
taking the area with the cycle average temperature of-5 to-3 ℃ or the cycle average ground temperature of 0 to 2 ℃ as a second perennial frozen soil area;
taking the area with the periodic average temperature of-3-0 ℃ or the periodic average ground temperature of 3-4 ℃ as a third permafrost area;
taking the area except the permafrost area in the preset area as a seasonal permafrost area to determine the contribution rate of the permafrost area change to the carbon reserve change, wherein the permafrost area comprises a first permafrost area, a second permafrost area and a third permafrost area;
performing land utilization type interpretation on the preset area, and acquiring the area of each land utilization type;
determining carbon reserves according to the area of each land utilization type in two adjacent periods and a preset carbon reserve estimation model so as to determine the contribution rate of permafrost region changes to the carbon reserve changes;
the contribution rate of the permafrost region change to the carbon reserve change satisfies the formula:
wherein R is l Representing the rate of contribution of permafrost region changes to the change in carbon reserves; r p Representing the contribution rate of vegetation carbon sequestration to the carbon reserve change; delta l represents the variation of carbon reserves under the condition of change of permafrost regions, and delta p represents the variation of carbon reserves under the condition of carbon fixation of vegetation.
2. The carbon storage influence estimation method according to claim 1, wherein the estimation model satisfies a formula:
wherein, T 0 Indicating the position of the sampling point within a predetermined area, Z OLS (T 0 ) Represents T 0 Periodic average air temperature/periodic average ground temperature value of location, delta 0 Denotes intercept, Y m (T 0 ) Represents T 0 Variable Y of position m Wherein the variable Y m Including digital elevation model, slope, longitude andlatitude information, δ m (T 0 ) Regression coefficients representing different variables; x is the number of variables,. Epsilon 0 Representing the residual error.
3. The carbon reserve influence estimation method according to claim 1, wherein after the step of determining an estimation model from the information to be processed, the method further comprises:
determining the difference value between the periodic average air temperature/the periodic average ground temperature in the information to be processed and the periodic average air temperature/the periodic average ground temperature determined by the estimation model at the same position;
determining a residual interpolation model according to the difference value;
determining a target model according to the estimation model and the residual interpolation model;
the step of determining the cycle average air temperature/cycle average ground temperature of each reference point in the preset region according to the estimation model comprises the following steps:
and determining the cycle average air temperature/cycle average ground temperature of each reference point in the preset area according to the target model.
4. The carbon reserve influence estimation method according to claim 3, wherein the residual interpolation model satisfies a formula:
wherein, Z ok (T 0 ) Represents T 0 Residual interpolation of the periodic average air temperature/periodic average ground temperature of the location; z (. Epsilon.) T0 ) Represents the cycle average air temperature/cycle average geothermal residual value at position i; lambda [ alpha ] i Representing a weight coefficient; n represents the number of stations in the neighborhood that have a significant influence on the estimated cycle average air temperature/cycle average ground temperature residual value.
5. A carbon storage amount influence estimation device, characterized by comprising:
the information acquisition unit is used for acquiring information to be processed in a preset area, wherein the information to be processed comprises periodic average air temperature/periodic average earth temperature, a digital elevation model, a slope direction, longitude and latitude information;
the processing unit is used for determining a periodic average air temperature/periodic average earth temperature estimation model according to the information to be processed, wherein the estimation model is used for determining a digital elevation model, a gradient, a slope direction, a longitude and an average air temperature/periodic average earth temperature corresponding to latitude information at any position in the preset area;
the processing unit is further used for determining the periodic average air temperature/periodic average ground temperature of each reference point in the preset area according to the ground temperature estimation model;
a processing unit further to:
taking a region with the periodic average temperature of less than-5 ℃ or the periodic average ground temperature of-4-0 ℃ as a first perennial frozen soil region;
taking the area with the periodic average temperature of-5 to-3 ℃ or the periodic average ground temperature of 0 to 2 ℃ as a second perennial frozen soil area;
taking the area with the periodic average temperature of-3-0 ℃ or the periodic average ground temperature of 3-4 ℃ as a third permafrost area;
taking the area except the permafrost area in the preset area as a seasonal permafrost area to determine the contribution rate of the permafrost area change to the carbon reserve change, wherein the permafrost area comprises a first permafrost area, a second permafrost area and a third permafrost area;
a processing unit further to:
interpreting the land utilization type of the preset area, and acquiring the area of each land utilization type;
determining carbon reserves according to the area of each land utilization type in two adjacent periods and a preset carbon reserve estimation model so as to determine the contribution rate of permafrost region changes to the carbon reserve changes;
the contribution rate of the permafrost region change to the carbon reserve change satisfies the formula:
wherein R is l Representing the rate of contribution of permafrost region changes to the change in carbon reserves; r is p Representing the contribution rate of vegetation carbon sequestration to the change of the carbon reserves; delta l represents the variation of carbon reserves under the condition of perennial frozen soil area variation, and delta p represents the variation of carbon reserves under the condition of vegetation carbon sequestration.
6. An electronic device, comprising:
a memory for storing one or more programs;
a processor;
the one or more programs, when executed by the processor, implement the method of any of claims 1-4.
7. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-4.
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