CN113850706A

CN113850706A - Regional carbon measuring and calculating method, display platform, cloud server and storage medium

Info

Publication number: CN113850706A
Application number: CN202111448676.3A
Authority: CN
Inventors: 雷宗雄; 周文闻; 肖镭; 冯烈丹; 邱剑; 李绪焜
Original assignee: Alibaba Cloud Computing Ltd
Current assignee: Alibaba Cloud Computing Ltd
Priority date: 2021-11-30
Filing date: 2021-11-30
Publication date: 2021-12-28

Abstract

The embodiment of the application provides a regional carbon measuring and calculating method, a display platform, a cloud server and a storage medium, wherein the measuring and calculating method comprises the following steps: acquiring high-precision map data of an area, and determining a plurality of plots with different plot types in the area, and a plot main body and a plot edge of each plot from the high-precision map data; the edge of the land is obtained after extending a set distance from the boundary of the land to the inside and the outside of the land; determining boundary areas of the plots with different plot types at the plot edges to obtain a plurality of plot edge boundary areas; determining the carbon absorption capacity of each land body and the carbon absorption capacity of the boundary area of the edge of each land; and determining the carbon absorption capacity of the region according to the carbon absorption capacity of the main body of each land and the carbon absorption capacity of the boundary area of the edge of each land. The embodiment of the application can at least realize accurate and integral carbon absorption measurement and calculation of the area, provide accurate and integral carbon absorption capacity of the area and provide guidance for activity planning of the area.

Description

Regional carbon measuring and calculating method, display platform, cloud server and storage medium

Technical Field

The embodiment of the application relates to the technical field of data processing, in particular to a regional carbon measuring and calculating method, a display platform, a cloud server and a storage medium.

Background

In order to achieve the dual carbon targets of carbon neutralization and carbon peak reaching, planning activities are needed in regions of cities, counties and the like from the carbon emission and carbon absorption conditions of the regions, and the planning activities involve carbon measurement and calculation of the regions of the cities, the counties and the like, such as carbon absorption capacity, carbon emission amount and the like of the regions. The carbon absorption capacity of the area refers to the capacity of the area to absorb the amount of carbon dioxide through means such as afforestation, vegetation restoration and the like, and the carbon absorption capacity is also called carbon sink capacity; the carbon emission of a region refers to the amount of carbon dioxide emitted by the region.

The method is very important to provide the whole and accurate carbon measurement and calculation results for accurately guiding the activity planning of the regions such as cities and counties, so that how to accurately and integrally measure and calculate the carbon of the regions becomes a technical problem which needs to be solved by the technical staff in the field.

Disclosure of Invention

In view of this, the embodiment of the present application provides a regional carbon measurement and calculation method, a display platform, a cloud server, and a storage medium, which implement accurate and overall carbon absorption measurement and calculation on a region at least when measuring and calculating the carbon absorption capacity of the region, so as to provide accurate and overall carbon absorption capacity of the region and provide accurate guidance for activity planning of the region.

In order to achieve the above object, the embodiments of the present application provide the following technical solutions.

In a first aspect, an embodiment of the present application provides a regional carbon estimation method, including:

acquiring high-precision map data of a region, and determining a plurality of plots with different plot types in the region, and a plot main body and a plot edge of each plot from the high-precision map data; the edge of the land is obtained after the boundary of the land extends a set distance to the inside and the outside of the land;

determining boundary areas of the plots with different plot types at the plot edges to obtain a plurality of plot edge boundary areas;

determining the carbon absorption capacity of each land body and the carbon absorption capacity of the boundary area of the edge of each land;

and determining the carbon absorption capacity of the region according to the carbon absorption capacity of the main body of each land and the carbon absorption capacity of the boundary area of the edge of each land.

In a second aspect, an embodiment of the present application provides a display platform, where the display platform displays high-precision map data of an area, and the high-precision map data displays carbon absorption capacity of the area;

wherein the high-precision map data includes a plurality of plots of different plot types in the region, the plots including plot bodies and plot edges; the edge of the land is obtained after the boundary of the land extends a set distance to the inside and the outside of the land; the carbon absorption capacity of the region is determined according to the carbon absorption capacity of each block body and the carbon absorption capacity of each block edge boundary area, and the block edge boundary areas are boundary areas of blocks of different block types on the block edges.

In a third aspect, an embodiment of the present application provides a cloud server, including at least one memory and at least one processor; the memory stores one or more computer-executable instructions that are invoked by the processor to perform the regional carbon estimation method as described in the first aspect above.

In a fourth aspect, embodiments of the present application provide a storage medium storing one or more computer-executable instructions that, when executed, implement the regional carbon estimation method according to the first aspect.

In a fifth aspect, an embodiment of the present application provides a computer program, which when executed, implements the regional carbon estimation method according to the first aspect.

According to the regional carbon measuring and calculating method, high-precision map data of a region can be obtained, and by means of the high-precision map data, the regional distribution of the region needing carbon measuring and calculating can be accurately determined, each region in the region and the region type of each region can be accurately determined, and the region can be divided into a region main body and a region edge; meanwhile, the carbon absorption radiation condition at the boundary of the land is considered at the edge of the land, and the carbon absorption radiation condition is obtained after the boundary of the land extends to the inside and the outside of the land for a set distance; the method and the device for measuring the carbon absorption radiation of the regional area based on the high-precision map data have the advantages that different types of plots and plot main bodies of the plots are divided, and the plot edges of the plots, which are subjected to carbon absorption radiation, are considered, so that a basis can be provided for subsequent accurate and integral carbon measurement and calculation of the regional area. When the carbon absorption capacity of the area is measured and calculated, the carbon absorption capacity of the area can be measured and calculated by the embodiment of the application and divided into the carbon absorption capacity measurement and calculation of the main body of the area and the edge of the area, and the carbon absorption conditions of the boundaries of the areas at the edges of different types of areas are different, so that the embodiment of the application can measure and calculate the carbon absorption capacity of the edges of the areas through measuring and calculating the carbon absorption capacity of the areas at the boundary regions of the edges of the areas of different types of areas, and the accurate carbon absorption capacity measurement and calculation of the edges of the areas are not performed from the angle of the edges of the areas, so that a foundation is provided for accurately measuring and calculating the carbon absorption capacity of the boundaries between the areas of different types of areas. Based on the above, the boundary area of the plots with different plot types at the plot edge can be determined through the high-precision map data, so as to obtain a plurality of plot edge boundary areas; further determining the carbon absorption capacity of each land body and the carbon absorption capacity of the boundary area of each land edge; and determining the carbon absorption capacity of the region according to the carbon absorption capacity of the main body of each land and the carbon absorption capacity of the boundary of the edge of each land.

Therefore, the method and the device can accurately determine the land distribution of the region through the high-precision map data, divide the land into the land main body and the land edge, and accurately measure and calculate the carbon absorption capacity of the land main body and the carbon absorption capacity of the land edge part to achieve overall and comprehensive measurement and calculation of the carbon absorption capacity of the land. Meanwhile, when the carbon absorption capacity of the edge part of the land parcel is measured and calculated, the embodiment of the application considers the carbon absorption conditions of mutual influence among land parcels of different types, and realizes accurate carbon absorption capacity measurement and calculation of the edge of the land parcel by determining the boundary area of the land parcel of different land parcels at the edge of the land parcel and further measuring and calculating the carbon absorption capacity of the boundary area of the edge of the land parcel. Therefore, the embodiment of the application can at least realize accurate and integral carbon absorption measurement and calculation of the area, provide accurate and integral carbon absorption capacity of the area and provide accurate guidance for activity planning of the area.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.

Fig. 1 is a flowchart of a regional carbon estimation method according to an embodiment of the present application.

Fig. 2 is a schematic view of the distribution of plots in a region.

Fig. 3 is an exemplary diagram of a land border area.

Fig. 4 is a flowchart of a method for determining carbon absorption capacity of a body of a plot according to an embodiment of the present application.

Fig. 5 is a flowchart of a method for determining a carbon absorption capability of a boundary area of a block edge according to an embodiment of the present disclosure.

Fig. 6 is another flowchart of a regional carbon estimation method according to an embodiment of the present disclosure.

Fig. 7 is a flowchart of a display method according to an embodiment of the present application.

FIG. 8 is a schematic diagram showing an interface.

Fig. 9 is a block diagram of a regional carbon estimation device according to an embodiment of the present application.

Fig. 10 is a block diagram of a cloud server.

Detailed Description

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 only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

At present, carbon measurement and calculation in regions mainly depend on statistical data collected by urban planning bureaus and forestry bureaus, and the statistical data is mainly gathered based on manual collection. For example, carbon emission data of carbon emission subjects such as enterprises and communities in a region are manually collected and summarized to measure the carbon emission of the region, and vegetation amount in the region is manually collected and summarized to measure the carbon absorption capacity. However, the period for manually collecting and summarizing statistical data is long, which only can be used for regional seasonal or annual carbon measurement and calculation, and the requirement for regional efficient carbon measurement and calculation is difficult to meet. Meanwhile, the problem of data entry errors is inevitable when the statistical data are manually collected and summarized, the problem of incompleteness due to the fact that the data cannot cover the whole area is caused, and the accurate and integral carbon measurement and calculation of the area cannot be carried out.

Based on this, the embodiment of the present application provides a novel regional carbon measurement and calculation scheme, and at least when measuring and calculating the carbon absorption capacity of a region, by combining with high-precision map data of the region, under the condition that each block of the region is divided into a block main body and a block edge, the carbon absorption capacity is measured and calculated for the block main body and the edge portion of each block, so as to realize accurate and overall carbon absorption capacity measurement and calculation for the region, thereby providing accurate and overall carbon absorption capacity of the region, and providing accurate guidance for activity planning of the region.

Fig. 1 schematically shows an alternative flowchart of a regional carbon estimation method provided in an embodiment of the present application. The method flow can be implemented by an electronic device with data processing capability, and as an optional implementation, the electronic device can be a cloud server in the case of performing data processing operation by using cloud computing. Referring to fig. 1, the method flow may include the following steps.

In step S110, high-precision map data of a region is acquired, and a plurality of plots of different plot types in the region, and a plot body and a plot edge of each plot are determined from the high-precision map data.

The area where the carbon measurement and calculation is provided in the embodiment of the present application may be an administrative area such as a city, a county, or the like, or may also be an area within a specified certain geographic range, which is not limited in the embodiment of the present application. According to the method and the device, high-precision map data of the area can be constructed for the area needing carbon measurement and calculation.

In some embodiments, the high-precision map data may be a multi-source remote sensing map, which is obtained by fusing multispectral data of an area and a remote sensing image. It should be noted that the multispectral data of the region can be acquired by spectrum acquisition by a multispectral sensor of a satellite, and generally includes 8 spectra: panchromatic, red, green, blue, yellow, near infrared, coast, red edge, and the like. However, the multispectral data of a region does not have high resolution, the accuracy is generally between 500 meters and 2 kilometers, and the factors such as parks, traffic lines and the like in the region cannot be accurately expressed, so that the comprehensive and accurate land parcel distribution of the region cannot be accurately expressed by simply using the multispectral data of the region. Based on this, in the embodiments of the present application, a Remote Sensing Image (RS) of the region is introduced based on the multispectral data of the region, and the multispectral data of the region and the Remote Sensing Image are fused to obtain high-precision map data of the region, where the high-precision map data can accurately express elements such as a garden and a traffic route in the region, and the high-precision map may have a high precision of 2 meters to 10 meters, for example. The remote sensing image of the area is a film or a photo for recording the size of electromagnetic waves of various ground objects in the area, and is mainly divided into an aerial photo and a satellite photo.

In other embodiments, the high-precision map data of the area may also be obtained in other manners, which is not limited to the manner of fusing multispectral data and remote sensing images of the area, as long as the obtained map data of the area can meet a specific precision requirement, and the precision requirement can accurately express the overall and accurate parcel distribution of the area, for example, the precision of the obtained map data is between 2 meters and 10 meters, and the obtained map data can be regarded as the high-precision map data of the area. As an alternative implementation, high-precision map data for a region may also be obtained from a map provider.

Based on the high-precision map data of the region, the method and the device for determining the region can determine the regions of different region types in the region, and the number of the regions of one region type is at least one, so that a plurality of regions of different region types in the region are obtained from the high-precision map data. In one example, the parcel type determined from the high accuracy map data may include: residential areas, garden areas, traffic networks, agricultural land, forests, greenhouses, rivers, and the like. In some embodiments, a parcel may comprise a parcel body and a parcel edge; for a land parcel, the embodiments of the present application may extend the boundary of the land parcel by a set distance both inside and outside the land parcel, and then use the extended boundary as the land parcel edge of the land parcel, and the land parcel body may be an area of the land parcel except the land parcel edge.

As an alternative implementation, the embodiment of the application can identify the outline of each land in the high-precision map data; further, for a land parcel, identifying the boundary of the land parcel based on the contour of the land parcel; after the boundary of the land parcel extends a set distance to the inside and the outside of the land parcel, the land parcel edge of the land parcel is obtained, and the area except the land parcel edge in the land parcel is used as a land parcel main body.

Fig. 2 schematically shows a plot distribution of a region. As shown in FIG. 2, in a simple example, the types of plots in a region may be divided into residential areas, agricultural lands, and forests; specifically, there are 3

residential area plots

211, 212, and 213, 2 agricultural land plots 221 and 222, and 1 forest plot 231 in fig. 2. After recognizing each land (211, 212, 213, 221, 222 and 231) and the land type of each land (for example, 211, 212 and 213 are residential areas, 221 and 222 are agricultural lands, and 231 is a forest) from the high-precision map data of the region, the embodiment of the present application can recognize the contour of each land, determine the boundary of each land from the contour of each land, and extend the boundary of each land to the inside and the outside of the land by a set distance to serve as the edge of the land; and taking the areas except the edges of the plots in each plot as plot main bodies of the plots respectively. As shown in fig. 2, after identifying the boundary 201 of the residential area block 211, the boundary 201 extends a set distance into the block 211 and simultaneously extends a set distance out of the block 211, thereby obtaining an extended boundary 202, the extended boundary 202 may serve as a block edge of the block 211, and an area except the block edge in the block 211 serves as a block main body. The boundaries of the other plots in fig. 2 may be extended similarly to obtain the plot edges of the other plots, and will not be described further herein.

In the measurement of the carbon absorption capacity of the land, the boundary of the land has a certain carbon absorption radiation capacity for both the inside and the outside of the land, and therefore, a certain carbon absorption measurement error exists simply by using the boundary of the land as the edge of the land. Based on the above, the boundary of the land parcel can be extended to the inside and the outside of the land parcel by a set distance, and the extended boundary is used as the land parcel edge of the land parcel, so that the carbon absorption radiation condition of the land parcel boundary is considered in the subsequent estimation of the carbon absorption capacity of the land parcel edge, and the possibility is provided for accurately estimating the carbon absorption capacity of the land parcel. As an alternative implementation, the set distance extended by the boundary of the land parcel may be, for example, 3 kilometers, and may be specifically set according to an actual situation, which is not limited in this application embodiment.

In step S111, boundary areas of the plots of different plot types at the plot edges are determined to obtain a plurality of plot edge boundary areas.

After determining a plurality of plots with different plot types, and a plot main body and a plot edge of each plot from high-precision map data of a region, the embodiment of the application can further determine the boundary area of the plots with different plot types at the plot edge, so as to obtain a plurality of plot edge boundary areas. As an optional implementation, a boundary region of the two adjacent plots of different plot types at the plot edge can be obtained, and thus a plurality of plot edge boundary regions can be obtained by the boundary of two adjacent plots of different plot types at the plot edge.

For ease of understanding, fig. 3 schematically illustrates an example view of a land edge boundary region. As shown in fig. 3, the

plots

310 and 320 are of different types, for example, plot 310 is an agricultural plot and plot 320 is a forest plot. In fig. 3, the land 310 is adjacent to the land 320, and the boundary 311 is the land edge of the land 310 and is extended from the boundary 321 of the land 310; boundary range 321 is the parcel edge of parcel 320, extended by boundary 322 of parcel 320. The boundary area 01 (shown by the dashed line in the figure) of the block edges 311 and 321 of the

adjacent blocks

310 and 320 with different block types can be used as the block edge boundary area of the

blocks

310 and 320. In an exemplary manner shown in fig. 3, in the embodiment of the present application, a parcel edge boundary area may be determined at a parcel edge boundary of any two adjacent parcels of different parcel types, so as to determine a plurality of parcel edge boundary areas from high-precision map data.

In step S112, the carbon absorption capacity of each parcel body, and the carbon absorption capacity of each parcel edge boundary region are determined.

In step S113, the carbon absorption capacity of the area is determined based on the carbon absorption capacity of each parcel body and the carbon absorption capacity of each parcel edge boundary region.

The carbon absorption capacity measurement and calculation of the region can be divided into carbon absorption capacity measurement and calculation of the land body and carbon absorption capacity measurement and calculation of the boundary area of the land edge. Therefore, the embodiment of the application can respectively determine the carbon absorption capacity of each plot main body and the carbon absorption capacity of each plot edge boundary area after determining the plot main body of each plot from the high-precision map data and determining the plot edge boundary area of the adjacent plots of different plot types at the plot edge boundary, thereby combining the carbon absorption capacity of each plot main body and the carbon absorption capacity of each plot edge boundary area to obtain the carbon absorption capacity of the area. For example, the carbon absorption capacity of each land body can be added to obtain the carbon absorption capacity of all land bodies, and the carbon absorption capacity of each land edge boundary area can be added to obtain the carbon absorption capacity of all land edge boundary areas; therefore, the carbon absorption capacity of all the land bulk bodies and the carbon absorption capacity of all the land edge boundary areas are added to obtain the carbon absorption capacity of the whole area.

In some embodiments, for a parcel body, embodiments of the present application may determine the carbon absorption capacity of the parcel body based on the parcel type of the parcel body and the parcel environmental information of the parcel body for carbon absorption. The plot environment information is environment information such as a ground surface and air used for carbon absorption of the plot, for example, carbon molecule content, water content, vegetation type, and the like. As an alternative implementation, the present embodiments may determine plot environmental information for each plot principal from the multi-spectral data.

In some embodiments, for a boundary area of a parcel, the embodiment of the present application may determine the carbon absorption capacity of the boundary area of the parcel based on a combination of types of parcels corresponding to the boundary area of the parcel and environmental information of the parcel used for carbon absorption of the boundary area of the parcel. The combination of land parcel types corresponding to the land parcel edge boundary area can be considered as follows: a combination of the plot types of two different types of adjacent plots of the plot edge boundary area is obtained. For example, for a land parcel edge boundary area obtained by the boundary of a forest land parcel and an agricultural land parcel at the land parcel edge, the combination of land parcel types corresponding to the land parcel edge boundary area is the combination of forest land and agricultural land. As an alternative implementation, the present application embodiment may determine the parcel environmental information of each parcel edge boundary region from the multi-spectral data.

Therefore, the method and the device can accurately determine the land distribution of the region through the high-precision map data, divide the land into the land main body and the land edge, and accurately measure and calculate the carbon absorption capacity of the land main body and the carbon absorption capacity of the land edge part to achieve overall and comprehensive measurement and calculation of the carbon absorption capacity of the land. Meanwhile, when the carbon absorption capacity of the edge part of the land parcel is measured and calculated, the embodiment of the application considers the carbon absorption conditions of mutual influence among land parcels of different types, and realizes accurate carbon absorption capacity measurement and calculation of the edge of the land parcel by determining the boundary area of the land parcel of different land parcels at the edge of the land parcel and further measuring and calculating the carbon absorption capacity of the boundary area of the edge of the land parcel. Therefore, the embodiment of the application can realize accurate and integral carbon absorption measurement and calculation of the area, provide accurate and integral carbon absorption capacity of the area and provide accurate guidance for activity planning of the area.

As an alternative implementation, fig. 4 is a flowchart illustrating an alternative method for determining the carbon absorption capacity of a body of a plot provided in an embodiment of the present application. As shown in fig. 4, the method flow may include the following steps.

In step S410, the plot environmental information of each plot body for carbon absorption is determined.

After the plot main bodies of the respective plots are determined from the high-precision map data, the embodiment of the application can determine the plot environment information for carbon absorption in the respective plot main bodies, for example, determine the plot environment information such as carbon molecule content, water content, vegetation types and the like in the respective plots. In some embodiments, after determining the respective parcel body, embodiments of the present application may determine parcel environmental information, such as carbon molecule content, water content, and vegetation type, for the respective parcel body based on the multispectral data.

The land environmental information is environmental information such as the land surface and the air used for carbon absorption of the land, and is not limited to the carbon molecule content, the water content, the vegetation type, and the like, and any air factor and land factor related to carbon absorption in the land can be used as the land environmental information used for carbon absorption in the embodiments of the present application.

In step S411, the carbon absorption capacity per unit area of each land body is determined based on the land environment information and the land type of each land body.

In some embodiments, for a land body, the embodiments of the present application may determine the carbon absorption capacity per unit area of the land body according to the land environment information and the land type of the land body. For example, the carbon absorption capacity per square kilometer of the body of the plot is determined.

As an alternative implementation, the embodiment of the present application may train a first carbon absorption factor model in advance, where the first carbon absorption factor model has a function of determining the carbon absorption capacity per unit area of the parcel body based on at least parcel environment information and a parcel type of the parcel body. For example, if the first carbon absorption factor model is inputted with at least the carbon molecule content, water content, and the type of the land, such as the type of the vegetation and the land environment information, the first carbon absorption factor model can output the carbon absorption capacity per unit area of the land.

Therefore, for each land parcel body, the embodiment of the present application may input at least the land parcel environment information and the land parcel type of each land parcel body into the first carbon absorption factor model, respectively, and obtain the carbon absorption capacity per unit area of each land parcel body output by the first carbon absorption factor model, respectively (for example, the first carbon absorption factor model may output the carbon absorption capacity per square kilometer of each land parcel body).

In one example, assuming that the first carbon absorption factor model is denoted as f, the region has K parcel bodies therein, and i denotes the ith parcel body, e denotes the parcel type of the ith parcel body, then f_e，iCan represent the carbon absorption capacity per unit area of the ith plot body under the plot type e. For example, the first carbon absorption factor model f is input with the plot environment information of the ith plot body and the plot type e of the ith plot body, and the carbon absorption capacity per unit area of the ith plot body in the plot type e output by the first carbon absorption factor model f is obtained. The plot environment information and the plot types of the K plot main bodies in the area are respectively input into the first carbon absorption factor model f, and then the carbon absorption capacity per unit area of each plot main body can be obtained.

In some embodiments, the first carbon absorption factor model f may be a carbon absorption model for different types of plots for estimating the amount of fixed carbon per unit area for each type of plot. In the embodiment of the application, the training feature vectors of a plurality of first-class regions (first-class regions such as city-level regions) can be obtained through database sources such as a statistics bureau, an environmental protection bureau, a city planning bureau and the like, and the training feature vector of one first-class region may include vectorization of at least one of the following information: the industrial type of the first type of region, the area ratio of each region type in the first type of region (for example, the area ratio of various region types such as forest, water area, farmland, urban land and the like in the region), the population density, the region environment information and the like. And training a first carbon absorption factor model by taking the carbon dioxide reduction of each first type region summarized by the data as a linear fitting target and by a logistic regression reasoning mode based on the training feature vectors of the plurality of first type regions.

As an alternative example, the first carbon absorption factor model may be expressed as:

；

when the carbon absorption capacity of the land bulk is determined by using the first carbon absorption factor model, e represents the land bulk type, x represents the training feature vector, and T represents the training weight of the training feature vector for the land bulk. The weight of each training feature vector can be preset, for example, the training weight of an industry type, the training weight of an area ratio of each block type, the training weight of population density, and the training weight of block environment information can be preset.θFor example, the preset training weight in the embodiment of the present application may continuously iterate the value of T in the fitting training, so that the training weight can stably express the mapping relationship between the training feature vector x and the carbon absorption amount.

In step S412, the carbon absorption capacity of each land body is determined based on the carbon absorption capacity per unit area of each land body and the area of each land body.

In some embodiments, after obtaining the carbon absorption capacity per unit area of each land body, the embodiments of the present application may multiply the carbon absorption capacity per unit area of each land body by the area of the corresponding land body to obtain the carbon absorption capacity of each land body. As an alternative implementation, for a land bulk, the embodiment of the present application may multiply the carbon absorption capacity per unit area of the land bulk by the area of the land bulk to obtain the carbon absorption capacity of the land bulk.

In one example, let f be the carbon absorption capacity per unit area of the ith plot body in the plot type e to which it belongs_e，iThe area of the ith land mass body is s_iThen, the carbon absorption capacity of the ith plot body can be expressed as: f. of_e，i×s_i。

Further, the carbon absorption capacity of all the land bodies in the area can be obtained by adding the carbon absorption capacities of all the land bodies in the area. For example, if a region has K land bodies, the carbon absorption capacity of all the land bodies in the region can be expressed as:

。

as an alternative implementation, fig. 5 is a flowchart illustrating an alternative method for determining the carbon absorption capacity of a boundary area of a block edge according to an embodiment of the present disclosure. As shown in fig. 5, the method flow may include the following steps.

In step S510, the plot environment information for carbon absorption of each plot edge boundary region is determined.

After determining each block edge boundary area from the high-precision map data, the embodiment of the present application may determine block environment information that each block edge boundary area is used for carbon absorption, for example, determine block environment information such as carbon molecule content, water content, and vegetation type of each block edge boundary area.

In some embodiments, after determining each plot edge boundary region, embodiments of the present application may determine plot environmental information, such as carbon molecule content, water content, and vegetation type, for each plot edge boundary region based on the multispectral data.

In step S511, the carbon absorption capacity per unit area of each parcel edge boundary area is determined according to the parcel type combination and parcel environmental information corresponding to each parcel edge boundary area.

In some embodiments, for a parcel edge boundary area, the embodiments of the present application may determine the carbon absorption capacity per unit area of the parcel edge boundary area according to a parcel type combination corresponding to the parcel edge boundary area and parcel environment information of the parcel edge boundary area. For example, the carbon absorption capacity per square kilometer of the plot edge boundary area is determined.

As an optional implementation, in the embodiment of the present application, a second carbon absorption factor model may be trained in advance, where the second carbon absorption factor model at least has a function of determining a carbon absorption capacity per unit area of a boundary area of a parcel based on parcel environment information and parcel type combinations of the boundary area of the parcel. For example, if the second carbon absorption factor model is input by combining at least the land type corresponding to the land edge boundary area and land environment information such as carbon molecule content, water content, and vegetation type, the second carbon absorption factor model can output the carbon absorption capacity per unit area of the land edge boundary area.

Therefore, for each parcel body, the embodiment of the present application may at least combine the parcel types and the parcel environment information of each parcel edge boundary area, and input the second carbon absorption factor model respectively, to obtain the unit area carbon absorption capacity of each parcel edge boundary area output by the second carbon absorption factor model respectively (for example, the first carbon absorption factor model may output the carbon absorption capacity per square kilometer of each parcel edge boundary area).

In one example, assuming that the second carbon absorption factor model is denoted as F, and there are M parcel edge boundary regions in the region, and j denotes the jth parcel edge boundary region, and n denotes a parcel type combination of the jth parcel edge boundary region, then F is_n，jCan represent the carbon absorption capacity per unit area of the jth plot edge boundary area in the plot type combination n. For example, at least the parcel environment information of the jth parcel edge boundary area and the parcel type combination n of the jth parcel edge boundary area are input into the second carbon absorption factor model F, and the carbon absorption capacity of the jth parcel edge boundary area output by the second carbon absorption factor model F in the unit area of the parcel type combination n to which the jth parcel edge boundary area belongs is obtained. And combining the plot environment information and the plot types of the M plot edge boundary areas in the region, and respectively inputting the second carbon absorption factor model F to obtain the carbon absorption capacity per unit area of each plot edge boundary area.

In some embodiments, the second carbon absorption factor model F may be a carbon absorption model for different types of combined plots for estimating the amount of fixed carbon per unit area at the junction for the different types of plots. The training of the second carbon absorption factor model F may be similar to the first carbon absorption factor model F, except that: the training of the first carbon absorption factor model is realized based on the training characteristic vector of the first type region and the carbon dioxide reduction of the first type region, and when the training of the second carbon absorption factor model is realized, the training of the second carbon absorption factor model is realized based on the training characteristic vector of the second type region and the carbon dioxide reduction of the second type region; the administrative level of the second type of region may be lower than that of the first type of region, for example, the first type of region is at the city level, the second type of region is at the county level, and the second type of region is in the parallel geographical zone of the set distance at the junction of different types of plots; for example, the second type of area is in a parallel geographic zone at the junction of the different types of plots, and the distance from the junction of the different types of plots is within a set distance.

As an optional implementation, in the embodiment of the present application, training feature vectors of a plurality of second-type regions may be obtained, and a training feature vector of a second-type region may include vectorization of the following information: the industrial type of the second type of region, the area ratio of each plot type in the second type of region (e.g., the area ratio of various plot types in the region, such as forest, water, farmland, urban land, etc.), population density, plot environment information, etc. And training a second carbon absorption factor model by taking the carbon dioxide reduction of each second region summarized by the data as a linear fitting target and adopting a logistic regression reasoning mode based on the training feature vectors of the plurality of second regions. The second type of area can be positioned in parallel geographical zones with set distance at the junctions of different types of plots

That is, in a possible implementation, the second carbon absorption factor model F may be trained by a logistic regression model in the same way, the model training is equivalent to the first carbon absorption factor model F, but the second carbon absorption factor model F is a linear fitting target based on the carbon dioxide reduction of a second type of area (e.g., county level grade) with finer granularity, and the position of the selected second type of area is within a parallel geographical zone of a set distance at a junction of different types of plots, for example, the second type of area is within a parallel geographical zone within 3 kilometers of a junction of different types of plots.

In step S512, the carbon absorption capacity of each land edge boundary area is determined according to the carbon absorption capacity per unit area of each land edge boundary area and the area of each land edge boundary area.

In some embodiments, after obtaining the carbon absorption capacity per unit area of each block edge boundary area, the carbon absorption capacity per unit area of each block edge boundary area may be multiplied by the area of the corresponding block edge boundary area to obtain the carbon absorption capacity of each block edge boundary area. As an optional implementation, for an edge boundary area of a land parcel, in the embodiment of the present application, the carbon absorption capacity per unit area of the edge boundary area of the land parcel may be multiplied by the area of the edge boundary area of the land parcel to obtain the carbon absorption capacity of the edge boundary area of the land parcel.

In one example, let f be the carbon absorption capacity per unit area of the jth parcel edge boundary region in parcel type combination n_n，jThe area of the boundary region of the jth land parcel edge is E_jThen, the carbon absorption capacity of the jth parcel edge boundary region can be expressed as: f_n，j×E_j。

Further, the carbon absorption capacity of all the boundary areas of the edges of the land can be added to obtain the carbon absorption capacity of all the boundary areas of the land. For example, if a region has M block edge boundary regions, the carbon absorption capacity of all block edge boundary regions in the region can be expressed as:

。

further, the embodiment of the application can determine the overall carbon absorption capacity of the area by combining the carbon absorption capacity of the main body of each land and the carbon absorption capacity of the boundary of the edge of each land. For example, the carbon absorption capacity of the area is obtained by adding the carbon absorption capacity of the main body of all the plots in the area to the carbon absorption capacity of the boundary area of the edge of all the plots. In one example, let the carbon absorption capacity of the region be E_carb-takeThen E is_carb-takeCan be expressed as:

。

the regional carbon measuring and calculating method provided by the embodiment of the application can be used for realizing macroscopic, integral and accurate carbon absorption capacity analysis on the region. When the carbon absorption capacity of the region is measured and calculated, the same type of land body is used for realizing that the macroscopic carbon absorption capacity tends to be consistent through ecological internal adjustment, and the carbon absorption capacity changes more complexly at the edge junction of different types of land blocks, particularly the edge junction of an urban land block and a forest land block, so that the embodiment of the application distinguishes the land body and the land block edge junction area in the region in detail and accurately on the basis of high-precision map data of the region. Based on the above, the embodiment of the application determines the carbon absorption capacity per unit area of each land mass in cooperation with the provided first carbon absorption factor model for evaluating the carbon fixation amount per unit area of each type of land mass, and determines the carbon absorption capacity per unit area of each land mass edge boundary area in cooperation with the provided second carbon absorption factor model for evaluating the carbon fixation amount per unit area of different types of land masses at the boundary. Thus determining the carbon absorption capacity of each land body by combining the area of each land body and the carbon absorption capacity of each unit area; and determining the carbon absorption capacity of the boundary area of each land block edge by combining the area of the boundary area of each land block edge and the carbon absorption capacity of the unit area. And then the carbon absorption capacity of the region is determined by combining the carbon absorption capacity of each land body and the carbon absorption capacity of the boundary area of each land edge, so that accurate and integral carbon absorption measurement and calculation of the region are realized, accurate and integral carbon absorption capacity of the region is provided, and accurate guidance is provided for activity planning of the region. Further, the carbon absorption capacity of the boundary area of the land bulk and the land bulk edge is determined, and the used land bulk environment information can be determined based on satellite remote sensing data (for example, the land bulk environment information is determined based on multispectral data), so that manual intervention is avoided, and the problem of inaccurate measurement and calculation caused by data falsification or recording errors is avoided.

In further embodiments, the present application provides for the estimation of carbon emissions from a region. Fig. 6 shows another alternative flowchart of a regional carbon estimation method provided in an embodiment of the present application. Referring to fig. 6, the method flow may include the following steps.

In step S610, carbon emission data collected by sensors disposed in a body of the land, the sensors being disposed at carbon emission observation points of the body of the land, is acquired.

The embodiment of the application can determine carbon emission observation points in a plurality of land bodies of a region, and arrange sensors at the carbon emission observation points to collect carbon emission data. In some embodiments, based on high-precision map data of a region, embodiments of the present application may determine a distribution of the region and an area where a body of the region is carbon-emitting, thereby selecting an observation point and arranging sensors in the area where the body of the region is carbon-emitting. For example, according to the embodiment of the application, the information of the land parcels such as traffic networks, parks, residents, agriculture and the like in the region can be determined based on high-precision map data, observation points are selected and the sensors are deployed and installed according to the main bodies of the land parcels such as traffic lines and industrial parks, so that the carbon emission data can be acquired. In some embodiments, the sensor may support the collection of information such as oxygen amount, sulfur dioxide amount, carbon dioxide amount, moisture amount, wind direction, etc. at the observation point, and collect data on a minute scale as well as trends in the data. And then based on the carbon emission data that the sensor that arranges in a plurality of landmass main parts gathered, this application embodiment can realize the observation of regional main carbon emission and trend of change.

In step S611, the carbon emission amount per unit area of each land body under the type of the land body to which it belongs is deduced from the land type of the land body and the carbon emission data collected by the sensors arranged in the land body.

For a land body, after acquiring carbon emission data collected by sensors arranged in the land body, the embodiment of the present application may deduce the amount of carbon emission per unit area of the land body in the corresponding land type based on the land type of the land body and the carbon emission data collected by the sensors arranged in the land body. Thus, the above deduction is performed for each plot in the area, and the unit area carbon emission amount of each plot main body in the area under the type of the plot to which it belongs can be deduced.

In some embodiments, for a body of land, the present application may deduce the amount of carbon emissions per unit area of the body of land under the type of land to which the body of land belongs through a carbon emission model based on carbon emission data collected from carbon emission observation points of the body of land. As an optional implementation, the carbon emission model may use carbon emission data collected by a sensor in the land bulk as a control variable, and a machine learning algorithm is adopted to fit an error between the carbon emission data collected by the sensor and the carbon emission data measured by the multispectral data at a carbon emission observation point, so as to deduce the carbon emission amount per unit area of the land bulk under the type of the land bulk based on the carbon emission data collected by the carbon emission observation point of the land bulk. That is, in the embodiment of the application, a point-to-surface deduction model can be fitted through low-frequency data of satellite remote sensing and data acquired by a sensor at a high frequency, so that carbon emission analysis of a land bulk body with finer strength is realized, and more accurate carbon emission per unit area of the land bulk body under the type of the land bulk is obtained.

As an alternative implementation, the embodiment of the present application may input at least the land type of the land body and the carbon emission data collected by the sensor in the land body into the carbon emission model, so as to obtain the carbon emission amount per unit area of the land body under the land type. The carbon emission model can take carbon emission data (such as oxygen amount, sulfur dioxide amount, carbon dioxide amount, moisture, wind direction and the like) collected by a sensor in the land body as a feature vector, and realizes calculation by adopting an SVM (support vector machine) fitting algorithm of a Gaussian kernel based on the land type of the land body.

In one example, the carbon emission model may be expressed as:

。

in some embodiments, for the ith land body, the land type e of the ith land body and the feature vector x of the carbon emission data of the ith land body collected by the sensor may be input into the carbon emission model, so as to obtain the unit area carbon emission amount of the ith land body in the corresponding land type. The carbon emission per unit area of the ith land body can be set to F_cshw，i。uRepresents the mathematical expectation of the feature vector x over the distribution; σ represents the standard deviation.

In step S612, determining the carbon emission amount of each land body according to the carbon emission amount per unit area of each land body under the type of the land to which the land body belongs and the area of each land body; and determining the carbon emission of the region according to the carbon emission of each land body.

After the carbon emission per unit area of each land body in the type of the land to which the land body belongs is obtained, the carbon emission of each land body can be determined according to the embodiment of the application based on the area of each land body. For example, the carbon emission amount of each land body in the area type of the land to which the land body belongs can be multiplied by the area of the corresponding land body to obtain the carbon emission amount of each land body. Let the area of the ith land parcel body be S_iThen, the carbon emission of the ith plot body can be expressed as: s_i×F_cshw，i. Furthermore, according to the embodiment of the application, the carbon emission of the region can be determined according to the carbon emission of each land body. For example, the carbon emissions of the individual plot bodies are added to obtain the carbon emissions of the region. The carbon emission of the region is E_carb-createAnd K land bodies in total, the carbon emission of the region can be expressed as:

。

it should be noted that, although the high-precision map data can obtain the carbon emission of the area through the multispectral data when the multispectral data is fused, the accuracy of the carbon emission acquired by the multispectral data is low, and the limit of the satellite acquisition cycle is added, so that the area cannot be accurately and efficiently analyzed by using the multispectral data. Based on this, in the embodiment of the application, the sensor is arranged at the carbon emission observation point where the main body of the land is mainly used for carbon emission, so as to collect the carbon emission data of the carbon emission observation point and realize accurate monitoring and collection of the carbon emission data of the main body of the land at the point position; and then, by utilizing the carbon emission model, combining the errors between the carbon emission data collected by the carbon emission observation point and the carbon emission data measured by the multispectral data, deducing the carbon emission amount of the land body in the unit area of the type of the land body to which the land body belongs according to the single-point carbon emission data collected by the sensor, thereby realizing the accurate analysis and estimation of the carbon emission amount of the land body in the unit area on the basis of combining the single-point data collected by the sensor and the data measured by the multispectral data. According to the method and the device, the carbon emission amount of each land body in the unit area under the type of the land to which the land body belongs can be obtained by combining the carbon emission amount of each land body with the area of each land body; and determining the carbon emission of the area based on the carbon emission of each land body, and realizing accurate, integral and efficient carbon emission measurement and calculation of the area.

Therefore, the short plates can be mutually supplemented through the fusion of the low-frequency data of the satellite remote sensing and the data acquired by the sensor at high frequency, the anatomical analysis of the global carbon emission of the region can be carried out through the satellite remote sensing data, and the global carbon emission of the region can be accurately deduced through the data acquired by the sensor at the point position; namely, a point-to-surface deduction model is fitted through low-frequency data of satellite remote sensing and data acquired by a sensor at high frequency, so that carbon emission analysis of finer degree of the whole area is realized, and more accurate and integral carbon emission is obtained.

Compared with a mode of separately utilizing remote sensing to measure and calculate the carbon emission, the scheme for measuring and calculating the carbon emission of the area provided by the embodiment of the application can realize finer quantitative analysis of the carbon emission of the area, and compared with a mode of separately measuring and calculating the carbon emission based on data acquired by a sensor, the scheme can realize planning analysis and global deduction of the overall carbon emission of the area. Further, the carbon emission data of the carbon emission observation point is derived from the sensor, and the satellite remote sensing data (such as multispectral data) can provide corresponding comparative data, so that in the process of determining the carbon emission amount of the region, the embodiment of the application can avoid manual intervention, and the problem of inaccurate measurement and calculation caused by falsification or recording errors of the data is avoided.

On the optional realization of obtaining the high-precision map data of the region, the embodiment of the application can fuse multispectral data and remote sensing images of the region to obtain the high-precision map data. In some embodiments, the multispectral data may be fused to the remote sensing image by an image difference method to obtain high-precision map data of a region, and different types of land blocks in the multispectral data are weighted differently in the fusion process. As an optional implementation, the multispectral data of the region and the administrative map of the region can be synchronized in the embodiment of the application, so that different types of plots are divided from the multispectral data, different weights are used based on the different types of plots, the multispectral data are fused with the remote sensing image through an image difference method, and the high-precision map data of the region are obtained, so that the high-precision resolution (10-meter level) of the obtained high-precision map data can be guaranteed, and the multispectral data are not distorted.

As an optional implementation, the embodiment of the present application may use an HIS (intensity I, chromaticity H, and saturation S) transformation algorithm to fuse multispectral data and remote sensing images of an area, so as to obtain high-precision map data of the area. When the remote sensing image with high resolution is fused with the multispectral data, the embodiment of the application can transform the multispectral data into an HIS color space by using a forward transformation formula according to RGB (red R, green G and blue B) values of an input image to obtain three components of intensity I, chroma H and saturation S; then, histogram matching is carried out on the remote sensing image with high resolution and the intensity component I of the multispectral data, based on a matching result, the intensity component I of the multispectral data is replaced by the preprocessed remote sensing image, and further the intensity component I, the chromaticity H and the saturation S after the multispectral data is replaced are converted into an RGB space by an inverse transformation formula, so that fused high-precision map data are obtained. In the above process, after the three components of the intensity I, the chromaticity H, and the saturation S of the multispectral data are extracted, different weights may be used based on different types of parcels, and the components of the different types of parcels in the intensity I, the chromaticity H, and the saturation S of the multispectral data are subjected to weighting adjustment, so that the different types of parcels in the fused high-precision map data have obvious boundaries, that is, different types of parcels in the multispectral data use different weights in the fusion process.

In further embodiments, after determining the carbon absorption capacity and carbon emission of the area, embodiments of the present disclosure may determine a carbon integration of the area according to the carbon absorption capacity and carbon emission of the area, for example, by comparing the carbon absorption capacity and carbon emission of the area to determine whether the carbon absorption capacity is greater than the carbon emission, the area has a carbon emission margin, or the carbon absorption capacity is less than the carbon emission, and the carbon emission of the area is excessive; thereby providing directional advice for the activity of the region based on the carbon synthesis of the region.

According to the embodiment of the application, the carbon absorption capacity and the carbon emission of the area can be calculated by automatically collecting and analyzing data under the condition of avoiding manual intervention, the accurate, integral and efficient carbon absorption capacity and carbon emission of the area are provided, and accurate guidance is provided for activity planning of the area.

In further embodiments, the cloud server may send the measured and calculated carbon absorption capacity of the region to the display platform, so that the display platform can display the carbon absorption capacity of the region in the high-precision map data of the region on the basis of displaying the high-precision map data of the region. The display platform can be a monitoring large screen of a server or a display interface of a terminal, and the like, and the embodiment of the application is not limited thereto. As an alternative implementation, fig. 7 shows an alternative flowchart of the presentation method provided in the embodiment of the present application. The method flow can be implemented by the presentation platform, and as shown in fig. 7, the method flow may include the following steps.

In step S710, displaying high-precision map data of a region, where the high-precision map data includes a plurality of plots of different plot types in the region, and the plots include plot bodies and plot edges; the edge of the land is obtained after the boundary of the land extends to the inside and the outside of the land by a set distance.

In the embodiment of the application, the display platform can display high-precision map data of a region. The detailed contents of the high-precision map data can refer to the description of the corresponding parts, and are not described herein again.

In step S711, acquiring the carbon absorption capacity of the area transmitted by the cloud server; the carbon absorption capacity of the region is determined according to the carbon absorption capacity of each block body and the carbon absorption capacity of each block edge boundary area, and the block edge boundary areas are boundary areas of blocks of different block types on the block edges.

After determining the carbon absorption capacity of the region, the cloud server can feed back the carbon absorption capacity of the region to the display platform. The specific manner of determining the carbon absorption capacity of the region by the cloud server can refer to the corresponding description above, and is not described herein again.

In step S712, the carbon absorption capacity of the region is shown at least in the high-precision map data.

The display platform can further display the carbon absorption capacity of the region in the displayed high-precision map data of the region based on the carbon absorption capacity of the region acquired from the server, so that a user can further check the carbon absorption capacity of the region on the basis of the high-precision map data of the region.

It can be seen that, in the embodiment of the application, the display platform can display high-precision map data of an area, and the high-precision map data shows the carbon absorption capacity of the area; wherein the high-precision map data includes a plurality of plots of different plot types in the region, the plots including plot bodies and plot edges; the edge of the land is obtained after the boundary of the land extends a set distance to the inside and the outside of the land; the carbon absorption capacity of the region is determined according to the carbon absorption capacity of each block body and the carbon absorption capacity of each block edge boundary area, and the block edge boundary areas are boundary areas of blocks of different block types on the block edges.

As an alternative example, taking the plot distribution of the region illustrated in fig. 2 as an example, on the basis of this, fig. 8 exemplarily shows a schematic diagram of the presentation interface. As shown in fig. 8, the display platform can display the carbon absorption capacity of the area measured and calculated by the cloud server on the basis of displaying the high-precision map data of the area.

In some further embodiments, the cloud server may further feed back the carbon absorption capacity of each parcel main body in the area and the carbon absorption capacity of each parcel edge boundary area to the display platform, so that the display platform may display the corresponding carbon absorption capacity on each parcel main body of the high-precision map data, and display the corresponding carbon absorption capacity on each parcel edge boundary area of the high-precision map data. In further embodiments, the cloud server may further feed back the measured and calculated carbon emission of the area to the display platform, so that the display platform may further display the carbon emission of the area in the high-precision map data. In further embodiments, the cloud server may also feed back the carbon emission amount of each land body in the region to the display platform, so that the display platform may further display the corresponding carbon emission amount on each land body of the high-precision map data.

In the following, the regional carbon estimation device provided in the embodiment of the present application is introduced, and the content of the device described below may be regarded as a functional module that is required by the cloud server to implement the regional carbon estimation method provided in the embodiment of the present application. The device content described below may be referred to in correspondence with the above content.

As an alternative implementation, fig. 9 exemplarily shows a block diagram of a regional carbon measuring and calculating device provided in an embodiment of the present application. As shown in fig. 9, the apparatus may include:

a map data obtaining module 910, configured to obtain high-precision map data of a region, where the high-precision map data includes a plurality of plots with different plot types in the region, and each plot includes a plot main body and a plot edge; the edge of the land is obtained after the boundary of the land extends a set distance to the inside and the outside of the land;

a boundary region determining module 911, configured to determine boundary regions of the plots with different plot types at the plot edges to obtain a plurality of plot edge boundary regions;

a main body and edge carbon absorption capacity determination module 912 configured to determine a carbon absorption capacity of the main body of each land and a carbon absorption capacity of the edge boundary area of each land;

a region carbon absorption capacity determination module 913, configured to determine the carbon absorption capacity of the region according to the carbon absorption capacity of the main body of each land and the carbon absorption capacity of the boundary area of each land edge.

In some embodiments, the body and edge carbon absorption capacity determination module 912 for determining the carbon absorption capacity of the individual parcel bodies comprises:

determining the plot environmental information of each plot main body for carbon absorption;

respectively determining the carbon absorption capacity of each land body in unit area according to the land environment information and the land type of each land body;

and determining the carbon absorption capacity of each land body according to the carbon absorption capacity per unit area of each land body and the area of each land body.

In some embodiments, the determining module 912 for determining the carbon absorption capacity per unit area of each land body according to the land environment information and the land type of each land body includes:

inputting the plot environment information of the plot main body and the plot type of the plot main body into a first carbon absorption factor model to obtain the carbon absorption capacity of the plot main body output by the first carbon absorption factor model in the unit area of the plot type; wherein the first carbon absorption factor model is used for evaluating the solid carbon amount of each type of land parcel in unit area.

In some further embodiments, the apparatus provided in this application may further be configured to:

acquiring training feature vectors of a plurality of first-class regions; training a first carbon absorption factor model by taking the carbon dioxide decrement of each first type of area as a linear fitting target based on the training feature vectors of the plurality of first types of areas through a logistic regression reasoning mode; the training feature vector of the first region comprises vectorization of at least one item of information: the industrial type of the first type region, the area ratio of each region type in the first type region, the population density and the region environment information.

In some embodiments, the body and edge carbon absorption capacity determination module 912, configured to determine the carbon absorption capacity of the edge boundary area of each plot, includes:

determining the plot environmental information of each plot edge junction area for carbon absorption;

respectively determining the carbon absorption capacity per unit area of each plot edge boundary area according to the plot type combination and the plot environment information corresponding to each plot edge boundary area;

and determining the carbon absorption capacity of each land edge boundary area according to the carbon absorption capacity per unit area of each land edge boundary area and the area of each land edge boundary area.

In some embodiments, the main body and edge carbon absorption capacity determining module 912, configured to respectively determine the carbon absorption capacity per unit area of each parcel edge boundary area according to the parcel type combination and the parcel environmental information corresponding to each parcel edge boundary area, includes:

and combining the plot environment information of the plot edge boundary area and the plot type corresponding to the plot edge boundary area, and inputting the second carbon absorption factor model to obtain the carbon absorption capacity of the plot edge boundary area output by the second carbon absorption factor model in the unit area of the plot type combination.

acquiring training feature vectors of a plurality of second-class regions; training a second carbon absorption factor model by taking the carbon dioxide decrement of each second type region as a linear fitting target based on the training feature vectors of the second type regions through a logistic regression reasoning mode; the second type of area is located in parallel geographical zones with set distances at junctions of different types of plots.

acquiring carbon emission data acquired by sensors arranged in a plot main body, wherein the sensors are arranged at carbon emission observation points of the plot main body;

deducing the carbon emission amount of each land body in unit area under the type of the land according to the type of the land body and carbon emission data acquired by sensors arranged in the land body;

determining the carbon emission of each land body according to the carbon emission per unit area of each land body under the type of the land to which the land body belongs and the area of each land body; and determining the carbon emission of the region according to the carbon emission of each land body.

In some embodiments, the apparatus provided in the embodiments of the present application, for deriving the carbon emission per unit area of each land body under the land type according to the land type of the land body and the carbon emission data collected by the sensors arranged in the land body, includes:

for a land body, based on carbon emission data collected by a carbon emission observation point of the land body, deducing the carbon emission amount per unit area of the land body under the type of the land to which the land body belongs through a carbon emission model; the carbon emission model takes carbon emission data collected by a sensor in the land parcel main body as a control variable, and adopts a machine learning algorithm to fit errors of carbon emission observation points between the carbon emission data collected by the sensor and the carbon emission data measured by multispectral data, so that the carbon emission data collected by the carbon emission observation points of the land parcel main body is used for deducing the unit area carbon emission amount of the land parcel main body under the type of the land parcel.

In some embodiments, the map data obtaining module 910, configured to obtain high-precision map data of a region, includes:

acquiring multispectral data and remote sensing images of a region;

and fusing the multispectral data with the remote sensing image through an image difference method to obtain high-precision map data of the region, wherein in the fusion process, different types of plots of the multispectral data use different weights.

The embodiment of the application further provides a cloud server, and the cloud server can be provided with the regional carbon measuring and calculating device. The cloud server provided by the embodiment of the application can be used for executing the regional carbon measuring and calculating method provided by the embodiment of the application. Optionally, fig. 10 illustrates an alternative block diagram of a cloud server. As shown in fig. 10, the cloud server may include: at least one processor 1, at least one communication interface 2, at least one memory 3 and at least one communication bus 4.

In the embodiment of the present application, the number of the processor 1, the communication interface 2, the memory 3, and the communication bus 4 is at least one, and the processor 1, the communication interface 2, and the memory 3 complete mutual communication through the communication bus 4.

Alternatively, the communication interface 2 may be an interface of a communication module for performing network communication.

Alternatively, the processor 1 may be a CPU (central Processing Unit), a GPU (Graphics Processing Unit), an NPU (embedded neural network processor), an FPGA (Field Programmable Gate Array), a TPU (tensor Processing Unit), an AI chip, an asic (application Specific Integrated circuit), or one or more Integrated circuits configured to implement the embodiments of the present application.

The memory 3 may comprise a high-speed RAM memory and may also comprise a non-volatile memory, such as at least one disk memory.

The memory 3 stores one or more computer-executable instructions, and the processor 1 calls the one or more computer-executable instructions to execute the regional carbon estimation method provided by the embodiment of the application.

Embodiments of the present application also provide a storage medium storing one or more computer-executable instructions that, when executed, implement the regional carbon estimation method provided in the embodiments of the present application.

The embodiment of the present application further provides a computer program, and when executed, the computer program implements the regional carbon estimation method provided in the embodiment of the present application.

While various embodiments have been described above in connection with what are presently considered to be the embodiments of the disclosure, the various alternatives described in the various embodiments can be readily combined and cross-referenced without conflict to extend the variety of possible embodiments that can be considered to be the disclosed and disclosed embodiments of the disclosure.

Although the embodiments of the present application are disclosed above, the present application is not limited thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the scope or spirit of the present disclosure, and it is intended that the scope of the present disclosure be defined by the appended claims.

Claims

1. A regional carbon estimation method comprises the following steps:

2. The method of claim 1, wherein the determining the carbon absorption capacity of each parcel body comprises:

3. The method as claimed in claim 2, wherein the determining the carbon absorption capacity per unit area of each land body separately according to the land environment information and the land type of each land body comprises:

4. The method of claim 3, further comprising:

5. The method of any one of claims 1-4, wherein the determining the carbon absorption capacity of each parcel edge interface area comprises:

6. The method as claimed in claim 5, wherein the determining the carbon absorption capacity per unit area of each land edge boundary area according to the land type combination and the land environment information corresponding to each land edge boundary area comprises:

combining the plot environment information of the plot edge boundary area and the plot type corresponding to the plot edge boundary area, and inputting a second carbon absorption factor model to obtain the carbon absorption capacity of the plot edge boundary area output by the second carbon absorption factor model in the unit area of the plot type combination;

the method further comprises the following steps:

7. The method of claim 1, further comprising:

8. The method of claim 7, wherein deriving the carbon emissions per area for each body of the plot for the type of plot based on the type of plot and the carbon emissions data collected by sensors disposed in the body of the plot comprises:

9. The method of claim 8, wherein the obtaining high precision map data for a region comprises:

acquiring multispectral data and remote sensing images of a region;

10. A display platform, wherein the display platform displays high-precision map data of an area, and the high-precision map data displays carbon absorption capacity of the area;

11. A cloud server comprising at least one memory and at least one processor; the memory stores one or more computer-executable instructions that are invoked by the processor to perform the regional carbon estimation method of any of claims 1-9.

12. A storage medium, wherein the storage medium stores one or more computer-executable instructions that, when executed, implement the regional carbon estimation method of any of claims 1-9.