An adaptive interpolation method and electronic device for carbon emission power density at the city block level

Abstract

This disclosure provides an adaptive interpolation method and electronic device for carbon emission power density at the city block level, relating to the field of data processing technology. The implementation scheme is as follows: Based on the differences in the gradient vectors of building development volume at various sampling points of a first urban plot, the location of a first interpolation sampling point in the sampling network of the first urban plot is determined, where the building development volume of the sampling point is the ratio of the building area to the base area of ​​the sampling point; based on the carbon emission power density of multiple first neighboring sampling points and the slope of the change in carbon emission power density of the multiple first neighboring sampling points, the carbon emission power density of the first interpolation sampling point is determined; based on the location and carbon emission power density of the first interpolation sampling point, interpolation is performed on the sampling network of the first urban plot. Using the scheme of this disclosure, the accuracy of carbon emission data interpolation can be improved, and the sampling cost of carbon emission data can be reduced.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology. Specifically, it relates to an adaptive interpolation method and electronic equipment for carbon emission power density at the city block level. Background Technology

[0002] In real-world urban settings, building carbon emissions are influenced by multiple factors. For example, the distribution of electricity, gas, and heat energy consumption in buildings exhibits strong spatial differences depending on building function density, usage time, and occupancy rate. Therefore, real-time carbon emission monitoring of buildings within urban areas is necessary to reduce carbon emissions in a targeted manner.

[0003] However, constrained by data security and cost control, it is difficult to deploy a comprehensive real-time carbon emission monitoring network, also known as a sampling network, across urban areas. Therefore, how to process carbon emission data from building clusters within urban areas to reduce sampling or monitoring costs is a technical problem that needs to be studied in this field. Summary of the Invention

[0004] This disclosure provides an adaptive interpolation method and electronic device for carbon emission power density at the city block level.

[0005] According to one aspect of this disclosure, an adaptive interpolation method for carbon emission power density at the city block level is provided, comprising:

[0006] Based on the difference between the gradient vectors of the building development volume of each sampling point of the first urban plot, the position of the first interpolation sampling point in the sampling network of the first urban plot is determined, wherein the building development volume of the sampling point is the ratio of the building area to the base area of ​​the sampling point.

[0007] The carbon emission power density of the first interpolation sampling point is determined based on the carbon emission power density of multiple first neighboring sampling points of the first interpolation sampling point and the slope of the change of the carbon emission power density of the multiple first neighboring sampling points.

[0008] Based on the location of the first interpolation sampling point and the carbon emission power density, the sampling network of the first urban plot is interpolated.

[0009] According to another aspect of this disclosure, an electronic device is provided, comprising:

[0010] At least one processor; and

[0011] The memory is communicatively connected to the at least one processor; wherein,

[0012] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform any of the city block-level carbon emission power density adaptive interpolation methods in the embodiments of this disclosure.

[0013] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are used to cause the computer to perform an adaptive interpolation method for carbon emission power density at the city block level according to any embodiment of this disclosure.

[0014] According to the technology disclosed herein, the location of the first interpolation sampling point in the sampling network of the first urban plot is determined based on the difference between the gradient vectors of the ratio of building development volume (i.e., building area to base area) at each sampling point of the first urban plot. This allows for accurate determination of the interpolation point's location, thereby identifying multiple first neighboring sampling points of the first interpolation sampling point. Furthermore, based on the carbon emission power density of the multiple first neighboring sampling points and the slope of their change, the carbon emission power density of the first interpolation sampling point can be determined. Based on the location and carbon emission power density of the first interpolation sampling point, the sampling network of the first urban plot is interpolated. Therefore, using the interpolation scheme of this disclosure, not only can the location of the sampling point be accurately determined based on the building development volume of each sampling point in the sampling network, but the carbon emission power density of the sampling point can also be accurately determined based on the carbon emission power density of its neighboring points and the slope of their change, thus enabling accurate interpolation, reducing the actual number of sampling points in the sampling network, and reducing sampling costs.

[0015] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0016] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0017] Figure 1 This is a flowchart of an embodiment of an adaptive interpolation method for carbon emission power density at the city block level according to this disclosure;

[0018] Figure 2 This is a schematic diagram of a newly added sampling point according to an embodiment of the present disclosure;

[0019] Figure 3 This is a structural block diagram of a city block-level carbon emission power density adaptive interpolation device according to an embodiment of the present disclosure;

[0020] Figure 4This is a block diagram of an electronic device according to an embodiment of the present disclosure. Detailed Implementation

[0021] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0022] Figure 1 This is a flowchart of an embodiment of an adaptive interpolation method for carbon emission power density at the city block level disclosed herein.

[0023] like Figure 1 As shown, the adaptive interpolation method for carbon emission power density at the city block level may include:

[0024] S110, Based on the difference between the gradient vectors of the building development volume of each sampling point of the first urban plot, determine the position of the first interpolation sampling point in the sampling network of the first urban plot, wherein the building development volume of the sampling point is the ratio of the building area of ​​the sampling point to the base area.

[0025] S120, Based on the carbon emission power density of multiple first neighboring sampling points of the first interpolation sampling point, and the slope of the change of the carbon emission power density of multiple first neighboring sampling points, determine the carbon emission power density of the first interpolation sampling point.

[0026] S130, based on the location of the first interpolation sampling point and the carbon emission power density, interpolate the sampling network of the first urban plot.

[0027] Understandably, any city can be divided into multiple plots, and any plot can serve as the first urban plot in this embodiment. Furthermore, the interpolation process for the city's sampling network can involve applying the carbon emission data processing method of this embodiment to the sampling networks of each plot within the city, and then combining the interpolated sampling networks of each plot into the city's sampling network.

[0028] Understandably, the first urban plot includes multiple sampling points, such as building sampling points, transportation equipment sampling points, etc. In the original sampling network, these sampling points can be actual sampling points. After performing the interpolation processing of the original sampling network according to this embodiment, the sampling points in the sampling network can also include interpolated sampling points.

[0029] For example, in step S110, the coordinate positions of multiple first interpolation sampling points can be determined. Then, in step S120, the carbon emission power density of each first interpolation sampling point is determined. Thus, based on the coordinate positions and carbon emission power densities of each first interpolation sampling point, interpolation can be performed on the sampling network of the first urban plot using multiple interpolation sampling points, improving interpolation efficiency.

[0030] For example, the gradient vector of the building development volume of each sampling point can be determined in the following way: select multiple neighboring sampling points of the sampling point, use the least squares method to fit the building development volume of the sampling point and its multiple neighboring sampling points into a curve, and perform differentiation on the sampling point based on the curve to obtain the gradient vector of the sampling point.

[0031] For example, if the curve is D, the coordinates of the sampling points are... Then the gradient vector of the sampling point is , .

[0032] For example, the differences between the gradient vectors of building development volume at various sampling points of the first urban plot are compared. The position of the first interpolation sampling point is determined between two sampling points with significant differences in building development volume. This first interpolation sampling point is then inserted into the corresponding position in the sampling network, and multiple first neighboring sampling points of the first interpolation sampling point are determined. Alternatively, the position of the first interpolation sampling point is determined along the direction of the maximum gradient vector in the gradient vector of the building development volume at each sampling point. Multiple sampling points can be inserted in this direction, or only one sampling point can be inserted.

[0033] For example, the first neighboring sampling points of the first interpolation sampling point can be multiple sampling points within a preset distance range centered on the first interpolation sampling point.

[0034] For example, the multiple first neighboring sampling points of the first interpolation sampling point can form a triangle with the first interpolation sampling point as the center, consisting of three sampling points. For example, these three sampling points are located on the three sides of the triangle, or at the three corners of the triangle.

[0035] For example, a cubic polynomial is used to fit the carbon emission power density of multiple first neighboring sampling points of the first interpolation sampling point and the slope of the change of carbon emission power density of multiple first neighboring sampling points to obtain a carbon emission power density curve. The carbon emission power density of the first interpolation sampling point on the carbon emission power density curve is taken as the carbon emission power density of the first interpolation sampling point.

[0036] For example, a cubic Hermite polynomial is used to interpolate the carbon emission power density and the slope of the change of carbon emission power density at the three sampling points of the aforementioned triangle to obtain the carbon emission power density at the first interpolated sampling point.

[0037] For example, the carbon emission power density of the first interpolation sampling point is marked at the location of the first interpolation sampling point in the sampling network of the first urban plot, thereby completing the interpolation of the first interpolation sampling point in the sampling network of the first urban plot.

[0038] According to the above implementation method, the location of the first interpolation sampling point in the sampling network of the first urban plot is determined based on the difference between the gradient vectors of the ratio of building development volume (i.e., building area to base area) of each sampling point in the first urban plot. In this way, the location of the interpolation point can be accurately determined, thereby determining multiple first neighboring sampling points of the first interpolation sampling point. Furthermore, based on the carbon emission power density of the multiple first neighboring sampling points of the first interpolation sampling point, and the slope of the change in carbon emission power density of the multiple first neighboring sampling points, the carbon emission power density of the first interpolation sampling point can be determined, and interpolation is performed on the sampling network of the first urban plot based on the location of the first interpolation sampling point and the carbon emission power density. Therefore, by adopting the interpolation scheme of this disclosure, not only can the location of the sampling point be accurately determined based on the building development volume of each sampling point in the sampling network, but also the carbon emission power density of the sampling point can be accurately determined based on the carbon emission power density of the neighboring points and the slope of the change in carbon emission power density, thereby performing accurate interpolation, reducing the actual number of sampling points in the sampling network, and reducing sampling costs.

[0039] In one implementation, determining the position of a first interpolation sampling point in the sampling network of the first urban plot based on the difference between the gradient vectors of the building development volume of each sampling point in the first urban plot includes: if the maximum value of the gradient vector in the gradient vector of the building development volume of each sampling point in the first urban plot is greater than a preset gradient vector threshold, performing the following interpolation operation: determining the position of a second interpolation sampling point in the direction of the maximum value of the gradient vector; determining the gradient vectors of the building development volume of the second interpolation sampling point and the building development volume of the second interpolation sampling point based on the building development volume of the neighboring sampling points of the second interpolation sampling point, and redetermining the gradient vectors of the neighboring sampling points of the second interpolation sampling point to redetermine the maximum value of the gradient vector, and determining whether to return to continue performing the interpolation operation; if the redetermined maximum value of the gradient vector is less than the gradient vector threshold, stopping the interpolation operation, and determining the position of the first interpolation sampling point based on the position of each second interpolation sampling point.

[0040] Understandably, with the gradient vectors of the neighboring sampling points of the second interpolation sampling point redefined, the gradient vectors of the building development quantities of each actual sampling point and the interpolation sampling point in the first urban plot have been redefined. However, the gradient vectors of the building development quantities of the sampling points may or may not have changed after the redefined gradient vectors.

[0041] In the first urban plot, the maximum value of the gradient vector is redefined from the gradient vectors of the redefined building development quantities at each actual sampling point and interpolation sampling point. If the redefined maximum value of the gradient vector is greater than the gradient vector threshold, the interpolation operation continues until the redefined maximum value of the gradient vector is less than the gradient vector threshold, at which point the interpolation operation stops.

[0042] For example, the coordinate positions of one or more second interpolation sampling points can be determined along the direction of the maximum gradient vector. These coordinate positions are specified locations within the sampling network in the world plane coordinate system.

[0043] For example, the building development volume of the second interpolation sampling point is obtained by averaging or taking the median of the building development volume of multiple neighboring sampling points.

[0044] For example, the method for updating the gradient vector of the building development volume of the second interpolation sampling point and its multiple neighboring sampling points can refer to the method for determining the gradient vector of the building development volume of the aforementioned sampling points, and will not be described in detail here.

[0045] For example, the position of the first interpolation sampling point is obtained by averaging or taking the median of the positions of each second interpolation sampling point.

[0046] According to the above implementation method, in the original sampling network of the first urban plot, the maximum value of the gradient vector of building development is selected, and a new interpolation sampling point is inserted in the direction of the maximum value of the gradient vector. The building development of the new interpolation sampling point can be obtained by averaging or taking the median of the building development of the neighboring sampling points. Then, the gradient vector of the building development of the interpolation sampling point is calculated, and the gradient vector of the building development of the neighboring sampling points is recalculated to determine whether to return to re-inserting a new interpolation sampling point. The iteration stops only when the maximum value of the re-determined gradient vector is less than a preset threshold, and all interpolation sampling points are merged to obtain an accurate first interpolation sampling point. Interpolation is then performed to improve the interpolation accuracy of the sampling network.

[0047] In one implementation, the slope of the change in carbon emission power density of any first neighboring sampling point of the first interpolation sampling point can be determined in the following way: Based on the first direction in which the change in carbon emission power density of the first urban plot is most gradual, the local principal direction angle of the first urban plot is determined; based on the local principal direction angle, a local orthogonal principal direction coordinate system with the first neighboring sampling point as the origin is constructed; based on the slope of the change in carbon emission power density of the first neighboring sampling point in the local orthogonal principal direction coordinate system, the slope of the change in carbon emission power density of the first neighboring sampling point in the local orthogonal principal direction coordinate system is determined; and then the slope of the change in carbon emission power density of the first neighboring sampling point in the world coordinate system is obtained through coordinate system transformation, that is, the slope of the change in carbon emission power density of the first neighboring sampling point is obtained.

[0048] Understandably, the world coordinate system in this embodiment refers to the world plane coordinate system. For the same coordinate system, the horizontal axis and the vertical axis are perpendicular to each other.

[0049] For example, the method of determining the carbon emission power density change slope of the first neighboring sampling point in the local orthogonal principal direction coordinate system based on the carbon emission power density change slope of the relevant neighboring sampling points in the local orthogonal principal direction coordinate system, and then obtaining the carbon emission power density change slope of the first neighboring sampling point in the world coordinate system through coordinate system transformation, specifically includes: determining the carbon emission power density change slope of the first neighboring sampling point in the horizontal axis direction based on the carbon emission power density change slope of multiple second neighboring sampling points in the horizontal axis direction of the first neighboring sampling point in the local orthogonal principal direction coordinate system, and determining the carbon emission power density change slope of the first neighboring sampling point in the vertical axis direction based on the carbon emission power density change slope of multiple third neighboring sampling points in the vertical axis direction of the first neighboring sampling point in the vertical axis direction; and converting the carbon emission power density change slope of the first neighboring sampling point in the horizontal and vertical axes direction of the local orthogonal principal direction coordinate system into the carbon emission power density change slope of the first neighboring sampling point in the horizontal and vertical axes direction of the world coordinate system. Therefore, based on the slope of the change in carbon emission power density of the first neighboring sampling point in the horizontal and vertical directions of the world coordinate system, the slope of the change in carbon emission power density of the first neighboring sampling point is determined.

[0050] For example, the local principal orientation angle of the first urban plot can also be the long axis of the street or the main orientation of the building complex of the plot.

[0051] For example, regarding the local principal orientation angle of the first urban plot A local orthogonal principal direction coordinate system is constructed with the first neighboring sampling point as the origin. The horizontal and vertical directions of this coordinate system are as follows:

[0052] ;

[0053] ;

[0054] in, This indicates the horizontal axis direction of the local orthogonal principal direction coordinate system. It represents the vertical axis direction of the local orthogonal principal direction coordinate system.

[0055] For example, determining the slope of carbon emission power density change of the first neighboring sampling point in the horizontal direction based on the slope of the change of carbon emission power density of multiple second neighboring sampling points in the horizontal direction of the local orthogonal principal direction coordinate system can include: for five consecutive adjacent second neighboring sampling points of the first neighboring sampling point, calculating the slope of the change of carbon emission power density between any two adjacent second neighboring sampling points in the horizontal direction, thus obtaining four slopes, and performing difference calculation on these four slopes to obtain the slope of carbon emission power density change of the first neighboring sampling point in the horizontal direction.

[0056] For example, determining the slope of carbon emission power density change of the first neighboring sampling point in the vertical direction of the local orthogonal principal direction coordinate system based on the slope of the change of carbon emission power density of multiple third neighboring sampling points in the vertical direction of the first neighboring sampling point can include: for five consecutive adjacent second neighboring sampling points of the first neighboring sampling point, calculating the slope of the change of carbon emission power density between any two adjacent second neighboring sampling points in the vertical direction, thus obtaining four slopes, and performing difference calculation on these four slopes to obtain the slope of the change of carbon emission power density of the first neighboring sampling point in the vertical direction.

[0057] For the two examples above, please refer to Akima's five-point difference formula; they will not be elaborated upon here.

[0058] For example, to characterize the anisotropy of carbon emission power density of urban buildings, the anisotropy ratio of the first urban plot can be used to scale the slope of carbon emission power density change of the first neighboring sampling point along the vertical axis of the local orthogonal principal direction coordinate system, while keeping the slope of carbon emission power density change along the horizontal axis unchanged. Then, a coordinate system transformation is performed to obtain the slope of carbon emission power density change of the first neighboring sampling point along both the horizontal and vertical axes of the world coordinate system. In this way, a more accurate slope of carbon emission power density change of the first neighboring sampling point can be obtained.

[0059] For example, coordinate system transformation can be represented by the following formula:

[0060] ;

[0061] in, Indicates the first nearest sampling point The slope of the change in carbon emission power density, and Indicates the first nearest sampling point In the horizontal direction of the locally orthogonal principal direction coordinate system and the vertical axis direction The slope of the change in carbon emission power density, and These represent the first nearest sampling points. In the horizontal direction of the world coordinate system and the vertical axis direction The slope of the change in carbon emission power density.

[0062] According to the above implementation method, based on the local principal orientation angle of the first urban plot, a local orthogonal principal orientation coordinate system is constructed with the first neighboring sampling point as the origin. Based on the slope of the carbon emission power density change of the first neighboring sampling point in the local orthogonal principal orientation coordinate system, the slope of the carbon emission power density change of the first neighboring sampling point in the local orthogonal principal orientation coordinate system is determined. Then, through coordinate system transformation, the slope of the carbon emission power density change of the first neighboring sampling point in the world coordinate system is obtained, thus yielding the slope of the carbon emission power density change of the first neighboring sampling point. In this way, the slope of the carbon emission power density change of the first neighboring sampling point can be accurately obtained.

[0063] In one embodiment, the above-mentioned conversion of the carbon emission power density change slope of the first neighboring sampling point in the horizontal and vertical directions of the local orthogonal principal direction coordinate system into the carbon emission power density change slope of the first neighboring sampling point in the horizontal and vertical directions of the world coordinate system includes: determining the anisotropy ratio based on the carbon emission power density of each sampling point in the first urban plot; scaling the carbon emission power density change slope of the first neighboring sampling point in the vertical direction of the local orthogonal principal direction coordinate system based on the anisotropy ratio; and converting the carbon emission power density change slope of the first neighboring sampling point in the horizontal direction of the local orthogonal principal direction coordinate system and the scaled carbon emission power density change slope in the vertical direction of the local orthogonal principal direction coordinate system into the carbon emission power density change slope of the first neighboring sampling point in the horizontal and vertical directions of the world coordinate system.

[0064] For example, the anisotropy ratio is determined based on the ratio between the sum of carbon emission power densities of all sampling points in the first urban plot in the second direction and the sum of carbon emission power densities of all sampling points in the first urban plot in the first direction; wherein the second direction is the direction in which the emission power density of the first urban plot changes most drastically, and the first direction is the direction in which the emission power density of the first urban plot changes most gently.

[0065] For example, multiplying the reciprocal of the anisotropy ratio by the slope of the carbon emission power density change at the first neighboring sampling point along the vertical axis of the local orthogonal principal direction coordinate system yields the scaled slope of the carbon emission power density change at the first neighboring sampling point along the vertical axis of the local orthogonal principal direction coordinate system.

[0066] In this example, the slope of the carbon emission power density change at the first neighboring sampling point takes into account the anisotropy of the carbon emission power density of urban buildings, thereby improving the rationality and accuracy of the slope of the carbon emission power density change at the first neighboring sampling point.

[0067] In one embodiment, the method further includes: constructing a structure tensor matrix based on the gradient vectors of building development at each sampling point in the first urban plot, wherein the elements in the first row and first column of the structure tensor matrix are the sum of the squares of the gradient vectors of building development at each sampling point along the horizontal axis of the world coordinate system, the elements in the first row and second column and the elements in the second row and first column are the sum of the products of the gradient vectors of building development at each sampling point along the horizontal axis of the world coordinate system and the gradient vectors along the vertical axis of the world coordinate system, and the elements in the second row and second column are the sum of the squares of the gradient vectors of building development at each sampling point along the vertical axis of the world coordinate system; constructing an eigenvalue equation for the structure tensor matrix; solving the eigenvalue equation to obtain the first direction, the second direction, the sum of the carbon emission power densities of all sampling points in the first direction in the first urban plot, and the sum of the carbon emission power densities of all sampling points in the second direction in the first urban plot.

[0068] For example, the structure tensor matrix can be represented by the following equation:

[0069] ;

[0070] in, Let represent the structural tensor matrix of the first urban plot. This represents the total number of sampling points in the first urban area. Indicates the first The building development volume of each sampling point is along the horizontal axis of the world coordinate system. gradient vector on, Indicates the first The building development volume of each sampling point along the vertical axis of the world coordinate system. The gradient vector on.

[0071] For example, the eigenvalue equation can be expressed as follows: ;

[0072] in, Represents the eigenvalues ​​of real numbers. Represents the structure tensor matrix Belongs to the eigenvalue of this real number eigenvectors.

[0073] In this example, since the structure tensor matrix is ​​a two-dimensional matrix with two rows and two columns, solving the eigenvalue equation constructed from this matrix yields two sets of results. Each set of results includes a real eigenvalue and an eigenvector. The real eigenvalue is called the eigenvalue of the structure tensor matrix, and the eigenvector is called the eigenvector of the structure tensor matrix belonging to that real eigenvalue.

[0074] For example, the two sets of results include: and ;in, This indicates the first direction where the carbon emission power density of the first urban plot is most gradual. This represents the sum of carbon emission power densities at all sampling points along the first direction where the carbon emission power density is most gradual within the first urban plot. The second direction represents the area with the most intense carbon emission power density in the first urban plot. It represents the sum of carbon emission power densities at all sampling points in the second direction where the carbon emission power density is most intense in the first urban plot.

[0075] After obtaining the above two sets of results, the local principal orientation angle and anisotropy ratio of the first urban plot can be determined.

[0076] For example, the first urban plot has the most gradual carbon emission power density in the first direction. It can be used as the local main orientation angle of the first urban plot.

[0077] For example, the anisotropy ratio of the first urban plot It can be represented as: .

[0078] According to the above implementation method, a structural tensor matrix is ​​constructed by taking the gradient vectors of the building development volume at each sampling point of the first urban plot along the horizontal and vertical axes of the world coordinate system. Eigenvalue equations are then constructed for the structural tensor matrix. By solving the eigenvalues ​​and eigenvectors of these equations, the two directions in which the carbon emission power density changes most gradually and drastically in the first urban plot, as well as the sum of the carbon emission power densities at all sampling points along each of these two directions, can be obtained. Furthermore, the local principal orientation angles and anisotropy ratio of the first urban plot can be obtained.

[0079] In one embodiment, the plurality of first neighboring sampling points are three sampling points forming a triangle with the first interpolation sampling point as the center. The carbon emission power density of the first interpolation sampling point is determined based on the carbon emission power density of the plurality of first neighboring sampling points and the slope of the change of the carbon emission power density of the plurality of first neighboring sampling points. This includes: determining the carbon emission power density weight and the carbon emission power density change slope weight of each first neighboring sampling point based on the coordinate position of each first neighboring sampling point and the gravity coordinate constraint weight of the first interpolation sampling point relative to each first neighboring sampling point; and weighting and summing the carbon emission power density and the carbon emission power density change slope of each first neighboring sampling point based on the carbon emission power density weight and the carbon emission power density change slope weight to obtain the carbon emission power density of the first interpolation sampling point.

[0080] For example, the carbon emission power density weights for each first neighboring sampling point can be calculated using the following function:

[0081] ;

[0082] in, Indicates the first nearest sampling point coordinates Indicates the first nearest sampling point Carbon emission power density weight, Indicates the first interpolation sampling point relative to the first neighboring sampling point The gravity coordinate constraint weights are such that the sum of the gravity coordinate constraint weights of the first interpolation sampling point relative to each of the first neighboring sampling points is 1.

[0083] For example, the weight of the slope of the carbon emission power density change for each first neighboring sampling point can be calculated using the following function:

[0084] ;

[0085] in, Indicates the first nearest sampling point The slope weight of the change in carbon emission power density and These represent the horizontal and vertical coordinates of the first interpolation sampling point in the world coordinate system, respectively.

[0086] In one example, three first neighboring sampling points are selected centered on the first interpolation sampling point. The values ​​are 1, 2, and 3. The two functions mentioned above are the value-shaped function and gradient-shaped function on the triangle, respectively.

[0087] For example, the carbon emission power density at the first interpolation sampling point can be calculated using the following function:

[0088] ;

[0089] in, This represents the carbon emission power density at the first interpolation sampling point. Indicates the first nearest sampling point carbon emission power density, Indicates the first nearest sampling point The slope of the change in carbon emission power density.

[0090] According to the above implementation method, by using the positional relationship between the neighboring sampling points and the first interpolation sampling point, as well as the carbon emission power density and the slope of change of the carbon emission power density of the neighboring sampling points, the carbon emission power density of the first interpolation sampling point can be accurately obtained, thereby improving the accuracy and rationality of interpolation.

[0091] In one embodiment, the method further includes: determining the sampling weight of the first urban plot based on the historical electricity consumption fluctuation variance, intraday peak-valley load ratio, and building volume ratio of the first urban plot; when the sampling weight is greater than a preset weight threshold and the area of ​​the first urban plot is greater than a preset area threshold, determining the location of new sampling points of the first urban plot based on the sampling point location and centroid location of the first urban plot; and sampling carbon emission power density data of the new sampling points based on the location of the new sampling points of the first urban plot to update the sampling network of the first urban plot.

[0092] For example, the historical electricity consumption fluctuation variance, intraday peak-valley load ratio, and building volume ratio of the first urban plot can be re-determined at regular intervals to re-determine the sampling weight of the first urban plot.

[0093] Understandably, the new sampling point is an actual sampling point added on the basis of the existing sampling network. The carbon emission power density of the actual sampling point needs to be calculated from the actual sampling data, rather than obtained by the interpolation method described in the above embodiment.

[0094] For example, the sampling weight of the first urban plot is obtained by weighting and summing the historical electricity fluctuation variance, intraday peak-valley load ratio and building volume ratio.

[0095] For example, such as Figure 2 As shown, with the centroid of the first urban plot as the center, the symmetrical points of the sampling points of the first urban plot are taken as new sampling points.

[0096] For example, for the carbon emission power density of any actual building sampling point, the carbon emission factors of the instantaneous electrical power, gas flow rate, and heat at that building sampling point can be used to perform a weighted summation of the instantaneous electrical power, gas flow rate, and heat at the building sampling point to obtain the carbon emission power density of the actual building sampling point. Alternatively, the building occupancy rate of the building sampling point can be used to linearly process the weighted summation result to obtain the carbon emission power density of the building sampling point.

[0097] According to the above implementation method, the historical electricity consumption fluctuation variance, daily peak-valley load ratio and building volume ratio of the first urban plot are obtained in real time and dynamically to determine the sampling weight of the first urban plot. If the sampling weight exceeds the preset threshold, a new sampling point is added to the sampling network of the first urban plot, and carbon emission power density data is sampled from the new sampling point to update the sampling network of the first urban plot. In this way, the number of sampling points in the sampling network of the first urban plot can be more reasonable, which facilitates subsequent interpolation and ensures the accuracy of interpolation.

[0098] In one embodiment, the sampling points in the first urban plot include building sampling points, which include multiple different floor sampling points. The method further includes: interpolating the carbon emission power density of each unsampled floor corresponding to the building sampling point based on the carbon emission power density of each floor sampling point in the building sampling points to obtain the carbon emission power density of each unsampled floor; and updating the carbon emission power density of the building sampling points based on the carbon emission power density of each floor sampling point in the building sampling points and the carbon emission power density of each unsampled floor.

[0099] For example, the sampling network of the first urban plot includes multiple sampling points, some of which are building sampling points. For these building sampling points, before performing the above-described plot interpolation method, the floor sampling points in the building sampling points can also be interpolated, i.e., the interpolation method provided in this example.

[0100] For example, the building sampling point corresponds to a building with multiple floors. Sampling is selectively performed on certain floors. The carbon emission power density of each floor sampling point is determined using the sampling data. The specific calculation process for the carbon emission power density in the preceding embodiment can be referred to, and will not be detailed here. Then, the carbon emission power density of the building sampling point is determined using the carbon emission power density of each floor sampling point. For example, the carbon emission power density of the building sampling point can be obtained by averaging or taking the median of the carbon emission power densities of each floor sampling point.

[0101] For example, for buildings with fewer than 12 floors, the floor sampling points are the first floor, the middle floors, and the top floor. For buildings with more than 12 floors, such as a 32-story building, the floor sampling points are floors 1, 8, 16, 24, and 32. Then, using the carbon emission power density of these floor sampling points, interpolation is performed on each unsampled floor in the building to obtain the carbon emission power density of each floor of the entire building, thereby reducing sampling costs.

[0102] For example, a linear fitting method can be used to interpolate the carbon emission power density of each unsampled floor corresponding to the building sampling point.

[0103] For example, the carbon emission power density of the building sampling points can be obtained by averaging or taking the median of the carbon emission power density of each floor sampling point and each unsampled floor.

[0104] According to the above implementation method, before interpolating the sampling network of urban plots, the unsampled floors in the buildings corresponding to the building sampling points in the sampling network can be interpolated to obtain the carbon emission power density of the unsampled floors. Then, the carbon emission power density of the entire building sampling points can be updated using the carbon emission power density of each floor in the building, thereby improving the accuracy of the carbon emission power density of the building sampling points.

[0105] In one implementation, the first city is divided into multiple geographically distinct city blocks, and the sampling network of the first city includes the sampling networks of each city block. The method further includes:

[0106] Based on the data reliability and data integrity of two adjacent first city plots, the carbon emission power density of each adjacent first city plot is weighted and averaged to obtain the carbon emission power density of the boundary sampling point between the two adjacent first city plots; based on the carbon emission power density of the boundary sampling point between the two adjacent first city plots, the sampling network of the first city is interpolated.

[0107] Understandably, the first city plot refers to any plot within the first city, which can be any city or geographical region.

[0108] Understandably, this boundary sampling point is an interpolated sampling point, not an actual sampling point.

[0109] For example, the boundary between two adjacent urban plots is usually a road in the middle, with some traffic facilities or landmark buildings on the road. Therefore, by using the average carbon emission power density of the two plots and performing a weighted average, the carbon emission power density of the boundary sampling point, i.e., the aforementioned boundary, can be obtained.

[0110] Understandably, data reliability refers to the reliability of the sampling data from sampling points within an urban plot. Data integrity refers to the completeness of the sampling data from sampling points within an urban plot. For example, the more actual sampling points and the fewer interpolated sampling points in an urban plot, the higher the data reliability and data integrity of that urban plot.

[0111] For example, the carbon emission power density at the boundary sampling point between two adjacent first urban plots can be calculated using the following formula:

[0112] ;

[0113] in, Indicates the first The city plot and the first Carbon emission power density at sampling points at the boundaries between urban plots and The first The city plot and the first The reliability of data for individual city land parcels and The first The city plot and the first Data integrity of individual city plots and The first The city plot and the first Carbon emission power density of urban plots, the first The city plot and the first The two urban plots are adjacent to each other.

[0114] According to the above implementation method, interpolation is performed at the boundary between two adjacent plots to obtain the boundary sampling point. This can improve the continuity between the sampling points of each plot in the sampling network of the entire urban area and reduce the sampling cost.

[0115] Figure 3This is a structural block diagram of a city block-level carbon emission power density adaptive interpolation device according to an embodiment of the present disclosure.

[0116] like Figure 3 As shown, the city block-level carbon emission power density adaptive interpolation device includes:

[0117] The interpolation location determination module 310 is used to determine the location of the first interpolation sampling point in the sampling network of the first urban plot based on the difference between the gradient vectors of the building development volume of each sampling point of the first urban plot, wherein the building development volume of the sampling point is the ratio of the building area to the base area of ​​the sampling point.

[0118] The interpolation index determination module 320 is used to determine the carbon emission power density of the first interpolation sampling point based on the carbon emission power density of a plurality of first neighboring sampling points of the first interpolation sampling point and the slope of the change of the carbon emission power density of the plurality of first neighboring sampling points.

[0119] The sampling network interpolation module 330 is used to interpolate the sampling network of the first urban plot based on the location of the first interpolation sampling point and the carbon emission power density.

[0120] In one embodiment, the interpolation position determination module 310 includes:

[0121] The interpolation location iteration unit is used to perform the following interpolation operation when the maximum value of the gradient vector in the gradient vector of the building development volume of each sampling point in the first urban plot is greater than a preset gradient vector threshold: determining the position of the second interpolation sampling point in the direction of the maximum value of the gradient vector; determining the building development volume of the second interpolation sampling point and the gradient vector of the building development volume of the second interpolation sampling point based on the building development volume of the neighboring sampling points of the second interpolation sampling point, and redetermining the gradient vector of the neighboring sampling points of the second interpolation sampling point to redetermine the maximum value of the gradient vector, and determining whether to return to continue performing the interpolation operation;

[0122] The interpolation position determination unit is used to stop the interpolation operation when the re-determined maximum value of the gradient vector is less than the gradient vector threshold, and to determine the position of the first interpolation sampling point based on the position of each of the second interpolation sampling points.

[0123] In one embodiment, the above-mentioned device further includes:

[0124] The main direction determination module is used to determine the local main direction angle of the first urban plot based on the first direction in which the change of carbon emission power density is most gradual.

[0125] The coordinate system construction module is used to construct a local orthogonal principal direction coordinate system with the first neighboring sampling point as the origin based on the local principal direction angle.

[0126] The first slope determination module is used to determine the slope of the carbon emission power density change of the first neighboring sampling point in the horizontal axis direction based on the slope of the change of carbon emission power density of multiple second neighboring sampling points in the horizontal axis direction of the first neighboring sampling point in the local orthogonal principal direction coordinate system, and to determine the slope of the carbon emission power density change of the first neighboring sampling point in the vertical axis direction based on the slope of the change of carbon emission power density of multiple third neighboring sampling points in the vertical axis direction of the first neighboring sampling point in the local orthogonal principal direction coordinate system.

[0127] The slope conversion module is used to convert the slope of carbon emission power density change of the first neighboring sampling point in the horizontal and vertical directions of the local orthogonal principal direction coordinate system into the slope of carbon emission power density change of the first neighboring sampling point in the horizontal and vertical directions of the world coordinate system.

[0128] The second slope determination module is used to determine the slope of the change in carbon emission power density of the first neighboring sampling point based on the slope of the change in carbon emission power density of the first neighboring sampling point in the horizontal and vertical directions of the world coordinate system.

[0129] In one embodiment, the slope conversion module includes:

[0130] An anisotropy ratio determination unit is used to determine the anisotropy ratio based on the carbon emission power density of each sampling point in the first urban plot;

[0131] The slope scaling unit is used to scale the slope of the carbon emission power density change of the first neighboring sampling point in the vertical axis direction of the local orthogonal principal direction coordinate system based on the anisotropy ratio.

[0132] The slope conversion unit is used to convert the slope of carbon emission power density change of the first neighboring sampling point in the horizontal axis direction of the local orthogonal principal direction coordinate system and the scaled slope of carbon emission power density change in the vertical axis direction of the local orthogonal principal direction coordinate system into the slope of carbon emission power density change of the first neighboring sampling point in the horizontal axis direction and the vertical axis direction of the world coordinate system.

[0133] In one embodiment, the anisotropy ratio determining unit is specifically used for:

[0134] The anisotropy ratio is determined based on the ratio between the sum of carbon emission power densities of all sampling points in the first urban plot along the second direction and the sum of carbon emission power densities of all sampling points in the first urban plot along the first direction; wherein the second direction is the direction in which the emission power density of the first urban plot changes most drastically.

[0135] In one embodiment, the above-mentioned device further includes:

[0136] The structure tensor construction module is used to construct a structure tensor matrix based on the gradient vectors of the building development volume of each sampling point in the first urban plot. The elements in the first row and first column of the structure tensor matrix are the sum of the squares of the gradient vectors of the building development volume of each sampling point in the horizontal direction of the world coordinate system. The elements in the first row and second column and the elements in the second row and first column are the sum of the products of the gradient vectors of the building development volume of each sampling point in the horizontal direction of the world coordinate system and the gradient vectors in the vertical direction of the world coordinate system. The elements in the second row and second column are the sum of the squares of the gradient vectors of the building development volume of each sampling point in the vertical direction of the world coordinate system.

[0137] An equation construction module is used to construct eigenvalue equations for the structure tensor matrix;

[0138] The equation solving module is used to solve the eigenvalue equation to obtain the first direction, the second direction, the sum of carbon emission power densities of all sampling points in the first urban plot in the first direction, and the sum of carbon emission power densities of all sampling points in the first urban plot in the second direction.

[0139] In one embodiment, the plurality of first neighboring sampling points are three sampling points forming a triangle with the first interpolation sampling point as the center, and the interpolation index determination module 320 includes:

[0140] The weight determination unit is used to determine the carbon emission power density weight and the carbon emission power density change slope weight of each of the first neighboring sampling points based on the coordinate positions of each of the first neighboring sampling points and the gravity coordinate constraint weight of the first interpolation sampling point relative to each of the first neighboring sampling points.

[0141] The carbon emission index determination unit is used to perform weighted summation of the carbon emission power density and the change slope of the carbon emission power density of each of the first neighboring sampling points based on the weight of the carbon emission power density and the weight of the change slope of the carbon emission power density of each of the first neighboring sampling points, so as to obtain the carbon emission power density of the first interpolation sampling point.

[0142] In one embodiment, the device further includes:

[0143] The sampling weight determination module is used to determine the sampling weight of the first urban plot based on the historical electricity consumption fluctuation variance, intraday peak-valley load ratio and building volume ratio of the first urban plot.

[0144] The sampling location determination module is used to determine the location of a new sampling point in the first urban plot based on the sampling point location and centroid location of the first urban plot when the sampling weight is greater than a preset weight threshold and the area of ​​the first urban plot is greater than a preset area threshold.

[0145] The data sampling module is used to sample the carbon emission power density of the newly added sampling points based on the location of the newly added sampling points in the first urban plot, so as to update the sampling network of the first urban plot.

[0146] In one implementation, the first city is divided into multiple geographically distinct city blocks, and the sampling network of the first city includes the sampling networks of each of the city blocks. The method further includes:

[0147] The boundary carbon emission determination module is used to perform a weighted average of the carbon emission power densities of the two adjacent first city plots based on their respective data reliability and data integrity, so as to obtain the carbon emission power density of the boundary sampling point between the two adjacent first city plots.

[0148] The boundary interpolation module is used to interpolate the sampling network of the first city based on the carbon emission power density of the boundary sampling points between two adjacent first city plots.

[0149] The specific functions and examples of each module and submodule of the apparatus in this disclosure can be found in the relevant descriptions of the corresponding steps in the above method embodiments, and will not be repeated here.

[0150] The acquisition, storage, and application of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0151] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0152] Figure 4 This is a structural block diagram of an electronic device according to an embodiment of the present disclosure. Figure 4As shown, the electronic device includes a memory 410 and a processor 420. The memory 410 stores a computer program that can run on the processor 420. There can be one or more memories 410 and processors 420. The memory 410 can store one or more computer programs, which, when executed by the electronic device, cause the electronic device to perform the methods provided in the above-described method embodiments. The electronic device may also include a communication interface 430 for communicating with external devices and performing data exchange and transmission.

[0153] If the memory 410, processor 420, and communication interface 430 are implemented independently, they can be interconnected via a bus to communicate with each other. This bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0154] Optionally, in a specific implementation, if the memory 410, processor 420 and communication interface 430 are integrated on a single chip, the memory 410, processor 420 and communication interface 430 can communicate with each other through an internal interface.

[0155] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. General-purpose processors can be microprocessors or any conventional processor. It is worth noting that the processor can be a processor supporting Advanced Reduced Instruction Set Machines (ARM) architecture.

[0156] Further, optionally, the aforementioned memory may include read-only memory and random access memory, and may also include non-volatile random access memory. The memory may be volatile or non-volatile, or may include both. Non-volatile memory may include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which serves as an external cache. Many forms of RAM are available by way of example, but not limitation. Examples include Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct RAMBUS RAM (DR RAM).

[0157] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this disclosure are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line, DSL) or wireless (e.g., infrared, Bluetooth, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer, or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)). It is worth noting that the computer-readable storage media mentioned in this disclosure may be non-volatile storage media; in other words, they may be non-transient storage media.

[0158] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0159] In the description of the embodiments of this disclosure, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0160] In the description of the embodiments disclosed herein, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone.

[0161] In the description of embodiments of this disclosure, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of this disclosure, unless otherwise stated, "a plurality of" means two or more.

[0162] The above description is merely an exemplary embodiment of this disclosure and is not intended to limit this disclosure. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the protection scope of this disclosure.

Claims

1. A city block-level adaptive interpolation method for carbon emission power density, characterized in that, include: Based on the difference between the gradient vectors of the building development volume of each sampling point of the first urban plot, the position of the first interpolation sampling point in the sampling network of the first urban plot is determined, wherein the building development volume of the sampling point is the ratio of the building area to the base area of ​​the sampling point. The carbon emission power density of the first interpolation sampling point is determined based on the carbon emission power density of multiple first neighboring sampling points of the first interpolation sampling point and the slope of the change of the carbon emission power density of the multiple first neighboring sampling points. Based on the location of the first interpolation sampling point and the carbon emission power density, the sampling network of the first urban plot is interpolated; the determination of the location of the first interpolation sampling point in the sampling network of the first urban plot based on the difference between the gradient vectors of building development at each sampling point in the first urban plot includes: If the maximum value of the gradient vector in the gradient vector of the building development volume of each sampling point in the first urban plot is greater than a preset gradient vector threshold, the following interpolation operation is performed: the position of the second interpolation sampling point is determined in the direction of the maximum value of the gradient vector; based on the building development volume of the neighboring sampling points of the second interpolation sampling point, the building development volume of the second interpolation sampling point and the gradient vector of the building development volume of the second interpolation sampling point are determined, and the gradient vector of the neighboring sampling points of the second interpolation sampling point is re-determined to re-determine the maximum value of the gradient vector, and it is determined whether to return to continue performing the interpolation operation; If the maximum value of the redefined gradient vector is less than the gradient vector threshold, the interpolation operation is stopped, and the position of the first interpolation sampling point is determined based on the position of each of the second interpolation sampling points.

2. The method according to claim 1, characterized in that, Also includes: Based on the first direction where the change in carbon emission power density of the first urban plot is most gradual, the local principal direction angle of the first urban plot is determined. Based on the local principal direction angle, a local orthogonal principal direction coordinate system is constructed with the first neighboring sampling point as the origin. Based on the slope of the change in carbon emission power density of multiple second neighboring sampling points in the horizontal direction of the local orthogonal principal direction coordinate system, the slope of the change in carbon emission power density of the first neighboring sampling point in the horizontal direction is determined; and based on the slope of the change in carbon emission power density of multiple third neighboring sampling points in the vertical direction of the local orthogonal principal direction coordinate system, the slope of the change in carbon emission power density of the first neighboring sampling point in the vertical direction is determined. The slope of the carbon emission power density change of the first neighboring sampling point in the horizontal and vertical directions of the local orthogonal principal direction coordinate system is converted into the slope of the carbon emission power density change of the first neighboring sampling point in the horizontal and vertical directions of the world coordinate system. The slope of the change in carbon emission power density of the first neighboring sampling point is determined based on the slope of the change in carbon emission power density of the first neighboring sampling point in the horizontal and vertical directions of the world coordinate system.

3. The method according to claim 2, characterized in that, The step of converting the slope of the carbon emission power density change of the first neighboring sampling point in the horizontal and vertical directions of the local orthogonal principal direction coordinate system into the slope of the carbon emission power density change of the first neighboring sampling point in the horizontal and vertical directions of the world coordinate system includes: Based on the carbon emission power density of each sampling point in the first urban plot, the anisotropy ratio is determined; Based on the anisotropy ratio, the slope of the carbon emission power density change of the first neighboring sampling point in the vertical direction of the local orthogonal principal direction coordinate system is scaled. The slope of carbon emission power density change of the first neighboring sampling point in the horizontal axis direction of the local orthogonal principal direction coordinate system and the scaled slope of carbon emission power density change in the vertical axis direction of the local orthogonal principal direction coordinate system are converted into the slope of carbon emission power density change of the first neighboring sampling point in the horizontal and vertical axes of the world coordinate system.

4. The method according to claim 3, characterized in that, The determination of the anisotropy ratio based on the carbon emission power density of each sampling point in the first urban plot includes: The anisotropy ratio is determined based on the ratio between the sum of carbon emission power densities of all sampling points in the first urban plot along the second direction and the sum of carbon emission power densities of all sampling points in the first urban plot along the first direction; wherein the second direction is the direction in which the emission power density of the first urban plot changes most drastically.

5. The method according to claim 4, characterized in that, Also includes: Based on the gradient vectors of building development at each sampling point in the first urban plot, a structure tensor matrix is ​​constructed. The element in the first row and first column of the structure tensor matrix is ​​the sum of the squares of the gradient vectors of the building development at each sampling point along the horizontal axis of the world coordinate system. The elements in the first row and second column and the elements in the second row and first column are the sum of the products of the gradient vectors of the building development at each sampling point along the horizontal axis of the world coordinate system and the gradient vectors along the vertical axis of the world coordinate system. The element in the second row and second column is the sum of the squares of the gradient vectors of the building development at each sampling point along the vertical axis of the world coordinate system. Construct eigenvalue equations for the structure tensor matrix; The eigenvalue equation is solved by eigenvalue analysis to obtain the first direction, the second direction, the sum of carbon emission power densities of all sampling points in the first urban plot in the first direction, and the sum of carbon emission power densities of all sampling points in the first urban plot in the second direction.

6. The method according to any one of claims 1-5, characterized in that, The plurality of first neighboring sampling points are three sampling points forming a triangle centered on the first interpolation sampling point. Determining the carbon emission power density of the first interpolation sampling point based on the carbon emission power density of the plurality of first neighboring sampling points and the slope of the change in the carbon emission power density of the plurality of first neighboring sampling points includes: Based on the coordinate positions of each of the first neighboring sampling points and the gravity coordinate constraint weights of the first interpolation sampling points relative to each of the first neighboring sampling points, the carbon emission power density weights and carbon emission power density change slope weights of each of the first neighboring sampling points are determined. Based on the carbon emission power density weights and carbon emission power density change slope weights of each of the first neighboring sampling points, the carbon emission power density and carbon emission power density change slope of each of the first neighboring sampling points are weighted and summed to obtain the carbon emission power density of the first interpolation sampling point.

7. The method according to any one of claims 1-5, characterized in that, The method further includes: Based on the historical electricity consumption fluctuation variance, intraday peak-valley load ratio and building volume ratio of the first urban plot, the sampling weight of the first urban plot is determined. If the sampling weight is greater than a preset weight threshold and the area of ​​the first urban plot is greater than a preset area threshold, the location of the new sampling point of the first urban plot is determined based on the sampling point location and centroid location of the first urban plot. Based on the location of the newly added sampling points in the first urban plot, carbon emission power density data are sampled from the newly added sampling points to update the sampling network of the first urban plot.

8. The method according to any one of claims 1-5, characterized in that, The first city is divided into multiple geographically distinct city blocks. The sampling network of the first city includes the sampling networks of each city block. The method further includes: Based on the data reliability and data integrity of each of the two adjacent first city plots, the carbon emission power density of each of the two adjacent first city plots is weighted and averaged to obtain the carbon emission power density of the boundary sampling point between the two adjacent first city plots. The sampling network of the first city is interpolated based on the carbon emission power density of the boundary sampling points between two adjacent first city plots.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.

Images