Carbon emission space distribution inversion method, device, equipment and storage medium

Abstract

The present application provides a kind of carbon emission space distribution inversion method, device, equipment and storage medium, comprising: obtaining the multi-source data and night light data of target area;Based on multi-source data and each carbon emission evaluation index of target area, the carbon emission potential value of each vector plot in target area is calculated;Based on night light data, the total carbon emission is calculated;Based on the total carbon emission and the carbon emission potential value of each vector plot, the carbon emission of each vector plot is distributed, and the carbon emission space distribution result is obtained.The present application constructs carbon emission evaluation index under micro scale, so as to calculate the carbon emission potential value of each vector plot in target area based on multi-source data, and then based on the total carbon emission of target area and the carbon emission potential value of each vector plot, the spatial distribution inversion of urban carbon emission on micro scale is carried out, which improves the accuracy of urban micro scale carbon emission space distribution inversion.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon emission, and particularly relates to a carbon emission space distribution inversion method, device, equipment and storage medium. BACKGROUND

[0002] Nowadays, global warming gradually becomes one of the major challenges faced by people in the social sustainable development, and the city, as the main carrier of human production and life, is also the main carrier of carbon emission. Therefore, the detailed space distribution inversion of urban carbon emission can assist city managers to effectively adjust the low-carbon development plan of the city.

[0003] The existing research on urban carbon emission is mostly limited to the macro level, and mainly uses VIIRS-NPP night light data to make up for the defects of timeliness and accuracy of energy consumption statistical data. However, the spatial resolution of the night light data currently used is about 500 m, which is difficult to be detailed to a more fine scale (such as a plot or a community), that is, it is difficult to perform space distribution inversion of urban carbon emission at a micro scale. SUMMARY

[0004] The present application provides a carbon emission space distribution inversion method, device, equipment and storage medium, which aims to realize the space distribution inversion of urban carbon emission at a micro scale and improve the accuracy of the space distribution inversion of urban carbon emission.

[0005] The present application provides a carbon emission space distribution inversion method, which comprises:

[0006] obtaining multi-source data and night light data of a target region;

[0007] calculating carbon emission potential values of each vector plot in the target region based on the multi-source data and each carbon emission evaluation index of the target region;

[0008] calculating the total carbon emission of the target region based on the night light data;

[0009] distributing carbon emission of each vector plot based on the total carbon emission of the target region and the carbon emission potential values of each vector plot, and obtaining the carbon emission space distribution result of the target region.

[0010] Optionally, according to the carbon emission space distribution inversion method provided by the present application, the calculation of the carbon emission potential values of each vector plot in the target region based on the multi-source data and each carbon emission evaluation index of the target region comprises:

[0011] calculating the index calculation value of each carbon emission evaluation index in each vector plot based on the multi-source data;

[0012] respectively, the index calculation value of each carbon emission evaluation index in each of the vector land blocks is standardized to obtain the index standardized value of each carbon emission evaluation index in each of the vector land blocks;

[0013] The index weight of each carbon emission evaluation index is calculated through a preset analytic hierarchy process algorithm.

[0014] Based on the index standardized value of each carbon emission evaluation index in each of the vector land blocks and the index weight of each carbon emission evaluation index, the carbon emission potential value of each vector land block is calculated.

[0015] Optionally, according to the carbon emission spatial distribution inversion method provided by the application, the carbon emission potential value of each vector land block is calculated based on the index standardized value of each carbon emission evaluation index in each of the vector land blocks and the index weight of each carbon emission evaluation index, which comprises:

[0016] For any one of the vector land blocks, the index standardized value of each carbon emission evaluation index in the vector land block is multiplied by the index weight of each carbon emission evaluation index to obtain the target value of each carbon emission evaluation index.

[0017] The target value of each carbon emission evaluation index in each of the vector land blocks is accumulated to obtain the carbon emission potential value of each vector land block.

[0018] Optionally, according to the carbon emission spatial distribution inversion method provided by the application, the index calculation value of each carbon emission evaluation index in each of the vector land blocks is standardized to obtain the index standardized value of each carbon emission evaluation index in each of the vector land blocks, which comprises:

[0019] For any one of the carbon emission evaluation indexes, based on the index calculation value of the carbon emission evaluation index in each vector land block, the maximum value and the minimum value corresponding to the carbon emission evaluation index are determined.

[0020] Based on the maximum value and the minimum value corresponding to the carbon emission evaluation index, the index calculation value of the carbon emission evaluation index in each vector land block is standardized to obtain the index standardized value of each carbon emission evaluation index.

[0021] Optionally, according to the carbon emission spatial distribution inversion method provided by the application, the carbon emission evaluation index at least comprises a factory density index, a population distribution density index, a road network density index, a user energy consumption index and a point of interest accessibility index.

[0022] The multi-source data at least includes factory distribution data, vector plot data, population signaling data, traffic network data, user energy consumption data, and point of interest location data.

[0023] Optionally, the carbon emission space distribution inversion method provided in the present application further comprises, before the total carbon emission of the target region is calculated based on the night light data of the target region:

[0024] Obtaining sample night light data and urban carbon emission of different sample regions;

[0025] Based on the sample night light data, the total night light brightness of each sample region is counted.

[0026] Based on the sample night light total brightness of each sample region and the urban carbon emission, a target fitting equation is constructed.

[0027] Optionally, the carbon emission space distribution inversion method provided in the present application, the total carbon emission of the target region is calculated based on the night light data, comprising:

[0028] Based on the night light data of the target region, the target night light total brightness of the target region is counted.

[0029] Based on the target night light total brightness and the target fitting equation, the total carbon emission of the target region is calculated.

[0030] The present application also provides a carbon emission space distribution inversion device, comprising:

[0031] An acquisition module is configured to acquire multi-source data and night light data of a target region.

[0032] A first calculation module is configured to calculate carbon emission potential values of each vector plot in the target region based on the multi-source data and each carbon emission evaluation index of the target region.

[0033] A second calculation module is configured to calculate the total carbon emission of the target region based on the night light data.

[0034] An inversion module is configured to allocate carbon emission to each vector plot based on the total carbon emission of the target region and the carbon emission potential values of each vector plot, so as to obtain a carbon emission space distribution result of the target region.

[0035] The present application also provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the carbon emission space distribution inversion method as described above when executing the program.

[0036] The application further provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the carbon emission space distribution inversion method according to any one of the above.

[0037] The application further provides a computer program product comprising a computer program which, when executed by a processor, implements the carbon emission space distribution inversion method according to any one of the above.

[0038] The carbon emission space distribution inversion method, device, equipment and storage medium provided by the application can calculate the carbon emission potential value of each vector land in the target region based on multi-source data by constructing a carbon evaluation index system in the city, and then inversely calculate the spatial distribution of carbon emission in the city at a micro scale based on the total carbon emission of the target region and the carbon emission potential value of each vector land, thereby improving the accuracy of the carbon emission space distribution inversion at a micro scale in the city. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description one by one. Obviously, the drawings in the following description are some embodiments of the application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0040] Figure 1 is a flowchart of the carbon emission space distribution inversion method provided by the application;

[0041] Figure 2 is a hierarchical structure diagram of each carbon emission evaluation index in the carbon emission space distribution inversion method provided by the application;

[0042] Figure 3 is a schematic diagram of the weight discrimination matrix provided by an embodiment of the application;

[0043] Figure 4 is a structural schematic diagram of the carbon emission space distribution inversion device provided by the application;

[0044] Figure 5 is a structural schematic diagram of the electronic equipment provided by the application. DETAILED DESCRIPTION

[0045] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below in combination with the drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present application.

[0046] The terminology used in this disclosure of one or more embodiments is for the purpose of describing particular embodiments only and is not intended to be limiting of one or more embodiments of the present application. As used in this disclosure the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0047] It will be understood that, although the terms first, second, etc. can be used herein to describe various information, these terms are not intended to denote a temporal sequence. Rather, these terms are used only as distinguish one from another. For example, without departing from the scope of one or more embodiments, first can be termed second, and similarly, second can be termed first. The term "if can be construed to mean "when" or "upon" or "responsive to" depending on the context, as used herein.

[0048] The technical solutions of the present application will be described below in combination with Figures 1-2 The example embodiments of the present application are described in detail.

[0049] Figure 1 is a flowchart of the carbon emission space distribution inversion method provided by the present application. As shown in the figure, the carbon emission space distribution inversion method comprises: Figure 1

[0050] Step 11, obtaining multi-source data and night light data of a target region;

[0051] ​It should be noted that the multi-source data includes factory distribution data, vector land data, population signaling data, traffic network data, user energy consumption data and point of interest location data, etc. Among them, the user signaling data and the user energy consumption data are used to measure the carbon emissions generated by the residents' life energy consumption in different areas of the city, the factory distribution data is used to measure the carbon emissions of the city industrial production, the road network data is used to measure the carbon emissions generated by the city transportation, the point of interest data is used to measure the third industry and public transportation carbon emissions generated by various infrastructures and bus stations, and the vector land is the smallest unit and carrier of the spatial distribution of carbon emissions on the microscopic scale. The night light data (VIIRS-NPP) is an average radiation composite remote sensing image data made of the night data of the day / night band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS).

[0052] Step 12, based on the multi-source data and the carbon emission evaluation indexes of the target area, the carbon emission potential value of each vector land in the target area is calculated.

[0053] It should be noted that by selecting corresponding quantifiable spatial feature indexes (that is, the carbon emission evaluation indexes in the embodiment) from three main carbon emission sources of industrial emission, traffic emission and resident life consumption, the selected indexes can express the main carbon emissions in the city to a certain extent.

[0054] In the embodiment of the application, the carbon emission evaluation indexes include factory density index, population distribution density index, road network density index, user energy consumption index, point of interest accessibility index and the like. Among them, the user energy consumption index includes garbage production index, and the point of interest accessibility index includes commercial center accessibility index, bus station accessibility index, infrastructure accessibility index and subway station accessibility index.

[0055] Specifically, based on the multi-source data, each carbon emission evaluation index in each of the vector plots is quantitatively processed to obtain an index calculation value of each carbon emission evaluation index in each of the vector plots, and further, the index calculation value of each carbon emission evaluation index in each of the vector plots is standardized to the interval of 0-1 to obtain an index standardized value of each carbon emission evaluation index in each of the vector plots. In addition, in this embodiment, data such as energy consumption of each industry in the target area is obtained, and the proportion of different carbon emission sources in the city is calculated, wherein the carbon emission sources generated by the city mainly include industrial emission, traffic emission and residential consumption, and then based on the proportion of different carbon emission sources, each carbon emission evaluation index is scored to calculate the index weight of each carbon emission evaluation index. Further, the index standardized value of each carbon emission evaluation index in each of the vector plots is multiplied by the index weight of each carbon emission evaluation index, and the results of multiplying each carbon emission evaluation index in each of the vector plots are accumulated to obtain the carbon emission potential value of each of the vector plots.

[0056] Step 13, based on the night light data, the total carbon emission of the target area is calculated.

[0057] Specifically, before calculating the total carbon emission of the target area, the night light data corresponding to different urban areas and the carbon emission of the city are obtained, the carbon emission of the city is the annual carbon emission of the city, and then based on the night light data corresponding to different urban areas, the total night light brightness of the urban area in a year is counted, and then based on the total night light brightness of different urban areas and the carbon emission of the city, a fitting relationship between the total night light brightness and the carbon emission of the city is constructed, and further, based on the night light data of the target area and the fitting relationship, the total carbon emission of the target area is calculated.

[0058] It should be noted that the execution order of steps 13 and 12 is not specifically limited, and step 12 can be executed first and then step 13, or step 12 can be executed first and then step 13.

[0059] Step 14, based on the total carbon emission of the target area and the carbon emission potential value of each of the vector plots, the carbon emission of each of the vector plots is distributed to obtain the carbon emission spatial distribution result of the target area.

[0060] It should be noted that the carbon emission potential value represents the potential proportion of the carbon emission corresponding to each vector plot.

[0061] Specifically, based on the total carbon emission amount of the target region, and in combination with the carbon emission potential value of each vector land block in the vector land block, carbon emission distribution is performed for each vector land block. As an implementable manner, the potential proportion between each vector land block can be determined based on the carbon emission potential value of each vector land block, and then the total carbon emission amount is distributed according to the potential proportion to obtain the carbon emission spatial distribution result of the target region.

[0062] The embodiment of the present application realizes the construction of the carbon evaluation index system at the urban micro scale by the above scheme, thereby calculating the carbon emission potential value of each vector land block in the target region based on the multi-source data, and then performing spatial distribution inversion of urban carbon emission at the micro scale based on the total carbon emission amount of the target region and the carbon emission potential value of each vector land block, thereby improving the accuracy of the spatial distribution inversion of urban carbon emission.

[0063] In one embodiment, the carbon emission potential value of each vector land block in the target region is calculated based on the multi-source data and each carbon emission evaluation index of the target region, which includes:

[0064] Based on the multi-source data, the index calculation value of each carbon emission evaluation index in each vector land block is calculated; the index calculation value of each carbon emission evaluation index in each vector land block is standardized respectively to obtain the index standardized value of each carbon emission evaluation index in each vector land block; the index weight of each carbon emission evaluation index is calculated by a preset analytic hierarchy process algorithm; and the carbon emission potential value of each vector land block is calculated based on the index standardized value of each carbon emission evaluation index in each vector land block and the index weight of each carbon emission evaluation index.

[0065] It should be noted that the carbon emission of a city is mainly composed of industrial emission, traffic emission, and resident life consumption, and the difference in carbon emission of different cities is mainly caused by population distribution density, industrial structure, energy intensity, etc., and then quantifiable spatial feature indexes can be selected from the three main carbon emission sources of industrial emission, traffic emission, and resident life consumption.

[0066] Specifically, the following steps are performed for any one of the vector land blocks:

[0067] For the road network density index: the vector land block is divided into a plurality of grids with the same area, and then the total length of the traffic road network in each grid is counted, and the road network density of each grid is calculated based on the total length of the traffic road network in each grid and the area of the grid, and then the road network density of each grid is superimposed to obtain the index calculation value of the road network density index of the vector land block, wherein the calculation method of the road network density of each grid is as follows:

[0068]

[0069] D road represents the density of the road network, Line total represents the total length of the traffic network, and S represents the area of the grid.

[0070] For the population distribution density index: the vector land is divided into a plurality of grids, the number of users in each grid is counted based on the user signaling data of each grid, and then the number of users in each grid is superimposed to obtain the index calculation value of the population density index of the vector land.

[0071] For the factory density index: the number of factories in the vector land is counted by spatial statistics or other methods to obtain the index calculation value of the factory density index of the vector land.

[0072] For the user energy consumption index: the consumption of electricity, heat, gas and the like of residents in all buildings in the vector land is counted, and the consumption is taken as the index calculation value of the user energy consumption index.

[0073] For the point of interest accessibility index: the distance between each type of point of interest and the center position of the vector land is calculated, and the nearest distance is selected as the index calculation value of the point of interest accessibility index. For example, for a bus station, the distance between each bus station and the center position of the vector land is calculated, and the nearest distance is selected as the index calculation value of the point of interest accessibility index.

[0074] Further, the index calculation value of each carbon emission evaluation index in each vector land is standardized, wherein the standardization is standardized in the interval of 0 to 1, thereby obtaining the index standardization value of each carbon emission evaluation index in each vector land. As shown in Figure 2 Figure 2 is a hierarchical structure diagram of each carbon emission evaluation index in the carbon emission spatial distribution inversion method provided by the application. First, the statistical data of the target region and the energy consumption of each industry are obtained, thereby determining the proportion of three main carbon emission sources of industrial emission, traffic emission and residential consumption, and then based on the proportion, the importance degree between each carbon emission evaluation index is compared, and the importance degree between two carbon emission evaluation indexes is expressed by a numerical value, thereby constructing a weight discrimination matrix corresponding to each carbon emission evaluation index, as shown in Figure 3 Figure 3 is a schematic diagram of the weight discrimination matrix provided by an embodiment of the application, thereby calculating the index weight of each carbon emission evaluation index based on the weight discrimination matrix, wherein the method for calculating the index weight includes arithmetic mean method, geometric mean method and eigenvalue method.​​

[0075] Further, the index standardized value of each carbon emission evaluation index in the vector plot is multiplied by the index weight of each carbon emission evaluation index, and the multiplied result is superimposed to obtain the carbon emission potential value of the vector plot.

[0076] The embodiment of the present application realizes that the index calculation values of each carbon emission evaluation index in different vector plots in a target region can be calculated according to different target regions, and the weights of each carbon emission evaluation index can be calculated through the analytic hierarchy process algorithm, so that the spatial distribution of carbon emission in the city can be simulated more accurately.

[0077] In one embodiment, the index calculation values of each carbon emission evaluation index in each vector plot are standardized to obtain the index standardized value of each carbon emission evaluation index in each vector plot, including:

[0078] For any one of the carbon emission evaluation indexes, the maximum value and the minimum value corresponding to the carbon emission evaluation index are determined based on the index calculation values of the carbon emission evaluation index in each vector plot, and the index calculation values of the carbon emission evaluation index in each vector plot are standardized to obtain the index standardized value of each carbon emission evaluation index.

[0079] Specifically, the following steps are performed for any one of the carbon emission evaluation indexes:

[0080] The maximum value and the minimum value corresponding to the carbon emission evaluation index are determined based on the index calculation values of the carbon emission evaluation index in each vector plot, and each index calculation value of the carbon emission evaluation index is standardized based on the maximum value and the minimum value corresponding to the carbon emission evaluation index and each index calculation value to be standardized, to obtain the index standardized value of each carbon emission evaluation index in the vector plot, wherein the formula of the standardization processing is as follows:

[0081] Ii=(Xmax-Xi) / (Xmax-Xmin)

[0082] Ii=(Xmax-Xi) / (Xmax-Xmin)

[0083] Wherein, Ii represents the index standardized value, Xi represents the index calculation value to be standardized, Xmax represents the maximum value, and Xmin represents the minimum value.

[0084] The embodiment of the present application realizes the standardization processing of the index calculation values of the carbon emission evaluation indexes of different vector blocks in the city micro scale, so as to accurately simulate the spatial distribution of the carbon emission in the city.

[0085] In one embodiment, the carbon emission potential value of each vector block is calculated based on the index standardized values of each carbon emission evaluation index in each vector block and the index weights of each carbon emission evaluation index, comprising:

[0086] For any one of the vector blocks, the index standardized values of each carbon emission evaluation index in the vector block are multiplied by the index weights of each carbon emission evaluation index to obtain the target values of each carbon emission evaluation index; the target values of each carbon emission evaluation index in each vector block are respectively accumulated to obtain the carbon emission potential value of each vector block.

[0087] Specifically, the following steps are performed for any one of the vector blocks:

[0088] Further, the index standardized values of each carbon emission evaluation index in each vector block are respectively multiplied by the index weights of each carbon emission evaluation index to obtain the target values of each carbon emission evaluation index in the vector block, and then the target values of each carbon emission evaluation index in each vector block are respectively accumulated to obtain the carbon emission potential value of each vector block, thereby obtaining the carbon emission potential value of the vector block. The carbon emission potential value calculation formula is as follows:

[0089]

[0090] Wherein, Cp represents the carbon emission potential value of the vector block, Ii represents the standardized value of the i-th carbon emission evaluation index, and Wi represents the index weight of the carbon emission evaluation index.

[0091] The embodiment of the present application obtains the carbon emission potential value of each vector block in the region by the weight of each carbon emission evaluation index in each vector block and the index weight of each carbon emission evaluation index, so as to accurately invert the spatial distribution of the carbon emission in the city at the micro scale.

[0092] In one embodiment, before the total carbon emission is calculated based on the nighttime light data of the target region, the method further comprises:

[0093] Obtain the nighttime light data of different sample regions and the carbon emission of the city; based on the nighttime light data of the different sample regions, the total nighttime light brightness of each sample region is counted; based on the total nighttime light brightness of each sample region and the carbon emission of the city, a target fitting equation is constructed.

[0094] It should be noted that the annual carbon emission data of each prefecture provided by the CEADs China Carbon Accounting Database, the energy consumption of each industry in the city, can be used to extract the carbon emission of each city, and the city carbon emission is the annual carbon emission in the sample area.

[0095] Specifically, since there is a linear relationship between the total night light intensity in the night light data and the city carbon emission, in the embodiment of the application, a plurality of prefectures are used as sample areas, and then the night light data and the city carbon emission of different sample areas are obtained, and then based on the night light data of the different sample areas, the total night light intensity of each sample area is counted, and further, based on the total night light intensity and the city carbon emission of each sample area, a target fitting equation is constructed, so that the total carbon emission of the target area can be obtained by substituting the total night light intensity corresponding to the night light data of the target area into the target fitting equation, wherein the expression of the target fitting equation is as follows:

[0096] C=k*T DN

[0097] Wherein, T DN represents the total night light intensity of the sample area, C represents the city carbon emission of the sample area, and k represents a constant.

[0098] The embodiment of the application constructs the target fitting equation between the total night light intensity of each city and the city carbon emission, so that when the total night light intensity of a certain area is obtained, the corresponding city carbon emission can be calculated, which lays a foundation for the inversion of the spatial distribution of carbon emission.

[0099] The carbon emission spatial distribution inversion device provided by the application is described below, and the carbon emission spatial distribution inversion device described below can be correspondingly referred to the carbon emission spatial distribution inversion method described above.

[0100] Figure 4 The structure diagram of the carbon emission spatial distribution inversion device provided by the application is shown in FIG. 1, and the carbon emission spatial distribution inversion device of the embodiment of the application comprises: Figure 4

[0101] The acquisition module 41 is configured to acquire multi-source data and night light data of a target area.

[0102] The first calculation module 42 is configured to calculate the carbon emission potential value of each vector land block in the target area based on the multi-source data and each carbon emission evaluation index of the target area.

[0103] ​The second calculation module 43 is configured to calculate the total carbon emission of the target region based on the night light data.

[0104] The inversion module 44 is configured to allocate the carbon emission of each vector land parcel based on the total carbon emission of the target region and the carbon emission potential value of each vector land parcel, to obtain the carbon emission spatial distribution result of the target region.

[0105] The first calculation module 42 is further configured to:

[0106] The index calculation value of each carbon emission evaluation index in each vector land parcel is calculated based on the multi-source data.

[0107] The index standardization value of each carbon emission evaluation index in each vector land parcel is obtained by standardizing the index calculation value of each carbon emission evaluation index in each vector land parcel.

[0108] The index weight of each carbon emission evaluation index is calculated by a preset analytic hierarchy process algorithm.

[0109] The carbon emission potential value of each vector land parcel is calculated based on the index standardization value of each carbon emission evaluation index in each vector land parcel and the index weight of each carbon emission evaluation index.

[0110] The first calculation module 42 is further configured to:

[0111] For any one carbon emission evaluation index, the maximum value and the minimum value corresponding to the carbon emission evaluation index are determined based on the index calculation value of the carbon emission evaluation index in each vector land parcel.

[0112] The index standardization value of each carbon emission evaluation index is obtained by standardizing the index calculation value of the carbon emission evaluation index in each vector land parcel based on the maximum value and the minimum value corresponding to the carbon emission evaluation index.

[0113] The first calculation module 42 is further configured to:

[0114] For any one vector land parcel, the target value of each carbon emission evaluation index is obtained by multiplying the index standardization value of each carbon emission evaluation index in the vector land parcel with the index weight of each carbon emission evaluation index.

[0115] The carbon emission potential value of each vector land parcel is obtained by accumulating the target value of each carbon emission evaluation index in each vector land parcel.

[0116] The carbon emission spatial distribution inversion device further comprises:

[0117] The carbon emission evaluation index at least includes a factory density index, a population distribution density index, a road network density index, a user energy consumption index, and a point of interest accessibility index.

[0118] The multi-source data at least includes factory distribution data, vector land data, population signaling data, traffic road network data, user energy consumption data, and point of interest location data.

[0119] The carbon emission space distribution inversion device further comprises:

[0120] Sample night light data of different sample areas and urban carbon emission are obtained.

[0121] Based on the sample night light data, total night light brightness of each sample area is counted.

[0122] Based on the sample night light total brightness of each sample area and the urban carbon emission, a target fitting equation is constructed.

[0123] The second calculation module 43 further comprises:

[0124] Based on the target area night light data, target total night light brightness of the target area is counted.

[0125] Based on the target total night light brightness and the target fitting equation, total carbon emission of the target area is calculated.

[0126] It should be noted that the above device provided by the embodiment of the present application can realize all method steps realized by the method embodiment, and can achieve the same technical effect, and the same part and beneficial effect of the method embodiment in this embodiment will not be described in detail.

[0127] Figure 5 is a structural schematic diagram of an electronic device provided by the present application, such as Figure 5As shown, the electronic device can include a processor 510, a memory 520, a communications interface 530, and a communications bus 540, wherein the processor 510, the memory 520, and the communications interface 530 complete mutual communication through the communications bus 540. The processor 510 can invoke a logical instruction in the memory 520 to execute a carbon emission space distribution inversion method, which includes: acquiring multi-source data and night light data of a target region; based on the multi-source data and each carbon emission evaluation index of the target region, calculating a carbon emission potential value of each vector land parcel in the target region; based on the night light data, calculating a total carbon emission amount of the target region; based on the total carbon emission amount of the target region and the carbon emission potential value of each vector land parcel, distributing carbon emission of each vector land parcel to obtain a carbon emission space distribution result of the target region.

[0128] In addition, the logical instruction in the memory 520 described above can be implemented in the form of a software function unit and sold or used as an independent product, which can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0129] In yet another aspect, the present application also provides a non-transitory computer readable storage medium having a computer program stored thereon, which is executed by a processor to implement the carbon emission space distribution inversion method provided by the above-mentioned methods, which includes: acquiring multi-source data and night light data of a target region; based on the multi-source data and each carbon emission evaluation index of the target region, calculating a carbon emission potential value of each vector land parcel in the target region; based on the night light data, calculating a total carbon emission amount of the target region; based on the total carbon emission amount of the target region and the carbon emission potential value of each vector land parcel, distributing carbon emission of each vector land parcel to obtain a carbon emission space distribution result of the target region.

[0130] In another aspect, the present application also provides a computer program product comprising a computer program, the computer program being stored in a non-transitory computer-readable storage medium, and the computer program being capable of executing the carbon emission space distribution inversion method provided by the above method when executed by a processor, the method comprising: obtaining multi-source data and night light data of a target region; calculating carbon emission potential values of each vector land parcel in the target region based on the multi-source data and each carbon emission evaluation index of the target region; calculating a total carbon emission amount of the target region based on the night light data; and distributing carbon emissions of each vector land parcel based on the total carbon emission amount of the target region and the carbon emission potential values of each vector land parcel to obtain a carbon emission space distribution result of the target region.

[0131] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0132] From the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be realized by means of software and necessary general hardware platforms, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of software products, which can be stored in a computer readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and include a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0133] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of carbon emission space distribution inversion, characterized in that, The method comprises the following steps: obtaining multi-source data of a target region and night light data; calculating carbon emission potential values of each vector land block in the target region based on the multi-source data and each carbon emission evaluation index of the target region, including: calculating index calculation values of each carbon emission evaluation index in each vector land block based on the multi-source data; respectively performing standardization processing on the index calculation values of each carbon emission evaluation index in each vector land block to obtain index standardized values of each carbon emission evaluation index in each vector land block; calculating index weights of each carbon emission evaluation index through a preset analytic hierarchy process algorithm; calculating the carbon emission potential values of each vector land block based on the index standardized values of each carbon emission evaluation index in each vector land block and the index weights of each carbon emission evaluation index; calculating a total carbon emission amount of the target region based on the night light data; distributing carbon emissions of each vector land block based on the total carbon emission amount of the target region and the carbon emission potential values of each vector land block to obtain a carbon emission spatial distribution result of the target region; the calculation of the carbon emission potential values of each vector land block based on the index standardized values of each carbon emission evaluation index in each vector land block and the index weights of each carbon emission evaluation index comprises: for any one vector land block, multiplying the index standardized values of each carbon emission evaluation index in the vector land block by the index weights of each carbon emission evaluation index to obtain target values of each carbon emission evaluation index; respectively performing accumulation processing on the target values of each carbon emission evaluation index in each vector land block to obtain the carbon emission potential values of each vector land block.

2. The carbon emission spatial distribution inversion method according to claim 1, characterized in that, the standardization processing of the index calculation values of each carbon emission evaluation index in each vector land block comprises: for any one carbon emission evaluation index, determining a maximum value and a minimum value corresponding to the carbon emission evaluation index based on the index calculation values of the carbon emission evaluation index in each vector land block; respectively performing standardization processing on the index calculation values of the carbon emission evaluation index in each vector land block based on the maximum value and the minimum value corresponding to the carbon emission evaluation index to obtain the index standardized values of each carbon emission evaluation index.

3. The carbon emission spatial distribution inversion method of claim 1, wherein, the carbon emission evaluation index at least comprises a factory density index, a population distribution density index, a road network density index, a user energy consumption index, and a point of interest accessibility index; the multi-source data at least comprises factory distribution data, vector land block data, population signaling data, traffic road network data, user energy consumption data, and point of interest location data.

4. The carbon emission spatial distribution inversion method of claim 1, wherein, before the calculation of the total carbon emission amount based on the night light data of the target region, the method further comprises the following steps: obtaining sample night light data and urban carbon emission amounts of different sample regions; statistically obtaining total night light brightnesses of the sample regions based on the sample night light data; Based on the total night light brightness of each sample area and the urban carbon emission, a target fitting equation is constructed.

5. The carbon emission spatial distribution inversion method according to claim 4, characterized in that, The total carbon emission of the target area is calculated based on the night light data, including: Based on the night light data of the target area, the total night light brightness of the target area is counted; Based on the total night light brightness of the target area and the target fitting equation, the total carbon emission of the target area is calculated.

6. A carbon emission space distribution inversion apparatus characterized by comprising: It includes: An acquisition module is configured to acquire multi-source data and night light data of a target area; A first calculation module is configured to calculate carbon emission potential values of each vector land parcel in the target area based on the multi-source data and each carbon emission evaluation index of the target area, including: calculating index calculation values of each carbon emission evaluation index in each vector land parcel based on the multi-source data; performing standardization processing on the index calculation values of each carbon emission evaluation index in each vector land parcel to obtain index standardized values of each carbon emission evaluation index in each vector land parcel; calculating index weights of each carbon emission evaluation index through a preset analytic hierarchy process algorithm; and calculating carbon emission potential values of each vector land parcel based on the index standardized values of each carbon emission evaluation index in each vector land parcel and the index weights of each carbon emission evaluation index; A second calculation module is configured to calculate the total carbon emission of the target area based on the night light data; An inversion module is configured to perform carbon emission distribution on each vector land parcel based on the total carbon emission of the target area and the carbon emission potential values of each vector land parcel to obtain a carbon emission spatial distribution result of the target area. The carbon emission potential values of each vector land parcel are calculated based on the index standardized values of each carbon emission evaluation index in each vector land parcel and the index weights of each carbon emission evaluation index, including: for any one vector land parcel, multiplying the index standardized values of each carbon emission evaluation index in the vector land parcel by the index weights of each carbon emission evaluation index to obtain target values of each carbon emission evaluation index; and performing accumulation processing on the target values of each carbon emission evaluation index in each vector land parcel to obtain the carbon emission potential values of each vector land parcel.

7. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the carbon emission spatial distribution inversion method according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the carbon emission spatial distribution inversion method according to any one of claims 1 to 5.

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