CN115689337A - Carbon emission spatial distribution inversion method, device, equipment and storage medium - Google Patents
Carbon emission spatial distribution inversion method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN115689337A CN115689337A CN202211249117.4A CN202211249117A CN115689337A CN 115689337 A CN115689337 A CN 115689337A CN 202211249117 A CN202211249117 A CN 202211249117A CN 115689337 A CN115689337 A CN 115689337A
- Authority
- CN
- China
- Prior art keywords
- carbon emission
- index
- target area
- vector plot
- evaluation index
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Circuit Arrangement For Electric Light Sources In General (AREA)
Abstract
The invention provides a carbon emission space distribution inversion method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring multi-source data and night light data of a target area; calculating to obtain the carbon emission potential value of each vector plot in the target area based on the multi-source data and each carbon emission evaluation index of the target area; calculating to obtain the total carbon emission based on the night light data; and distributing the carbon emission to each vector plot based on the total carbon emission amount and the carbon emission potential value of each vector plot to obtain a carbon emission space distribution result. According to the method, the carbon emission evaluation index is constructed under the microscale, so that the carbon emission potential value of each vector plot in the target area is calculated based on multi-source data, and further, the spatial distribution inversion of the urban carbon emission is carried out on the microscale based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot, and the accuracy of the spatial distribution inversion of the urban microscale carbon emission is improved.
Description
Technical Field
The invention relates to the technical field of carbon emission, in particular to a carbon emission spatial distribution inversion method, a carbon emission spatial distribution inversion device, carbon emission spatial distribution inversion equipment and a storage medium.
Background
At present, global warming gradually becomes one of the major challenges facing the sustainable development of people society, and cities are used as main carriers of human production and life and carbon emission, and the detailed spatial distribution inversion is performed on the carbon emission of the cities, so that city managers can be assisted to make corresponding adjustment on the low-carbon development planning inside the cities.
The existing research on urban carbon emission is mostly confined on a macroscopic level, VIIRS-NPP night light data is mainly used for overcoming the defects of timeliness and insufficient precision of energy consumption statistical data, however, the spatial resolution of the night light data which is mostly used at present is about 500m, and the night light data is difficult to be detailed to a finer scale (such as a plot and a community), that is, the urban carbon emission is difficult to be subjected to spatial distribution inversion on a microscopic scale.
Disclosure of Invention
The invention provides a carbon emission spatial distribution inversion method, a device, equipment and a storage medium, aiming at realizing the inversion of the spatial distribution of urban carbon emission on the microscopic scale and improving the inversion accuracy of the urban carbon emission spatial distribution.
The invention provides a carbon emission space distribution inversion method, which comprises the following steps:
acquiring multi-source data and night light data of a target area;
calculating to obtain the carbon emission potential value of each vector plot in the target area based on the multi-source data and each carbon emission evaluation index of the target area;
calculating the total carbon emission amount of the target area based on the night light data;
and distributing the carbon emission to each vector plot based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot to obtain a carbon emission spatial distribution result of the target area.
Optionally, according to the inversion method for spatial distribution of carbon emission provided by the present invention, the calculating a carbon emission potential value of each vector parcel in the target area based on the multi-source data and each carbon emission evaluation index of the target area includes:
calculating to obtain an index calculation value of each carbon emission evaluation index in each vector plot based on the multi-source data;
respectively standardizing the index calculation value of each carbon emission evaluation index in each vector plot to obtain the index standardized value of each carbon emission evaluation index in each vector plot;
calculating index weight of each carbon emission evaluation index through a preset hierarchical analysis algorithm;
and calculating the carbon emission potential value of each vector plot based on the index standard value of each carbon emission evaluation index in each vector plot and the index weight of each carbon emission evaluation index.
Alternatively, according to the inversion method for spatial distribution of carbon emission provided in the present invention, the calculating a carbon emission potential value of each vector plot based on an index normalized value of each carbon emission evaluation index in each vector plot and an index weight of each carbon emission evaluation index includes:
for any vector plot, multiplying the index standard value of each carbon emission evaluation index in the vector plot by the index weight of each carbon emission evaluation index to obtain the target value of each carbon emission evaluation index;
and respectively accumulating the target values of the carbon emission evaluation indexes in each vector plot to obtain the carbon emission potential value of each vector plot.
Optionally, according to the inversion method of spatial distribution of carbon emissions provided by the present invention, the normalizing the index calculation value of each carbon emission evaluation index in each vector plot to obtain the index normalized value of each carbon emission evaluation index in each vector plot includes:
for any one carbon emission evaluation index, determining a maximum value and a minimum value corresponding to the carbon emission evaluation index based on index calculation values corresponding to the carbon emission evaluation index in each vector plot;
and respectively standardizing the index calculation values of the carbon emission evaluation indexes corresponding to the vector plots based on the maximum value and the minimum value corresponding to the carbon emission evaluation indexes to obtain the index standardized value of each carbon emission evaluation index.
Optionally, according to the inversion method of the spatial distribution of carbon emission provided by the present invention, the evaluation index of carbon emission at least includes a plant density index, a population distribution density index, a road network density index, a user energy consumption index, and a point of interest reachability index;
the multi-source data at least comprises factory distribution data, vector plot data, population signaling data, traffic network data, user energy consumption data and interest point position data.
Optionally, according to the inversion method of spatial distribution of carbon emissions provided by the present invention, before the calculating the total amount of carbon emissions based on the night light data of the target area, the method further includes:
acquiring night light data of samples in different sample areas and urban carbon emission;
counting the total night light brightness of each sample area based on the night light data of each sample;
and constructing and obtaining a target fitting equation based on the total night lamplight brightness of the samples in the sample areas and the urban carbon emission.
Optionally, according to the inversion method of spatial distribution of carbon emission provided by the present invention, the calculating the total amount of carbon emission in the target area based on the night light data includes:
counting the total target night light brightness of the target area based on the night light data of the target area;
and calculating to obtain the total carbon emission amount of the target area based on the target night lamplight total brightness and the target fitting equation.
The invention also provides a carbon emission spatial distribution inversion device, which comprises:
the acquisition module is used for acquiring multi-source data and night light data of the target area;
the first calculation module is used for calculating and obtaining the carbon emission potential value of each vector plot in the target area based on the multi-source data and each carbon emission evaluation index of the target area;
the second calculation module is used for calculating and obtaining the total carbon emission amount of the target area based on the night light data;
and the inversion module is used for distributing carbon emission to each vector plot based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot to obtain a carbon emission space distribution result of the target area.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the carbon emission spatial distribution inversion method as described in any one of the above.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for inversion of a spatial distribution of carbon emissions as described in any one of the above.
The present invention also provides a computer program product comprising a computer program which, when executed by a processor, implements a method for inverting a spatial distribution of carbon emissions as described in any one of the above.
According to the carbon emission spatial distribution inversion method, the device, the equipment and the storage medium, the carbon evaluation index system is constructed in the city, so that the carbon emission potential value of each vector plot in the target area is calculated based on multi-source data, and further, the spatial distribution inversion on the micro scale is carried out on the urban carbon emission based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot, so that the accuracy of the inversion of the urban micro-scale carbon emission spatial distribution is improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed to be used in the description of the embodiments or the prior art are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for inverting the spatial distribution of carbon emissions provided by the present invention;
FIG. 2 is a schematic diagram of a hierarchical structure of each carbon emission evaluation index in the carbon emission spatial distribution inversion method provided by the present invention;
FIG. 3 is a diagram illustrating a weight discrimination matrix according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an inversion apparatus for spatial distribution of carbon emissions provided by the present invention;
fig. 5 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the one or more embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of the invention. As used in one or more embodiments of the present invention, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present invention refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that, although the terms first, second, etc. may be used herein to describe various information in one or more embodiments of the present invention, such information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first can also be referred to as a second and, similarly, a second can also be referred to as a first without departing from the scope of one or more embodiments of the present invention. Depending on the context, the word "if" as used herein may be interpreted as "at" \8230; … "when" or "when 8230; \8230"; "when".
Exemplary embodiments of the present invention will be described in detail below with reference to fig. 1 to 2.
Fig. 1 is a schematic flow chart of a carbon emission spatial distribution inversion method provided by the present invention. As shown in fig. 1, the carbon emission spatial distribution inversion method includes:
step 11, acquiring multi-source data and night light data of a target area;
the multi-source data includes data such as factory distribution data, vector plot data, population signaling data, traffic network data, energy consumption data for users, and interest point location data. Wherein, the user signaling data and the user energy consumption data are used for measuring the carbon emission generated by the domestic living energy of different areas in the city, the factory distribution data are used for measuring the carbon emission generated by the city industrial production, the road network data are used for measuring the carbon emission generated by the city transportation, the interest point data is used for measuring the carbon emission of third industries and public transport generated by various infrastructures and bus stops, and the vector plot is used as the minimum unit and the carrier of the carbon emission space distribution on the micro scale. The night light data (VIIRS-NPP) is average radiation composite remote sensing image data produced by night data of a day/night band (DNB) of a Visible Infrared Imaging Radiometer Suite (Visible Infrared Imaging Radiometer Suite).
it should be noted that, by selecting the corresponding quantifiable spatial characteristic index (i.e., the carbon emission evaluation index in the embodiment) from three main carbon emission generation sources of industrial emission, traffic emission and residential life consumption, the selected index should be able to express the main carbon emission in the city to a certain extent.
In the embodiment of the present invention, the carbon emission evaluation index includes index information such as a plant density index, a population distribution density index, a road network density index, a user energy consumption index, a point of interest reachability index, and the like, wherein the user energy consumption index includes a garbage yield index, and the point of interest reachability index includes a business center reachability index, a bus stop reachability index, a basic setting reachability index, a subway stop reachability index, and the like.
Specifically, based on the multi-source data, each carbon emission evaluation index in each vector plot is quantized to obtain an index calculation value of each carbon emission evaluation index in each vector plot, further, the index calculation value of each carbon emission evaluation index in each vector plot is normalized to be within a range of 0-1, so that an index normalized value of each carbon emission evaluation index in each vector plot is obtained, additionally, in the present embodiment, data such as each industry energy consumption condition in the target area are obtained, and according to the proportion of different carbon emission sources inside a city, wherein the carbon emission sources generated by the city mainly include industrial emission, traffic emission and residential life consumption, further, based on the proportion of the different carbon emission sources, each carbon emission evaluation index is scored, so that an index weight of each carbon emission evaluation index is calculated, further, the index normalized value of each carbon emission evaluation index in each vector plot is multiplied by each weight of each carbon emission evaluation index, and each carbon emission evaluation index in each vector plot is accumulated, so that a potential carbon emission vector value is obtained.
specifically, night light data and urban carbon emission corresponding to different urban areas are obtained before the total carbon emission of a target area is calculated, the urban carbon emission is annual carbon emission of a city, the total night light brightness of the urban area for one year is counted based on the night light data corresponding to the different urban areas, a fitting relation between the total night light brightness and the urban carbon emission is constructed based on the total night light brightness and the urban carbon emission of the different urban areas, and the total carbon emission of the target area is calculated based on the night light data of the target area and the fitting relation.
It should be noted that the execution sequence of step 13 and step 12 is not specifically limited, and step 12 may be executed first and then step 13 is executed, or step 12 may be executed first and then step 13 is executed.
And 14, distributing carbon emission to each vector plot based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot to obtain a carbon emission spatial distribution result of the target area.
It should be noted that the potential carbon emission value represents a potential proportion of the carbon emission corresponding to each vector plot.
Specifically, based on the total carbon emission amount of the target area, the carbon emission potential value of each vector plot in the vector plots is combined to perform carbon emission distribution for each vector plot, and as an implementation manner, the potential proportion between each vector plot can be determined based on the carbon emission potential value of each vector plot, and then the total carbon emission amount is distributed according to the potential proportion, so as to obtain the carbon emission spatial distribution result of the target area.
According to the embodiment of the invention, the carbon evaluation index system is constructed under the urban micro-scale, so that the carbon emission potential value of each vector plot in the target area is calculated based on multi-source data, and further, the urban carbon emission is inverted on the micro-scale based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot, and the accuracy of the inversion of the urban carbon emission spatial distribution is improved.
In one embodiment, the calculating the carbon emission potential value of each vector plot in the target region based on the multi-source data and each carbon emission evaluation index of the target region includes:
calculating to obtain an index calculation value of each carbon emission evaluation index in each vector plot based on the multi-source data; respectively standardizing the index calculation value of each carbon emission evaluation index in each vector plot to obtain the index standardized value of each carbon emission evaluation index in each vector plot; calculating index weight of each carbon emission evaluation index through a preset hierarchical analysis algorithm; and calculating the carbon emission potential value of each vector plot based on the index standardized value of each carbon emission evaluation index in each vector plot and the index weight of each carbon emission evaluation index.
It should be noted that carbon emission generated in cities mainly consists of three aspects of industrial emission, traffic emission and resident life consumption, and the carbon emission difference of different cities mainly results from the aspects of population distribution density, industrial structure, energy intensity and the like, so that quantifiable spatial characteristic indexes can be selected from three main carbon emission generation sources of industrial emission, traffic emission and resident life consumption.
Specifically, the following steps are performed for any one of the vector blocks:
aiming at the road network density index: dividing the vector plots into a plurality of grids with the same area, further counting the total length of a traffic network in each grid, calculating the network density of each grid based on the total length of the traffic network in each grid and the area of each grid, further superposing the network densities of each grid to obtain an index calculation value of a network density index of the vector plots, wherein the calculation method of the network density of each grid is as follows:
wherein D is road Line representing road network density total The total length of the traffic network is shown and S represents the area of the grid.
Aiming at population distribution density indexes: dividing the vector plot into a plurality of grids, counting the number of users of each grid based on user signaling data of each grid, and further superposing the number of users of each grid to obtain an index calculation value of the population density index of the vector plot.
Aiming at the density index of the factory: and counting the number of factories in the vector plot by methods such as space statistics and the like to obtain an index calculation value of the factory density index of the vector plot.
For the user energy consumption index: and counting the consumption of the resident electricity, heat, gas and the like in all the buildings in the vector plot, and taking the consumption as an index calculation value of the user energy consumption index.
For point of interest reachability index: and calculating the distances between various interest points and the center position of the vector plot, selecting the nearest distance as an index calculation value of the reachability index of the interest points, for example, for bus stops, calculating the distance between each bus stop and the center position of the vector plot, and selecting the nearest distance as the index calculation value of the reachability index of the interest points.
Further, the index calculation value of each carbon emission evaluation index in each vector plot is respectively subjected to standardization treatment, wherein the standardization treatment is to standardize the index calculation value within a range of 0 to 1, so that the index standardization value of each carbon emission evaluation index in each vector plot is obtained. As shown in fig. 2, fig. 2 is a schematic hierarchical structure diagram of each carbon emission evaluation index in the carbon emission spatial distribution inversion method provided by the present invention, the statistical data of the target area and the energy consumption condition of each industry are obtained first, so as to determine the specific gravity of three main carbon emission generation sources, namely industrial emission, traffic emission and residential life consumption, and further based on the specific gravity, the importance degree between each carbon emission evaluation index is compared, and the importance degree between two carbon emission evaluation indexes is expressed by using a numerical value, so as to construct and obtain a weight discrimination matrix corresponding to each carbon emission evaluation index, as shown in fig. 3, fig. 3 is a schematic diagram of a weight discrimination matrix provided by an embodiment of the present invention, so as to calculate and obtain the index weight of each carbon emission evaluation index based on the weight discrimination matrix, wherein the method for calculating the index weight includes methods such as an arithmetic mean method, a geometric mean method, a characteristic value method, and the like.
Furthermore, the index standardization 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 results are superposed to obtain the carbon emission potential value of the vector plot.
According to the embodiment of the invention, through the scheme, the purpose that the index calculation values of all carbon emission evaluation indexes in different vector land blocks in the target area can be calculated according to local conditions according to different target areas is achieved, and the weight of each carbon emission evaluation index is calculated through a hierarchical analysis algorithm, so that the spatial distribution of carbon emission in a city can be simulated more accurately.
In one embodiment, the normalizing the index calculation value of each carbon emission evaluation index in each vector plot to obtain the index normalized value of each carbon emission evaluation index in each vector plot 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 index calculation values corresponding to the carbon emission evaluation index in each vector plot; and respectively standardizing the index calculation values of the carbon emission evaluation indexes corresponding to the vector plots based on the maximum value and the minimum value corresponding to the carbon emission evaluation indexes to obtain the index standardized values of the carbon emission evaluation indexes.
Specifically, the following steps are performed for any one of the carbon emission evaluation indexes:
determining a maximum value and a minimum value corresponding to the carbon emission evaluation index based on the index calculation value corresponding to the carbon emission evaluation index in each vector plot, further normalizing each index calculation value of the carbon emission evaluation index by using each index calculation value to be normalized, the maximum value and the minimum value corresponding to the carbon emission evaluation index to obtain an index normalized value of each carbon emission evaluation index in the vector plot, wherein a formula of the normalization processing is as follows:
ii = (Xi-Xmin)/(Xmax-Xmin); or
Ii＝(Xmax-Xi)/(Xmax-Xmin)
Where Ii denotes the index normalization value, xi denotes the calculated value of the index to be normalized, xmax denotes the maximum value, and Xmin denotes the minimum value.
According to the embodiment of the invention, through the scheme, the index calculation values of the carbon emission evaluation indexes of different vector plots under the urban microscale are subjected to standardization treatment, so that the spatial distribution of the carbon emission in the city is accurately simulated and obtained.
In one embodiment, the calculating a carbon emission potential value for each of the vector plots based on the index normalized value for each carbon emission evaluation index and the index weight for each carbon emission evaluation index comprises:
for any vector plot, multiplying the index standard value of each carbon emission evaluation index in the vector plot by the index weight of each carbon emission evaluation index to obtain the target value of each carbon emission evaluation index; and respectively accumulating the target values of the carbon emission evaluation indexes in each vector plot to obtain the carbon emission potential value of each vector plot.
Specifically, the following steps are performed for any one of the vector blocks:
further, multiplying the index standardization value of each carbon emission evaluation index in the vector plot by the index weight of each carbon emission evaluation index one by one to obtain the target value of each carbon emission evaluation index in the vector plot, and then accumulating the target values of each carbon emission evaluation index in each vector plot to obtain the carbon emission potential value of each vector plot. Wherein, the carbon emission potential value calculation formula is as follows:
where Cp denotes a carbon emission potential value of the vector plot, ii denotes a normalized value of the ith carbon emission evaluation index, and Wi denotes an index weight of the ith carbon emission evaluation index.
According to the embodiment of the invention, the carbon emission potential value of each vector plot in the area is obtained by weighting each carbon emission evaluation index in each vector plot and the index weight of each carbon emission evaluation index, so that the spatial distribution of carbon emission in the city is accurately inverted on a microscopic scale.
In one embodiment, before calculating the total carbon emission based on the night light data of the target area, the method further includes:
acquiring night light data and urban carbon emission of different sample areas; counting the total night light brightness of each sample area based on the night light data of the different sample areas; and constructing and obtaining a target fitting equation based on the total night lamplight brightness and the urban carbon emission of each sample area.
It should be noted that the annual carbon emission data of each local city and the energy consumption situation of each industry in the city, which are provided by the ceds chinese carbon accounting database, can be used to extract information such as the carbon emission of each city, where the urban carbon emission is the annual carbon emission in the sample area.
Specifically, because a linear relationship exists between the total night light brightness and the urban carbon emission in the night light data, in the embodiment of the present invention, multiple prefectures are used as sample areas, and then night light data and urban carbon emission of different sample areas are obtained, and further, the total night light brightness of each sample area is counted based on the night light data of different sample areas, and further, a target fitting equation is constructed based on the total night light brightness and the urban carbon emission of each sample area, so that the total night light brightness corresponding to the night light data of a target area is substituted into the target fitting equation, and the total carbon emission of the target area can be obtained, where the expression of the target fitting equation is as follows:
C＝k×T DN
wherein, T DN And C represents the total night light brightness of the sample area, C represents the urban carbon emission of the sample area, and k represents a constant.
According to the embodiment of the invention, the target fitting equation between the total night light brightness and the urban carbon emission of each city is constructed, so that the corresponding urban carbon emission can be calculated when the total night light brightness of a certain area is obtained, and a foundation is laid for inverting the spatial distribution of the carbon emission.
The carbon emission spatial distribution inversion apparatus provided by the present invention is described below, and the carbon emission spatial distribution inversion apparatus described below and the carbon emission spatial distribution inversion method described above may be referred to with each other.
Fig. 4 is a schematic structural diagram of a carbon emission spatial distribution inversion apparatus provided in the present invention, and as shown in fig. 4, the apparatus according to an embodiment of the present invention includes:
an obtaining module 41, configured to obtain multi-source data of a target area and night light data;
a first calculating module 42, configured to calculate, based on the multi-source data and each carbon emission evaluation index of the target area, a carbon emission potential value of each vector plot in the target area;
a second calculating module 43, configured to calculate, based on the night light data, a total carbon emission amount of the target area;
and the inversion module 44 is configured to perform carbon emission distribution on each vector plot based on the total carbon emission amount of the target region and the carbon emission potential value of each vector plot, so as to obtain a spatial distribution result of carbon emission in the target region.
The first computing module 42 is further configured to:
calculating to obtain an index calculation value of each carbon emission evaluation index in each vector plot based on the multi-source data;
respectively standardizing the index calculation value of each carbon emission evaluation index in each vector plot to obtain the index standardized value of each carbon emission evaluation index in each vector plot;
calculating index weight of each carbon emission evaluation index through a preset hierarchical analysis algorithm;
and calculating the carbon emission potential value of each vector plot based on the index standard value of each carbon emission evaluation index in each vector plot and the index weight of each carbon emission evaluation index.
The first computing module 42 is further configured to:
for any one carbon emission evaluation index, determining a maximum value and a minimum value corresponding to the carbon emission evaluation index on the basis of index calculation values corresponding to the carbon emission evaluation index in each vector plot;
and respectively standardizing the index calculation values of the carbon emission evaluation indexes corresponding to the vector plots based on the maximum value and the minimum value corresponding to the carbon emission evaluation indexes to obtain the index standardized value of each carbon emission evaluation index.
The first calculation module 42 is further configured to:
for any one vector plot, multiplying the index standard value of each carbon emission evaluation index in the vector plot by the index weight of each carbon emission evaluation index to obtain the target value of each carbon emission evaluation index;
and respectively accumulating the target values of the carbon emission evaluation indexes in each vector plot to obtain the carbon emission potential value of each vector plot.
The carbon emission spatial distribution inversion apparatus further includes:
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 plot data, population signaling data, traffic network data, user energy consumption data and interest point position data.
The carbon emission spatial distribution inversion apparatus further includes:
acquiring night light data of samples in different sample areas and urban carbon emission;
counting the total night light brightness of each sample area based on the night light data of each sample;
and constructing and obtaining a target fitting equation based on the total night lamplight brightness and the urban carbon emission of the samples in each sample area.
The second calculation module 43 further comprises:
counting the total target night light brightness of the target area based on the night light data of the target area;
and calculating to obtain the total carbon emission amount of the target area based on the target night lamplight total brightness and the target fitting equation.
It should be noted that, the apparatus provided in the embodiment of the present invention can implement all the method steps implemented by the method embodiment and achieve the same technical effect, and detailed descriptions of the same parts and beneficial effects as the method embodiment in this embodiment are omitted here.
Fig. 5 is a schematic structural diagram of an electronic device provided in the present invention, and as shown in fig. 5, the electronic device may include: a processor (processor) 510, a memory (memory) 520, a communication Interface (Communications Interface) 530, and a communication bus 540, wherein the processor 510, the memory 520, and the communication Interface 530 communicate with each other via the communication bus 540. Processor 510 may invoke logic instructions in memory 520 to perform a method of carbon emissions spatial distribution inversion, the method comprising: acquiring multi-source data and night light data of a target area; calculating to obtain the carbon emission potential value of each vector plot in the target area based on the multi-source data and each carbon emission evaluation index of the target area; calculating the total carbon emission amount of the target area based on the night light data; and distributing carbon emission to each vector plot based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot to obtain a carbon emission space distribution result of the target area.
In addition, the logic instructions in the memory 520 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention or a part thereof which substantially contributes to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the carbon emission spatial distribution inversion method provided by the above methods, the method comprising: acquiring multi-source data and night light data of a target area; calculating to obtain the carbon emission potential value of each vector plot in the target area based on the multi-source data and each carbon emission evaluation index of the target area; calculating the total carbon emission amount of the target area based on the night light data; and distributing the carbon emission to each vector plot based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot to obtain a carbon emission spatial distribution result of the target area.
In another aspect, the present invention also provides a computer program product comprising a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of executing the carbon emission spatial distribution inversion method provided by the above methods, the method comprising: acquiring multi-source data and night light data of a target area; calculating to obtain the carbon emission potential value of each vector plot in the target area based on the multi-source data and each carbon emission evaluation index of the target area; calculating the total carbon emission amount of the target area based on the night light data; and distributing carbon emission to each vector plot based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot to obtain a carbon emission space distribution result of the target area.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for inverting a spatial distribution of carbon emissions, comprising:
acquiring multi-source data and night light data of a target area;
calculating to obtain the carbon emission potential value of each vector plot in the target area based on the multi-source data and each carbon emission evaluation index of the target area;
calculating the total carbon emission amount of the target area based on the night light data;
and distributing the carbon emission to each vector plot based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot to obtain a carbon emission spatial distribution result of the target area.
2. The carbon emission spatial distribution inversion method according to claim 1, wherein the calculating a carbon emission potential value of each vector plot in the target area based on the multi-source data and each carbon emission evaluation index of the target area comprises:
calculating to obtain an index calculation value of each carbon emission evaluation index in each vector plot based on the multi-source data;
respectively standardizing the index calculation value of each carbon emission evaluation index in each vector plot to obtain the index standardized value of each carbon emission evaluation index in each vector plot;
calculating index weight of each carbon emission evaluation index through a preset hierarchical analysis algorithm;
and calculating the carbon emission potential value of each vector plot based on the index standard value of each carbon emission evaluation index in each vector plot and the index weight of each carbon emission evaluation index.
3. The method of claim 2, wherein the calculating a carbon emission potential value for each of the vector plots based on the normalized value of the index for each carbon emission evaluation indicator in each of the vector plots and the weight of the index for each carbon emission evaluation indicator comprises:
for any one vector plot, multiplying the index standard value of each carbon emission evaluation index in the vector plot by the index weight of each carbon emission evaluation index to obtain the target value of each carbon emission evaluation index;
and respectively accumulating the target values of the carbon emission evaluation indexes in each vector plot to obtain the carbon emission potential value of each vector plot.
4. The method of claim 2, wherein the normalizing the index calculation value of each carbon emission evaluation index in each vector plot to obtain the index normalized value of each carbon emission evaluation index in each vector plot 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 index calculation values corresponding to the carbon emission evaluation index in each vector plot;
and respectively standardizing the index calculation values of the carbon emission evaluation indexes corresponding to the vector plots based on the maximum value and the minimum value corresponding to the carbon emission evaluation indexes to obtain the index standardized values of the carbon emission evaluation indexes.
5. The carbon emission spatial distribution inversion method according to claim 1, wherein the carbon emission evaluation index at least includes a plant 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 plot data, population signaling data, traffic network data, user energy consumption data and interest point position data.
6. The method of claim 1, wherein before calculating the total carbon emission based on the night light data of the target area, the method further comprises:
acquiring night light data of samples in different sample areas and urban carbon emission;
counting the total night light brightness of each sample area based on the night light data of each sample area;
and constructing and obtaining a target fitting equation based on the total night lamplight brightness of the samples in the sample areas and the urban carbon emission.
7. The method of claim 6, wherein the calculating a total amount of carbon emissions in the target area based on the night light data comprises:
counting the total target night light brightness of the target area based on the night light data of the target area;
and calculating to obtain the total carbon emission amount of the target area based on the target night lamplight total brightness and the target fitting equation.
8. An apparatus for inverting a spatial distribution of carbon emissions, comprising:
the acquisition module is used for acquiring multi-source data and night light data of the target area;
the first calculation module is used for calculating and obtaining the carbon emission potential value of each vector plot in the target area based on the multi-source data and each carbon emission evaluation index of the target area;
the second calculation module is used for calculating and obtaining the total carbon emission amount of the target area based on the night light data;
and the inversion module is used for distributing carbon emission to each vector plot based on the total carbon emission amount of the target area and the carbon emission potential value of each vector plot to obtain a carbon emission space distribution result of the target area.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the program, implements the carbon emission spatial distribution inversion method of any of claims 1 to 7.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the carbon emission spatial distribution inversion method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211249117.4A CN115689337A (en) | 2022-10-12 | 2022-10-12 | Carbon emission spatial distribution inversion method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211249117.4A CN115689337A (en) | 2022-10-12 | 2022-10-12 | Carbon emission spatial distribution inversion method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115689337A true CN115689337A (en) | 2023-02-03 |
Family
ID=85064915
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211249117.4A Pending CN115689337A (en) | 2022-10-12 | 2022-10-12 | Carbon emission spatial distribution inversion method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115689337A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117034588A (en) * | 2023-07-31 | 2023-11-10 | 广东省科学院广州地理研究所 | Industrial carbon emission space simulation method and system based on noctilucent remote sensing and interest points |
-
2022
- 2022-10-12 CN CN202211249117.4A patent/CN115689337A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117034588A (en) * | 2023-07-31 | 2023-11-10 | 广东省科学院广州地理研究所 | Industrial carbon emission space simulation method and system based on noctilucent remote sensing and interest points |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Jiang et al. | An assessment of urbanization sustainability in China between 1990 and 2015 using land use efficiency indicators | |
| Jiang et al. | Measuring urban sprawl in Beijing with geo-spatial indices | |
| CN110428126B (en) | Urban population spatialization processing method and system based on multisource open data | |
| Chen et al. | A new method for building-level population estimation by integrating LiDAR, nighttime light, and POI data | |
| CN101853290A (en) | Meteorological service performance evaluation method based on geographical information system (GIS) | |
| Marcotullio et al. | A top-down regional assessment of urban greenhouse gas emissions in Europe | |
| CN112418690A (en) | Analysis and diagnosis method and system for urban physical examination indexes | |
| CN115689337A (en) | Carbon emission spatial distribution inversion method, device, equipment and storage medium | |
| CN108182196B (en) | Urban traffic demand prediction method based on POI | |
| CN115994685A (en) | Method for evaluating current situation of homeland space planning | |
| CN110889196B (en) | Water environment bearing capacity assessment method and device based on water quality model and storage medium | |
| Chen et al. | Mapping gridded gross domestic product distribution of China using deep learning with multiple geospatial big data | |
| CN102930384A (en) | Human-water harmony degree-based municipal water resource safety evaluation system and method | |
| Sun et al. | Vulnerability assessment and impact factor analysis of marine economic system based on fuzzy comprehensive evaluation model | |
| CN109710720A (en) | A kind of crime risk such environmental effects analysis method for taking background effect into account | |
| Jiang et al. | Understanding Housing Prices Using Geographic Big Data: A Case Study in Shenzhen | |
| Liu et al. | How to resolve the conflicts of urban functional space in planning: A perspective of urban moderate boundary | |
| CN116128378A (en) | Urban physical examination evaluation method, system, storage medium and electronic equipment | |
| Jin et al. | Investigating urban land dynamic change and its spatial determinants in Harbin city, China | |
| CN115860213A (en) | Multi-scenario city emergency sampling place site selection optimization method, system, equipment and medium | |
| Zhou et al. | Spatial–temporal characteristics of geological disaster resilience in poverty and disaster-prone areas in China: a case study of Ganzi Prefecture | |
| Liao et al. | The driving mechanisms for human settlement and ecological environment in the upper minjiang watershed, China | |
| Luo et al. | Analysis and research on sustainable development factors of the sports industry based on chaos theory | |
| Wang et al. | A framework for analyzing energy consumption in urban built-up areas based on single photonic radar and spatial big data | |
| Ghiassi et al. | Utilization of GIS data for urban-scale energy inquiries: a sampling approach |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |