CN115438295A - Night light correction method and CO estimation 2 Method of discharging amount - Google Patents

Night light correction method and CO estimation 2 Method of discharging amount Download PDF

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CN115438295A
CN115438295A CN202211386385.0A CN202211386385A CN115438295A CN 115438295 A CN115438295 A CN 115438295A CN 202211386385 A CN202211386385 A CN 202211386385A CN 115438295 A CN115438295 A CN 115438295A
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night light
pixel
monitored
area
ntl
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田启明
徐彬仁
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Beijing Yingshi Ruida Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
    • G01F22/00—Methods or apparatus for measuring volume of fluids or fluent solid material, not otherwise provided for
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/22—Fuels, explosives
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/22—Fuels, explosives
    • G01N33/222—Solid fuels, e.g. coal
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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    • G01N33/22—Fuels, explosives
    • G01N33/225—Gaseous fuels, e.g. natural gas
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9021—SAR image post-processing techniques
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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    • G06Q50/26—Government or public services

Abstract

The invention relates to a night light correction method and CO estimation 2 The method for discharging the amount of the discharge is used for solving the problem that the range of human activities observed by the existing night light is larger than the actual range. Wherein the night light correctionA method for monitoring the actual range of human activity, comprising the steps of: acquiring a satellite grid map of an area to be monitored, wherein the satellite grid map comprises a plurality of pixels, and acquiring night light data NTL, night light weight omega, population space distribution data POP, building pixel SAR identified by radar and normalized vegetation index NDVI of each pixel; NDVI = (NIR-Red)/(NIR + Red), NIR is a near infrared band, and Red is a Red band; correcting the NTL to obtain corrected Icorpect, wherein the correction formula is as follows: icorrect = ω NTL ln (POP SAR + 1) ((1-NDVI)).

Description

Night light correction method and estimation methodCalculating CO 2 Method of discharging amount
Technical Field
The invention relates to the technical field of carbon emission estimation, in particular to a night light correction method and CO estimation 2 A method of discharging the amount.
Background
Since the industrial revolution, a large amount of CO was emitted due to human activities 2 The greenhouse gases are equal, so that the concentration of the greenhouse gases in the atmosphere is increased sharply, and the greenhouse effect is increased increasingly. According to statistics, the global annual average atmospheric CO before industrialization 2 The concentration was 278ppm (1 ppm is parts per million) and 2012 is the global annual average atmospheric CO 2 The concentration is 393.1ppm, and the average CO in the atmosphere of northern hemisphere by 4 months in 2014 2 The concentration is over 400ppm for the first time.
Carbon dioxide (CO) 2 ) Is a main greenhouse gas, CO, discharged in the process of human production 2 The emission manifest is governing national and global CO 2 Emissions and basic tools to analyze the source.
At present, the main method of meshing carbon emission is to perform spatial meshing on carbon emission data through population spatial distribution or night light data in combination with energy emission data. However, the spatial meshing of the carbon emission is realized only through population data, and the regular activities of human beings, such as the activity condition of a residential area, the land transportation condition and the like, cannot be embodied; although the change of human activities can be reflected only by night light, the observed human activities are larger than the actual range and are not accurate enough because the night light has the function of space expansion.
Disclosure of Invention
In view of the above analysis, the present invention provides a night light correction method and an estimated CO 2 The method for discharging the amount of the discharge is used for solving the problem that the range of human activities observed by the existing night light is larger than the actual range.
In one aspect, the invention provides a night light correction method for monitoring the actual activity range of human beings, comprising the following steps:
acquiring a satellite grid map of an area to be monitored, wherein the satellite grid map comprises a plurality of pixels, and acquiring night light data NTL, night light weight omega, population space distribution data POP, building pixel SAR identified by radar and normalized vegetation index NDVI of each pixel;
NDVI = (NIR-Red)/(NIR + Red), NIR is a near infrared band, and Red is a Red band;
correcting the night light data NTL to obtain corrected night light data Icorpect, wherein the correction formula is as follows:
Icorrect =ω* NTL * ln（POP*SAR+1）*（1-NDVI）。
further, the NTL is derived from a night light product NPP-DNB released by the national space agency of America;
the building pixel SAR identified by the radar is from Sentinel-1A/B;
the normalized vegetation index NDVI is derived from MOD13A3 or MYD13A3 on AURA or TERRA satellites of the national space agency of America;
the population space distribution data POP is derived from Landscan global population distribution data.
Further, in the modified formula, if NTL > 0, ω =1; if NTL is less than or equal to 0, ω =0;
if the radar identifies a building, SAR =1; if the radar identifies non-buildings, SAR =0.
In another aspect, the present invention also provides an apparatus for estimating CO 2 The method for estimating the discharge amount based on the corrected night light data comprises the following steps:
s100: the corrected night light data Icorpect of each pixel is obtained by the correction method;
s200: obtaining fossil fuel consumption of the area to be monitored
Figure 308939DEST_PATH_IMAGE001
Consumption of fossil fuels by the area to be monitored
Figure 184491DEST_PATH_IMAGE001
Calculating fossil fuel CO of the region to be monitored 2 Discharge capacity
Figure 948048DEST_PATH_IMAGE002
；
S300: carrying out normalization processing on the corrected night light data Icorpect;
s400: will be described in
Figure 359176DEST_PATH_IMAGE002
Decomposing the image into each pixel to obtain non-point source CO of each pixel 2 Discharge capacity;
s500: CO per picture element 2 The emission is the non-point source CO 2 Emission and point source CO 2 The sum of the emissions.
Further, in S200, the method includes the following steps:
s201: obtaining a certain fossil fuel consumption of the area to be monitored
Figure 840972DEST_PATH_IMAGE001
Calculating the carbon emission of the corresponding fossil fuel
Figure 989057DEST_PATH_IMAGE003
The calculation formula is as follows:
Figure 748066DEST_PATH_IMAGE004
wherein, in the step (A),
Figure 690614DEST_PATH_IMAGE005
a carbon emission factor for a corresponding fossil fuel;
s202: by a correction factor
Figure 535073DEST_PATH_IMAGE006
Amending the
Figure 486849DEST_PATH_IMAGE003
To obtain
Figure 959418DEST_PATH_IMAGE007
，
Figure 479392DEST_PATH_IMAGE007
In order to correspond to the carbon emission of fossil fuels after correction,
Figure 670202DEST_PATH_IMAGE008
；
s203: calculating CO for fossil fuels 2 Discharge capacity
Figure 160089DEST_PATH_IMAGE009
，
Figure 392225DEST_PATH_IMAGE010
Wherein, in the step (A),
Figure 942155DEST_PATH_IMAGE011
is CO 2 Molecular weight ratio to carbon;
S204：
Figure 354682DEST_PATH_IMAGE012
。
further, the fossil fuel consumption of the area to be monitored
Figure 789206DEST_PATH_IMAGE001
Derived from national statistics yearbook.
Further, the fossil fuel type of the area to be monitored comprises one or more of coal, oil and natural gas.
Further, the
Figure 236368DEST_PATH_IMAGE005
、
Figure 957199DEST_PATH_IMAGE006
、
Figure 263547DEST_PATH_IMAGE011
Derived from the IPCC guidelines.
Further, in S300, the normalization formula is:
Figure 95236DEST_PATH_IMAGE013
wherein, in the step (A),
Figure 396905DEST_PATH_IMAGE014
is the corrected night light data of the pixel j,
Figure 429583DEST_PATH_IMAGE015
is the maximum value of the corrected night light data in all the pixels,
Figure 816702DEST_PATH_IMAGE016
is the minimum value of the corrected night light data in all the pixels,
Figure 452082DEST_PATH_IMAGE017
and the value is the normalized value of the corrected night light data of the pixel j.
Further, in S400, a non-point source CO of a pixel j 2 Discharge capacity
Figure 507458DEST_PATH_IMAGE018
，
Figure 570092DEST_PATH_IMAGE019
Wherein, in the step (A),
Figure 710086DEST_PATH_IMAGE020
and the weight of the j pixels in the area to be monitored is obtained.
Compared with the prior art, the invention can realize at least one of the following beneficial effects:
(1) The invention corrects the traditional pure night light by combining active remote sensing and passive remote sensing, and can reduce the error caused by light corrosion, wherein the active remote sensing parameter is SAR parameter, the passive remote sensing parameter comprises omega, POP and NDVI parameter, so as to effectively reduce the error caused by the expansion of night light, improve CO 2 The spatial resolution of the grid discharge amount can reach 500 multiplied by 500m;
(2) Base (C)The corrected night light data can be used for more quickly and accurately aligning CO 2 The emission is gridded to obtain CO of each pixel element of the area to be monitored 2 On one hand, the carbon emission condition of a certain area can be known more intuitively, so that the spatial information of the carbon source/sink of the area to be monitored is mined, the spatial structure analysis of the carbon source/sink of the area is carried out, and the method has important value for supporting the carbon in the area and specifying the planned path; on the other hand, as the region CO 2 Fast estimation of emissions compared to conventional CO 2 The estimation method is tedious and long, and is quicker and more convenient;
(3) Higher resolution CO 2 The emission amount can better reflect the details of the emission intensity, and the CO can be found more accurately 2 And the emission source is beneficial to formulation of carbon emission planning and propulsion of low-carbon measures.
In the invention, the technical schemes can be combined with each other to realize more preferable combination schemes. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
FIG. 1 shows the CO of Beijing in the embodiment 2 The discharge amount is gridded and visualized.
Detailed Description
The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form a part hereof, and which together with the embodiments of the invention serve to explain the principles of the invention and not to limit its scope.
In the description of the embodiments of the present invention, it should be noted that, unless otherwise explicitly stated or limited, the term "connected" should be interpreted broadly, and may be, for example, a fixed connection, a detachable connection, or an integral connection, which may be a mechanical connection, an electrical connection, which may be a direct connection, or an indirect connection via an intermediate medium. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
The terms "top," "bottom," "at 8230; \8230above," "below," and "at 8230; \8230above," and "above" are used throughout to describe relative positions of components with respect to the device, such as the relative positions of the top and bottom substrates inside the device. It will be appreciated that the devices are multifunctional, regardless of their orientation in space.
The general working surface of the invention can be a plane or a curved surface, can be inclined or horizontal. For convenience of explanation, the embodiments of the present invention are placed on a horizontal plane and used on the horizontal plane, and are defined as "high and low" and "up and down".
In order to solve the problem that night light has a space expansion effect and the human activity range observed based on the night light is larger than the actual range, night light data are subjected to space correction through night light weight omega, population space distribution data POP, building pixel SAR identified by radar and normalized vegetation index NDVI, and CO is finally obtained 2 The discharge amount is subjected to meshing.
Example one
The embodiment discloses a night light correction method for monitoring the actual activity range of human beings, which comprises the following steps:
acquiring a satellite grid map of the area to be monitored, wherein the satellite grid map comprises a plurality of pixels, and acquiring night light data NTL, night light weight omega, population space distribution data POP, radar-identified building pixel SAR and normalized vegetation index NDVI of each pixel; wherein NDVI = (NIR-Red)/(NIR + Red), NIR is a near infrared band, and Red is a Red band.
Correcting the NTL to obtain corrected Icorpect, wherein the correction formula is as follows:
Icorrect =ω* NTL * ln（POP*SAR+1）*（1-NDVI）。
in many studies, the traditional vegetation-corrected night light index formula is NTL (1-NDVI). In consideration of the fact that the traditional vegetation index is relatively single in night light correction, and therefore, in consideration of the fact that population is in direct proportion to night light, the invention provides a method for correcting night light based on the traditional vegetation index, and man-made buildings identified by population and radar are added into a traditional correction formula, so that corrected night light data are more accurate, and a more real human actual activity range is obtained.
ω =1 if NTL > 0; if NTL is less than or equal to 0, then omega =0, and omega is a default value of the light intensity at night; if the radar identifies a building, SAR =1; if the radar identifies non-buildings, SAR =0.
Wherein the NTL is derived from a night light product NPP-DNB released by the national space agency of America, the spatial resolution is 500m, and the time resolution is 1 month. The building pixel SAR identified by the radar is from Sentinel-1A/B, the spatial resolution is 5 x 20m, and the time resolution is 6 days. The normalized vegetation index NDVI is derived from MOD13A3 or MYD13A3 on AURA or TERRA satellites of the national space agency (MOD 13A3 is data of Terra satellites, namely data of morning stars; MYD13A3 is data of Aqua satellites, namely data of afternoon stars), the spatial resolution is 1km, and the time resolution is 1 month. The population spatial distribution data POP is derived from Landscan global population distribution data, the spatial resolution is 1km, and the time resolution is 1 year. The NTL of the night light is positively correlated with POP of the population in space, namely the higher the POP value is, the higher the NTL value is. The NTL and NDVI have opposite change trends, namely the larger the NDVI value is, the smaller the NTL value is.
[ example 1 ]
TABLE 1 night light data calculation table after correcting some pixels in certain area
Figure 758945DEST_PATH_IMAGE021
(wherein the unit of NTL, icorpect is w/cm 2 /sr/μm)
Example two
The embodiment discloses a method for estimating CO 2 Method for estimating emission amount of CO based on corrected night light data obtained by the correction method according to the first embodiment 2 Emission of CO, the estimation 2 The method for discharging the CO from the area to be monitored simultaneously 2 The emission is subjected to a gridding method so as to quickly and conveniently obtain the high-resolution CO of the region 2 And (4) carrying out discharge amount visualization distribution.
The estimated CO 2 The principle of the method of emission lies in the CO in fossil fuels (coal, oil and natural gas) 2 The emissions may be due to the combustion of fossil fuels, i.e. to the consumption of fossil fuels. Non-terrestrial fossil fuel CO from international (marine and aviation) and fishery sources 2 Emissions are included in the terrestrial emissions estimation because there is no separate fuel consumption statistic from the energy statistics we use for estimation. The present invention estimates CO by consumption of fossil fuels 2 And (4) discharging the amount. The invention converts the consumption of fossil fuel into CO in a certain area to be monitored 2 On the basis of emission, combining high spatial resolution satellite night light data to monitor the CO in the area to be monitored 2 Point emission sources and area emission sources were converted into 500m × 500m grid data.
Since the source of the consumption of fossil fuel is the national statistical yearbook and the lowest level of the region of the national statistical yearbook is the grade city, the lowest level of the region that can be gridded according to the invention is the grade city.
The estimated CO 2 The discharge amount gridding method comprises the following steps:
s100: according to the modification method of the first embodiment, modified night light data Icorrect of each pixel is obtained, and illustratively, the modified night light data of the pixel j is represented as
Figure 35205DEST_PATH_IMAGE022
；
S200: obtaining fossil fuel consumption of the area to be monitored
Figure 534320DEST_PATH_IMAGE001
Consumption of fossil fuel by the area to be monitored
Figure 771397DEST_PATH_IMAGE001
Calculating fossil fuel CO of the area to be monitored 2 Discharge capacity
Figure 748580DEST_PATH_IMAGE002
；
S300: normalizing the corrected night light data Icorrect;
s400: will be described in
Figure 410506DEST_PATH_IMAGE002
Decomposing the image into each pixel to obtain non-point source CO of each pixel 2 Discharge capacity;
s500: CO per picture element 2 The emission is the non-point source CO 2 Discharge and point source CO 2 The sum of the emissions.
The invention fuses the energy emission data of China and the night light data of the satellite corrected by the ground object type, simultaneously considers the emission distribution of point sources such as a power plant, a cement plant and the like, and finally generates the CO with high spatial resolution 2 Emission grid data. (night light is refined with building category, and the scale of the moon is linearly classified into the scale of the day)
The invention converts the annual energy consumption data of China into CO 2 On the basis of emission, the high spatial resolution satellite night light data is combined to convert national grade and municipal CO 2 Point emission sources and area emission sources were converted into 500m × 500m grid data.
The step S200 comprises the following steps:
s201: obtaining a certain fossil fuel consumption of the area to be monitored
Figure 690308DEST_PATH_IMAGE001
Calculating the carbon emission of the corresponding fossil fuel
Figure 539316DEST_PATH_IMAGE003
The calculation formula is as follows:
Figure 320190DEST_PATH_IMAGE004
wherein, in the process,
Figure 944944DEST_PATH_IMAGE005
a carbon emission factor for a corresponding fossil fuel;
s202: by a correction factor
Figure 785861DEST_PATH_IMAGE006
Amending the
Figure 856585DEST_PATH_IMAGE003
To obtain
Figure 50937DEST_PATH_IMAGE007
，
Figure 421876DEST_PATH_IMAGE007
In order to correspond to the carbon emission of fossil fuels after correction,
Figure 168115DEST_PATH_IMAGE008
；
s203: calculating CO for fossil fuels 2 Discharge capacity
Figure 867081DEST_PATH_IMAGE009
，
Figure 724178DEST_PATH_IMAGE010
Wherein, in the step (A),
Figure 215203DEST_PATH_IMAGE011
is CO 2 Molecular weight ratio to carbon;
S204：
Figure 7709DEST_PATH_IMAGE012
。
fossil fuel consumption of the area to be monitored
Figure 53026DEST_PATH_IMAGE001
SourceAnd counting the yearbook in the country.
The fossil fuel category of the area to be monitored comprises one or more of coal, oil and natural gas, and exemplarily, if the fossil fuel category of the area to be monitored comprises coal and oil, the fossil fuel category of the area to be monitored comprises coal and oil
Figure 979393DEST_PATH_IMAGE003
Comprising coal
Figure 433246DEST_PATH_IMAGE003
And of petroleum
Figure 521288DEST_PATH_IMAGE003
，
Figure 319480DEST_PATH_IMAGE005
Also comprising coal
Figure 659325DEST_PATH_IMAGE005
And of petroleum
Figure 593783DEST_PATH_IMAGE005
I.e. separately calculated postaddition from different kinds of fossil fuels
Figure 118305DEST_PATH_IMAGE002
。
The above
Figure 13580DEST_PATH_IMAGE005
、
Figure 281750DEST_PATH_IMAGE006
、
Figure 336294DEST_PATH_IMAGE011
The data of (2) were derived from IPCC (International Panel on Climate Change, united nations inter-government Committee for Climate Change) guidelines.
Figure 641505DEST_PATH_IMAGE001
The unit is the unit of the heat of the earth,
Figure 148709DEST_PATH_IMAGE003
、
Figure 220571DEST_PATH_IMAGE007
、
Figure 237943DEST_PATH_IMAGE009
the unit is ton.
In S300, the normalization formula is:
Figure 104268DEST_PATH_IMAGE013
wherein, in the step (A),
Figure 98769DEST_PATH_IMAGE014
the corrected night light data of the pixel j is the light intensity value of the pixel j;
Figure 584108DEST_PATH_IMAGE015
the maximum value of the corrected night light data in all the pixels is the maximum value of the light intensity in all the pixels;
Figure 347664DEST_PATH_IMAGE016
the minimum value of the corrected night light data in all the pixels is the minimum value of the light intensity in the pixels;
Figure 384890DEST_PATH_IMAGE017
the value is the normalized value of the corrected night light data of the pixel j, namely the value of the pixel j after the light intensity is normalized. And calculating the value of each pixel after the light intensity is normalized according to the normalization formula.
In S400, the non-point source CO of the pixel j 2 Discharge capacity
Figure 476474DEST_PATH_IMAGE018
，
Figure 890138DEST_PATH_IMAGE019
Wherein, in the process,
Figure 508201DEST_PATH_IMAGE020
adding the value of the corrected night light data of the area to be monitored after normalization, dividing the value of the corrected night light data of each pixel after normalization by the value of the corrected night light data of all the pixels of the area to be monitored after normalization, namely obtaining the proportion of each pixel in the area to be monitored, and then adding the fossil fuel CO in the area to be monitored 2 The emission is multiplied by the specific gravity of each pixel to be converted into CO on each grid 2 And (4) discharging the amount.
In S500, CO of point source 2 The emission is CO of power plants or/and cement plants which are operated nationwide 2 The discharge amount data is subjected to geographic spatialization according to longitude and latitude, and if a power plant or/and a cement plant is/are arranged on the pixel j, the CO of the pixel j 2 The discharge amount is non-point source CO 2 Emission and point source CO 2 Sum of discharge, point source CO 2 The emission is CO of power plants and cement plants in the pixel 2 The sum of the discharge amount; if the pixel j has neither a power plant nor a cement plant, the point source CO is in the point source state 2 If the discharge amount is zero, the CO of the pixel element j is 2 The discharge amount is equal to non-point source CO 2 And (4) discharging the amount.
CO of the power plant or cement plant 2 The emissions are derived from global energy statistics.
CO on each pixel (i.e. grid) 2 The emission is coated on the grid map of the area to be monitored by a certain color, and then the CO of the area to be monitored can be obtained 2 The discharge amount gridding can be seen, as shown in FIG. 1, the CO of Beijing area 2 The discharge amount is gridded and visualized. Preferably, CO of the same region 2 Is coated with the same color system, CO in FIG. 1 2 The higher the discharge amount of (c) the lighter the color of the coating used.
[ example 2 ]
TABLE 2 CO of a certain pixel in Beijing area 2 Discharge capacityCalculation table
Figure 591695DEST_PATH_IMAGE023
Those skilled in the art will appreciate that all or part of the processes for implementing the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, for instructing the relevant hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The method identifies artificial building data and vegetation and population data of passive remote sensing through satellite night light and active radar remote sensing, and estimates CO by only depending on the satellite night light in the prior art 2 The method for discharging the CO gas is used for correcting, so that the data error caused by the expansion of the light at night of the satellite is solved, and the CO gas in the exact area is obtained 2 The discharge amount is converted into carbon content (hereinafter referred to as fossil fuel) by synchronously converting domestic fossil fuel and non-terrestrial fossil fuel from international fuel, fishery and the like, and the unoxidized fuel in the combustion process of the fossil fuel is corrected, so that the counted carbon content data is converted into CO 2 Estimating the discharge amount, grading the data of the middle satellite night lights with different intensities according to national grade boundaries of the cities, normalizing the different intensities of the satellite night lights of the cities to obtain specific values of the satellite night light intensities of the cities, accumulating the normalized values of the night light intensities of the satellites of the cities, dividing the normalized pixel value by the sum of all pixel values of the corresponding city to obtain the proportion of each pixel in each city, and then classifying the fossil fuel CO of the city 2 Multiplying the discharge amount by the specific gravity of each pixel element, and adding CO of each city grade 2 The point emission source and the area emission source are converted into grid data of 500m multiplied by 500m, and the national CO is estimated 2 Emissions and displaying CO at higher resolution relative to current statistical solutions with statistics of this grid data 2 Emission intensity of emission amountThe details of (2) are favorable for accurately finding CO in the subsequent process 2 Source of emission when subsequently to CO 2 When emission is improved, the method is convenient and fast, the defect that carbon emission is counted only through population data or satellite night light data at present is overcome, the CO is counted and calculated through multiple data sources through an active radar, and the CO is achieved 2 The emission amount is accurately counted, and meanwhile, one grid data is displayed, so that CO can be reflected better 2 Details of emission intensity of the emission to facilitate accurate subsequent CO finding 2 The emission source is favorable for improving CO in the later period 2 The discharge amount is used for improving the air environment in which people live. (where fossil fuels are coal, oil and natural gas, and CO in these 2 The emissions can be attributed to the combustion of fossil fuels, non-terrestrial fossil fuels CO from international (marine and aviation) and fishery sources 2 Emissions are included in the land emissions estimation).
While the invention has been described with reference to specific preferred embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the following claims.

Claims (10)

1. A night light correction method is used for monitoring the actual activity range of human beings and is characterized by comprising the following steps:
acquiring a satellite grid map of an area to be monitored, wherein the satellite grid map comprises a plurality of pixels, and acquiring night light data NTL, night light weight omega, population space distribution data POP, radar-identified building pixel SAR and normalized vegetation index NDVI of each pixel;
NDVI = (NIR-Red)/(NIR + Red), NIR is a near infrared band, and Red is a Red band;
correcting the night light data NTL to obtain corrected night light data Icorpect, wherein the correction formula is as follows:
Icorrect =ω* NTL * ln（POP*SAR+1）*（1-NDVI）。
2. the night light correction method according to claim 1, wherein the night light data NTL is derived from a night light product NPP-DNB released by the national space agency;
the building pixel SAR identified by the radar is from Sentinel-1A/B;
the normalized vegetation index NDVI is derived from MOD13A3 or MYD13A3 on AURA or TERRA satellites of the national space agency of America;
the population space distribution data POP is derived from Landscan global population distribution data.
3. A night light correction method according to claim 1, wherein in the correction formula, if NTL > 0, ω =1; if NTL is less than or equal to 0, ω =0;
if the radar identifies a building, SAR =1; if the radar identifies non-buildings, SAR =0.
4. Estimating CO 2 A method of estimating an amount of emissions based on the modified night light data according to any one of claims 1 to 3, comprising the steps of:
s100: obtaining the modified night light data Icorpect for each pixel according to the modification method of any one of claims 1 to 3;
s200: obtaining fossil fuel consumption of the area to be monitored
Figure 700620DEST_PATH_IMAGE001
Consumption of fossil fuel by the area to be monitored
Figure 424993DEST_PATH_IMAGE001
Calculating fossil fuel CO of the area to be monitored 2 Discharge capacity
Figure 205867DEST_PATH_IMAGE002
；
S300: carrying out normalization processing on the corrected night light data Icorpect;
s400: will be described in
Figure 456720DEST_PATH_IMAGE002
Decomposing the image into each pixel to obtain non-point source CO of each pixel 2 Discharge capacity;
s500: CO per picture element 2 The emission is the non-point source CO 2 Discharge and point source CO 2 Sum of the discharge amount.
5. Estimating CO according to claim 4 2 The method for discharging the amount of the fuel is characterized in that the step S200 includes the steps of:
s201: obtaining a certain fossil fuel consumption of the area to be monitored
Figure 173003DEST_PATH_IMAGE001
Calculating the carbon emission of the corresponding fossil fuel
Figure 509307DEST_PATH_IMAGE003
The calculation formula is as follows:
Figure 828293DEST_PATH_IMAGE004
wherein, in the step (A),
Figure 74597DEST_PATH_IMAGE005
a carbon emission factor for a corresponding fossil fuel;
s202: by a correction factor
Figure 820836DEST_PATH_IMAGE006
Modify the
Figure 378857DEST_PATH_IMAGE003
To obtain
Figure 141014DEST_PATH_IMAGE007
，
Figure 100880DEST_PATH_IMAGE007
In order to correspond to the carbon emission of fossil fuels after correction,
Figure 18020DEST_PATH_IMAGE008
；
s203: calculating CO for fossil fuels 2 Discharge capacity
Figure 469861DEST_PATH_IMAGE009
，
Figure 130650DEST_PATH_IMAGE010
Wherein, in the step (A),
Figure 945022DEST_PATH_IMAGE011
is CO 2 Molecular weight ratio to carbon;
S204：
Figure 174009DEST_PATH_IMAGE012
。
6. estimating CO according to claim 5 2 Method of discharging quantities, characterized in that the fossil fuel consumption of said area to be monitored
Figure 972201DEST_PATH_IMAGE001
Derived from the national statistics yearbook.
7. Estimating CO according to claim 5 2 The method for discharging the amount is characterized in that the type of the fossil fuel of the area to be monitored comprises one or more of coal, oil and natural gas.
8. Estimating CO according to claim 5 2 Method of discharging an amount of exhaust gas, characterized in that
Figure 171101DEST_PATH_IMAGE005
、
Figure 246504DEST_PATH_IMAGE006
、
Figure 771027DEST_PATH_IMAGE011
Derived from the IPCC guidelines.
9. Estimating CO according to claim 4 2 The method for discharging amount is characterized in that in S300, the normalization formula is:
Figure 525356DEST_PATH_IMAGE013
wherein, in the step (A),
Figure 433007DEST_PATH_IMAGE014
is the corrected night light data for pixel j,
Figure 221971DEST_PATH_IMAGE015
the maximum value of the corrected night light data in all the pixels,
Figure 651816DEST_PATH_IMAGE016
is the minimum value of the corrected night light data in all the pixels,
Figure 299966DEST_PATH_IMAGE017
and the value is the normalized value of the corrected night light data of the pixel j.
10. Estimating CO according to claim 4 2 The method for discharging the amount is characterized in that in S400, the non-point source CO of the pixel j 2 Discharge capacity
Figure 106248DEST_PATH_IMAGE018
，
Figure 890664DEST_PATH_IMAGE019
Wherein, in the process,
Figure 756989DEST_PATH_IMAGE020
and the weight of the j pixels in the area to be monitored is obtained.
CN202211386385.0A 2022-11-07 2022-11-07 Night light correction method and CO estimation 2 Method of discharging amount Pending CN115438295A (en)

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