A method and device for calculating urban heat island concentration and a computer device

Abstract

The application discloses a kind of urban heat island concentration calculation method, device and computer equipment, the method includes: according to GNSS observation value calculation zenith troposphere wet delay;According to the zenith troposphere wet delay, the three-dimensional vertical distribution information of wet refractive index is obtained;In horizontal direction, obtain horizontal constraint information;In vertical direction, obtain vertical constraint information;According to the horizontal constraint information and the vertical constraint information, the three-dimensional vertical distribution information is solved, and wet refractive index profile is obtained;According to the relationship between the wet refractive index profile and atmospheric temperature, the urban heat island concentration is calculated.The present application is combined with horizontal constraint and vertical constraint to exclude relevant factor interference, and then based on search method, temperature and humidity pressure can be solved, and then urban heat island concentration can be accurately estimated.

Description

Technical Field

[0001] This invention relates to the field of urban environmental monitoring technology, and in particular to a method, apparatus and computer equipment for calculating urban heat island concentration. Background Technology

[0002] Due to concentrated urban populations, developed industries, traffic congestion, and severe air pollution, coupled with the fact that most urban buildings are constructed of stone and concrete with low heat capacity and high thermal conductivity, and the obstruction or weakening effect of buildings on wind, urban annual temperatures are significantly higher than those in the surrounding suburbs, thus creating the urban heat island effect. When GNSS electromagnetic wave signals pass through the neutral atmosphere, they are affected by temperature, water vapor pressure, and pressure, causing signal bending and tropospheric delay. The zenith tropospheric delay can be estimated from GNSS observation data using single-difference or double-difference methods. The zenith tropospheric delay typically consists of two parts: the zenith still water tropospheric delay and the zenith moist tropospheric delay. The zenith still water tropospheric delay changes relatively slowly and can be accurately obtained using models. Subtracting the zenith still water tropospheric delay from the total zenith tropospheric delay yields the zenith moist tropospheric delay. Based on GNSS tomography, the moist refractive index can be inferred from the moist tropospheric delay. The wet refractive index is mainly related to water vapor pressure and temperature. To monitor the concentration of urban heat islands, it is necessary to calculate the atmospheric temperature from the wet refractive index.

[0003] However, in actual calculations, due to too many unknown factors (including atmospheric temperature) and interference factors, it is impossible to directly calculate the atmospheric temperature from the wet refractive index, thus failing to achieve the purpose of estimating the heat island concentration. Summary of the Invention

[0004] This invention provides a method, apparatus, and computer for calculating urban heat island concentration. Based on a search method, temperature and humidity pressure can be obtained to eliminate interference from related factors, thereby accurately estimating the urban heat island concentration.

[0005] To achieve the above objectives, a first aspect of this application provides a method for calculating urban heat island concentration, comprising:

[0006] Calculate the wetted tropospheric delay based on GNSS observations;

[0007] The three-dimensional vertical distribution information of wet refractive index is obtained based on the wet delay of the zenith troposphere;

[0008] In the horizontal direction, obtain horizontal constraint information;

[0009] In the vertical direction, obtain vertical constraint information;

[0010] Based on the horizontal constraint information and the vertical constraint information, the three-dimensional vertical distribution information is calculated to obtain the wet refractive index profile;

[0011] The urban heat island concentration is calculated based on the relationship between the wet refractive index profile and atmospheric temperature.

[0012] In one possible implementation of the first aspect, obtaining the three-dimensional vertical distribution information of the wet refractive index based on the zenith tropospheric wet delay specifically includes:

[0013] The wetted zenith tropospheric delay is projected onto the original satellite propagation path using a projection function to obtain the slant path tropospheric delay.

[0014] Based on the relationship between the oblique path tropospheric delay and the wet refractive index, the three-dimensional vertical distribution information of the wet refractive index is obtained; the three-dimensional vertical distribution information is represented by a tomographic equation.

[0015] In one possible implementation of the first aspect, obtaining horizontal constraint information in the horizontal direction specifically includes:

[0016] The horizontal constraint coefficients are obtained using a Gaussian distance weighting function.

[0017] In one possible implementation of the first aspect, obtaining vertical constraint information in the vertical direction specifically includes:

[0018] Based on the space formed by the three-dimensional vertical distribution information, Gaussian exponential variation information is obtained;

[0019] Based on the Gaussian exponent variation information, the relationship between the wet refractive indices of two adjacent layers in the vertical direction is obtained.

[0020] In one possible implementation of the first aspect, the step of solving the three-dimensional vertical distribution information based on the horizontal constraint information and the vertical constraint information to obtain the wet refractive index profile specifically includes:

[0021] Based on the horizontal and vertical constraint information, the three-dimensional vertical distribution information is solved using Kalman filtering to obtain the wet refractive index profile.

[0022] In one possible implementation of the first aspect, calculating the urban heat island concentration based on the relationship between the wet refractive index profile and atmospheric temperature specifically includes:

[0023] Based on the relationship between the wet refractive index profile and atmospheric temperature, the atmospheric temperature value is estimated within a preset search range.

[0024] The difference between the temperature values ​​retrieved from urban GNSS stations and those retrieved from rural GNSS stations is taken as the urban heat island concentration.

[0025] In one possible implementation of the first aspect, the step of searching for and estimating the atmospheric temperature value within a preset search range based on the relationship between the wet refractive index profile and atmospheric temperature specifically includes:

[0026] Based on the relationship between the wet refractive index profile and atmospheric temperature, the linear relationship between atmospheric temperature and elevation, and the near-exponential relationship between water vapor pressure and elevation, the atmospheric temperature and water vapor pressure values ​​are estimated using the best priority search method within a preset search range.

[0027] In one possible implementation of the first aspect, the preset search range is specifically set as follows:

[0028] Use the ERA5 product to obtain the initial values ​​of temperature and vapor pressure;

[0029] Using the sounding product as a benchmark, the range of difference between the initial value and the benchmark is obtained, and a sub-range is selected from the range of difference as the preset search range.

[0030] A second aspect of this application provides an urban heat island concentration calculation device, comprising:

[0031] The first calculation module is used to calculate the wetted tropospheric delay based on GNSS observations;

[0032] A three-dimensional information module is used to obtain the three-dimensional vertical distribution information of the wet refractive index based on the wet delay of the zenith troposphere;

[0033] The horizontal constraint module is used to obtain horizontal constraint information in the horizontal direction;

[0034] The vertical constraint module is used to obtain vertical constraint information in the vertical direction;

[0035] The calculation module is used to calculate the three-dimensional vertical distribution information based on the horizontal constraint information and the vertical constraint information to obtain the wet refractive index profile.

[0036] The second calculation module is used to calculate the urban heat island concentration based on the relationship between the wet refractive index profile and atmospheric temperature.

[0037] A second aspect of this application provides a computer device including a processor and a memory, the memory being used to store a computer program that, when executed by the processor, implements the urban heat island concentration calculation method as described above.

[0038] Compared to existing technologies, the present invention provides a method, apparatus, and computer equipment for calculating urban heat island concentration. First, it accurately obtains the three-dimensional vertical distribution information of atmospheric wet refractive index based on GNSS tomography. Next, utilizing the functional relationship between atmospheric wet refractive index and temperature and vapor pressure, as well as the functional relationship between temperature and vapor pressure and elevation between adjacent layers, an optimal temperature and moisture pressure can be determined using a search method, eliminating unknown and interfering factors involved in the calculation process. Finally, the temperature retrieved from urban GNSS stations is subtracted from the temperature retrieved from rural GNSS stations to accurately estimate the urban heat island concentration.

[0039] The estimation of urban heat island concentration using the embodiments of the present invention can improve the spatiotemporal resolution of urban heat island concentration. It can not only study the horizontal variation characteristics of urban heat island concentration, but also explore its vertical variation characteristics, making full use of the advantages of GNSS positioning analysis. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating a method for calculating urban heat island concentration according to an embodiment of the present invention. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Please see Figure 1 An embodiment of the present invention provides a method for calculating urban heat island concentration, comprising:

[0043] S10. Calculate the wetted tropospheric delay at the zenith based on GNSS observations.

[0044] S11. Obtain the three-dimensional vertical distribution information of wet refractive index based on the wet delay of the zenith troposphere.

[0045] S12. Obtain horizontal constraint information in the horizontal direction.

[0046] S13. In the vertical direction, obtain vertical constraint information.

[0047] S14. Based on the horizontal constraint information and the vertical constraint information, the three-dimensional vertical distribution information is calculated to obtain the wet refractive index profile.

[0048] S15. Calculate the urban heat island concentration based on the relationship between the wet refractive index profile and atmospheric temperature.

[0049] This embodiment calculates atmospheric temperature and vapor pressure from the wet refractive index, solving the problem of unsolvable equations due to insufficient observation equations. First, it accurately obtains the three-dimensional vertical distribution information of the atmospheric wet refractive index using GNSS tomography. Then, utilizing the functional relationship between atmospheric wet refractive index and temperature and vapor pressure, as well as the functional relationship between temperature and vapor pressure and elevation between adjacent layers, an optimal temperature and wet pressure can be determined using a search method. Finally, the temperature retrieved from urban GNSS stations is subtracted from the temperature retrieved from rural GNSS stations to estimate the urban heat island concentration.

[0050] For example, obtaining the three-dimensional vertical distribution information of the wet refractive index based on the wet delay of the zenith troposphere specifically includes:

[0051] The wetted zenith tropospheric delay is projected onto the original satellite propagation path using a projection function to obtain the slant path tropospheric delay.

[0052] Based on the relationship between the oblique path tropospheric delay and the wet refractive index, the three-dimensional vertical distribution information of the wet refractive index is obtained; the three-dimensional vertical distribution information is represented by a tomographic equation.

[0053] The wet tropospheric delay (ZWD) can be calculated from GNSS observations using either the non-difference or double-difference method. The ZWD can then be projected onto the oblique path tropospheric delay (SWD) using a projection function (restoring the original satellite propagation path from the zenith direction). The functional relationship between SWD and the wet refractive index Nw can be expressed as follows:

[0054]

[0055]

[0056] This represents the fourth-order Newton-Cotes coefficients of the nodes in the j-th part of the i-th grid; ΔSWD represents the atmospheric wet refractive index at the corresponding node; m represents the number of grids through which the electromagnetic wave signal passes; S represents the distance the signal travels through the grid; and ΔSWD represents the noise.

[0057] For example, obtaining horizontal constraint information in the horizontal direction specifically includes:

[0058] The horizontal constraint coefficients are obtained using a Gaussian distance weighting function.

[0059] Due to the influence of the geometric distribution of ground GNSS stations and GNSS satellite constellations, many tomographic grids may not have signal crossings. Therefore, tomographic equation (2) usually cannot be solved directly using adjustment methods. Certain constraints need to be added to equation (2) before it can be solved. In the horizontal direction, the Gaussian distance weighting function is usually used to obtain the horizontal constraint coefficient B.

[0060]

[0061] In the formula, i,j,k represent the coordinates of the grid in the east-west, north-south, and elevation directions; d i,j,k σ represents the distance between the grid of the desired water vapor and the grid of the known water vapor; nl represents the number of grids in the latitudinal direction; and nn represents the number of grids in the radial direction.

[0062] For example, obtaining vertical constraint information in the vertical direction specifically includes:

[0063] Based on the space formed by the three-dimensional vertical distribution information, Gaussian exponential variation information is obtained;

[0064] Based on the Gaussian exponent variation information, the relationship between the wet refractive indices of two adjacent layers in the vertical direction is obtained.

[0065] To establish the connection between grids through which signals pass vertically and those through which signals do not, and to improve the well-posedness of the tomographic equations, vertical constraint information needs to be added during the tomographic solution process. Through the study of radiosonde and occultation data, it was found that the wet refractive index space exhibits a Gaussian exponential variation pattern.

[0066]

[0067] In the formula, N w (h) represents the wetted refractive index at elevation h; H z Indicates the wet refractive index level; N C h0 is a constant; h0 is the station height. According to formula (4), the relationship between the wet refractive indices of two adjacent layers in the vertical direction can be expressed as:

[0068]

[0069] Where the subscripts "i,j,k" represent the grid coordinates in the east-west, north-south, and elevation directions; h k and h k+1 These represent the heights of the lower and upper boundaries of the k-th tomographic grid, respectively.

[0070] For example, the step of calculating the three-dimensional vertical distribution information based on the horizontal constraint information and the vertical constraint information to obtain the wet refractive index profile specifically includes:

[0071] Based on the horizontal and vertical constraint information, the three-dimensional vertical distribution information is solved using Kalman filtering to obtain the wet refractive index profile.

[0072] Based on horizontal and vertical constraints, and by combining formulas (2), (3), and (5), the tomography equation can be solved using Kalman filtering to obtain the wet refractive index N. w Cross-section. And N w With water vapor pressure P w The following relationship exists between temperature T and temperature:

[0073]

[0074] Where, k1 = 77.6, k2 = 72, k3 = 3.75 × 10 5 ;R d and R w These are the gas constants for dry and wet atmospheres, respectively. To include two variables in formula (6), one is water vapor pressure and the other is temperature, the atmospheric temperature T cannot be directly calculated from formula (6).

[0075] In the vertical direction, temperature decreases linearly with elevation:

[0076] T i+1 =T i -β·(h i+1 -h i (7)

[0077] Among them, T i ,T i+1 They are respectively the i-th th The position and the (i+1)th th Atmospheric temperature at the grid; h i ,h i+1 Distribution representation of the i-th th At the grid position and at the (i+1)th position th Elevation at the grid point; β represents the temperature lapse rate.

[0078] In the vertical direction, the water vapor pressure exhibits an approximately exponential variation:

[0079]

[0080] in, They are respectively the i-th th At the grid position and at the (i+1)th position th The water vapor pressure at the grid; a and b are constants that can be solved using radiosonde or occultation data.

[0081] By combining formulas (6), (7) and (8), a search range is given for temperature and vapor pressure (initial values ​​of temperature and vapor pressure are obtained using ERA5 products, and the range of difference between the initial value and the reference value is obtained using the sounding product, from which a sub-range is established as the search range), and the atmospheric temperature and vapor pressure are estimated using the best priority search method.

[0082] For example, calculating the urban heat island concentration based on the relationship between the wet refractive index profile and atmospheric temperature specifically includes:

[0083] Based on the relationship between the wet refractive index profile and atmospheric temperature, the atmospheric temperature value is estimated within a preset search range.

[0084] The difference between the temperature values ​​retrieved from urban GNSS stations and those retrieved from rural GNSS stations is taken as the urban heat island concentration.

[0085] For example, the step of searching for and estimating atmospheric temperature values ​​within a preset search range based on the relationship between the wet refractive index profile and atmospheric temperature specifically includes:

[0086] Based on the relationship between the wet refractive index profile and atmospheric temperature, the linear relationship between atmospheric temperature and elevation, and the near-exponential relationship between water vapor pressure and elevation, the atmospheric temperature and water vapor pressure values ​​are estimated using the best priority search method within a preset search range.

[0087] Once the atmospheric temperature is obtained, the urban heat island concentration UHI can be calculated:

[0088] UHI GNSS =T GNSs (urban)-T GNSS (rural) (9)

[0089] Among them, T GNSS (urban) represents the atmospheric temperature obtained by urban stations based on GNSS tomography; T GNSS (rural) represents the atmospheric temperature obtained by rural stations based on GNSS tomography.

[0090] For example, the specific method for setting the preset search range is as follows:

[0091] Use the ERA5 product to obtain the initial values ​​of temperature and vapor pressure;

[0092] Using the sounding product as a benchmark, the range of difference between the initial value and the benchmark is obtained, and a sub-range is selected from the range of difference as the preset search range.

[0093] Compared to existing technologies, the urban heat island concentration calculation method provided in this invention first accurately obtains the three-dimensional vertical distribution information of atmospheric wet refractive index based on GNSS tomography. Next, utilizing the functional relationship between atmospheric wet refractive index and temperature and water vapor pressure, as well as the functional relationship between temperature and water vapor pressure and elevation between adjacent layers, an optimal temperature and wet pressure can be determined using a search method, eliminating unknown and interfering factors involved in the calculation process. Finally, the temperature retrieved from urban GNSS stations is subtracted from the temperature retrieved from rural GNSS stations to accurately estimate the urban heat island concentration.

[0094] The estimation of urban heat island concentration using the embodiments of the present invention can improve the spatiotemporal resolution of urban heat island concentration. It can not only study the horizontal variation characteristics of urban heat island concentration, but also explore its vertical variation characteristics, making full use of the advantages of GNSS positioning analysis.

[0095] One embodiment of this application provides an urban heat island concentration calculation device, including: a first calculation module, a three-dimensional information module, a horizontal constraint module, a vertical constraint module, a solution module, and a second calculation module.

[0096] The first calculation module is used to calculate the wetted tropospheric delay based on GNSS observations;

[0097] A three-dimensional information module is used to obtain the three-dimensional vertical distribution information of the wet refractive index based on the wet delay of the zenith troposphere;

[0098] The horizontal constraint module is used to obtain horizontal constraint information in the horizontal direction;

[0099] The vertical constraint module is used to obtain vertical constraint information in the vertical direction;

[0100] The calculation module is used to calculate the three-dimensional vertical distribution information based on the horizontal constraint information and the vertical constraint information to obtain the wet refractive index profile.

[0101] The second calculation module is used to calculate the urban heat island concentration based on the relationship between the wet refractive index profile and atmospheric temperature.

[0102] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be elaborated further here.

[0103] Compared to existing technologies, the urban heat island concentration calculation device provided in this invention first accurately obtains the three-dimensional vertical distribution information of atmospheric wet refractive index based on GNSS tomography. Next, utilizing the functional relationship between atmospheric wet refractive index and temperature and vapor pressure, as well as the functional relationship between temperature and vapor pressure and elevation between adjacent layers, an optimal temperature and moisture pressure can be determined using a search method, eliminating unknown and interfering factors involved in the calculation process. Finally, the temperature retrieved from urban GNSS stations is subtracted from the temperature retrieved from rural GNSS stations to accurately estimate the urban heat island concentration.

[0104] The estimation of urban heat island concentration using the embodiments of the present invention can improve the spatiotemporal resolution of urban heat island concentration. It can not only study the horizontal variation characteristics of urban heat island concentration, but also explore its vertical variation characteristics, making full use of the advantages of GNSS positioning analysis.

[0105] One embodiment of this application provides a computer device, including a processor and a memory, wherein the memory is used to store a computer program, and the computer program, when executed by the processor, implements the urban heat island concentration calculation method as described above.

[0106] The computer device may be a smartphone, tablet, desktop computer, or cloud server, among other computing devices. This computer device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the computer device may include input / output devices, network access devices, etc.

[0107] The processor referred to can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0108] In some embodiments, the memory may be an internal storage unit of the computer device, such as a hard drive or RAM. In other embodiments, the memory may be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory may include both internal and external storage units of the computer device. The memory is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory can also be used to temporarily store data that has been output or will be output.

[0109] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for calculating urban heat island concentration, characterized in that, include: Calculate the wetted tropospheric delay based on GNSS observations; The three-dimensional vertical distribution information of wet refractive index is obtained based on the wet delay of the zenith troposphere; In the horizontal direction, obtain horizontal constraint information; In the vertical direction, obtain vertical constraint information; Based on the horizontal constraint information and the vertical constraint information, the three-dimensional vertical distribution information is calculated to obtain the wet refractive index profile; The urban heat island concentration is calculated based on the relationship between the wet refractive index profile and atmospheric temperature. Specifically, obtaining the three-dimensional vertical distribution information of the wet refractive index based on the wet delay of the zenith troposphere includes: The wetted zenith tropospheric delay is projected onto the original satellite propagation path using a projection function to obtain the slant path tropospheric delay. Based on the relationship between the oblique path tropospheric delay and the wet refractive index, the three-dimensional vertical distribution information of the wet refractive index is obtained; the three-dimensional vertical distribution information is represented by a tomographic equation.

2. The method for calculating urban heat island concentration as described in claim 1, characterized in that, The step of obtaining horizontal constraint information in the horizontal direction specifically includes: The horizontal constraint coefficients are obtained using a Gaussian distance weighting function.

3. The method for calculating urban heat island concentration as described in claim 1, characterized in that, The step of obtaining vertical constraint information in the vertical direction specifically includes: Based on the space formed by the three-dimensional vertical distribution information, Gaussian exponential variation information is obtained; Based on the Gaussian exponent variation information, the relationship between the wet refractive indices of two adjacent layers in the vertical direction is obtained.

4. The method for calculating urban heat island concentration as described in claim 1, characterized in that, The step of calculating the three-dimensional vertical distribution information based on the horizontal and vertical constraint information to obtain the wet refractive index profile specifically includes: Based on the horizontal and vertical constraint information, the three-dimensional vertical distribution information is solved using Kalman filtering to obtain the wet refractive index profile.

5. The method for calculating urban heat island concentration as described in claim 1, characterized in that, The calculation of urban heat island concentration based on the relationship between the wet refractive index profile and atmospheric temperature specifically includes: Based on the relationship between the wet refractive index profile and atmospheric temperature, the atmospheric temperature value is estimated within a preset search range. The difference between the temperature values ​​retrieved from urban GNSS stations and those retrieved from rural GNSS stations is taken as the urban heat island concentration.

6. The method for calculating urban heat island concentration as described in claim 5, characterized in that, The step of searching for and estimating atmospheric temperature values ​​within a preset search range based on the relationship between the wet refractive index profile and atmospheric temperature specifically includes: Based on the relationship between the wet refractive index profile and atmospheric temperature, the linear relationship between atmospheric temperature and elevation, and the near-exponential relationship between water vapor pressure and elevation, the atmospheric temperature and water vapor pressure values ​​are estimated using the best priority search method within a preset search range.

7. The method for calculating urban heat island concentration as described in claim 5 or 6, characterized in that, The specific method for setting the preset search range is as follows: Use the ERA5 product to obtain the initial values ​​of temperature and vapor pressure; Using the sounding product as a benchmark, the range of difference between the initial value and the benchmark is obtained, and a sub-range is selected from the range of difference as the preset search range.

8. A device for calculating urban heat island concentration, characterized in that, include: The first calculation module is used to calculate the wetted tropospheric delay based on GNSS observations; A three-dimensional information module is used to obtain the three-dimensional vertical distribution information of the wet refractive index based on the wet delay of the zenith troposphere; The horizontal constraint module is used to obtain horizontal constraint information in the horizontal direction; The vertical constraint module is used to obtain vertical constraint information in the vertical direction; The calculation module is used to calculate the three-dimensional vertical distribution information based on the horizontal constraint information and the vertical constraint information to obtain the wet refractive index profile. The second calculation module is used to calculate the urban heat island concentration based on the relationship between the wet refractive index profile and atmospheric temperature. The three-dimensional information module is used to obtain the three-dimensional vertical distribution information of the wet refractive index based on the wet lag in the zenith troposphere, specifically including: The wetted zenith tropospheric delay is projected onto the original satellite propagation path using a projection function to obtain the slant path tropospheric delay. Based on the relationship between the oblique path tropospheric delay and the wet refractive index, the three-dimensional vertical distribution information of the wet refractive index is obtained; the three-dimensional vertical distribution information is represented by a tomographic equation.

9. A computer device, characterized in that, It includes a processor and a memory, the memory being used to store a computer program that, when executed by the processor, implements the urban heat island concentration calculation method as described in any one of claims 1 to 7.

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