Calculation method, equipment and storage medium of PML-urban evapotranspiration model based on remote sensing of urban underlying surface

Abstract

The present invention belongs to the technical field of urban water cycle and evapotranspiration calculation, and discloses a method, device and storage medium for calculating the evapotranspiration model of urban surface remote sensing PML-urban, including: step 1. obtaining basic data, the basic data at least including urban meteorological data, urban surface type spatial distribution data, urban vegetation feature data, urban administrative planning, urban digital ground elevation data, and urban building type data; step 2. dividing the basic data into multiple data units based on the surface characteristics; step 3. calculating the surface evapotranspiration and the evapotranspiration of human activities for each data unit; step 4. calculating the urban evapotranspiration based on the surface evapotranspiration and the evapotranspiration of human activities of all data units. The present invention comprehensively considers the differences in the characteristics of the urban surface, accurately simulates and estimates the evapotranspiration value of the city, and is of great significance to the construction of urban green development, sponge city construction planning, ecological restoration, etc.

Description

Technical Field

[0001] The invention belongs to the technical field of urban water cycle and evapotranspiration calculation, and specifically relates to a calculation method, equipment and storage medium for an urban underlying surface remote sensing PML-urban evapotranspiration model. Background Art

[0002] Changes in urban water cycle processes caused by global climate change and rapid urbanization are a hot topic in current urban hydrology research. Urban water cycle processes include hydrophysical processes, water quality and ecological processes, and human processes. Urban evapotranspiration (ET) is one of the important components of the urban water cycle process, which includes evapotranspiration from natural underlying surfaces, evaporation from impervious surfaces, evapotranspiration from buildings, evapotranspiration from human activities, and water vapor from biological respiration. Accurate estimation of urban ET and research on its changing laws are the core and key to a deep understanding of the urban water cycle process, and have important research significance for the improvement of disciplines such as urban hydrology, urban water resources management, and urban ecosystems.

[0003] Urban development has caused impermeable roads and buildings in cities to replace the original natural underlying surface, which has changed the physical properties of the underlying surface, weakened its water holding capacity, and caused rainfall to directly form runoff and flow into urban drainage pipes. At the same time, the vegetation in urban built-up areas has decreased, and the transpiration capacity of vegetation has weakened, resulting in a possible decrease in ET in urban areas compared to natural areas. However, due to the high heterogeneity of land use in urban areas, and the difficulty in accurately quantifying variables such as urban building height, roughness length, zero plane displacement, and anthropogenic heat sources, coupled with the relatively small amount of data currently available for urban ET verification, it is still very difficult to establish an accurate urban ET estimation model.

[0004] At present, the commonly used urban ET estimation methods include methods based on the water balance principle and energy balance method. The methods based on the water balance principle mainly consider the impact of urban water supply, water use, water consumption and drainage on the urban regional water cycle, such as the use of urban water consumption models and water balance models. The water balance principle requires less data types and is easy to calculate. However, due to the complex pipelines in urban areas and limited record data such as water supply and drainage data, the data used in the urban water consumption model is difficult to obtain and the spatial scale of the calculation is small, which limits its application in larger spatial scales. The energy balance method mainly estimates urban evapotranspiration based on the surface energy balance formula. The required conventional meteorological data is relatively easy to obtain. It is currently widely used in the field of urban ET estimation, such as SEBS, SEBAL, TSEB and other models.

[0005] It should be pointed out that existing studies have shown that in urban areas, the heat generated by dense populations and frequent human activities cannot be ignored, and will significantly affect the estimation accuracy of ET in urban areas. Traditional energy balance methods often ignore the heat items generated by human activities and the energy transfer items in the horizontal direction. In addition, the changes in land use / cover conditions brought about by urbanization will also significantly change the evapotranspiration process. At present, with the increasing convenience of obtaining high-resolution remote sensing image data, anthropogenic heat flux remote sensing data and other data, when estimating urban evapotranspiration, considering the impact of anthropogenic heat flux and land use changes on urban evapotranspiration will significantly improve the estimation accuracy of evapotranspiration. This is also an important direction for improving the current urban ET estimation method. Existing scholars have proposed urban evapotranspiration estimation models based on the original energy balance model, such as SEBS-urban and uSEBAL models, which are based on urban human activities.

[0006] However, the coupling degree between the computational model and urban land use is not high. Often, only one or two surface parameters consider the special physical properties of urban impervious surfaces, which cannot reflect the impact of the high heterogeneity of the underlying surface in urban areas on ET. On the other hand, most existing models select one or several days with clear remote sensing graphics to calculate the results to represent the temporal fluctuation of ET in the entire region, and lack a continuous time series urban ET estimation model. In addition, with the further development of social economy and the promotion of green development of the Yangtze River Economic Belt, the understanding and research on the laws of urban evapotranspiration need to be further deepened and carried out. Further research on the laws of urban evapotranspiration will provide important scientific basis and technical support for the construction of a comprehensive simulation platform for urban water environment. There are still many challenges in improving the simulation effect of urban hydrological cycle processes, especially accurate evapotranspiration simulation under complex urban underlying surfaces. Summary of the invention

[0007] The purpose of the present invention is to address the shortcomings of the existing technology, take into account the high heterogeneity of the surface in urban areas, the complex underlying surface conditions in urban areas, and the different physical properties from the traditional watershed scale, and provide a method, device and storage medium for calculating the evapotranspiration model of urban underlying surface remote sensing PML-urban for the problem of evapotranspiration estimation in urban areas.

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0009] The present invention discloses a method for calculating an urban underlying surface remote sensing PML-urban evapotranspiration model, comprising the following steps:

[0010] Step 1. Obtain basic data, which at least includes urban meteorological data, urban underlying surface type spatial distribution data, urban vegetation feature data, urban administrative planning, urban digital ground elevation data, and urban building type data;

[0011] Step 2: Divide the basic data into multiple data units based on different underlying surface characteristics of the land;

[0012] Step 3. Calculate the surface evapotranspiration and evapotranspiration generated by human activities for each of the data units;

[0013] Step 4: Calculate urban evapotranspiration based on the surface evapotranspiration of all the data units and the evapotranspiration generated by human activities.

[0014] Preferably, in step 3, the surface evapotranspiration ET includes vegetation transpiration E s and soil evaporation E c , that is, ET=E s +E c ; The calculation process is:

[0015] Assume that the energy used for soil evapotranspiration is A s The ratio of the total energy A is f, and the estimation formula of surface evapotranspiration is:

[0016]

[0017] Where: λ = 2.454MJ / kg, representing the latent heat of vaporization; ε = △ / γ, where △ is the slope of the temperature-saturated water vapor pressure curve, and γ is the psychrometric constant; ρ a is the air density; D a =e s -e a is the vapor pressure difference, e s The temperature is T a The saturated water vapor pressure of air at a is the actual water vapor pressure; c p is the specific heat of air at constant pressure; G a is the aerodynamic conductivity; G s A is the ground conductance, representing the physiological regulation of stomatal conductance on vegetation transpiration and the effect of soil moisture on soil evaporation; A = R n -G n is the effective energy; R n is the net radiation of the surface; G n is the soil heat flux; G a A is the aerodynamic conductivity; c / A=1–τ,τ=exp(-k A ·LAI), A c and A s are the available energy of vegetation and the energy absorbed by soil, and the sum of the two is the total energy used for evapotranspiration; k A is the available energy attenuation coefficient; G cis leaf conductance; LAI is remote sensing leaf area index.

[0018] Preferably, in the process of calculating the surface evapotranspiration, the urban surface net radiation is calculated according to the type of the underlying surface characteristics of the data unit, and the formula is as follows:

[0019] R n =(1-α)R S ↓+R L ↓-(ε0σLST 4 )-(1-ε0)R L ↓ (2)

[0020] Where: R n represents the net radiation of the surface; R s Represents shortwave radiation; R L represents long-wave radiation, and the direction of the arrow represents the direction of radiation; LST represents the land surface temperature; α represents the land surface albedo, where the values ​​are 0.13, 0.20, 0.10, 0.25, and 0.30 respectively based on the underlying surface type: forest, grassland, wetland, urban impervious surface, and bare soil; σ represents the Stefan-Boltzmann constant; ε0 represents the surface radiation emissivity in urban areas, and the values ​​are as follows:

[0021]

[0022] Preferably, in the process of calculating the surface evapotranspiration, the blade conductance G is calculated in combination with the water vapor pressure difference. c :

[0023]

[0024] Where: Q h =0.8A is the visible light radiation energy above the canopy; g sx is the maximum stomatal conductance of vegetation, k Q is the shortwave radiation attenuation coefficient, D 50 It represents the vapor pressure difference when the stomatal conductance is half of the maximum value, Q 50 It represents the visible light radiation energy absorbed by the leaves when the stomatal conductance is half of the maximum value;

[0025] And / or, in the process of calculating surface evapotranspiration, the air conductivity G is calculated in combination with meteorological data a :

[0026]

[0027] Where: z m is the height of the instrument for measuring wind speed and humidity; d is the height of the zero plane; z om and z ovare the roughness lengths for momentum transfer and water vapor transport, respectively; k is the Karman constant, which is 0.41; u m is the wind speed (m / s); in this paper, d=2h / 3, z om =0.123h, z ov =0.1z om , h is the vegetation height.

[0028] Preferably, in the process of calculating the surface evapotranspiration, when estimating the evapotranspiration of a continuous time series, if the calculation is based on a daily time scale, the soil heat flux G n The heat absorbed during the day and the heat dissipated at night are approximately equal, so they can be set to zero; that is, according to the above formula, the ground conductance G s :

[0029]

[0030] Where: Gi = A / ((ρacp / γ)Da) represents the "meteorological" conductivity. According to the spatial distribution of the urban underlying surface, the entire calculation area is divided into six calculation grid types: forest, grassland, artificial wetland, urban impervious surface, and bare soil;

[0031] When there is no vegetation on the urban plot, there is no vegetation transpiration on the entire plot, and equation (6) becomes:

[0032]

[0033] Preferably, in the process of calculating surface evapotranspiration, f actually represents the soil moisture index. The calculation method of the soil moisture index is determined according to different land use types in the city and in combination with the principle of previous rainfall index, as follows:

[0034]

[0035] Preferably, in step 3, the process of calculating the evapotranspiration generated by human activities is:

[0036] Combined with the urban night light remote sensing image, the anthropogenic heat flux value in the urban area is first estimated as follows:

[0037]

[0038] Where: Q f1 and Q f2 represent the anthropogenic heat flux in winter and summer and in spring and autumn, respectively, where Q fl1 (=50W·m -2 ) and Q fu1 (=75W·m -2 ) are the minimum and maximum values ​​of anthropogenic heat flux in winter and summer, respectively, Q fl2(=30W·m -2 ) and Q fu2 (=50W·m -2 ) represent the minimum and maximum values ​​of urban heat flux in spring and autumn respectively; k b The representative building type coefficients for the four types of urban roads, industrial land, commercial land, residential land, and educational land are 1.25, 1.5, 1, 0.5, and 0.75 respectively according to the nature of their human activities; NTL nor Represents the normalized urban night light remote sensing value.

[0039] Preferably, in step 4, urban evapotranspiration is calculated based on the surface energy balance formula, namely:

[0040] A=R n -G n +Q f (10).

[0041] Secondly, the present invention also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the computer program, the method for calculating the urban surface remote sensing PML-urban evapotranspiration model described in any one of the above items is implemented.

[0042] In addition, the present invention also discloses a computer-readable storage medium on which a computer program is stored, characterized in that when the computer program is executed by a processor, the urban underlying surface remote sensing PML-urban evapotranspiration model calculation method described in any one of the above is implemented.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] The present invention comprehensively considers the differences in the characteristics of urban underlying surfaces, and can simultaneously consider various urban underlying surface types such as lakes, depressions, roads, impervious surfaces, and pervious surfaces with different vegetation. Based on the PML-urban model, the present invention accurately simulates and estimates the evapotranspiration values ​​of urban areas, and provides accurate evapotranspiration numerical results for further estimating urban water resources ledgers and urban water resources management. It is of great significance to urban water issues such as urban green development and construction, sponge city construction planning, and ecological restoration, which is mainly reflected in the following aspects:

[0045] (1) Based on the spatial distribution of urban underlying surfaces and considering the differences in the physical properties of different underlying surfaces, the present invention divides urban areas into three categories and nine subcategories of data units for calculation. Different models use different observation parameters for different categories, thus overcoming the disadvantage that the traditional evapotranspiration calculation model has weak coupling with the underlying surface.

[0046] (2) The remote sensing PML-urban evapotranspiration model combined with the urban underlying surface characteristics adopted in the present invention can more accurately simulate the size of daily evapotranspiration in urban areas;

[0047] (3) The present invention covers fields such as meteorology, hydrology, remote sensing, and mathematics, involves multidisciplinary cross-integration, and has a clear model structure. It can be adopted by relevant departments such as national urban construction and water conservancy at the same time, and can provide more reasonable technology and decision-making support for colleagues from multiple departments. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a flow chart of the calculation method of the urban underlying surface remote sensing PML-urban evapotranspiration model according to Example 1 of the present invention.

[0049] Figure 2 This is a schematic diagram of the structure of an electronic device according to Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0050] The present invention will be further described below in conjunction with the embodiments shown in the accompanying drawings.

[0051] As attached Figure 1 As shown, this embodiment discloses a method for calculating an urban surface remote sensing PML-urban evapotranspiration model, including the following steps:

[0052] Step 1. Obtain basic data, which at least includes urban meteorological data, spatial distribution data of urban underlying surface types, urban vegetation feature data, urban administrative planning, urban digital ground elevation data, and urban building type data.

[0053] In a specific implementation, urban meteorological data include at least: daily average near-ground temperature, air pressure, air specific humidity, total wind speed, downward short-wave radiation from the ground, downward long-wave radiation from the ground, and ground precipitation rate; the underlying surface types in the spatial distribution data of urban underlying surface types include at least: permeable surface, impermeable surface, roads, lakes, green space, and artificial wetlands; urban building types include at least: industrial land, commercial land, residential land, and educational and teaching land.

[0054] Step 2: Divide the basic data into multiple data units based on different underlying surface characteristics of the land.

[0055] In a specific implementation, the urban surface is divided into at least three categories: vegetation, water, and urban buildings, so that different parameter groups will be used for calculation based on different attributes of urban land use in step 3. Specifically,

[0056] The vegetation category includes at least: trees, grasslands and bare land without vegetation. The main crop types on the plots, vegetation height and other parameters are counted, and the corresponding vegetation parameters are determined, including vegetation height, shortwave radiation attenuation coefficient, maximum stomatal conductance of vegetation, water vapor pressure difference when stomatal conductance is half of the maximum value, and visible light radiation energy absorbed by leaves when stomatal conductance is half of the maximum value.

[0057] The water body category includes at least artificial wetlands. For this type of land, it is assumed that the soil moisture content has reached saturation and the soil evaporation capacity has reached its maximum value when calculating evapotranspiration.

[0058] The urban building category includes at least: urban roads, industrial land, commercial land, residential land, and educational and teaching land. The urban impervious surfaces are marked with impervious roads and building types. The basic types of buildings are divided based on administrative planning and urban digital elevation information.

[0059] Step 3. Calculate the surface evapotranspiration and evapotranspiration caused by human activities for each data unit.

[0060] In a specific embodiment, in step 3, the surface evapotranspiration ET includes vegetation transpiration E s and soil evaporation E c , that is, ET=E s +E c ; The calculation process is:

[0061] Assume that the energy used for soil evapotranspiration is A s The ratio of the total energy A is f, and the estimation formula of surface evapotranspiration is:

[0062]

[0063] Where: λ = 2.454MJ / kg, representing the latent heat of vaporization; ε = △ / γ, where △ is the slope of the temperature-saturated water vapor pressure curve, and γ is the psychrometric constant; ρ a is the air density; D a =e s -e a is the vapor pressure difference, e s The temperature is T a The saturated water vapor pressure of air at a is the actual water vapor pressure; c p is the specific heat of air at constant pressure; G a is the aerodynamic conductivity; G s A is the ground conductance, representing the physiological regulation of stomatal conductance on vegetation transpiration and the effect of soil moisture on soil evaporation; A = R n -G n is the effective energy; R n is the net radiation of the surface; G nis the soil heat flux; G a A is the aerodynamic conductivity; c / A=1–τ,τ=exp(-k A ·LAI), A c and A s are the available energy of vegetation and the energy absorbed by soil, and the sum of the two is the total energy used for evapotranspiration; k A is the available energy attenuation coefficient; G c is leaf conductance; LAI is remote sensing leaf area index.

[0064] In the process of calculating surface evapotranspiration, the urban surface net radiation is calculated according to the type of underlying surface characteristics of the data unit. The formula is as follows:

[0065] R n =(1-α)R S ↓+R L ↓-(ε0σLST 4 )-(1-ε0)R L ↓ (2)

[0066] Where: R n represents the net radiation of the surface; R s Represents shortwave radiation; R L represents long-wave radiation, and the direction of the arrow represents the direction of radiation; LST represents the land surface temperature; α represents the land surface albedo, where the values ​​are 0.13, 0.20, 0.10, 0.25, and 0.30 respectively based on the underlying surface type: forest, grassland, wetland, urban impervious surface, and bare soil; σ represents the Stefan-Boltzmann constant; ε0 represents the land surface radiation emissivity in urban areas, and the values ​​are as follows:

[0067]

[0068] Secondly, in the process of calculating surface evapotranspiration, the leaf conductance G is calculated in combination with the water vapor pressure difference. c :

[0069]

[0070] Where: Q h =0.8A is the visible light radiation energy above the canopy; g sx is the maximum stomatal conductance of vegetation, k Q is the shortwave radiation attenuation coefficient, D 50 It represents the vapor pressure difference when the stomatal conductance is half of the maximum value, Q 50 It represents the visible light radiation energy absorbed by the leaves when the stomatal conductance is half of its maximum value.

[0071] Secondly, in the process of calculating surface evapotranspiration, the air conductivity G is calculated in combination with meteorological data. a :

[0072]

[0073] Where: z m is the height of the instrument for measuring wind speed and humidity; d is the height of the zero plane; z om and z ov are the roughness lengths for momentum transfer and water vapor transport, respectively; k is the Karman constant, which is 0.41; u m is the wind speed (m / s); in this paper, d=2h / 3, z om =0.123h, z ov =0.1z om , h is the vegetation height.

[0074] In addition, in the process of calculating surface evapotranspiration, when estimating continuous time series evapotranspiration, if the calculation is based on daily time scale, the soil heat flux G n The heat absorbed during the day and the heat dissipated at night are approximately equal, so they can be set to zero; that is, according to the above formula, the ground conductance G s :

[0075]

[0076] Where: G i =A / ((ρ a c p / γ)D a ) represents the “meteorological” conductivity. According to the spatial distribution of the urban underlying surface, the entire calculation area is divided into six calculation grid types: forest, grassland, artificial wetland, urban impervious surface, and bare soil;

[0077] When there is no vegetation on the urban plot, there is no vegetation transpiration on the entire plot, and equation (6) becomes:

[0078]

[0079] In another specific embodiment, compared with natural watersheds, the water holding capacity of impermeable surfaces in urban built-up areas is very poor, and rainfall often directly forms runoff and flows into the pipe network and is discharged at the urban pipe drain outlet. At the same time, hardened land surfaces will prevent soil water vapor from escaping into the air and prevent soil evaporation. Therefore, the soil wetland index in urban areas should be lower than that in natural areas, and water bodies can provide sufficient moisture conditions for evaporation. The humidity index can be maintained at a high level. According to different land use types in the city, the calculation method of the soil humidity index is determined in combination with the principle of the previous rainfall index. Therefore, in the process of calculating surface evaporation, f actually represents the soil humidity index. According to different land use types in the city, the calculation method of the soil humidity index is determined in combination with the principle of the previous rainfall index, as follows:

[0080]

[0081] In a specific implementation, in step 3, the process of calculating evapotranspiration generated by human activities is:

[0082] Combined with the urban night light remote sensing image, the anthropogenic heat flux value in the urban area is first estimated as follows:

[0083]

[0084] Where: Q f1 and Q f2 represent the anthropogenic heat flux in winter and summer and in spring and autumn, respectively, where Q fl1 (=50W·m -2 ) and Q fu1 (=75W·m -2 ) are the minimum and maximum values ​​of anthropogenic heat flux in winter and summer, respectively, Q fl2 (=30W·m -2 ) and Q fu2 (=50W·m -2 ) represent the minimum and maximum values ​​of urban heat flux in spring and autumn respectively; k b The representative building type coefficients for the four types of urban roads, industrial land, commercial land, residential land, and educational land are 1.25, 1.5, 1, 0.5, and 0.75 respectively according to the nature of their human activities; NTL nor Represents the normalized urban night light remote sensing value.

[0085] Step 4. Calculate urban evapotranspiration based on the surface evapotranspiration of all data units and the evapotranspiration generated by human activities.

[0086] In a specific implementation, in step 4, urban evapotranspiration is calculated based on the surface energy balance formula, that is, the night light remote sensing inversion method is used to calculate the urban anthropogenic heat flux, and it is added to the surface energy balance formula (i.e., formula (3)), and the evapotranspiration of the urban land is calculated after integrating the surface energy. That is:

[0087] A=R n -G n +Q f (10)

[0088] The method of this embodiment comprehensively considers the differences in the characteristics of urban underlying surfaces, and considers various urban underlying surface types such as lakes, depressions, roads, impervious surfaces, and pervious surfaces with different vegetation. Based on the PML-urban model, the evapotranspiration values ​​of urban areas are accurately simulated and estimated, and accurate evapotranspiration values ​​are provided for further estimation of urban water resources ledgers and urban water resources management. It is of great significance to urban water issues such as urban green development and construction, sponge city construction planning, and ecological restoration, which is mainly reflected in the following aspects:

[0089] (1) Based on the spatial distribution of urban underlying surfaces, this embodiment considers the different physical properties of different underlying surfaces and divides the urban area into three categories and nine subcategories of data units for calculation. Different models use different observation parameters for different categories, thus overcoming the disadvantage that the traditional evapotranspiration calculation model has weak coupling with the underlying surface.

[0090] (2) The remote sensing PML-urban evapotranspiration model used in this embodiment, which combines the characteristics of the urban underlying surface, can more accurately simulate the size of daily evapotranspiration in urban areas;

[0091] (3) This embodiment includes fields such as meteorology, hydrology, remote sensing, and mathematics, involving the cross-integration of multiple disciplines. The model structure is clear and can be adopted by relevant departments such as national urban construction and water conservancy at the same time, providing more reasonable technical and decision-making support for colleagues from multiple departments.

[0092] <Example 2>

[0093] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the urban underlying surface remote sensing PML-urban evapotranspiration model calculation method of embodiment 1 is implemented.

[0094] Figure 2 A schematic diagram of the structure of an electronic device provided in this embodiment. Figure 2 A block diagram of an exemplary electronic device 90 suitable for use in implementing embodiments of the present invention is shown. Figure 2 The electronic device 90 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0095] like Figure 2 As shown, the electronic device 90 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 90 may include, but are not limited to: at least one processor 91, at least one memory 92, and a bus 93 connecting different system components (including the memory 92 and the processor 91).

[0096] The bus 93 includes a data bus, an address bus, and a control bus.

[0097] The memory 92 may include a volatile memory, such as a random access memory (RAM) 921 and / or a cache memory 922 , and may further include a read-only memory (ROM) 923 .

[0098] The memory 92 may also include a program tool 925 having a set (at least one) of program modules 924, such program modules 924 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include the implementation of a network environment.

[0099] The processor 91 executes various functional applications and data processing by running computer programs stored in the memory 92 .

[0100] The electronic device 90 may also communicate with one or more external devices 94 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input / output (I / O) interface 95. Furthermore, the electronic device 90 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 96. The network adapter 96 communicates with other modules of the electronic device 90 via a bus 93. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 90, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0101] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0102] <Example 3>

[0103] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the urban underlying surface remote sensing PML-urban evapotranspiration model calculation method of embodiment 1.

[0104] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0105] In a possible implementation, the present invention can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the battery replacement control method based on the bottom height of the battery replacement vehicle of Example 1.

[0106] Among them, the program code for executing the present invention can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0107] The protection scope of the present invention is not limited to the above-mentioned embodiments. Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the scope and spirit of the present invention. If these changes and modifications fall within the scope of the claims of the present invention and their equivalents, the present invention is intended to include these changes and modifications.

Claims

1. A method for calculating the urban surface remote sensing PML-urban evapotranspiration model, characterized in that: The following steps are involved: Step 1. Obtain basic data, which at least includes urban meteorological data, urban underlying surface type spatial distribution data, urban vegetation feature data, urban administrative planning, urban digital ground elevation data, and urban building type data; Step 2: Divide the basic data into multiple data units based on different underlying surface characteristics of the land; Step 3. Calculate the surface evapotranspiration and evapotranspiration generated by human activities for each of the data units; Step 4. Calculate urban evapotranspiration based on the surface evapotranspiration of all the data units and the evapotranspiration generated by human activities; Wherein, in step 3, the surface evapotranspiration ET includes vegetation transpiration E s and soil evaporation E c , that is, ET=E s +E c ; The calculation process is: Assume that the energy used for soil evapotranspiration is A s The ratio of the total energy A is f, and the estimation formula of surface evapotranspiration is: Where: λ = 2.454MJ / kg, representing the latent heat of vaporization; ε = △ / γ, where △ is the slope of the temperature-saturated water vapor pressure curve, and γ is the psychrometric constant; ρ a is the air density; D a =e s -e a is the vapor pressure difference, e s The temperature is T a The saturated water vapor pressure of air at time e a is the actual water vapor pressure; c p is the specific heat of air at constant pressure; G a is the aerodynamic conductivity; G s A is the ground conductance, representing the physiological regulation of stomatal conductance on vegetation transpiration and the effect of soil moisture on soil evaporation; A = R n -G n is the effective energy; R n is the net radiation of the surface; G n is the soil heat flux; G a A is the aerodynamic conductivity; c / A=1–τ,τ=exp(-k A ·LAI), A c and A s are the available energy of vegetation and the energy absorbed by soil, and the sum of the two is the total energy used for evapotranspiration; k A is the available energy attenuation coefficient; G c is leaf conductance; LAI is remote sensing leaf area index; The urban surface net radiation is calculated according to the type of underlying surface characteristics of the data unit, and the formula is as follows: R n =(1-α)R S ↓+R L ↓-(ε0σLST 4 )-(1-ε0)R L ↓ (2) Where: R n represents the net radiation of the surface; R s Represents short-wave radiation; R L represents long-wave radiation, and the direction of the arrow represents the direction of radiation; LST represents the surface temperature; α represents the surface albedo; σ represents the Stefan-Boltzmann constant; ε0 represents the surface radiation emissivity in urban areas; Calculate blade conductance G based on vapor pressure difference c : Where: Q h =0.8A is the visible light radiation energy above the canopy; g sx is the maximum stomatal conductance of vegetation, k Q is the shortwave radiation attenuation coefficient, D 50 It represents the vapor pressure difference when the stomatal conductance is half of the maximum value, Q 50 It represents the visible light radiation energy absorbed by the leaves when the stomatal conductance is half of the maximum value; Calculate air conductivity G in combination with meteorological data a : Where: z m is the height of the instrument for measuring wind speed and humidity; d is the height of the zero plane; z om and z ov are the roughness lengths for momentum transfer and water vapor transport, respectively; k is the Karman constant; u m is the wind speed; d = 2h / 3, z om =0.123h, z ov =0.1z om , h is the vegetation height; When estimating evapotranspiration in a continuous time series, if the calculation is based on daily time scale, the soil heat flux G n The heat absorbed during the day and the heat dissipated at night are approximately equal, so they are set to zero; that is, according to the above formula, the ground conductance G s : Where: Gi = A / ((ρacp / γ)Da) represents the "meteorological" conductivity.

2. The urban surface remote sensing PML-urban evapotranspiration model calculation method according to claim 1 is characterized by: In the formula (1), the surface albedo α of the underlying surface type: forest, grassland, wetland, urban impervious surface, and bare soil are taken as 0.13, 0.20, 0.10, 0.25, and 0.30 respectively; the surface radiation emissivity ε0 in urban areas is taken as follows:

3. The urban surface remote sensing PML-urban evapotranspiration model calculation method according to claim 1 is characterized by: In the formula (5), according to the spatial distribution of the urban underlying surface, the entire calculation area is divided into six calculation grid types: forest, grassland, artificial wetland, urban impervious surface, and bare soil; When there is no vegetation on the urban plot, there is no vegetation transpiration on the entire plot, and equation (5) becomes:

4. The urban surface remote sensing PML-urban evapotranspiration model calculation method according to claim 1 is characterized by: In the process of calculating surface evapotranspiration, f actually represents the soil moisture index. The calculation method of the soil moisture index is determined according to different land use types in the city and the principle of the previous rainfall index, as follows:

5. The urban surface remote sensing PML-urban evapotranspiration model calculation method according to claim 1 is characterized by: In step 3, the process of calculating the evapotranspiration generated by human activities is: Combined with the urban night light remote sensing image, the anthropogenic heat flux value in the urban area is first estimated as follows: Where: Q f1 and Q f2 represents the anthropogenic heat flux in winter and summer and in spring and autumn, respectively, where Q fl1 =50W·m -2 and Q fu1 =75W·m -2 are the minimum and maximum values ​​of anthropogenic heat flux in winter and summer, respectively, Q fl2 =30W·m -2 and Q fu2 =50W·m -2 represent the minimum and maximum values ​​of urban heat flux in spring and autumn respectively; k b The representative building type coefficients for the four types of urban roads, industrial land, commercial land, residential land, and educational land are 1.25, 1.5, 1, 0.5, and 0.75 respectively according to the nature of their human activities; NTL nor Represents the normalized urban night light remote sensing value.

6. The method for calculating the urban surface remote sensing PML-urban evapotranspiration model according to claim 5 is characterized by: In step 4, urban evapotranspiration is calculated based on the surface energy balance formula, namely: A=R n -G n +Q f (10)。 7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the urban surface remote sensing PML-urban evapotranspiration model calculation method according to any one of claims 1 to 6 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for calculating the urban surface remote sensing PML-urban evapotranspiration model according to any one of claims 1 to 6 is implemented.

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