A method and device for soil profile temperature inversion considering temperature diurnal cycle characteristics

Abstract

The application provides a soil profile temperature inversion method and device considering temperature daily cycle characteristics, the method constructs a target soil profile temperature daily cycle model based on a one-dimensional heat conduction equation; obtains time-series ground temperature data, soil parameter data, geographic coordinates and date information of a target region, and inversely obtains ground temperature key parameters describing the temperature intra-day change process of the target region, the ground temperature key parameters including daily average temperature, ground temperature amplitude and ground temperature peak time; calculates the thermal damping depth and the length of the day of each pixel of the target region; and substitutes the daily average temperature, the ground temperature amplitude and the ground temperature peak time, the length of the day, the thermal damping depth of each pixel of the target region into the target soil profile temperature daily cycle model, calculates the soil profile temperature of the target region based on a preset time resolution and depth resolution, so that the continuous and accurate inversion of the soil temperature of different regions and different depths is realized.

Description

Technical Field

[0001] This application relates to the field of remote sensing and geoinformation science, and more specifically, to a method and apparatus for soil profile temperature inversion that takes into account the characteristics of the daily temperature cycle. Background Technology

[0002] Soil temperature is a crucial parameter in the energy exchange process between the Earth's surface and the atmosphere, directly influencing key ecological processes such as soil moisture dynamics, vegetation growth, and carbon cycling. Soil profile temperature information is essential for understanding surface thermodynamic processes, optimizing crop growth models, and improving the accuracy of meteorological and hydrological simulations. Especially against the backdrop of climate change and intensified human activities, the demand for dynamic monitoring of soil profile temperature is growing rapidly.

[0003] Remote sensing technology provides a new technical means for soil temperature monitoring, especially supporting large-scale, high-frequency surface observations. However, existing soil temperature inversion studies mostly focus on single-layer surface temperature estimation, with limited research on dynamic modeling and inversion of soil profile temperatures at different depths. Furthermore, because soil thermal diffusion characteristics are influenced by soil texture, moisture state, and thermodynamic processes, achieving high-precision soil profile temperature inversion that takes into account diurnal temperature cycles based on remote sensing observations presents significant challenges.

[0004] Existing methods for soil temperature estimation based on remote sensing data mostly employ empirical regression models. These models estimate soil temperature at different depths by establishing statistical relationships between remote sensing factors such as land surface temperature (LST) and vegetation index (NDVI) and soil temperature. However, these regression models heavily rely on measured data for parameter fitting, resulting in limited applicability and difficulty adapting to variations in different climate zones, soil types, and vegetation conditions. Furthermore, these methods primarily rely on statistical fitting and do not consider the physical mechanisms of soil heat conduction and diffusion, making it difficult to accurately reflect the dynamic temperature transfer patterns within the profile. Consequently, the accuracy of soil temperature retrieved from remote sensing is relatively low, and it is challenging to generate full-time soil profile temperatures. Summary of the Invention

[0005] In view of this, the purpose of this application is to provide a method and apparatus for soil profile temperature inversion that takes into account the daily temperature cycle characteristics, which can realize continuous and accurate inversion of soil temperature at different depths in different regions.

[0006] This application provides a soil profile temperature inversion method that takes into account the characteristics of the daily temperature cycle, including:

[0007] Step S1: Construct a daily temperature cycle model for the target soil profile based on the one-dimensional heat conduction equation; the daily temperature cycle model for the target soil profile characterizes the relationship between soil profile temperature and time and depth.

[0008] Step S2: Obtain time-series surface temperature data, soil parameter data, geographic coordinates, and date information for the target area;

[0009] Step S3: Based on the time-series surface temperature data, key surface temperature parameters describing the intraday temperature variation process of the target area are retrieved. These key surface temperature parameters include the daily average temperature. Surface temperature amplitude and peak time of surface temperature ;

[0010] Step S4: Based on the soil parameter data, calculate the thermal damping depth Zd of each pixel in the target area; based on the geographic coordinates and date information, determine the daytime length of the target area. Step S5: The daily average temperature of the target area Surface temperature amplitude and peak time of surface temperature Day length The thermal damping depth Zd of each pixel is substituted into the daily cycle model of the target soil profile temperature, and the soil profile temperature of the target area is calculated based on the preset time resolution and depth resolution.

[0011] In some embodiments, the soil profile temperature inversion method that takes into account the diurnal temperature cycle characteristics includes, in the step of constructing a diurnal temperature cycle model of the target soil profile based on a one-dimensional heat conduction equation, the following:

[0012] Construct a one-dimensional heat conduction equation to describe the heat conduction process of surface temperature transfer from the surface to the depths;

[0013] Based on the given initial and boundary conditions, the one-dimensional heat conduction equation is solved to obtain the solution to the one-dimensional heat conduction equation;

[0014] The daily temperature cycle is defined as starting from sunrise on the current day and ending at sunrise on the next day. The daily temperature change cycle is divided into a daytime warming phase and a nighttime cooling phase. Based on the daily variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, a daily temperature cycle model of soil profile during the daytime warming phase is constructed.

[0015] Based on the surface radiative cooling characteristics, the temperature change process during the nighttime cooling phase is modeled, and the function is made continuous at the time points of change during the daytime warming phase and the nighttime cooling phase, thus obtaining a daily cycle model of soil profile temperature during the nighttime cooling phase.

[0016] By combining the daily temperature cycle models of the soil profile during the daytime warming phase and the nighttime cooling phase, the daily temperature cycle model of the target soil profile is obtained.

[0017] In some embodiments, the soil profile temperature inversion method considering diurnal temperature cycle characteristics includes, in constructing a diurnal temperature cycle model of the soil profile during the diurnal temperature cycle, based on the diurnal variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, the following steps:

[0018] Based on the diurnal variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, trigonometric functions are used to construct the soil profile temperature during the daytime warming phase. and daily average temperature Amplitude at different depths The moment of the highest temperature at depth z Day length The relationship between these factors was used to determine the daily cycle model of soil profile temperature during the daytime warming phase.

[0019] Based on the surface radiative cooling characteristics, the temperature change process during the nighttime cooling phase is modeled, and the function is made continuous at the time points of change during the daytime warming phase and the nighttime cooling phase, resulting in a daily cycle model of soil profile temperature during the nighttime cooling phase, including:

[0020] Based on the characteristics of surface radiative cooling, an exponential function was used to construct the soil profile temperature during the daytime warming phase. and daily average temperature Amplitude at different depths The moment of the highest temperature at depth z Day length The relationship between the two phases is established, and the function is made continuous at the time points of change during the daytime warming phase and the nighttime cooling phase, thus obtaining a daily cycle model of soil profile temperature during the nighttime cooling phase.

[0021] Among them, the amplitude at different depths It is the amplitude of surface temperature. Determined; the moment of the highest temperature at depth z. Based on the peak time of the surface temperature and day length It's confirmed.

[0022] In some embodiments, in the soil profile temperature inversion method that takes into account the daily temperature cycle characteristics, the daily average temperature of the target area is... Surface temperature amplitude and peak time of surface temperature Day length The thermal damping depth Zd of each pixel is substituted into the daily temperature cycle model of the target soil profile. Based on the preset time resolution and depth resolution, the soil profile temperature of the target area is calculated, including:

[0023] Based on the surface temperature amplitude Calculate the temperature amplitude at depth z, given the thermal damping depth Zd. ;

[0024] Based on the peak time of surface temperature The length of daylight The thermal damping depth Zd is used to calculate the time of the highest temperature at depth z. ;

[0025] The average daily temperature Temperature amplitude at depth z Day length The moment of the highest temperature at depth z Substituting depth z and time t into the daily temperature cycle model of the target soil profile, the soil profile temperature values ​​corresponding to depth z and time t in the target area are obtained.

[0026] In some embodiments, the soil profile temperature inversion method that takes into account the diurnal temperature cycle characteristics includes, in part, calculating the soil profile temperature of the target area based on a preset time resolution and depth resolution, comprising:

[0027] The soil profile temperature point values ​​corresponding to different dates, different depths z, and different times t in the target area are obtained by continuous daily calculation based on the preset time resolution and depth resolution.

[0028] Based on the annual soil profile temperature point values, annual soil profile temperature data that meets the preset depth resolution in space, the preset time resolution in time, and has a vertical stratification structure are obtained.

[0029] In some embodiments, the soil profile temperature inversion method that takes into account the diurnal temperature cycle characteristics is wherein the diurnal temperature cycle model for the daytime warming phase is:

[0030] ; ;……(1);

[0031] The diurnal temperature cycle model for the soil profile during the nighttime cooling phase is as follows:

[0032] ; ;……(2);

[0033] The temperature amplitude at depth z for:

[0034] ;……(3);

[0035] The highest temperature moment at depth z for:

[0036] ;……(4);

[0037] in, The soil profile temperature values ​​corresponding to depth z and time t; Characterized by daily average temperature; Characterizing the amplitude of surface temperature; Characterizing the amplitude at different depths; Characterizes the peak time of surface temperature; The moment when the highest temperature is reached at depth z; The term "daytime length" is used to characterize the length of daylight; "r" represents the first attenuation coefficient, defined as r = 1 / Zd, where Zd represents the thermal damping depth Zd; and "K" represents the second attenuation coefficient, defined as K = ; This marks the start of the daytime warming phase. This marks the end of the daytime warming phase.

[0038] In some embodiments, in the soil profile temperature inversion method that takes into account the diurnal temperature cycle characteristics, the step of calculating the thermal damping depth Zd of each pixel in the target area based on the soil parameter data includes:

[0039] Calculate soil porosity and soil saturation;

[0040] Based on the soil porosity and soil saturation, a soil thermal conductivity model is constructed to calculate the total thermal conductivity of the soil.

[0041] Calculate the heat capacity per unit volume of soil based on the heat capacity of dry soil and water.

[0042] Calculate the soil thermal diffusivity based on the total thermal conductivity and heat capacity per unit volume of the soil.

[0043] Based on the soil thermal diffusivity and diurnal cycle, the thermal damping depth Zd of the target area is calculated.

[0044] In some embodiments, the soil profile temperature inversion method that takes into account the diurnal temperature cycle characteristics includes, in the step of constructing a soil thermal conductivity model based on the soil porosity and soil saturation, and calculating the total thermal conductivity of the soil, the following steps are taken:

[0045] Based on the soil porosity and soil particle density, the dry soil density and the dry soil thermal conductivity are calculated.

[0046] The solid thermal conductivity is calculated by weighting the quartz and non-quartz components, and the saturated thermal conductivity is calculated by combining the solid thermal conductivity, the soil porosity, and the thermal conductivity of water.

[0047] Calculate the wetting regulator based on soil saturation;

[0048] The total thermal conductivity of the soil is calculated by combining the dry thermal conductivity, saturated thermal conductivity and wetting adjustment factor.

[0049] In some embodiments, the soil profile temperature inversion method that takes into account the diurnal temperature cycle characteristics includes, in the step of inverting the key surface temperature parameters describing the intra-diurnal temperature variation process of the target area based on the time-series surface temperature data, the following:

[0050] The time-series land surface temperature data to be fitted is obtained; the time-series land surface temperature data to be fitted is obtained by satellite inversion; the time-series land surface temperature data includes land surface temperature observation data of multiple time points in the target area within a day; the time-series land surface temperature data to be fitted includes land surface temperature observation data obtained by various satellite inversions.

[0051] Substitute the time series points into the daily temperature cycle model of the target soil profile to obtain the model simulation value corresponding to the time series point;

[0052] An objective function is constructed using the sum of squared differences between the observed surface temperature data at time points and the simulated values ​​from the model. The objective function is then globally optimized using a simulated annealing algorithm to find the key surface temperature parameters that minimize the value of the objective function.

[0053] In some embodiments, a soil profile temperature inversion device that takes into account the diurnal temperature cycle characteristics is also provided, the device comprising:

[0054] A construction module is used to construct a daily temperature cycle model of the target soil profile based on a one-dimensional heat conduction equation; the daily temperature cycle model of the target soil profile characterizes the relationship between soil profile temperature and time and depth.

[0055] The acquisition module is used to acquire time-series surface temperature data, soil parameter data, geographic coordinates, and date information of the target area; the inversion module is used to invert the key surface temperature parameters describing the intraday temperature variation process of the target area based on the time-series surface temperature data, wherein the key surface temperature parameters include daily average temperature. Surface temperature amplitude and peak time of surface temperature ;

[0056] The first calculation module is used to calculate the thermal damping depth Zd of each pixel in the target area based on the soil parameter data; and to determine the daytime length of the target area based on the geographic coordinates and date information. ;

[0057] The second calculation module is used to calculate the daily average temperature of the target area. Surface temperature amplitude and peak time of surface temperature Day length The thermal damping depth Zd of each pixel is substituted into the daily cycle model of the target soil profile temperature, and the soil profile temperature of the target area is calculated based on the preset time resolution and depth resolution.

[0058] This application provides a method and apparatus for soil profile temperature inversion that takes into account the diurnal temperature cycle characteristics. Based on the heat conduction equation, an inversion model is constructed, thereby using surface temperature data products and soil parameter data to estimate the soil temperature change process at different depths. It eliminates the need for remote sensing satellite data; only surface temperature data and soil parameter data are required to deduce the soil profile temperature, accurately inverting the diurnal temperature cycle dynamics. It can characterize the temperature coupling relationship between different soil depths from the perspective of energy transfer mechanisms, improving the scientific rigor and applicability of the model. By introducing heat conduction constraints and combining remote sensing observations with surface boundary conditions, the instability of linear regression methods under vegetation cover and climatic conditions is effectively suppressed, achieving continuous and accurate inversion of soil temperature at different depths. Because it is driven by a physical model, it has better generalization ability under regional differences and multi-temporal observations, and can be widely applied to land surface process simulation, hydrological cycle analysis, agricultural monitoring, and climate change research, improving its spatiotemporal adaptability and application value. Attached Figure Description

[0059] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 A flowchart of the soil profile temperature inversion method considering the daily temperature cycle characteristics described in this application embodiment is shown;

[0061] Figure 2 A flowchart illustrating the method for constructing a daily temperature cycle model of a target soil profile based on a one-dimensional heat conduction equation, as described in an embodiment of this application, is shown.

[0062] Figure 3 A schematic diagram of the daily temperature cycle model of the target soil profile described in the embodiments of this application is shown;

[0063] Figure 4This document illustrates a flowchart of a method for obtaining key surface temperature parameters describing the intraday temperature variation process of a target area, as described in an embodiment of this application.

[0064] Figure 5 This diagram illustrates the soil profile temperature obtained by the soil profile temperature inversion method that takes into account the daily temperature cycle characteristics described in this application embodiment.

[0065] Figure 6 The following is a verification result of the temperature product obtained by the soil profile temperature inversion method that takes into account the daily temperature cycle characteristics described in the embodiments of this application;

[0066] Figure 7 A schematic diagram of the soil profile temperature inversion device that takes into account the daily temperature cycle characteristics described in this application embodiment is shown. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0068] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0069] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0070] Soil temperature is a crucial parameter in the energy exchange process between the Earth's surface and the atmosphere, directly influencing key ecological processes such as soil moisture dynamics, vegetation growth, and carbon cycling. Soil profile temperature information is essential for understanding surface thermodynamic processes, optimizing crop growth models, and improving the accuracy of meteorological and hydrological simulations. Especially against the backdrop of climate change and intensified human activities, the demand for dynamic monitoring of soil profile temperature is growing rapidly.

[0071] Remote sensing technology provides a new technical means for soil temperature monitoring, especially supporting large-scale, high-frequency surface observations. However, existing soil temperature inversion studies mostly focus on single-layer surface temperature estimation, with limited research on dynamic modeling and inversion of soil profile temperatures at different depths. Furthermore, because soil thermal diffusion characteristics are influenced by soil texture, moisture state, and thermodynamic processes, achieving high-precision soil profile temperature inversion that takes into account diurnal temperature cycles based on remote sensing observations presents significant challenges.

[0072] Common methods for soil profile temperature inversion that take into account the diurnal temperature cycle characteristics include: 1. Statistical regression method: for example, combining observational data such as surface temperature and vegetation index to estimate the temperature distribution of a certain layer of surface and soil; 2. Physical inversion method: using multi-angle microwave brightness temperature data, combined with temperature-dependent soil dielectric models and microwave radiation transfer models to invert the temperature profile.

[0073] Empirical regression models estimate soil temperature at different depths by establishing statistical relationships between remotely sensed factors such as land surface temperature (LST) and vegetation index (NDVI) and soil temperature. However, these models heavily rely on measured data for parameter fitting, resulting in limited applicability and difficulty adapting to variations in climate zones, soil types, and vegetation conditions. Furthermore, this method primarily relies on statistical fitting and fails to consider the physical mechanisms of soil heat conduction and diffusion, making it difficult to accurately reflect the dynamic temperature transfer patterns within the profile.

[0074] The accuracy of soil temperature retrieved by remote sensing is relatively low, and it is difficult to generate full-time soil profile temperature data.

[0075] Based on this, this application provides a soil profile temperature inversion method that takes into account the diurnal temperature cycle characteristics. The method constructs a diurnal temperature cycle model of the target soil profile based on a one-dimensional heat conduction equation. This model characterizes the relationship between soil profile temperature and time and depth. It acquires time-series surface temperature data, soil parameter data, geographic coordinates, and date information for the target area. Based on the time-series surface temperature data, it inverts key surface temperature parameters describing the intraday temperature variation process of the target area, including the daily average temperature. Surface temperature amplitude and peak time of surface temperature Based on the soil parameter data, calculate the thermal damping depth Zd for each pixel in the target area; based on the geographic coordinates and date information, determine the daytime length of the target area. The daily average temperature of the target area Surface temperature amplitude and peak time of surface temperature Day length The thermal damping depth Zd of each pixel is substituted into the daily temperature cycle model of the target soil profile. Based on the preset time resolution and depth resolution, the soil profile temperature of the target area is calculated. Using surface temperature data products and soil parameter data, the soil temperature change process at different depths is estimated. Without the need for remote sensing satellite data, only surface temperature data and soil parameter data are required to deduce the soil profile temperature, and the daily temperature cycle dynamics of the soil profile are accurately inverted. The inversion model is constructed based on the heat conduction equation, which can characterize the temperature coupling relationship between different soil depths from the perspective of energy transfer mechanism, thus improving the scientificity and applicability of the model. The introduction of heat conduction constraints, combined with remote sensing observation and surface boundary conditions, effectively suppresses the instability of the linear regression method under vegetation cover and climate condition differences, and realizes continuous and accurate inversion of soil temperature at different depths. Due to the use of physical model driving, it has better generalization ability under regional differences and multi-temporal observations, and can be widely used in land surface process simulation, hydrological cycle analysis, agricultural monitoring and climate change research, thus improving its spatiotemporal adaptability and application value.

[0076] Please refer to Figure 1 , Figure 1 A flowchart of the soil profile temperature inversion method considering the diurnal temperature cycle characteristics described in this application embodiment is shown, as follows: Figure 1 As shown, the method includes the following steps S1-S5:

[0077] Step S1: Construct a daily temperature cycle model for the target soil profile based on the one-dimensional heat conduction equation; the daily temperature cycle model for the target soil profile characterizes the relationship between soil profile temperature and time and depth.

[0078] Step S2: Obtain time-series surface temperature data, soil parameter data, geographic coordinates, and date information for the target area; Step S3: Based on the time-series surface temperature data, retrieve key surface temperature parameters describing the intraday temperature variation process of the target area, including daily average temperature. Surface temperature amplitude and peak time of surface temperature Step S4: Based on the soil parameter data, calculate the thermal damping depth Zd of each pixel in the target area; based on the geographic coordinates and date information, determine the daytime length of the target area. Step S5: The daily average temperature of the target area Surface temperature amplitude and peak time of surface temperature Day length The thermal damping depth Zd of each pixel is substituted into the daily cycle model of the target soil profile temperature, and the soil profile temperature of the target area is calculated based on the preset time resolution and depth resolution.

[0079] In step S1, a daily temperature cycle model of the target soil profile is constructed based on a one-dimensional heat conduction equation; the daily temperature cycle model of the target soil profile characterizes the relationship between soil profile temperature and time and depth.

[0080] In some embodiments, please refer to Figure 2 A daily temperature cycle model for the target soil profile is constructed based on a one-dimensional heat conduction equation, including the following steps S201-S206:

[0081] S201. Construct a one-dimensional heat conduction equation to describe the heat conduction process of surface temperature transfer from the surface to the depths;

[0082] S202. Based on the given initial and boundary conditions, solve the one-dimensional heat conduction equation to obtain the solution of the one-dimensional heat conduction equation;

[0083] S203. The daily temperature cycle is defined as starting from sunrise time of the current day and ending at sunrise time of the next day, and the daily temperature change cycle is divided into a daytime warming phase and a nighttime cooling phase.

[0084] S204. Based on the diurnal variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, a diurnal cycle model of soil profile temperature during the daytime warming phase is constructed.

[0085] S205. Based on the surface radiative cooling characteristics, the temperature change process of the nighttime cooling phase is modeled, and the function is made continuous at the time points of change in the daytime warming phase and the nighttime cooling phase, so as to obtain the daily cycle model of soil profile temperature in the nighttime cooling phase.

[0086] S206. By combining the daily cycle model of soil profile temperature during the daytime warming phase and the nighttime cooling phase, the daily cycle model of the target soil profile temperature is obtained.

[0087] In some embodiments, constructing a diurnal temperature cycle model of the soil profile during the daytime warming phase, based on the diurnal variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, includes:

[0088] Based on the diurnal variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, trigonometric functions are used to construct the soil profile temperature during the daytime warming phase. and daily average temperature Amplitude at different depths The moment of the highest temperature at depth z Day length The relationship between these factors was used to determine the daily cycle model of soil profile temperature during the daytime warming phase.

[0089] Based on the surface radiative cooling characteristics, the temperature change process during the nighttime cooling phase is modeled, and the function is made continuous at the time points of change during the daytime warming phase and the nighttime cooling phase, resulting in a daily cycle model of soil profile temperature during the nighttime cooling phase, including:

[0090] Based on the characteristics of surface radiative cooling, an exponential function was used to construct the soil profile temperature during the daytime warming phase. and daily average temperature Amplitude at different depths The moment of the highest temperature at depth z Day length The relationship between the two phases is established, and the function is made continuous at the time points of change during the daytime warming phase and the nighttime cooling phase, thus obtaining a daily cycle model of soil profile temperature during the nighttime cooling phase.

[0091] Among them, the amplitude at different depths It is the amplitude of surface temperature. Determined; the moment of the highest temperature at depth z. Based on the peak time of the surface temperature and day length It's confirmed.

[0092] Solar radiation is the main driving force of soil diurnal cycle. The vertical distribution of soil temperature is mainly driven by surface heat input (such as solar radiation) and is gradually transferred from the surface to the deep layer through heat conduction mechanism. Under typical natural conditions, the surface temperature is significantly affected by the diurnal radiation flux. The change signal is conducted into the soil in the form of heat waves, forming a vertical temperature fluctuation with obvious diurnal periodicity. This heat conduction process can be regarded as an unsteady one-dimensional heat conduction process, which is usually described by a one-dimensional heat diffusion equation, namely the following formula (5): ;……(5);

[0093] The one-dimensional thermal diffusion equation describes the fundamental physical laws governing the vertical (one-dimensional) conduction of heat in the soil medium; it indicates the rate of temperature change at a point in the soil per unit time. The curvature of the temperature spatial distribution near the depth at that point Proportional, of which, The thermal diffusivity is a key physical property of soil, used to measure its ability to conduct heat. The value depends on parameters such as the soil's thermal conductivity, volumetric heat capacity, water content, and texture.

[0094] In actual soils, the thermal diffusivity typically varies with soil moisture, porosity, and particle composition, resulting in a nonlinear heat transfer process. During the day, incident radiation causes the surface temperature to rise, and heat is gradually conducted downwards. At night, the surface temperature decreases, and the soil releases heat, forming a reverse conduction. This heat transfer process exhibits hysteresis and attenuation; the temperature wave gradually delays and its amplitude decreases as it propagates deeper.

[0095] Based on the heat conduction equation, given initial and boundary conditions, the one-dimensional heat conduction equation is solved to obtain the solution to the one-dimensional heat conduction equation.

[0096] For example, given initial conditions Boundary conditions The solution to the equation is ;in, The daily average temperature characterizing the soil profile; Characterizes the amplitude at depth z; it represents the temperature at that depth, circumferentially around the daily average temperature. The magnitude of the fluctuation; The amplitude representing the Earth's surface (z=0); Indicates the period of temperature change; Characterizes phase delay; The third attenuation coefficient, which characterizes the rate attenuation and delay of temperature waves as they propagate into deeper soil layers, is related to soil properties and periodicity.

[0097] The solution to the one-dimensional heat conduction equation is obtained under ideal conditions; the actual diurnal variation of soil temperature is more complex; the solution to the one-dimensional heat conduction equation reveals the physical law of soil profile temperature change, namely, that the temperature wave will undergo exponential attenuation of amplitude and phase delay when it propagates into the deeper soil layers.

[0098] However, the actual diurnal variation of surface temperature is complex. Therefore, the perfect cosine function of the solution to the one-dimensional heat conduction equation cannot be directly used as the target soil profile temperature diurnal cycle model.

[0099] The intraday temperature cycle is defined as starting from sunrise on the current day and ending at sunrise on the next day. Based on the different temperature variation patterns during the day and night, the intraday temperature variation cycle is divided into a daytime warming phase and a nighttime cooling phase. Soil profile temperature daily cycle models are constructed for the daytime warming phase and the nighttime cooling phase, respectively. The function is made continuous at the time points of change in the daytime warming phase and the nighttime cooling phase to obtain a hybrid target soil profile temperature daily cycle model.

[0100] Please refer to Figure 3 , Figure 3 A schematic diagram of the daily temperature cycle model of the target soil profile described in the embodiments of this application is shown; as follows: Figure 3 As shown, based on the diurnal variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, a diurnal cycle model of soil profile temperature during the daytime warming phase is constructed. Specifically, trigonometric functions are used to construct the diurnal cycle model of soil profile temperature during the daytime warming phase. The diurnal cycle model of soil profile temperature during the daytime warming phase is as follows:

[0101] ; ;……(1);

[0102] The diurnal temperature cycle model for the soil profile during the nighttime cooling phase is as follows:

[0103] ; ;……(2);

[0104] Based on the surface radiative cooling characteristics, an exponential function is used to model the temperature change process during the nighttime cooling phase. In order to better combine the daytime and nighttime models, the function is made continuous at the time points of change in both, thus obtaining the daily cycle model of soil profile temperature during the nighttime cooling phase.

[0105] The temperature amplitude at depth z for:

[0106] ;……(3);

[0107] The highest temperature moment at depth z for:

[0108] ;……(4);

[0109] in, The soil profile temperature values ​​corresponding to depth z and time t; Characterized by daily average temperature; Characterizing the amplitude of surface temperature; Characterizing the amplitude at different depths; Characterizes the peak time of surface temperature; The moment when the highest temperature is reached at depth z; The term "daytime length" is used to characterize the length of daylight; "r" represents the first attenuation coefficient, defined as r = 1 / Zd, where Zd represents the thermal damping depth Zd; and "K" represents the second attenuation coefficient, defined as K = ; This marks the start of the daytime warming phase. This marks the end of the daytime warming phase.

[0110] Among them, the That is, in the solution of the one-dimensional heat conduction equation ; p in the equation represents the period.

[0111] like Figure 3 As shown, both the daily soil profile temperature cycle model during the daytime warming phase and the daily soil profile temperature cycle model during the nighttime cooling phase include three key surface temperature parameters, namely the daily average temperature. Surface temperature amplitude and peak time of surface temperature This set of parameters forms a bridge connecting the observed data with the temperature at different depths of the inverted soil profile.

[0112] The average daily temperature Surface temperature amplitude and peak time of surface temperature The parameters can be obtained by fitting temperature data products and remain unchanged when inverting temperature changes at different depths.

[0113] Please refer to Figure 3 , Figure 3 The solid line in the figure represents the soil temperature at the first depth, and the dashed line represents the soil temperature at the second depth, which is greater than that at the first depth. It can be seen that the soil temperature fluctuation in the shallow layer is greater than that in the deep layer, which indicates that the surface soil is more sensitive to changes in diurnal temperature, while the temperature change in the deep soil is more stable. At the same time, it also conforms to the temperature amplitude at depth z given by the above formula (3). for This formula shows that the temperature amplitude decreases as depth z increases. Figure 3 The decrease in amplitude in the middle follows the pattern shown in the formula.

[0114] Figure 3 The temperature peaks in the medium-deep soil layers occurred significantly later than those in the shallow soil layers, indicating that heat conduction and soil heat capacity affect the rate of temperature propagation at different depths, and the timing of temperature peaks at different soil depths shows a lag.

[0115] exist Figure 3 In the process, soil temperatures at different depths exhibit similar fluctuation patterns, which correspond to the diurnal variation of sunlight and ambient temperature. This indicates that although the amplitude and phase are different, the temperature curves of shallow and deep layers show a diurnal cycle pattern similar to that driven by the surface. Therefore, the soil profile temperature diurnal cycle model constructed in this application calculates the amplitude and phase at different depths using the above formulas (3) and (4), so that the model is driven by the same set of physical state parameters regardless of whether it is deep or shallow.

[0116] In other words, although the temperature change patterns during the daytime warming phase and the nighttime cooling phase are different, and the corresponding daily temperature cycle models of the soil profile are different for these two phases, both the trigonometric function during the day and the exponential function at night are driven by the same set of physical state parameters.

[0117] This set of parameters (daily average temperature) Surface temperature amplitude and peak time of surface temperature As the spatial location and time of the target area change, that is, the average daily temperature of different target areas on different dates varies. Surface temperature amplitude and peak time of surface temperature They are different.

[0118] Based on this, in step S2, time-series surface temperature data, soil parameter data, geographic coordinates, and date information of the target area are acquired. Then, in step S3, based on the time-series surface temperature data, key surface temperature parameters describing the intraday temperature variation process of the target area are retrieved. These key surface temperature parameters include the daily average temperature. Surface temperature amplitude and peak time of surface temperature .

[0119] In this way, a daily cycle model of soil profile temperature for the target date, specific to the target region, is obtained.

[0120] In some embodiments, please refer to Figure 4 The process of retrieving key surface temperature parameters describing the intraday temperature variation process of the target area based on the time-series surface temperature data includes the following steps S401-S403:

[0121] S401. Obtain the time-series land surface temperature data to be fitted; the time-series land surface temperature data to be fitted is obtained by satellite inversion; the time-series land surface temperature data includes land surface temperature observation data of multiple time points in the target area within a day; the time-series land surface temperature data to be fitted includes land surface temperature observation data obtained by various satellite inversions.

[0122] S402. Substitute the time series point into the daily temperature cycle model of the target soil profile to obtain the model simulation value corresponding to the time series point;

[0123] S403. Construct an objective function using the sum of squared differences between the observed surface temperature data at the time series points and the simulated values ​​of the model, and perform global optimization of the objective function using the simulated annealing algorithm to solve for the key surface temperature parameters that minimize the value of the objective function.

[0124] Here, the time-series surface temperature data to be fitted for the target area is determined based on the geographic coordinates and date information of the target area.

[0125] In some embodiments, surface temperatures retrieved from a first series of satellites are used as fitting data, supplemented by data from a second series of satellites. The first set of surface temperature data originates from surface temperatures retrieved by three satellites (B, C, and D) in the first series, with transit times approximately 1:40, 2:00, 10:15, 13:40, 14:00, and 22:15 local time. The transit times of the second series of satellite data are approximately 1:30, 10:30, 13:30, and 22:30 local time. These two sets of data are substituted into the daily temperature cycle model of the target soil profile. The sum of squares of the differences between observed values ​​and model-simulated values ​​is established as the error function of the objective function. Then, a simulated annealing algorithm is introduced for global optimization, retrieving key parameters describing the intraday temperature variation process daily, and fitting the daily average temperature. Surface temperature amplitude and peak time of surface temperature .

[0126] In some embodiments, the surface depth of the surface temperature observation data obtained from different types of satellites is different; for example, the surface temperature observation data obtained from two types of satellites correspond to the surface layer (depth of 0) and the depth of 5cm, respectively. By introducing a shallow layer (such as 5cm) of observation data, it is equivalent to setting a calibration point on the heat wave propagation path, thereby improving the inversion accuracy and physical reliability of the model.

[0127] In step S4, based on the soil parameter data, the thermal damping depth Zd of each pixel in the target area is calculated; based on the geographic coordinates and date information, the daytime length of the target area is determined. .

[0128] Day length in the target area The length of a day is derived from sunrise and sunset times. Based on the specified date and geographical coordinates (latitude and longitude), the sunrise and sunset times (in hours) of that location are calculated.

[0129] Specifically, based on the geographic coordinates and date information, the day length of the target area is determined. Specifically, sunrise and sunset times are obtained based on latitude and date information, and the corresponding length of daylight is obtained by subtracting the two. (That is, the duration of daylight, or the length of daylight).

[0130] After completing the key surface parameter (the daily average temperature) Surface temperature amplitude and peak time of surface temperature Based on the inversion, the thermal damping depth Zd of each pixel is calculated by further combining soil type data (moisture content, gravel content, clay ratio, etc.).

[0131] The thermal damping depth Zd is calculated based on soil properties such as sand content (sf), clay content (cf), and volumetric water content (vmc). First, the soil porosity and saturation are estimated, and a physical model of soil thermal conductivity is constructed accordingly. Then, the heat capacity per unit volume is calculated by combining the heat capacity of dry soil and water, and the soil thermal diffusivity is derived. Finally, the thermal damping depth is calculated.

[0132] In some embodiments, calculating the thermal damping depth Zd of each pixel in the target area based on the soil parameter data includes:

[0133] Calculate soil porosity and soil saturation;

[0134] Based on the soil porosity and soil saturation, a soil thermal conductivity model is constructed to calculate the total thermal conductivity of the soil.

[0135] Calculate the heat capacity per unit volume of soil based on the heat capacity of dry soil and water.

[0136] Calculate the soil thermal diffusivity based on the total thermal conductivity and heat capacity per unit volume of the soil.

[0137] Based on the soil thermal diffusivity and diurnal cycle, the thermal damping depth Zd of the target area is calculated.

[0138] In some embodiments, the step of constructing a soil thermal conductivity model based on the soil porosity and soil saturation, and calculating the total thermal conductivity of the soil, includes:

[0139] Based on the soil porosity and soil particle density, the dry soil density and the dry soil thermal conductivity are calculated.

[0140] The solid thermal conductivity is calculated by weighting the quartz and non-quartz components, and the saturated thermal conductivity is calculated by combining the solid thermal conductivity, the soil porosity, and the thermal conductivity of water.

[0141] Calculate the wetting regulator based on soil saturation;

[0142] The total thermal conductivity of the soil is calculated by combining the dry thermal conductivity, saturated thermal conductivity and wetting adjustment factor.

[0143] In some embodiments, the specific process for calculating soil porosity is as follows:

[0144] According to sand content ( ) and clay content ( Soil porosity is estimated using empirical formula (6). :

[0145] ;……(6);

[0146] in, For soil porosity, Sand content, This refers to the clay content.

[0147] The specific process for calculating soil saturation is as follows:

[0148] Soil saturation Sr is calculated using volumetric water content (vmc) and porosity based on the following formula (7):

[0149] ;……(7);

[0150] in, Characterizing soil saturation Characterizing volumetric water content, Soil porosity.

[0151] The soil thermal conductivity model is shown in the following formulas (8), (9), (10), (11), and (12):

[0152] Combined with the thermal conductivity of dry soil saturated thermal conductivity With regulatory factors The total thermal conductivity was obtained. :

[0153] ;……(8);

[0154] in, Total thermal conductivity Thermal conductivity of dry soil As a regulating factor, Saturated thermal conductivity;

[0155] Calculate the thermal conductivity of dry soil Specifically, firstly, based on soil porosity and soil particle density (ρ) s =2700kg / m³), the soil dry density is estimated based on the following formula (9). :

[0156] ;……(9);

[0157] in, Soil dry density, For soil porosity, Soil particle density;

[0158] The thermal conductivity of dry soil is then calculated based on the following formula (10):

[0159] ;……(10);

[0160] in, Thermal conductivity of dry soil This refers to the dry density of the soil.

[0161] The saturated thermal conductivity Specifically, based on the thermal conductivity of solids The thermal conductivity of the solid is calculated by weighting the quartz and non-quartz components. Calculated based on the following formula (11):

[0162] ;……(11);

[0163] Among them, the For solid thermal conductivity, The thermal conductivity of quartz The thermal conductivity is that of non-quartz. This refers to the quartz component content;

[0164] Combined with soil porosity Thermal conductivity with water =0.57W / m / K, calculate the saturated thermal conductivity. :

[0165] ;……(12);

[0166] in, For saturated thermal conductivity, For solid thermal conductivity, For soil porosity, The thermal conductivity of water.

[0167] Moisture regulating factor The calculation process is as follows:

[0168] Based on the following formula (13), according to soil saturation Calculate the wetting regulation factor ;

[0169] when ≤0.1: ,when >0.1: ;……(13);

[0170] Among them, the Characterizing soil saturation Characterizing wetting regulators;

[0171] The process of calculating the heat capacity per unit volume is as follows:

[0172] The heat capacity Cv of soil per unit volume is calculated based on the following formula (14):

[0173] ;……(14);

[0174] in, The dry density of the soil, Heat capacity per unit volume Specific heat capacity of soil solids; Water content by volume; This is the specific heat capacity of water;

[0175] The process of calculating thermal diffusivity is as follows:

[0176] The thermal diffusivity is obtained by dividing the thermal conductivity by the volumetric heat capacity based on the following formula (15). :

[0177] ;……(15);

[0178] in, For soil thermal diffusivity, Total thermal conductivity This refers to the heat capacity per unit volume.

[0179] Finally, the thermal damping depth Zd is calculated:

[0180] Based on the following formula (16), under the condition of a daily period Tp = 86400 seconds, the expression for the thermal damping depth Zd is:

[0181] ;……(16);

[0182] Among them, the For thermal damping depth, For soil thermal diffusivity, It has a daily cycle.

[0183] The thermal damping depth Zd determines the attenuation and delay of temperature waves as they propagate into deeper soil layers. Here, by combining soil property parameters to calculate the thermal damping depth Zd, the heat conduction model can accurately match target areas with different soil types (such as sandy soil and clay) and wet / dry conditions (such as arid and humid). This allows for a more accurate description of the heat conduction effect in soils with different properties, improving the accuracy of soil profile temperature inversion that takes into account the daily temperature cycle characteristics.

[0184] In some embodiments, the daily average temperature of the target area Surface temperature amplitude and peak time of surface temperature Day length The thermal damping depth Zd of each pixel is substituted into the daily cycle model of the target soil profile temperature, and the soil profile temperature of the target area is calculated based on the preset time resolution and depth resolution.

[0185] The daily average temperature of the target area Surface temperature amplitude and peak time of surface temperature Day length The thermal damping depth Zd of each pixel is substituted into the daily temperature cycle model of the target soil profile. Based on the preset time resolution and depth resolution, the soil profile temperature of the target area is calculated, including:

[0186] Based on the surface temperature amplitude Calculate the temperature amplitude at depth z, given the thermal damping depth Zd. ;

[0187] Based on the peak time of surface temperature The length of daylight The thermal damping depth Zd is used to calculate the time of the highest temperature at depth z. ;

[0188] The average daily temperature Temperature amplitude at depth z Day length The moment of the highest temperature at depth z Substituting depth z and time t into the daily temperature cycle model of the target soil profile, the soil profile temperature values ​​corresponding to depth z and time t in the target area are obtained.

[0189] In some embodiments, calculating the soil profile temperature of the target area based on preset time resolution and depth resolution includes:

[0190] The soil profile temperature point values ​​corresponding to different dates, different depths z, and different times t in the target area are obtained by continuous daily calculation based on the preset time resolution and depth resolution.

[0191] Based on the annual soil profile temperature point values, annual soil profile temperature data that meets the preset depth resolution in space, the preset time resolution in time, and has a vertical stratification structure are obtained.

[0192] The time resolution refers to the time interval of the output soil profile temperature. For example, it can be set to hourly to generate soil temperature data for 24 hours a day; it can also be set to a higher resolution, such as half an hour or fifteen minutes, to capture more rapid temperature change details. The "preset time resolution" can be flexibly set according to application requirements.

[0193] In this embodiment of the application, the key parameters of land surface temperature obtained by inversion (daily average temperature) Surface temperature amplitude and peak time of surface temperature ), and the calculated thermal damping depth Zd and day length The data were then incorporated into a daily soil temperature cycle model, with z-values ​​set to (5cm, 10cm, 20cm, 30cm, 40cm), and hourly simulations were performed. By continuously calculating daily and stitching together the annual data, spatially continuous, high-resolution (hourly) annual soil temperature data with vertical stratification was obtained, enabling the inversion of soil temperature at different depths.

[0194] The depth resolution refers to the hierarchical spacing of the output soil profile temperature in the vertical direction (depth dimension); for example, depth z is set to 5cm, 10cm, 20cm, 30cm, 40cm. In practical applications, it can be set to a denser layer, such as one layer every 5 centimeters, up to a depth of 1 meter; or a specific depth can be set according to specific applications (such as agricultural seeding layer, frozen soil active layer).

[0195] In other words, the soil profile temperature data that this application ultimately outputs is a dataset containing four-dimensional information in terms of time, space (vertical direction), and provides a comprehensive description of the soil thermal condition.

[0196] Please refer to Figure 5 , Figure 5This paper shows a schematic diagram of soil profile temperature obtained by the soil profile temperature inversion method that takes into account the daily temperature cycle characteristics described in the embodiments of this application, reflecting the change of soil temperature profile with soil depth at different time points.

[0197] The depth-time evolution of soil temperature can reveal key processes of underground heat transfer. In this embodiment, based on a model that has been validated using field observations, hourly soil temperature sequences at depths of 5–30 cm were generated, and typical soil temperature profile characteristics of four representative months—January (Jan), April (Apr), July (Jul), and October (Oct)—were analyzed. Figure 5 The monthly mean daily cycle depth-time soil temperature profiles for four typical land cover types (Savannas, Grasslands, Woody Savannas, and Barren) are presented for the four months mentioned above. Figure 5 Temperatures representing different seasons and land cover types show that, from a seasonal perspective, January exhibits a typical shallow winter cold structure, with diurnal variation signals mainly limited to the upper 5–10 cm; in April, daytime warming intensifies, and the effective depth of heat downward propagation can reach 15–20 cm; July is a high-energy season, with the surface receiving the strongest heat and the deepest heat diffusion (up to 20–30 cm), exhibiting a significant phase lag with increasing depth; October is a transitional season, with weakened daytime warming and a correspondingly shallower heat transfer depth.

[0198] Throughout the four months, the soil temperature profile exhibited typical thermal diffusion characteristics: the near-surface temperature amplitude was large, decayed rapidly with depth, and was accompanied by a significant phase delay; while the propagation depth showed significant seasonal differences (shallowest in winter and deepest in summer).

[0199] Please refer to Figure 6 , Figure 6 The following is a verification result of the temperature product obtained by the soil profile temperature inversion method considering the daily temperature cycle characteristics described in this application embodiment; as shown... Figure 6As shown, the temperature product (soil profile temperature obtained by the soil profile temperature inversion method considering the daily temperature cycle characteristics described in this application embodiment) and the measured data (measured temperature at corresponding location, time and soil depth) are matched in time and space; where In-situ ST (K) is the measured station temperature data (unit: Kelvin), Number of points is the number of points used to represent the density; Retrieved ST (K) is the inverted soil profile temperature (unit: Kelvin); the soil temperatures at different depths (5cm, 10cm, 20cm, 30cm) are verified, and the temperature inversion results are generally good, the number of data N is sufficiently rich, the root mean square error (RMSE) of temperature for each layer is less than 4.6k, and the correlation coefficient R is greater than 0.87.

[0200] This application provides a soil profile temperature inversion method that takes into account the daily temperature cycle characteristics. Based on the heat conduction theory, a daily temperature cycle model of the soil profile is constructed. Based on the daily temperature variation characteristics of the soil and soil properties, the soil temperature at different depths can be inverted. It does not require remote sensing satellite data, but only surface temperature data and soil parameter data are needed to deduce the soil profile temperature.

[0201] Existing methods often rely on empirical models or linear regression relationships, neglecting the physical processes of vertical soil temperature changes. However, the soil profile temperature inversion method provided in this application, which considers the daily temperature cycle characteristics, constructs an inversion model based on the heat conduction equation. This model can characterize the temperature coupling relationship between different soil depths from the perspective of energy transfer mechanisms, improving the scientific rigor and applicability of the model. By introducing heat conduction constraints and combining remote sensing observations with surface boundary conditions, the instability of linear regression methods under vegetation cover and climatic conditions is effectively suppressed, achieving continuous and accurate inversion of soil temperatures at different depths. Because it is driven by a physical model, the method has better generalization ability under regional differences and multi-temporal observations, and can be widely applied to land surface process simulation, hydrological cycle analysis, agricultural monitoring, and climate change research, exhibiting stronger spatiotemporal adaptability and application value.

[0202] Based on the same inventive concept, this application also provides a soil profile temperature inversion device that takes into account the daily temperature cycle characteristics, corresponding to the soil profile temperature inversion method that takes into account the daily temperature cycle characteristics. Since the principle of the device in this application is similar to the soil profile temperature inversion method that takes into account the daily temperature cycle characteristics described above in this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0203] Please refer to Figure 7 , Figure 7A schematic diagram of the soil profile temperature inversion device considering the daily temperature cycle characteristics described in this application is shown, as follows: Figure 7 As shown, the soil profile temperature inversion device that takes into account the daily temperature cycle characteristics includes:

[0204] Module 701 is used to construct a daily temperature cycle model of the target soil profile based on a one-dimensional heat conduction equation; the daily temperature cycle model of the target soil profile characterizes the relationship between soil profile temperature and time and depth.

[0205] The acquisition module 702 is used to acquire time-series surface temperature data, soil parameter data, geographic coordinates, and date information of the target area.

[0206] Inversion module 703 is used to invert key surface temperature parameters describing the intraday temperature variation process of the target area based on the time-series surface temperature data. The key surface temperature parameters include daily average temperature. Surface temperature amplitude and peak time of surface temperature ;

[0207] The first calculation module 704 is used to calculate the thermal damping depth Zd of each pixel in the target area based on the soil parameter data; and to determine the daytime length of the target area based on the geographic coordinates and date information. ;

[0208] The second calculation module 705 is used to calculate the daily average temperature of the target area. Surface temperature amplitude and peak time of surface temperature Day length The thermal damping depth Zd of each pixel is substituted into the daily cycle model of the target soil profile temperature, and the soil profile temperature of the target area is calculated based on the preset time resolution and depth resolution.

[0209] In some embodiments, in the soil profile temperature inversion device that takes into account the diurnal temperature cycle characteristics, the construction module, when constructing a target soil profile temperature diurnal cycle model based on a one-dimensional heat conduction equation, is specifically used for:

[0210] Construct a one-dimensional heat conduction equation to describe the heat conduction process of surface temperature transfer from the surface to the depths;

[0211] Based on the given initial and boundary conditions, the one-dimensional heat conduction equation is solved to obtain the solution to the one-dimensional heat conduction equation;

[0212] The daily temperature cycle is defined as starting from sunrise on the current day and ending at sunrise on the next day. The daily temperature change cycle is divided into a daytime warming phase and a nighttime cooling phase. Based on the daily variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, a daily temperature cycle model of soil profile during the daytime warming phase is constructed.

[0213] Based on the surface radiative cooling characteristics, the temperature change process during the nighttime cooling phase is modeled, and the function is made continuous at the time points of change during the daytime warming phase and the nighttime cooling phase, thus obtaining a daily cycle model of soil profile temperature during the nighttime cooling phase.

[0214] By combining the daily temperature cycle models of the soil profile during the daytime warming phase and the nighttime cooling phase, the daily temperature cycle model of the target soil profile is obtained.

[0215] In some embodiments, in the soil profile temperature inversion device that takes into account the diurnal temperature cycle characteristics, the construction module, when constructing the diurnal temperature cycle model of the soil profile during the diurnal temperature cycle during the daytime warming phase based on the diurnal variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, is specifically used for:

[0216] Based on the diurnal variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, trigonometric functions are used to construct the soil profile temperature during the daytime warming phase. and daily average temperature Amplitude at different depths The moment of the highest temperature at depth z Day length The relationship between these factors was used to determine the daily cycle model of soil profile temperature during the daytime warming phase.

[0217] The construction module, when modeling the temperature change process of the nighttime cooling phase based on surface radiative cooling characteristics, and ensuring the function is continuous at the time points of change between the daytime warming phase and the nighttime cooling phase, to obtain a daily cycle model of soil profile temperature during the nighttime cooling phase, is specifically used for:

[0218] Based on the characteristics of surface radiative cooling, an exponential function was used to construct the soil profile temperature during the daytime warming phase. and daily average temperature Amplitude at different depths The moment of the highest temperature at depth z Day length The relationship between the two phases is established, and the function is made continuous at the time points of change during the daytime warming phase and the nighttime cooling phase, thus obtaining a daily cycle model of soil profile temperature during the nighttime cooling phase.

[0219] Among them, the amplitude at different depths It is the amplitude of surface temperature. Determined; the moment of the highest temperature at depth z. Based on the peak time of the surface temperature and day length It's confirmed.

[0220] In some embodiments, in the soil profile temperature inversion device that takes into account the daily temperature cycle characteristics, the second calculation module calculates the daily average temperature of the target area. Surface temperature amplitude and peak time of surface temperature Day length The thermal damping depth Zd of each pixel is substituted into the daily temperature cycle model of the target soil profile. Based on the preset time resolution and depth resolution, when calculating the soil profile temperature of the target area, it is specifically used for:

[0221] Based on the surface temperature amplitude Calculate the temperature amplitude at depth z, given the thermal damping depth Zd. ;

[0222] Based on the peak time of surface temperature The length of daylight The thermal damping depth Zd is used to calculate the time of the highest temperature at depth z. ;

[0223] The average daily temperature Temperature amplitude at depth z Day length The moment of the highest temperature at depth z Substituting depth z and time t into the daily temperature cycle model of the target soil profile, the soil profile temperature values ​​corresponding to depth z and time t in the target area are obtained.

[0224] In some embodiments, in the soil profile temperature inversion device that takes into account the diurnal temperature cycle characteristics, the second calculation module, when calculating the soil profile temperature of the target area based on a preset time resolution and depth resolution, is specifically used for:

[0225] The soil profile temperature point values ​​corresponding to different dates, different depths z, and different times t in the target area are obtained by continuous daily calculation based on the preset time resolution and depth resolution.

[0226] Based on the annual soil profile temperature point values, annual soil profile temperature data that meets the preset depth resolution in space, the preset time resolution in time, and has a vertical stratification structure are obtained.

[0227] In some embodiments, in the soil profile temperature inversion device that takes into account the diurnal temperature cycle characteristics, the diurnal temperature cycle model of the soil profile during the daytime warming phase is as follows:

[0228] ; ;……(1);

[0229] The diurnal temperature cycle model for the soil profile during the nighttime cooling phase is as follows:

[0230] ; ;……(2);

[0231] The temperature amplitude at depth z for:

[0232] ;……(3);

[0233] The highest temperature moment at depth z for:

[0234] ;……(4);

[0235] in, The soil profile temperature values ​​corresponding to depth z and time t; Characterized by daily average temperature; Characterizing the amplitude of surface temperature; Characterizing the amplitude at different depths; Characterizes the peak time of surface temperature; The moment when the highest temperature is reached at depth z; The term "daytime length" is used to characterize the length of daylight; "r" represents the first attenuation coefficient, defined as r = 1 / Zd, where Zd represents the thermal damping depth; and "K" represents the second attenuation coefficient, defined as K = ; This marks the start of the daytime warming phase. This marks the end of the daytime warming phase.

[0236] In some embodiments, in the soil profile temperature inversion device that takes into account the diurnal temperature cycle characteristics, the first calculation module, when calculating the thermal damping depth Zd of each pixel in the target area based on the soil parameter data, is specifically used for:

[0237] Calculate soil porosity and soil saturation;

[0238] Based on the soil porosity and soil saturation, a soil thermal conductivity model is constructed to calculate the total thermal conductivity of the soil.

[0239] Calculate the heat capacity per unit volume of soil based on the heat capacity of dry soil and water.

[0240] Calculate the soil thermal diffusivity based on the total thermal conductivity and heat capacity per unit volume of the soil.

[0241] Based on the soil thermal diffusivity and diurnal cycle, the thermal damping depth Zd of the target area is calculated.

[0242] In some embodiments, in the soil profile temperature inversion device that takes into account the diurnal temperature cycle characteristics, the first calculation module, when calculating the total thermal conductivity of the soil based on the soil porosity and soil saturation, is specifically used for:

[0243] Based on the soil porosity and soil particle density, the dry soil density and the dry soil thermal conductivity are calculated.

[0244] The solid thermal conductivity is calculated by weighting the quartz and non-quartz components, and the saturated thermal conductivity is calculated by combining the solid thermal conductivity, the soil porosity, and the thermal conductivity of water.

[0245] Calculate the wetting regulator based on soil saturation;

[0246] The total thermal conductivity of the soil is calculated by combining the dry thermal conductivity, saturated thermal conductivity and wetting adjustment factor.

[0247] In some embodiments, in the soil profile temperature inversion device that takes into account the diurnal temperature cycle characteristics, the inversion module, when inverting key surface temperature parameters describing the intra-diurnal temperature variation process of the target area based on the time-series surface temperature data, is specifically used for:

[0248] The time-series land surface temperature data to be fitted is obtained; the time-series land surface temperature data to be fitted is obtained by satellite inversion; the time-series land surface temperature data includes land surface temperature observation data of multiple time points in the target area within a day; the time-series land surface temperature data to be fitted includes land surface temperature observation data obtained by various satellite inversions.

[0249] Substitute the time series points into the daily temperature cycle model of the target soil profile to obtain the model simulation value corresponding to the time series point;

[0250] An objective function is constructed using the sum of squared differences between the observed surface temperature data at time points and the simulated values ​​from the model. The objective function is then globally optimized using a simulated annealing algorithm to find the key surface temperature parameters that minimize the value of the objective function.

[0251] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces; the indirect coupling or communication connection of devices or modules can be electrical, mechanical, or other forms.

[0252] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0253] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0254] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a platform server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0255] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method of soil profile temperature inversion taking into account temperature diurnal cycle characteristics, characterized in that, The method comprises: Step S1, constructing a target soil profile temperature diurnal cycle model based on a one-dimensional heat conduction equation; the target soil profile temperature diurnal cycle model represents the relationship between soil profile temperature and time and depth; Step S2, obtaining time-series ground surface temperature data, soil parameter data, geographic coordinates and date information of a target region; Step S3, based on the time-series land surface temperature data, inverse derivation of land surface temperature key parameters describing the temperature diurnal variation process of the target region, the land surface temperature key parameters including daily average temperature , land surface temperature amplitude , and land surface temperature peak time ; Step S4, based on the soil parameter data, calculate the thermal damping depth Zd of each pixel of the target area; based on the geographic coordinates and date information, determine the length of the day of the target area ; Step S5, inputting the daily average temperature of the target region into the target soil profile temperature daily cycle model, calculating the soil profile temperature of the target region based on preset time resolution and depth resolution; , diurnal amplitude of land surface temperature , diurnal peak time of land surface temperature , length of day , thermal damping depth Zd of each pixel, into the target soil profile temperature daily cycle model, calculating the soil profile temperature of the target region based on preset time resolution and depth resolution; The target soil profile temperature diurnal cycle model is constructed based on a one-dimensional heat conduction equation, which comprises: constructing a one-dimensional heat conduction equation describing the heat conduction process of ground surface temperature from the surface layer to the deep layer; solving the one-dimensional heat conduction equation based on given initial conditions and boundary conditions to obtain the solution of the one-dimensional heat conduction equation; determining the diurnal cycle period of temperature as starting from the sunrise time of the day to the end of the sunrise time of the next day, and dividing the diurnal variation period of temperature into a daytime warming stage and a nighttime cooling stage; constructing a soil profile temperature diurnal cycle model of the daytime warming stage based on the diurnal variation characteristics of ground surface temperature in the daytime warming stage and the solution of the one-dimensional heat conduction equation; modeling the temperature variation process in the nighttime cooling stage based on the ground surface radiation cooling characteristics, and making the function continuous at the time points of change in the daytime warming stage and the nighttime cooling stage to obtain the soil profile temperature diurnal cycle model of the nighttime cooling stage; and integrating the soil profile temperature diurnal cycle models of the daytime warming stage and the nighttime cooling stage to obtain the target soil profile temperature diurnal cycle model.

2. The soil profile temperature inversion method considering temperature diurnal cycle characteristics according to claim 1, characterized in that, The soil profile temperature diurnal cycle model of the daytime warming stage is constructed based on the diurnal variation characteristics of ground surface temperature in the daytime warming stage and the solution of the one-dimensional heat conduction equation, which comprises: Based on the diurnal variation characteristics of surface temperature during the daytime warming phase and the solution of the one-dimensional heat conduction equation, trigonometric functions are used to construct the soil profile temperature during the daytime warming phase. and daily average temperature Amplitude at different depths The moment of the highest temperature at depth z Day length The relationship between these factors was used to determine the daily cycle model of soil profile temperature during the daytime warming phase. The temperature variation process in the nighttime cooling stage is modeled based on the ground surface radiation cooling characteristics, and the function is made continuous at the time points of change in the daytime warming stage and the nighttime cooling stage to obtain the soil profile temperature diurnal cycle model of the nighttime cooling stage, which comprises: Based on the characteristics of surface radiation cooling, the soil profile temperature in the daytime warming stage is constructed by using an exponential function and daily average temperature , amplitude at different depths , the highest temperature moment at depth z , the length of day , and the time points of change in the daytime warming stage and the nighttime cooling stage to make the function continuous, obtaining the soil profile temperature diurnal cycle model in the nighttime cooling stage; wherein the amplitudes of the different depths are surface temperature amplitudes determined; the time of maximum temperature at the depth z is determined based on the surface temperature peak time and the length of day .

3. The soil profile temperature inversion method considering temperature diurnal cycle characteristics according to claim 2, characterized in that, said daily average temperature of the target region , diurnal amplitude of surface temperature , and diurnal peak time of surface temperature , length of day , and the thermal damping depth Zd of each pixel are substituted into the target soil profile temperature daily cycle model, and the soil profile temperature of the target region is calculated based on a preset time resolution and depth resolution, comprising: based on the ground temperature amplitude and the thermal damping depth Zd, the temperature amplitude at depth z is calculated ; Based on the time of the peak surface temperature , the length of the day the thermal damping depth Zd, the time of the peak temperature at the depth z ; the daily average temperature the temperature amplitude at depth z the length of day the time of the maximum temperature at depth z and depth z and time t into the target soil profile temperature daily cycle model to obtain the soil profile temperature value at depth z and time t for the target region.

4. The soil profile temperature inversion method considering temperature diurnal cycle characteristics according to claim 3, characterized in that, The soil profile temperature of the target region is calculated based on the preset time resolution and depth resolution, which comprises: The soil profile temperature point values corresponding to different dates, different depths z and different times t of the target region are obtained through continuous daily calculation based on the preset time resolution and depth resolution; Based on the soil profile temperature point values of the whole year, the whole-year soil profile temperature data with a vertical layered structure that meets the preset depth resolution in space and the preset time resolution in time are obtained.

5. The soil profile temperature inversion method considering diurnal temperature cycle characteristics according to claim 2, characterized in that, The soil profile temperature diurnal cycle model of the daytime warming stage is: ； (1)； The soil profile temperature diurnal cycle model of the nighttime cooling stage is: ； (2)； The temperature amplitude at the depth z is: (3)； the highest temperature moment at the depth z is: (4)； wherein characterizes the soil profile temperature value corresponding to the depth z, the time t; said characterizes the daily average temperature; characterizes the ground surface temperature amplitude; characterizes the amplitude at different depths; characterizes the ground surface temperature peak time; characterizes the moment of the highest temperature at the depth z; characterizes the length of the day; r characterizes a first attenuation coefficient defined as r = 1 / Zd, Zd characterizes a thermal damping depth; K characterizes a second attenuation coefficient defined as K = 1 / 2Zd; ; is the beginning time of the daytime warming phase; is the end time of the daytime warming phase.

6. The soil profile temperature inversion method considering temperature diurnal cycle characteristics according to claim 4, characterized in that, The thermal damping depth Zd of each pixel of the target region is calculated based on the soil parameter data, which comprises: calculating soil porosity and soil saturation; constructing a soil thermal conductivity model based on the soil porosity and soil saturation to calculate the total thermal conductivity of the soil; calculating the unit volume heat capacity of the soil based on the heat capacity of dry soil and water; calculating the soil thermal diffusivity based on the total thermal conductivity and the unit volume heat capacity of the soil; Calculate a thermal damping depth Zd of the target region based on the soil thermal diffusivity and a diurnal cycle.

7. The soil profile temperature inversion method considering temperature diurnal cycle characteristics according to claim 6, characterized in that, Construct a soil thermal conductivity model based on the soil porosity and soil saturation, and calculate a total thermal conductivity of the soil, including: Calculate a dry soil density based on the soil porosity and soil particle density, and calculate a dry soil thermal conductivity; Calculate a solid thermal conductivity by weighting a quartz component and a non-quartz component, and calculate a saturated thermal conductivity in combination with the solid thermal conductivity, the soil porosity, and a thermal conductivity of water; Calculate a wetness adjustment factor according to the soil saturation; Calculate the total thermal conductivity of the soil in combination with the dry soil thermal conductivity, the saturated thermal conductivity, and the wetness adjustment factor.

8. The soil profile temperature inversion method considering temperature diurnal cycle characteristics according to claim 1, characterized in that, Invert, based on the time-series ground temperature data, ground temperature key parameters describing a diurnal temperature variation process of the target region, including: Obtain time-series ground temperature data to be fitted; the time-series ground temperature data to be fitted is obtained by satellite inversion; the time-series ground temperature data includes ground temperature observation data of the target region at multiple time-series points in a day; the time-series ground temperature data to be fitted includes multiple kinds of ground temperature observation data obtained by satellite inversion; Substitute the time-series points into the target soil profile temperature diurnal cycle model to obtain model simulation values corresponding to the time-series points; Construct an objective function by using a square sum of differences between the ground temperature observation data of the time-series points and the model simulation values, and globally optimize the objective function by a simulated annealing algorithm to solve ground temperature key parameters that minimize the value of the objective function.

9. A device for soil profile temperature inversion taking into account the temperature diurnal cycle characteristics, characterized in that, The device includes: A construction module configured to construct a target soil profile temperature diurnal cycle model based on a one-dimensional heat conduction equation; the target soil profile temperature diurnal cycle model represents a variation relationship between soil profile temperature and time and depth; An acquisition module configured to acquire time-series ground temperature data, soil parameter data, geographic coordinates, and date information of a target region; an inversion module configured to, based on the time-series land surface temperature data, invert land surface temperature key parameters describing temperature diurnal variation processes of the target area, the land surface temperature key parameters including a daily mean temperature , a land surface temperature amplitude , and a land surface temperature peak time ; The first calculation module is configured to calculate thermal damping depth Zd of each pixel of the target region based on the soil parameter data; determine the length of day of the target region based on the geographic coordinates and date information ; a second calculation module, configured to calculate the daily average temperature of the target region by substituting the daily average temperature of each pixel into the target soil profile temperature daily cycle model based on a preset time resolution and depth resolution; a surface temperature amplitude and a surface temperature peak time a day length a thermal damping depth Zd of each pixel into the target soil profile temperature daily cycle model, and calculate the soil profile temperature of the target region based on a preset time resolution and depth resolution; The construction module, when constructing the target soil profile temperature diurnal cycle model based on the one-dimensional heat conduction equation, is specifically configured to: construct a one-dimensional heat conduction equation describing a heat conduction process of ground temperature transmission from a surface layer to a deep layer; solve the one-dimensional heat conduction equation based on given initial conditions and boundary conditions to obtain a solution of the one-dimensional heat conduction equation; determine a diurnal cycle period of temperature as starting from sunrise time of a day to ending at sunrise time of the next day, and divide the diurnal variation period of temperature into a daytime temperature increasing stage and a nighttime temperature cooling stage; construct a soil profile temperature diurnal cycle model of the daytime temperature increasing stage based on a diurnal temperature variation characteristic of the daytime temperature increasing stage and the solution of the one-dimensional heat conduction equation; model a temperature variation process of the nighttime temperature cooling stage based on a ground radiation cooling characteristic, and make a function continuous at time points varying between the daytime temperature increasing stage and the nighttime temperature cooling stage to obtain a soil profile temperature diurnal cycle model of the nighttime temperature cooling stage; and integrate the soil profile temperature diurnal cycle models of the daytime temperature increasing stage and the nighttime temperature cooling stage to obtain the target soil profile temperature diurnal cycle model.

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