Dynamic simulation method for ground surface reflection of corn farmland

Abstract

The invention discloses a corn farmland surface albedo dynamic simulation method, and relates to the field of ecological simulation, and the method comprises the steps: S1, obtaining the ecological environment information of a previous corn farmland and the corresponding previous surface albedo, the previous corn farmland ecological environment information is analyzed and processed to obtain previous soil parameters, previous corn growth parameters and previous environment influence parameters; s2, combining the soil parameters, the corn growth parameters, the environmental influence parameters and the corresponding previous surface albedo to construct a corn farmland surface albedo dynamic simulation model; and S3, obtaining current corn farmland ecological environment information, obtaining a corresponding earth surface albedo according to the corn farmland earth surface albedo dynamic simulation model, and predicting and simulating a future target time period. According to the surface reflection dynamic simulation method, prediction simulation is carried out through a large amount of previous data, the obtained data are finer, and the complex relation in the corn farmland surface reflection process can be better simulated.

Description

Technical Field

[0001] The invention relates to the field of ecological simulation, in particular to a method for simulating the dynamic reflection of corn farmland surface. Background Art

[0002] Surface albedo is a physical quantity that describes the ability of the surface to reflect solar radiation. It is of great significance for understanding the surface energy balance, climate change, and energy exchange processes in agricultural ecosystems. Under specific underlying surface conditions such as corn fields, surface albedo is affected by many factors, including solar altitude angle, soil moisture, vegetation conditions (such as leaf area index LAI), etc.

[0003] Traditional surface albedo simulation methods often fail to accurately reflect the changes in these complex factors, so it is necessary to develop more sophisticated dynamic parameterization schemes. Taking the Jinzhou corn farmland ecosystem as an example, researchers proposed a dynamic parameterization scheme for surface albedo based on many years of flux, meteorological and biological factor observation data. This scheme establishes a relationship model between surface albedo and factors such as solar altitude angle, surface soil moisture and leaf area index, and simulates changes in surface albedo by dynamically adjusting these parameters.

[0004] In order to solve these problems, a method for dynamic simulation of corn field surface albedo is urgently needed. Summary of the invention

[0005] To solve the above problems, this application proposes a method for simulating the dynamic reflection of corn field surface, which includes the following steps:

[0006] S1. Obtain past corn farmland ecological environment information and corresponding past surface albedo, and analyze and process the past corn farmland ecological environment information to obtain past soil parameters, past corn growth parameters, and past environmental impact parameters;

[0007] S2. Construct a dynamic simulation model of corn field surface albedo by combining soil parameters, corn growth parameters, environmental impact parameters and corresponding past surface albedo;

[0008] S3. Obtain the current ecological environment information of corn farms, obtain the corresponding current surface albedo according to the dynamic simulation model of corn farm surface albedo, and predict and simulate the future target time period.

[0009] Preferably, the soil parameters in S1 include: past soil texture categories, past soil pH values, past soil fertility parameters, past soil internal moisture parameters, past soil surface moisture parameters and past soil porosity values;

[0010] Past corn growth parameters include: past corn plant height, past corn stem diameter, and past corn leaf area index;

[0011] Past environmental impact parameters include: past solar altitude angle, past ambient temperature, past precipitation content and status.

[0012] Preferably, the method for constructing a dynamic simulation model of corn farmland surface albedo in S2 includes:

[0013] Acquire past soil parameters, and construct a soil block group according to a number of past soil parameters, wherein the soil block group includes a number of equal soil blocks;

[0014] Establish several time axes with time as the horizontal axis and environmental impact parameters as the vertical axis, obtain past environmental impact parameters, and form environmental impact parameter curves based on past environmental impact parameters at different times;

[0015] With the surface albedo as the vertical axis, the past surface albedo is obtained, and a past surface albedo curve is formed according to the past surface albedo at different times;

[0016] Distribute the soil blocks corresponding to the environmental impact parameters and surface albedo at the same time node on the time axis;

[0017] Get the past corn growth parameters and build the current corn plants on the soil blocks;

[0018] According to the environmental impact parameter curve and the change trend of past soil parameters, the humidity influence relationship of past precipitation content, past environmental temperature, and past soil internal moisture parameters on past soil surface humidity parameters is obtained, and a humidity relationship expression is generated according to the humidity influence relationship;

[0019] The humidity relationship expression is:

[0020]

[0021] Among them, R is the soil surface moisture parameter, a is the ambient temperature conversion coefficient, b is the soil internal moisture parameter conversion coefficient, c is the precipitation content conversion coefficient, T is the ambient temperature, r is the soil internal moisture parameter, and V is the precipitation content.

[0022] Preferably, the corn farmland surface albedo dynamic simulation model in S2 includes a non-growing season simulation sub-model and a growing season simulation sub-model, wherein the construction method of the non-growing season sub-model does not include obtaining past corn growth parameters and constructing corn plants at the current time on the soil block;

[0023] The construction of the non-growing season sub-model also includes:

[0024] According to the changing trends of the environmental impact parameter curve, the past soil parameters and the past surface albedo curve, the first albedo influence relationship of the past solar altitude angle, the past soil surface moisture parameter and the surface albedo is obtained, and the first surface albedo expression is formed according to the first albedo influence relationship;

[0025] The first surface albedo expression is:

[0026] α1=d×ln(h θ )+e×lnR;

[0027] Among them, h θ is the solar altitude angle, α1 is the first albedo, d is the first solar altitude angle conversion coefficient, and e is the first soil surface moisture conversion coefficient.

[0028] Preferably, the construction content of the growing season sub-model also includes:

[0029] According to the changing trends of environmental impact parameter curves, past soil parameters and past corn growth parameters, the leaf area influence relationship of environmental impact parameters and soil parameters on corn leaf area index is obtained to establish a leaf area index relationship mapping network;

[0030] The past solar altitude angle h is obtained based on the changing trends of the environmental impact parameter curve, past soil parameters, past corn growth parameters and past surface albedo curve. θ , the second albedo influence relationship of past soil surface moisture parameters, leaf area index and surface albedo, and forming a second surface albedo expression according to the second albedo influence relationship;

[0031] The second surface albedo expression is:

[0032]

[0033] Among them, h θ is the solar altitude angle, α2 is the second albedo, f is the second solar altitude angle conversion coefficient, g is the second soil surface moisture conversion coefficient, i is the leaf area index conversion coefficient, and S is the leaf area index.

[0034] Preferably, the current ecological environment information of corn farmland is obtained, the corresponding current surface albedo is obtained according to the dynamic simulation model of corn farmland surface albedo, and the specific contents of predicting and simulating the future target time period are as follows:

[0035] Obtain the current ecological environment information of corn farmland, analyze the current ecological environment information of corn farmland to obtain the current soil parameters, current corn growth parameters and current environmental impact parameters;

[0036] Determine whether the corn farm is in the growing season or non-growing season based on the current rainfall status;

[0037] If the corn farm is currently in the non-growing season, the appropriate soil block group is determined based on the soil parameters and the target matching time node is determined based on the current past environmental impact parameters, and the first albedo of the target matching time node is used as the current corn farm albedo;

[0038] Obtain environmental impact parameters of the future target stage, match the target change trend on the time axis according to the environmental impact parameters of the future target stage, predict the soil surface moisture parameters of the future target stage according to the target change trend to obtain the predicted surface moisture parameters, and calculate the predicted first albedo according to the predicted surface moisture parameters and the solar altitude angle of the future target stage;

[0039] The current corn farmland ecological environment information is analyzed to obtain the current corn farmland area information, and the soil blocks matching the future target stage are selected and arranged to simulate the changes in corn farmland in the future target stage.

[0040] Preferably, if the current corn farm is in the growing season, a suitable soil block group is determined according to soil parameters and a target matching time node is determined according to current past environmental impact parameters, and the second albedo of the target matching time node is used as the current corn farm albedo;

[0041] Obtain environmental impact parameters for future target stages, and match target change trends on the time axis based on the environmental impact parameters for future target stages;

[0042] According to the target change trend, the soil surface moisture parameter and the corn leaf area index in the future target stage are predicted to obtain the predicted surface moisture parameter and the predicted corn leaf area index;

[0043] The predicted second albedo is calculated based on the predicted surface moisture parameter, the predicted corn leaf area index and the sun altitude angle in the future target period;

[0044] The current corn farmland ecological environment information is analyzed to obtain the current corn farmland area information, and the soil blocks matching the future target stage are selected and arranged to simulate the changes in corn farmland in the future target stage.

[0045] A corn farmland surface albedo dynamic simulation system, comprising:

[0046] Data acquisition and analysis module: obtain past corn farmland ecological environment information and corresponding past surface albedo, analyze and process the past corn farmland ecological environment information to obtain past soil parameters, past corn growth parameters and past environmental impact parameters;

[0047] Initial model building module: Combine soil parameters, corn growth parameters, environmental impact parameters and corresponding past surface albedo to build a dynamic simulation model of corn farmland surface albedo;

[0048] Model prediction and simulation module: obtain the current ecological environment information of corn farms, obtain the corresponding current surface albedo according to the dynamic simulation model of corn farm surface albedo, and predict and simulate the future target time period.

[0049] In summary, the method for dynamic simulation of surface albedo of corn farmland of the present invention, compared with traditional technology, establishes a dynamic simulation model of surface albedo of corn farmland, collects a large number of parameters affecting surface albedo, predicts unknown surface albedo through training model, and performs real-time simulation. The dynamic simulation method of surface albedo mentioned in this application performs prediction and simulation through a large amount of past data, and obtains more refined data, which can better simulate the complex relationship in the surface albedo process of corn farmland.

[0050] The technical method of the present invention is further described in detail below through the drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A step diagram of a method for dynamically simulating the surface albedo of a corn farmland according to the present invention;

[0052] Figure 2 The present invention is a schematic diagram of a module of a corn farmland surface albedo dynamic simulation system. DETAILED DESCRIPTION

[0053] The technical method of the present invention is further described below by means of the accompanying drawings and embodiments. It should be noted that unless otherwise specifically stated, the relative arrangement of the components and steps, numerical expressions and numerical values ​​described in these embodiments do not limit the scope of the present application.

[0054] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present application, its application, or uses.

[0055] Technologies, systems, and devices known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, systems, and devices should be considered part of the specification.

[0056] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0057] Unless otherwise defined, technical or scientific terms used in the present invention shall have the common meanings understood by one having ordinary skills in the field to which the present invention belongs.

[0058] Corn fields are a typical underlying surface type, and their surface albedo is affected by many factors, including vegetation coverage, soil moisture, leaf area index, etc. Therefore, studying the dynamic changes of corn field surface albedo is of great significance for understanding the surface energy exchange process and improving the accuracy of climate model prediction.

[0059] The present invention provides a method for simulating the dynamic reflection of the surface of a corn field, comprising the following steps:

[0060] S1. Obtain past corn farmland ecological environment information and corresponding past surface albedo, and analyze and process the past corn farmland ecological environment information to obtain past soil parameters, past corn growth parameters, and past environmental impact parameters;

[0061] Preferably, the soil parameters in S1 include: past soil texture categories, past soil pH values, past soil fertility parameters, past soil internal moisture parameters, past soil surface moisture parameters and past soil porosity values;

[0062] Past corn growth parameters include: past corn plant height, past corn stem diameter, and past corn leaf area index;

[0063] Past environmental impact parameters include: past solar altitude angle, past ambient temperature, past precipitation content and status.

[0064] S2. Construct a dynamic simulation model of corn field surface albedo by combining soil parameters, corn growth parameters, environmental impact parameters and corresponding past surface albedo;

[0065] Preferably, the method for constructing a dynamic simulation model of corn farmland surface albedo in S2 includes:

[0066] Acquire past soil parameters, and construct a soil block group according to a number of past soil parameters, wherein the soil block group includes a number of equal soil blocks;

[0067] Establish several time axes with time as the horizontal axis and environmental impact parameters as the vertical axis, obtain past environmental impact parameters, and form environmental impact parameter curves based on past environmental impact parameters at different times;

[0068] With the surface albedo as the vertical axis, the past surface albedo is obtained, and a past surface albedo curve is formed according to the past surface albedo at different times;

[0069] Distribute the soil blocks corresponding to the environmental impact parameters and surface albedo at the same time node on the time axis;

[0070] Get the past corn growth parameters and build the current corn plants on the soil blocks;

[0071] According to the environmental impact parameter curve and the change trend of past soil parameters, the humidity influence relationship of past precipitation content, past environmental temperature, and past soil internal moisture parameters on past soil surface humidity parameters is obtained, and a humidity relationship expression is generated according to the humidity influence relationship;

[0072] The humidity relationship expression is:

[0073]

[0074] Among them, R is the soil surface moisture parameter, a is the ambient temperature conversion coefficient, b is the soil internal moisture parameter conversion coefficient, c is the precipitation content conversion coefficient, T is the ambient temperature, r is the soil internal moisture parameter, and V is the precipitation content.

[0075] There are significant differences in the influencing factors, relationship models, and simulation accuracy of the surface albedo in the growing and non-growing seasons of corn fields. The non-growing season is mainly affected by the solar altitude angle and surface soil moisture, while the growing season also needs to consider the effects of biological factors such as leaf area index and vegetation coverage. By establishing a dynamic parameterized model and continuously optimizing the model parameters, the simulation accuracy of the surface albedo can be improved, providing strong support for research in the fields of climate change, ecological monitoring, and agricultural planning.

[0076] Preferably, the corn farmland surface albedo dynamic simulation model in S2 includes a non-growing season simulation sub-model and a growing season simulation sub-model, wherein the construction method of the non-growing season sub-model does not include obtaining past corn growth parameters and constructing corn plants at the current time on the soil block;

[0077] The construction of the non-growing season sub-model also includes:

[0078] According to the changing trends of the environmental impact parameter curve, the past soil parameters and the past surface albedo curve, the first albedo influence relationship of the past solar altitude angle, the past soil surface moisture parameter and the surface albedo is obtained, and the first surface albedo expression is formed according to the first albedo influence relationship;

[0079] The first surface albedo expression is:

[0080] α1=d×ln(h θ )+e×lnR;

[0081] Among them, h θ is the solar altitude angle, α1 is the first albedo, d is the first solar altitude angle conversion coefficient, and e is the first soil surface moisture conversion coefficient.

[0082] Preferably, the construction content of the growing season sub-model also includes:

[0083] According to the changing trends of environmental impact parameter curve, past soil parameters and past corn growth parameters, the leaf area influence relationship of environmental impact parameters and soil parameters on corn leaf area index is obtained to establish a leaf area index relationship mapping network;

[0084] The past solar altitude angle h is obtained based on the changing trends of the environmental impact parameter curve, past soil parameters, past corn growth parameters and past surface albedo curve. θ , the second albedo influence relationship of past soil surface moisture parameters, leaf area index and surface albedo, and forming a second surface albedo expression according to the second albedo influence relationship;

[0085] The second surface albedo expression is:

[0086]

[0087] Among them, h θ is the solar altitude angle, α2 is the second albedo, f is the second solar altitude angle conversion coefficient, g is the second soil surface moisture conversion coefficient, i is the leaf area index conversion coefficient, and S is the leaf area index.

[0088] Leaf area index can be used to estimate vegetation cover.

[0089] The leaf area index is an important indicator for measuring the degree of vegetation coverage, which is defined as the ratio of the total area of ​​plant leaves per unit surface area to the surface area. This index reflects the density and growth of vegetation and is an important parameter for studying ecosystem functions and biodiversity.

[0090] Vegetation coverage refers to the proportion of vegetation coverage in a certain area to the total area of ​​the area, usually expressed as a percentage. It is an important parameter for evaluating land use and land cover changes.

[0091] There is a certain relationship between leaf area index and vegetation coverage. Different types of vegetation (such as forest, grassland, farmland, etc.) have different leaf area index and vegetation coverage relationships. In the same vegetation type, vegetation at different growth stages may also show different leaf area index and vegetation coverage values.

[0092] In practical applications, FVC can be estimated by measuring LAI, and vegetation coverage can also be used as an influencing factor in the leaf area index conversion coefficient and the second soil surface moisture conversion coefficient.

[0093] S3. Obtain the current ecological environment information of corn farms, obtain the corresponding current surface albedo according to the dynamic simulation model of corn farm surface albedo, and predict and simulate the future target time period.

[0094] Preferably, the current ecological environment information of corn farmland is obtained, the corresponding current surface albedo is obtained according to the dynamic simulation model of corn farmland surface albedo, and the specific contents of predicting and simulating the future target time period are as follows:

[0095] Obtain the current ecological environment information of corn farmland, analyze the current ecological environment information of corn farmland to obtain the current soil parameters, current corn growth parameters and current environmental impact parameters;

[0096] Determine whether the corn farm is in the growing season or non-growing season based on the current rainfall status;

[0097] If the corn farm is currently in the non-growing season, the appropriate soil block group is determined based on the soil parameters and the target matching time node is determined based on the current past environmental impact parameters, and the first albedo of the target matching time node is used as the current corn farm albedo;

[0098] Obtain environmental impact parameters of the future target stage, match the target change trend on the time axis according to the environmental impact parameters of the future target stage, predict the soil surface moisture parameters of the future target stage according to the target change trend to obtain the predicted surface moisture parameters, and calculate the predicted first albedo according to the predicted surface moisture parameters and the solar altitude angle of the future target stage;

[0099] The current corn farmland ecological environment information is analyzed to obtain the current corn farmland area information, and the soil blocks matching the future target stage are selected and arranged to simulate the changes in corn farmland in the future target stage.

[0100] Preferably, if the current corn farm is in the growing season, a suitable soil block group is determined according to soil parameters and a target matching time node is determined according to current past environmental impact parameters, and the second albedo of the target matching time node is used as the current corn farm albedo;

[0101] Obtain environmental impact parameters for future target stages, and match target change trends on the time axis based on the environmental impact parameters for future target stages;

[0102] According to the target change trend, the soil surface moisture parameter and the corn leaf area index in the future target stage are predicted to obtain the predicted surface moisture parameter and the predicted corn leaf area index;

[0103] The predicted second albedo is calculated based on the predicted surface moisture parameter, the predicted corn leaf area index and the sun altitude angle in the future target period;

[0104] The current corn farmland ecological environment information is analyzed to obtain the current corn farmland area information, and the soil blocks matching the future target stage are selected and arranged to simulate the changes in corn farmland in the future target stage.

[0105] A corn farmland surface albedo dynamic simulation system, comprising:

[0106] Data acquisition and analysis module: obtain past corn farmland ecological environment information and corresponding past surface albedo, analyze and process the past corn farmland ecological environment information to obtain past soil parameters, past corn growth parameters and past environmental impact parameters;

[0107] Initial model building module: Combine soil parameters, corn growth parameters, environmental impact parameters and corresponding past surface albedo to build a dynamic simulation model of corn farmland surface albedo;

[0108] Model prediction and simulation module: obtain the current ecological environment information of corn farms, obtain the corresponding current surface albedo according to the dynamic simulation model of corn farm surface albedo, and predict and simulate the future target time period.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical method of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical method to deviate from the spirit and scope of the technical method of the present invention.

Claims

1. A method for simulating the dynamic reflection of corn farmland surface, characterized in that: The following steps are involved: S1. Obtain past corn farmland ecological environment information and corresponding past surface albedo, and analyze and process the past corn farmland ecological environment information to obtain past soil parameters, past corn growth parameters, and past environmental impact parameters; S2. Construct a dynamic simulation model of corn field surface albedo by combining soil parameters, corn growth parameters, environmental impact parameters and corresponding past surface albedo; S3. Obtain the current ecological environment information of the corn farmland, obtain the corresponding current surface albedo according to the dynamic simulation model of the corn farmland surface albedo, and predict and simulate the future target time period.

2. A method for dynamic simulation of corn farmland surface albedo according to claim 1, characterized in that: The soil parameters in S1 include: past soil texture category, past soil pH value, past soil fertility parameter, past soil internal moisture parameter, past soil surface moisture parameter and past soil porosity value; Past corn growth parameters include: past corn plant height, past corn stem diameter, and past corn leaf area index; Past environmental impact parameters include: past solar altitude angle, past ambient temperature, past precipitation content and status.

3. A method for dynamic simulation of corn farmland surface albedo according to claim 2, characterized in that: The construction method of the dynamic simulation model of corn farmland surface albedo in S2 includes: Acquire past soil parameters, and construct a soil block group according to a number of past soil parameters, wherein the soil block group includes a number of equal soil blocks; Establish several time axes with time as the horizontal axis and environmental impact parameters as the vertical axis, obtain past environmental impact parameters, and form environmental impact parameter curves based on past environmental impact parameters at different times; With the surface albedo as the vertical axis, the past surface albedo is obtained, and a past surface albedo curve is formed according to the past surface albedo at different times; Distribute the soil blocks corresponding to the environmental impact parameters and surface albedo at the same time node on the time axis; Get the past corn growth parameters and build the current corn plants on the soil blocks; According to the environmental impact parameter curve and the change trend of past soil parameters, the humidity influence relationship of past precipitation content, past environmental temperature, and past soil internal moisture parameters on past soil surface humidity parameters is obtained, and a humidity relationship expression is generated according to the humidity influence relationship; The humidity relationship expression is: Among them, R is the soil surface moisture parameter, a is the ambient temperature conversion coefficient, b is the soil internal moisture parameter conversion coefficient, c is the precipitation content conversion coefficient, T is the ambient temperature, r is the soil internal moisture parameter, and V is the precipitation content.

4. A method for dynamic simulation of corn farmland surface albedo according to claim 3, characterized in that: The dynamic simulation model of corn farmland surface albedo in S2 includes a non-growing season simulation sub-model and a growing season simulation sub-model, wherein the construction method of the non-growing season sub-model does not include obtaining past corn growth parameters and constructing corn plants at the current time on the soil block; The construction of the non-growing season sub-model also includes: According to the changing trends of the environmental impact parameter curve, the past soil parameters and the past surface albedo curve, the first albedo influence relationship of the past solar altitude angle, the past soil surface moisture parameter and the surface albedo is obtained, and the first surface albedo expression is formed according to the first albedo influence relationship; The first surface albedo expression is: α1=d×ln(h θ )+e×lnR; Among them, h θ is the solar altitude angle, α1 is the first albedo, d is the first solar altitude angle conversion coefficient, and e is the first soil surface moisture conversion coefficient.

5. A method for dynamic simulation of corn farmland surface albedo according to claim 4, characterized in that: The construction of the growing season sub-model also includes: According to the changing trends of environmental impact parameter curve, past soil parameters and past corn growth parameters, the leaf area influence relationship of environmental impact parameters and soil parameters on corn leaf area index is obtained to establish a leaf area index relationship mapping network; The past solar altitude angle h is obtained based on the changing trends of the environmental impact parameter curve, past soil parameters, past corn growth parameters and past surface albedo curve. θ , the second albedo influence relationship of past soil surface moisture parameters, leaf area index and surface albedo, and forming a second surface albedo expression according to the second albedo influence relationship; The second surface albedo expression is: Among them, h θ is the solar altitude angle, α2 is the second albedo, f is the second solar altitude angle conversion coefficient, g is the second soil surface moisture conversion coefficient, i is the leaf area index conversion coefficient, and S is the leaf area index.

6. A method for dynamic simulation of corn farmland surface albedo according to claim 5, characterized in that: Obtain the current ecological environment information of corn farmland, obtain the corresponding current surface albedo according to the dynamic simulation model of corn farmland surface albedo, and predict and simulate the specific contents of the future target time period as follows: Obtain the current ecological environment information of corn farmland, analyze the current ecological environment information of corn farmland to obtain the current soil parameters, current corn growth parameters and current environmental impact parameters; Determine whether the corn farm is in the growing season or non-growing season based on the current rainfall status; If the corn farm is currently in the non-growing season, the appropriate soil block group is determined based on the soil parameters and the target matching time node is determined based on the current past environmental impact parameters, and the first albedo of the target matching time node is used as the current corn farm albedo; Obtain environmental impact parameters of the future target stage, match the target change trend on the time axis according to the environmental impact parameters of the future target stage, predict the soil surface moisture parameters of the future target stage according to the target change trend to obtain the predicted surface moisture parameters, and calculate the predicted first albedo according to the predicted surface moisture parameters and the solar altitude angle of the future target stage; The current corn farmland ecological environment information is analyzed to obtain the current corn farmland area information, and the soil blocks matching the future target stage are selected and arranged to simulate the changes in corn farmland in the future target stage.

7. A method for dynamic simulation of corn farmland surface albedo according to claim 6, characterized in that: If the corn farm is currently in the growing season, the appropriate soil block group is determined based on the soil parameters and the target matching time node is determined based on the current past environmental impact parameters, and the second albedo of the target matching time node is used as the current corn farm albedo; Obtain environmental impact parameters for future target stages, and match target change trends on the time axis based on the environmental impact parameters for future target stages; According to the target change trend, the soil surface moisture parameter and the corn leaf area index in the future target stage are predicted to obtain the predicted surface moisture parameter and the predicted corn leaf area index; The predicted second albedo is calculated based on the predicted surface moisture parameter, the predicted corn leaf area index and the sun altitude angle in the future target period; The current corn farmland ecological environment information is analyzed to obtain the current corn farmland area information, and the soil blocks matching the future target stage are selected and arranged to simulate the changes in corn farmland in the future target stage.

8. A corn field surface albedo dynamic simulation system, characterized in that: include: Data acquisition and analysis module: obtain past corn farmland ecological environment information and corresponding past surface albedo, analyze and process the past corn farmland ecological environment information to obtain past soil parameters, past corn growth parameters and past environmental impact parameters; Initial model building module: Combine soil parameters, corn growth parameters, environmental impact parameters and corresponding past surface albedo to build a dynamic simulation model of corn farmland surface albedo; Model prediction and simulation module: obtain the current ecological environment information of corn farms, obtain the corresponding current surface albedo according to the dynamic simulation model of corn farm surface albedo, and predict and simulate the future target time period.

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