Water and soil loss treatment method and system based on wind erosion area

Abstract

The invention relates to the technical field of water and soil loss treatment, and discloses a water and soil loss treatment method and system based on a wind erosion area, and the system comprises a multi-dimensional monitoring module and an intelligent management module. According to the system, environment data and climate data of all areas are obtained through a multi-dimensional monitoring module and are classified to form a data set, an intelligent management module analyzes the water and soil loss degree of each area, corresponding earth surface exposure difference and erosion coefficient are generated, dynamic quantitative indexes are synthesized, and the water and soil loss degree is calculated. And the intelligent management module analyzes the climate change trend of each region, generates a corresponding wind power fluctuation index and a monitoring data set, quantifies the wind power fluctuation intensity, pays attention to individual differentiation, and obtains the corresponding wind power fluctuation index and monitoring data set. And the intelligent management module evaluates the water and soil loss degree, the wind power change degree and the climate change degree, outputs corresponding treatment decisions, realizes partitioned policy application, establishes an emergency protection mechanism, and is high in resource allocation efficiency and good in dynamic treatment effect.

Description

Technical Field

[0001] The invention relates to the technical field of soil and water loss control, and in particular to a soil and water loss control method and system based on a wind erosion area. Background Art

[0002] Wind erosion mostly occurs in arid, semi-arid and some semi-humid areas, and has a profound impact on land resources and ecosystems. Wind erosion has significant regional and seasonal characteristics. In terms of regionality, it often occurs in areas with dry climate and sparse vegetation, such as Xinjiang, central and western Inner Mongolia, and the Hexi Corridor in Gansu. These places have little precipitation, loose surface materials and lack of effective vegetation cover protection. In terms of seasonality, it is mainly concentrated in winter and spring, when the vegetation is dormant or withered, the exposed surface area increases, and at the same time, cold air activities are frequent and strong winds increase, providing dynamic conditions for wind erosion. Wind erosion mainly includes blowing erosion and abrasion. Under long-term action, it will form unique wind erosion landforms such as wind erosion depressions, wind erosion grooves, and wind erosion residual hills, which will seriously damage the integrity and productivity of the land, leading to a decrease in soil fertility and an increase in land desertification, which will in turn affect local agricultural and animal husbandry production and threaten the living environment and ecological security of residents. Conventional management of soil and water loss in wind erosion areas focuses on windbreak and sand fixation and vegetation coverage improvement. Common measures include planting trees and grass, selecting drought-resistant and wind-resistant plants such as sea buckthorn, caragana, and haloxylon ammodendron, combining artificial afforestation with natural vegetation enclosure, creating windbreaks and grassland protection networks, using plant roots to stabilize the soil and enhance its resistance to erosion. The setting up of mechanical sand barriers is also indispensable. Square sand barriers are set up on the sand using reeds, wheat straw, and branches to increase surface friction, reduce wind force, intercept sand, help stabilize the sand and promote vegetation recovery. At the same time, rationally plan land use, transform the agricultural industrial structure, promote water-saving irrigation agriculture, reduce excessive reclamation and grazing and other human disturbances, and curb soil and water loss at the root.

[0003] At present, the traditional soil and water loss control methods based on wind erosion areas have not fully considered the regional characteristics and actual conditions, and it is difficult to achieve dynamic optimization configuration. In wind erosion areas with vast land and sparse population, the deployment of mechanical sand barriers is delayed, the protection effect is poor, and the sustainable utilization rate is not high. Summary of the invention

[0004] 1. Technical issues to be resolved In view of the shortcomings of the prior art, the present invention provides a method and system for soil and water loss control based on wind erosion areas, which has the advantages of focusing on individual differences and good dynamic control effects. It solves the problem that traditional methods for soil and water loss control based on wind erosion areas are difficult to achieve dynamic optimization configuration and have low sustainable utilization rate.

[0005] (II) Technical solution To achieve the above object, the present invention provides the following technical solutions: A soil and water loss control method based on a wind erosion area, comprising the following steps: Step 1: Connect the monitoring device and the big data platform through the network to obtain the environmental data and climate data of all regions, and classify and form an environmental data set and a climate data set; Step 2: Set a monitoring period with a fixed duration , and then, in combination with the environmental data set, analyze the degree of soil and water loss in each region and generate the corresponding surface exposure difference and erosion coefficient ; Step 3: According to the climate data set, analyze the climate change trend of each region and generate the corresponding wind fluctuation index and monitoring data group ; Step 4: Set fixed values for the exposure threshold , erosion threshold and fluctuation threshold , and then, in combination with the surface exposure difference , erosion coefficient , wind fluctuation index and monitoring data group , evaluate the degree of soil and water loss, the degree of wind change, and the degree of climate change, and output the corresponding control decision.

[0006] Preferably, in the above Step 1, the expression of the environmental data set is , to represent the environmental data of the first to the th regions. The environmental data includes short-wave infrared band reflectivity, near-infrared band reflectivity, terrain slope, surface soil loss thickness, vegetation coverage, soil type, occupied area, and the number of plant species, represents the time point for obtaining the regional environmental data.

[0007] Preferably, in the above Step 1, the expression of the climate data set is , to represent the climate data of the first to the th regions. The climate data includes daily wind speed, daily temperature, daily rainfall, and daily evaporation, represents the time point for obtaining the regional climate data.

[0008] Preferably, in the above Step 2, the calculation process of the surface exposure difference is as follows: According to the environmental data set, count within the monitoring period , the Environmental data of an area, and the monitoring period At the start, the short-wave infrared band reflectance of the th area is marked as , and the monitoring period At the start, the near-infrared band reflectance of the th area is marked as , and the monitoring period At the end, the short-wave infrared band reflectance of the th area is marked as , and the monitoring period At the end, the near-infrared band reflectance of the th area is marked as ;

[0009] In the formula, represents the surface bare index of the th area calculated by the normalized difference index principle at the end of the monitoring period , represents the surface bare index of the th area calculated by the normalized difference index principle at the start of the monitoring period , represents the surface bare difference of the th area within the monitoring period , .

[0010] Preferably, in the second step, the erosion coefficient is calculated as follows: According to the environmental data set, the terrain slope of the th area is marked as , the surface soil loss thickness of the th area is marked as , the vegetation coverage of the th area is marked as , and the occupied area of the th area is marked as ; Statistical environmental data of the th area within the monitoring period , and the change amount of the terrain slope of the th area within the monitoring period is marked as , the change amount of the surface soil loss thickness of the th area within the monitoring period is marked as , and the monitoring period Within, the change in vegetation coverage of the th area is marked as ; If the soil type of the th area belongs to sandy soil,

[0011] In the formula, represents the weight for the ratio of surface exposure difference to occupied area, represents the weight for the ratio of terrain slope to change amount, represents the weight for the ratio of change amount to vegetation coverage, , and are all constants, and , represents calculating the erosion coefficient , and of the th area according to the weights, ; If the soil type of the th area belongs to clay,

[0012] In the formula, represents the weight for the ratio of surface exposure difference to occupied area, represents the weight for the ratio of surface soil loss thickness to change amount, represents the weight for the ratio of change amount to vegetation coverage, , and are all constants, and , represents calculating the erosion coefficient , and of the th area according to the weights, .

[0013] Preferably, in the third step, the calculation process of the wind power fluctuation index is as follows: According to the climate dataset, count the climate data of the th area within the monitoring period , and mark the daily wind speed of the th area within the monitoring period as , to represent the first time point to the Daily wind speed at each time point;

[0014]

[0015] In the formula, represents the monitoring period Within, the average value of the daily wind speed in the th area, represents the th area at the , daily wind speed at the th time point, .

[0016] Preferably, in the third step, the monitoring data set The calculation process is as follows: According to the climate data set, count the climate data of the th area within the monitoring period , and mark the daily temperature of the th area within the monitoring period as , to represent the daily temperature from the first time point to the th time point. Mark the daily rainfall of the th area within the monitoring period as , to represent the daily rainfall from the first time point to the th time point. Mark the daily evaporation of the th area within the monitoring period as , to represent the daily evaporation from the first time point to the th time point;

[0017] In the formula, represents the daily temperature of the th area at the th time point, represents the daily evaporation of the th area at the th time point, represents calculating the ratio of temperature to evaporation at each time point in sequence, Indicates the daily rainfall of the th area at the th time point, Indicates calculating the ratio of rainfall to wind speed at each time point in sequence, represents the monitoring data set of the

[0018] Preferably, in step four, if the vegetation coverage of the th area ≥ 50%, the surface exposure difference < exposure threshold , and the erosion coefficient < erosion threshold , it indicates that the soil and water loss degree of the th area is relatively light, and the existing plant species quantity should be maintained. Without considering the vegetation coverage, the surface exposure difference of the th area ≥ exposure threshold , or when the erosion coefficient ≥ erosion threshold , it indicates that the soil and water loss degree of the th area is medium, and the plant species and quantity for windbreak and sand fixation should be increased. Without considering the vegetation coverage, the surface exposure difference ≥ exposure threshold , and the erosion coefficient ≥ erosion threshold indicates that the soil and water loss degree of the

[0019] th area is severe, and it should be given priority to treatment, and the plant species, plant quantity and mechanical sand barrier quantity for windbreak and sand fixation should be increased. Preferably, in step four, if the wind fluctuation index of the th area exceeds the fluctuation threshold , it indicates that the wind change in the th area is strong, and mechanical sand barriers should be arranged in time for protection. If in the monitoring data set of the th area, any one of the numerical values is greater than or equal to 1, it indicates that the climate change in the th area is strong, and the plant species and quantity for windbreak and sand fixation should be increased, and the mechanical sand barriers should be updated in time.

[0020] A soil and water loss treatment system for wind erosion areas, including a multi-dimensional monitoring module and an intelligent management module; The multi-dimensional monitoring module consists of an environmental data unit and a climate data unit. The environmental data unit collects an environmental data set through a network-connected monitoring device. The environmental data set includes environmental data for all regions. The climate data unit collects a climate data set through a network-connected big data platform. The climate data set includes climate data for all regions; The intelligent management module consists of a soil and water assessment unit, a climate assessment unit, and a dynamic governance unit. The soil and water assessment unit is set with a monitoring cycle of a fixed duration , and combined with the environmental data set, analyzes the degree of soil erosion in each region and generates a corresponding surface exposure difference and erosion coefficient . The climate assessment unit analyzes the climate change trend in each region based on the climate data set and generates a corresponding wind force fluctuation index and monitoring data set . The dynamic governance unit is set with fixed numerical exposure thresholds , erosion thresholds and fluctuation thresholds . Then, combined with the surface exposure difference , erosion coefficient , wind force fluctuation index and monitoring data set , it evaluates the degree of soil erosion, wind force change, and climate change, and outputs corresponding governance decisions.

[0021] Compared with the prior art, the present invention provides a method and system for controlling soil erosion in a wind erosion area, having the following beneficial effects: 1. Through the multi-dimensional monitoring module, the present invention is network-connected to a monitoring device and a big data platform to obtain environmental data and climate data for all regions, and classifies and forms an environmental data set and a climate data set. The intelligent management module is set with a monitoring cycle of a fixed duration , and combined with the environmental data set, analyzes the degree of soil erosion in each region and generates a corresponding surface exposure difference and erosion coefficient . By integrating dynamic quantitative indicators, it accurately evaluates the degree of surface exposure change and soil erosion potential of each region. The intelligent management module analyzes the climate change trend in each region based on the climate data set and generates a corresponding wind force fluctuation index and monitoring data set , quantifies the wind force fluctuation intensity, pays attention to individual differences, greatly reduces manual intervention, shortens the governance response time, and at the same time reduces decision-making biases caused by subjective judgment, and is applicable to the governance of wind erosion areas in large-scale and complex environments.

[0022] 2. The present invention sets fixed numerical exposure thresholds through the intelligent management module 、 Erosion threshold and fluctuation threshold , combined with the surface exposure difference , erosion coefficient , wind fluctuation index and monitoring data set , evaluate the degree of soil and water loss, wind force change and climate change, and output corresponding treatment decisions, so as to implement area-specific policies, avoid waste of resources caused by over-treatment, establish an emergency protection mechanism at the same time, can quickly respond to high-risk areas, have high resource allocation efficiency and good dynamic treatment effect. Brief Description of the Drawings

[0023] Figure 1 is the method step diagram of the present invention; Figure 2 is the system flow chart of the present invention. Detailed Embodiments

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

[0025] Since the traditional method for controlling soil and water loss in wind erosion areas does not fully consider the regional characteristics and actual situations, it is difficult to achieve dynamic optimization and allocation. In the sparsely populated wind erosion areas, the deployment of mechanical sand barriers is delayed, the protection effect is poor, and the sustainable utilization rate is not high. Therefore, a method and system for controlling soil and water loss in wind erosion areas are provided. Please refer to Figure 1 - Figure 2 , the method for controlling soil and water loss in wind erosion areas includes the following steps: Step 1: Connect the monitoring device and the big data platform through the network, obtain the environmental data and climate data of all regions, and classify them into an environmental data set and a climate data set; The expression of the environmental data set is , to represent the environmental data of the first to the th regions. The environmental data includes short-wave infrared band reflectivity, near-infrared band reflectivity, terrain slope, surface soil loss thickness, vegetation coverage, soil type, floor area and plant species quantity, represents the time point for obtaining the regional environmental data. Specifically, remote sensing images of the target area are obtained through the monitoring device, and these images usually contain information in multiple bands, so that many parameters such as short-wave infrared band reflectivity and near-infrared band reflectivity can be obtained; The expression of the climate dataset is , to represent the climate data of the first to the th regions. The climate data includes daily wind speed, daily temperature, daily rainfall, and daily evaporation volume. represents the time point for obtaining the regional climate data. Real-time acquisition of multi-source heterogeneous data provides a data basis with high precision and high spatio-temporal resolution for subsequent analysis, significantly improving the scientific nature and credibility of the evaluation model. Step 2: Set a monitoring period with a fixed duration , and then combine it with the environmental dataset to analyze the soil erosion degree of each region and generate the corresponding surface bare difference and erosion coefficient ; The calculation process of the surface bare difference is as follows: According to the environmental dataset, count the environmental data of the th region within the monitoring period , and mark the short-wave infrared band reflectance of the th region at the beginning of the monitoring period as , mark the near-infrared band reflectance of the th region at the beginning of the monitoring period as , mark the short-wave infrared band reflectance of the th region at the end of the monitoring period as , and mark the near-infrared band reflectance of the th region at the end of the monitoring period as ;

[0026] In the formula, represents the surface bare index of the th region at the end of the monitoring period calculated through the principle of the normalized difference index. represents the surface bare index of the th region at the beginning of the monitoring period calculated through the principle of the normalized difference index. represents the surface bare difference of the th region within the monitoring period , and so on, to accurately evaluate the degree of change in the surface bare representation of each region. Erosion coefficient The calculation process is as follows: According to the environmental data set, mark the terrain slope of the th area as , mark the surface soil erosion thickness of the th area as , mark the vegetation coverage of the th area as , mark the floor area of the th area as ; Statistically analyze the environmental data of the th area within the monitoring period, and mark the change amount of the terrain slope of the th area within the monitoring period as , mark the change amount of the surface soil erosion thickness of the th area within the monitoring period as , mark the change amount of the vegetation coverage of the th area within the monitoring period as , and mark the change amount of the vegetation coverage of the ; If the soil type of the th area belongs to sandy soil,

[0027] In the formula, represents the weight for the ratio of surface exposure difference to floor area, represents the weight for the ratio of terrain slope to change amount, represents the weight for the ratio of change amount to vegetation coverage, , and are all constants, and , represents the erosion coefficient , and of the th area calculated according to the weights, ; If the soil type of the th area belongs to clay,

[0028] In the formula, represents the weight for the ratio of surface exposure difference to floor area, represents the weight for the ratio of surface soil erosion thickness to change amount, Indicates the weight for the ratio of the change amount to the vegetation coverage , and are all constants, and , Indicates that according to the , and weights, the erosion coefficient of the th area is calculated. According to the soil type, the weights are flexibly configured, and the comprehensive dynamic quantification index is used to accurately evaluate the soil erosion potential; Step 3: According to the climate dataset, analyze the climate change trend of each area and generate the corresponding wind power fluctuation index and the monitoring data group ; The calculation process of the wind power fluctuation index is as follows: According to the climate dataset, count the climate data of the th area within the monitoring period , and mark the daily wind speed of the th area within the monitoring period as , to represent the daily wind speed from the first time point to the th time point;

[0029]

[0030] In the formula, represents the average value of the daily wind speed of the th area within the monitoring period , represents the daily wind speed of the th area at the th time point, , represents that according to the standard deviation formula, the wind power fluctuation index of the th area is calculated to quantify the wind power fluctuation intensity; The calculation process of the monitoring data group is as follows: According to the climate dataset, count the climate data of the th area within the monitoring period , and mark the daily temperature of the th area within the monitoring period as , to Denote the daily temperature from the first time point to the th time point, and mark the daily rainfall in the th area within the monitoring period as ; , to Denote the daily rainfall from the first time point to the th time point, and mark the daily evaporation in the th area within the monitoring period as ; , to Denote the daily evaporation from the first time point to the th time point;

[0031] In the formula, denotes the daily temperature of the th area at the th time point, denotes the daily evaporation of the th area at the th time point, denotes calculating the ratio of temperature to evaporation at each time point in sequence, denotes the daily rainfall of the th area at the th time point, denotes calculating the ratio of rainfall to wind speed at each time point in sequence, denotes the monitoring data set of the th area, which focuses on individual differences, greatly reduces manual intervention, shortens the governance response time, and at the same time reduces the decision-making deviation caused by subjective judgment, and is applicable to the governance of wind erosion areas in large-scale and complex environments; Step Four: Set fixed values for the bare threshold , erosion threshold and fluctuation threshold , and then combine the surface bare difference , erosion coefficient , wind force fluctuation index and monitoring data set to evaluate the degree of soil and water loss, wind force change degree and climate change degree, and output the corresponding governance decisions; If the vegetation coverage of the th area ≥ 50%, the surface bare difference < bare threshold , and the erosion coefficient < erosion threshold , it means that the The soil and water loss in a certain area is relatively light. The existing number of plant species should be maintained. Without considering the vegetation coverage, the surface exposure difference in the th area is ≥ exposure threshold , or the erosion coefficient ≥ erosion threshold . When this is the case, it indicates that the soil and water loss in the th area is moderate. The types and quantities of plants for wind prevention and sand fixation should be increased. Without considering the vegetation coverage, the surface exposure difference ≥ exposure threshold , and the erosion coefficient ≥ erosion threshold . When this is the case, it indicates that the soil and water loss in the th area is severe and should be given priority for treatment. The types and quantities of plants for wind prevention and sand fixation and the quantity of mechanical sand barriers should be increased. By implementing area-specific measures, while avoiding waste of resources caused by over-treatment, it is also possible to quickly respond to high-risk areas, significantly improving the treatment efficiency and ecological restoration effect; If the wind fluctuation index in the th area exceeds the fluctuation threshold , it indicates that the wind changes strongly in the th area, and mechanical sand barriers should be arranged in a timely manner for protection. If in the monitoring data set of the th area , any one of the values is greater than or equal to 1, it indicates that the climate changes strongly in the th area. The types and quantities of plants for wind prevention and sand fixation should be increased, and the mechanical sand barriers should be updated in a timely manner, and an emergency protection mechanism should be established, with high resource allocation efficiency; A soil and water loss treatment system for the wind erosion area includes a multi-dimensional monitoring module and an intelligent management module; The multi-dimensional monitoring module consists of an environmental data unit and a climate data unit. The environmental data unit collects an environmental data set through a network-connected monitoring device. The environmental data set includes the environmental data of all areas. The climate data unit collects a climate data set through a network-connected big data platform. The climate data set includes the climate data of all areas; The intelligent management module consists of a soil and water assessment unit, a climate assessment unit, and a dynamic treatment unit. The soil and water assessment unit sets a monitoring period of a fixed duration , and then combines the environmental data set to analyze the soil and water loss degree of each area and generate the corresponding surface exposure difference and erosion coefficient . The climate assessment unit analyzes the climate change trend of each area based on the climate data set and generates the corresponding wind fluctuation index and monitoring data set , focusing on individual differences, the dynamic governance unit is set with a fixed value of the bare threshold , erosion threshold and fluctuation threshold , combined with the surface bare difference , erosion coefficient , wind fluctuation index and monitoring data set , evaluate the degree of soil and water loss, the degree of wind change and the degree of climate change, and output the corresponding governance decisions, with good dynamic governance effect.

[0032] Example 1: In this experiment, the Hexi Corridor area in Gansu was selected as the experimental object, and the monitoring period was set to 10 days. After monitoring, on the 1st day of the monitoring period , the short-infrared band reflectance of this area was 0.4%, and the near-infrared band reflectance was 0.6%. On the 10th day of the monitoring period , the short-infrared band reflectance of this area was 0.7%, and the near-infrared band reflectance was 0.6%. The surface bare difference of this area The calculation process is as follows:

[0033]

[0034] In the formula, represents the surface bare index of this area calculated after 10 days through the principle of normalized difference index, represents the surface bare index of this area calculated 10 days ago through the principle of normalized difference index, represents the surface bare difference of this area within 10 days is , the vegetation coverage of this area is 50%, and the erosion coefficient is 1.1, the bare threshold is set to 0.4, the erosion threshold is set to 1.2. After judgment, the vegetation coverage of this area is 50%, and the surface bare difference <bare threshold , and the erosion coefficient <erosion threshold , the degree of soil and water loss in this area is relatively light, and the existing number of plant species should be maintained.

[0035] Example 2: In this experiment, an area of 1000 square meters was selected as the experimental object. After detection, the soil type of this area belongs to sandy, and the surface bare difference is 0.3, the terrain slope is 5 degrees, within 30 days, the change in terrain slope is 1 degree, the vegetation coverage is 60%, within 30 days, the change in vegetation coverage is 10%, and the erosion coefficient of this area The calculation process is as follows:

[0036]

[0037] In the formula, represents the weight for the ratio of the surface exposure difference to the occupied area, represents the weight for the ratio of the terrain slope to the change amount, represents the weight for the ratio of the change amount to the vegetation coverage, 、 and are all constants, and , according to 、 and weights, the erosion coefficient of this area is calculated as is , the exposure threshold is set to 0.1, the erosion threshold is set to 1.2. After judgment, without considering the vegetation coverage, the surface exposure difference ≥ exposure threshold , and the erosion coefficient ≥ erosion threshold , indicating that the soil and water loss degree of this area is serious, and it should be preferentially treated by increasing the types of plants for wind prevention and sand fixation, the number of plants, and the number of mechanical sand barriers.

[0038] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A soil and water loss control method based on the wind erosion area, characterized in that It includes the following steps: Step 1: Connect the monitoring device and the big data platform through the network, obtain the environmental data and climate data of all regions, and classify and form an environmental data set and a climate data set; Step 2: Set a monitoring period with a fixed duration , and then, in combination with the environmental data set, analyze the soil erosion degree of each area and generate the corresponding surface exposure difference and erosion coefficient ; Step 3: Analyze the climate change trends in each region based on the climate dataset and generate the corresponding wind power fluctuation index and the monitoring data set ; Step 4: Set the bare threshold with a fixed value , erosion threshold and fluctuation threshold , and then combine with the surface bare difference , erosion coefficient , wind force fluctuation index and monitoring data group , evaluate the degree of soil and water loss, wind force change and climate change, and output the corresponding treatment decisions.

2. The soil and water loss control method based on the wind erosion area according to claim 1, wherein: In the first step, the expression of the environmental data set is , to represent the environmental data of the first to the th regions. The environmental data includes short-wave infrared band reflectance, near-infrared band reflectance, terrain slope, surface soil erosion thickness, vegetation coverage, soil type, floor area, and the number of plant species. represents the time point for obtaining the regional environmental data.

3. The soil and water loss control method based on the wind erosion area according to claim 2, wherein: In the first step, the expression of the climate dataset is , to represent the climate data of the first to the th regions. The climate data includes daily wind speed, daily temperature, daily rainfall, and daily evaporation, represents the time point for obtaining the regional climate data.

4. The soil and water loss control method based on the wind erosion area according to claim 3, characterized in that: In the second step described above, the ground surface exposure is poor The calculation process is as follows: According to the environmental data set, count the environmental data of the th area within the monitoring period, and mark the short-wave infrared band reflectance of the th area at the start of the monitoring period as , mark the near-infrared band reflectance of the th area at the start of the monitoring period as , mark the short-wave infrared band reflectance of the th area at the end of the monitoring period as , mark the near-infrared band reflectance of the th area at the end of the monitoring period as ; ； In the formula, represents the surface exposure index of the th region at the end of the monitoring period calculated by the principle of the normalized difference index, represents the surface exposure index of the th region at the start of the monitoring period calculated by the principle of the normalized difference index, represents the surface exposure difference of the th region within the monitoring period and .

5. The soil and water loss control method based on the wind erosion area according to claim 4, wherein: In the second step described above, the erosion coefficient The calculation process is as follows: According to the environmental data set, mark the terrain slope of the th area as , mark the surface soil loss thickness of the th area as , mark the vegetation coverage of the th area as , mark the floor area of the th area as ; Statistical monitoring period Within the th region's environmental data, and mark the change in the terrain slope of the th region within the monitoring period as , mark the change in the surface soil erosion thickness of the th region within the monitoring period as ; mark the change in the vegetation coverage of the th region within the monitoring period as , mark the change in the vegetation coverage of the th region within the monitoring period as ; ; If the soil type of the th region belongs to sandy soil, ； In the formula, represents the weight for the ratio of the poor surface exposure to the floor area, represents the weight for the ratio of the terrain slope to the change amount, represents the weight for the ratio of the change amount to the vegetation coverage, , and are all constants, and , represents that according to the , and weights, the erosion coefficient of the th area is calculated; If the soil type of the th region belongs to clay, ； In the formula, represents the weight for the ratio of the poor surface exposure to the occupied area, represents the weight for the ratio of the surface soil erosion thickness to the change amount, represents the weight for the ratio of the change amount to the vegetation coverage, 、 and are all constants, and , represents that according to the 、 and weights, the erosion coefficient of the th area is calculated as .

6. The soil and water loss control method based on the wind erosion area according to claim 5, characterized in that: In the third step, the wind power fluctuation index The calculation process is as follows: According to the climate dataset, the statistical monitoring period within, the th region's climate data, and during the monitoring period within, the th region's daily wind speed is marked as , to indicating the daily wind speed from the first time point to the th time point; ， ； In the formula, represents the average daily wind speed in the th monitoring period in the th area, represents the daily wind speed at the th time point in the th area, , represents the wind power fluctuation index of the th area calculated according to the standard deviation formula .

7. The soil and water loss control method based on the wind erosion area according to claim 6, characterized in that: In the third step, the monitoring data group The calculation process is as follows: According to the climate dataset, the statistical monitoring period Within, the th region's climate data, and during the monitoring period Within, the th region's daily temperature is marked as , To Indicates the daily temperature from the first time point to the th time point. During the monitoring period Within, the th region's daily rainfall is marked as , To Indicates the daily rainfall from the first time point to the th time point. During the monitoring period Within, the th region's daily evaporation is marked as , To Indicates the daily evaporation from the first time point to the th time point; ； In the formula, represents the daily temperature of the th region at the th time point, represents the daily evaporation of the th region at the th time point, represents calculating the ratio of temperature to evaporation for each time point in sequence, represents the daily rainfall of the th region at the th time point, represents calculating the ratio of rainfall to wind speed for each time point in sequence, represents the monitoring data set of the th region.

8. The soil and water loss control method based on the wind erosion area according to claim 7, characterized in that: In Step 4, if the vegetation coverage of the th area ≥ 50%, the surface exposure difference < exposure threshold , and the erosion coefficient < erosion threshold , it means that the soil and water loss degree of the th area is relatively light. The existing plant species quantity should be maintained. Without considering the vegetation coverage, when the surface exposure difference of the th area ≥ exposure threshold , or the erosion coefficient ≥ erosion threshold , it means that the soil and water loss degree of the th area is medium. The plant species and quantity for wind prevention and sand fixation should be increased. Without considering the vegetation coverage, when the surface exposure difference ≥ exposure threshold , and the erosion coefficient ≥ erosion threshold , it means that the soil and water loss degree of the th area is serious. Priority should be given to treatment, and the plant species, plant quantity and mechanical sand barrier quantity for wind prevention and sand fixation should be increased.

9. The soil and water loss control method based on the wind erosion area according to claim 8, characterized in that: In the fourth step, if the wind fluctuation index of the region exceeds the fluctuation threshold , it indicates that the wind in the region changes strongly, and mechanical sand barriers should be arranged in time for protection. If in the region's monitoring data set , any value is greater than or equal to 1, it indicates that the climate in the region changes strongly, and the types and quantities of windbreak and sand-fixation plants should be increased, and the mechanical sand barriers should be updated in time.

10. A soil and water loss control system for wind erosion areas, which is applied to the soil and water loss control method for wind erosion areas described in any one of claims 1-9, and is characterized in that: It includes a multi-dimensional monitoring module and an intelligent management module; The multi-dimensional monitoring module is composed of an environmental data unit and a climate data unit. The environmental data unit collects the environmental data set through the network connection monitoring device. The environmental data set includes the environmental data of all regions. The climate data unit collects the climate data set through the network connection big data platform. The climate data set includes the climate data of all regions; The intelligent management module consists of a soil and water assessment unit, a climate assessment unit, and a dynamic governance unit. The soil and water assessment unit is set with a monitoring cycle of a fixed duration. , combined with the environmental data set, analyze the degree of soil and water loss in each region and generate the corresponding surface exposure difference. and erosion coefficient. , the climate assessment unit analyzes the climate change trend in each region according to the climate data set and generates the corresponding wind force fluctuation index. and monitoring data set. , the dynamic governance unit is set with an exposure threshold of a fixed value. , erosion threshold. and fluctuation threshold. , combined with the surface exposure difference. , erosion coefficient. , wind force fluctuation index. and monitoring data set. , evaluate the degree of soil and water loss, the degree of wind force change, and the degree of climate change, and output the corresponding governance decisions.

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