A desert ecological environment monitoring and early warning method and system

Abstract

The present invention relates to the technical field of desert environment monitoring, and discloses a desert ecological environment monitoring and early warning method and system. The method comprises: determining the vegetation index and soil spectral characteristics of the monitoring area based on aerial images of the monitoring area, and evaluating the monitoring score of the monitoring area. Based on the relationship between the monitoring score and the historical monitoring score, determining whether to conduct environmental monitoring of the monitoring area, wherein: when the monitoring score is less than the historical monitoring score, the monitoring area is subjected to environmental monitoring. Based on the soil data and environmental data of the monitoring area, the soil score and environmental score of the monitoring area are determined, and the desertification score of the monitoring area is evaluated. The historical desertification scores of the monitoring area in adjacent time periods are obtained, and the early warning level of the monitoring area is determined based on the difference between the desertification score and the historical desertification score. The present invention timely evaluates the ecological status of the monitoring area by comprehensively analyzing the data of the monitoring area, thereby achieving early warning and effective management of desertification.

Description

Technical Field

[0001] The present invention relates to the technical field of desert environment monitoring, and in particular to a desert ecological environment monitoring and early warning method and system. Background Art

[0002] In the field of desert ecological and environmental monitoring, desertification is becoming increasingly serious due to the impacts of global climate change and human activities. This phenomenon not only threatens the stability of ecosystems but also has profound impacts on agricultural production, drinking water safety, and local economic development. For example, soil erosion and plant wilting in arid regions can lead to reduced agricultural yields, affecting farmers' livelihoods and even causing social problems. Therefore, effectively and scientifically addressing desertification has become a pressing global challenge.

[0003] To effectively combat desertification, timely acquisition of ecological change information within monitored areas and early warnings have become crucial research areas. However, current monitoring methods primarily rely on ground-based observations or regular manual surveys. These traditional methods often have limited coverage and fail to fully reflect the dynamics of large-scale desertification. Furthermore, data updates are often infrequent, resulting in delayed feedback on ecological changes and consequently delayed response measures, making it difficult to meet the demands for rapid assessment and real-time early warning of widespread desertification. For example, monitoring stations in certain areas may be impossible to establish due to funding or technical constraints, resulting in the loss of important data on ecological changes. Furthermore, manual surveys require significant manpower and resources, and the results are often subject to subjective factors, resulting in significant data bias. Consequently, these traditional monitoring methods are becoming increasingly unsuitable for the demands of modern ecological monitoring.

[0004] Therefore, there is an urgent need to invent a monitoring and early warning technology for the desert ecological environment to solve the problem that the existing desertification monitoring methods rely on ground stations and manual surveys, resulting in small data coverage, low update frequency, delayed feedback, and cannot meet the needs of rapid assessment and real-time early warning. Summary of the Invention

[0005] In view of this, the present invention proposes a desert ecological environment monitoring and early warning method and system, aiming to solve the problem that the current desertification monitoring method relies on ground stations and manual surveys, resulting in small data coverage, low update frequency, delayed feedback, and cannot meet the needs of rapid assessment and real-time early warning.

[0006] The present invention proposes a desert ecological environment monitoring and early warning method, comprising:

[0007] Acquiring aerial images of the monitoring area, determining a vegetation index and soil spectral characteristics of the monitoring area based on the aerial images, and evaluating a monitoring score of the monitoring area based on the vegetation index and soil spectral characteristics;

[0008] Obtain historical monitoring scores of the monitoring area during adjacent time periods, and determine whether to perform environmental monitoring on the monitoring area based on a relationship between the monitoring score and the historical monitoring scores, wherein:

[0009] When the monitoring score is less than the historical monitoring score, environmental monitoring is performed on the monitoring area;

[0010] Acquiring soil data and environmental data of the monitoring area, determining a soil score of the monitoring area based on the soil data, determining an environmental score of the monitoring area based on the environmental data, and determining a wasteland score of the monitoring area based on the soil score and the environmental score;

[0011] Obtain historical wasteland scores of the monitoring area in adjacent time periods, and determine the warning level of the monitoring area based on a wasteland score difference between the wasteland score and the historical wasteland score.

[0012] Furthermore, when evaluating the monitoring score of the monitoring area based on the vegetation index and soil spectral characteristics, the following steps are included:

[0013] Dividing the aerial image into a plurality of regions based on a preset distance R, obtaining a reflection frequency of a red light band and an infrared reflectivity of each region in the aerial image, and determining a vegetation index and soil reflectivity characteristic of each region based on the reflection frequency of the red light band and the infrared reflectivity;

[0014] The vegetation health value of each of the regions is determined based on the vegetation index and soil reflectance characteristics of each of the regions, and the vegetation health value of each of the regions is substituted into Formula I to determine the monitoring score, wherein Formula I is as follows:

[0015]

[0016] Wherein, S is the monitoring score, n is the total number of the regions, Vi is the vegetation health value of the i-th region, and Wi is the weight of the i-th region.

[0017] Furthermore, determining the soil score of the monitoring area based on the soil data includes:

[0018] Obtaining a soil collection depth and a corresponding soil moisture in the soil data, and stratifying the soil according to the soil collection depth and the corresponding soil moisture;

[0019] Obtaining the thickness of the surface soil layer in each of the soil layers, obtaining the historical soil layer thickness of the surface soil layer in adjacent time periods, and determining the soil score based on the relationship between the soil layer thickness and the historical soil layer thickness;

[0020] When the soil layer thickness is less than or equal to the historical soil layer thickness, the soil score is determined to be Xmin;

[0021] When the soil layer thickness is greater than the historical soil thickness, a thickness difference between the soil layer thickness and the historical soil thickness is obtained, and the soil score is determined based on the thickness difference.

[0022] Furthermore, determining the soil score based on the thickness difference includes:

[0023] determining the soil score according to a relationship between the thickness difference and a preconfigured first preset thickness difference and a second preset thickness difference;

[0024] When the thickness difference is less than the first preset thickness difference, the soil score is determined to be X1;

[0025] When the thickness difference is greater than or equal to the first preset thickness difference and the thickness difference is less than the second preset thickness difference, determining the soil score to be X2;

[0026] When the thickness difference is greater than or equal to the second preset thickness difference, determining the soil score to be X3;

[0027] The first preset thickness difference is smaller than the second preset thickness difference, and 0<Xmin<X1<X2<X3.

[0028] Furthermore, when the soil score is determined to be Xi, i=1, 2, 3, including:

[0029] Obtaining a mean soil particle size of the surface soil and a collected volume of the surface soil, and determining a soil porosity value of the surface soil based on the mean soil particle size and the collected volume;

[0030] Obtaining historical soil porosity values ​​of surface soil in adjacent time periods, and determining whether to adjust the soil score Xi based on the relationship between the soil porosity value and the historical soil porosity value;

[0031] When the soil porosity value is less than or equal to the historical soil porosity value, it is determined that the soil score Xi is not adjusted;

[0032] When the soil porosity value is greater than the historical soil porosity value, an adjustment coefficient is determined according to the porosity value difference between the soil porosity value and the historical soil porosity value, and the soil score Xi is adjusted according to the adjustment coefficient.

[0033] Furthermore, when determining the adjustment coefficient based on the pore value difference between the soil pore value and the historical soil pore value, the adjustment coefficient includes:

[0034] determining the adjustment coefficient according to a relationship between the pore value difference and the first preset pore value difference and the second preset pore value difference;

[0035] When the pore value difference is less than the first preset pore value difference, the adjustment coefficient is determined to be K1;

[0036] When the pore value difference is greater than or equal to the first preset pore value difference, and the pore value difference is less than the second preset pore value difference, the adjustment coefficient is determined to be K2;

[0037] When the pore value difference is greater than or equal to the second preset pore value difference, the adjustment coefficient is determined to be K3;

[0038] The first preset pore value difference is smaller than the second preset pore value difference, and 1<K1<K2<K3.

[0039] Furthermore, when determining the environmental score of the monitoring area based on the environmental data, it includes:

[0040] Obtaining the number of sandstorms, total precipitation, and average temperature values ​​in the monitoring area within a preset period, and determining the environmental score based on the relationship between the average temperature value and a preset temperature value;

[0041] When the average temperature value is less than the preset temperature value, the environmental score is determined to be Jmin;

[0042] When the average temperature value is greater than or equal to the preset temperature value, the number of sandstorms, the total precipitation, and the average temperature value are substituted into Formula II to determine the environmental score, wherein Formula II is as follows:

[0043] Ji=z1×a+z2×d+z3×f;

[0044] Wherein, Ji is the environmental score, i=1, 2, 3, a is the number of sandstorms, d is the total precipitation, f is the average temperature value, z1-z3 are weight coefficients, and the sum of z1-z3 is 1.

[0045] Furthermore, when determining the wasteland score of the monitored area based on the soil score and the environment score, it includes:

[0046] A correction coefficient is determined based on a relationship between the environmental score and a preset first environmental score and a preset second environmental score. The soil score is corrected based on the correction coefficient, and the corrected soil score is determined as the wasteland score of the monitored area, wherein:

[0047] When the environmental score is less than or equal to the first preset environmental score, the correction coefficient is determined to be P1;

[0048] When the environmental score is greater than the first preset environmental score, and the first preset environmental score is less than or equal to the second preset environmental score, determining the correction coefficient to be P2;

[0049] When the environmental score is greater than the second preset environmental score, the correction coefficient is determined to be P3;

[0050] The first preset environment score is smaller than the second preset environment score, and 1<P1<P2<P3.

[0051] Furthermore, when determining the warning level of the monitoring area based on the difference between the wasteland score and the historical wasteland score, it includes:

[0052] pre-configuring a first preset wasteland score difference and a second preset wasteland score difference, and determining a warning level of the monitoring area according to a relationship between the wasteland score difference and the first preset wasteland score difference and the second preset wasteland score difference;

[0053] When the wasteland scoring difference is less than the first preset wasteland scoring difference, the warning level of the monitoring area is determined to be a low level;

[0054] When the wasteland score difference is greater than or equal to the first preset wasteland score difference, and the wasteland score difference is less than the second preset wasteland score difference, the warning level of the monitoring area is determined to be medium;

[0055] When the wasteland scoring difference is greater than or equal to the second preset wasteland scoring difference, the warning level of the monitoring area is determined to be high;

[0056] The first preset wasteland score difference is smaller than the second preset wasteland score difference, and low level < medium level < high level.

[0057] Compared to existing technologies, the present invention offers the following advantages: by acquiring aerial imagery, it can quickly capture vegetation growth and soil characteristics over a large area. This data can reflect key ecological indicators such as vegetation coverage and health, as well as soil moisture and nutrient status, helping scientists comprehensively understand the ecological health of the monitored area. Compared to traditional ground-based monitoring methods, aerial photography not only saves significant manpower and material resources but also reduces data bias caused by human interference, making ecological monitoring results more objective and reliable. Furthermore, by combining historical monitoring data, current monitoring scores can be compared with historical scores to determine current trends in ecological status. This dynamic comparison approach eliminates isolated monitoring tasks and integrates them into time series analysis, effectively identifying potential risks of ecological deterioration. For example, when the monitoring score falls below the historical monitoring score, an environmental monitoring alert is automatically triggered, enabling timely response to environmental changes and ensuring the implementation of necessary management measures to prevent further desertification. Furthermore, by integrating soil and environmental data to calculate soil and environmental scores, desertification scores can be assessed. Soil and environmental factors are important factors influencing ecological health. By scientifically calculating these scores, a comprehensive understanding of the multiple factors influencing the ecology of the monitored area can be achieved. This multi-dimensional assessment not only identifies potential ecological problems but also provides more targeted interventions for environmental management. Finally, by comparing the scores with historical desertification scores, the current warning level for the monitored area can be determined. This mechanism ensures continuous monitoring and assessment of desertification risks, enabling monitors to promptly identify changes in the ecosystem and adjust management strategies accordingly.

[0058] On the other hand, this application also provides a desert ecological environment monitoring and early warning system, including:

[0059] a first evaluation module, configured to obtain an aerial image of a monitoring area, determine a vegetation index and soil spectral characteristics of the monitoring area based on the aerial image, and evaluate a monitoring score of the monitoring area based on the vegetation index and soil spectral characteristics;

[0060] a central control module electrically connected to the first evaluation module, the central control module being configured to obtain historical monitoring scores of the monitoring area during adjacent time periods, and determine whether to perform environmental monitoring on the monitoring area based on a relationship between the monitoring score and the historical monitoring score, wherein: when the monitoring score is less than the historical monitoring score, the central control module performs environmental monitoring on the monitoring area;

[0061] a second evaluation module electrically connected to the central control module, the second evaluation module being configured to obtain soil data and environmental data of the monitored area, determine a soil score of the monitored area based on the soil data, determine an environmental score of the monitored area based on the environmental data, and determine a wasteland score of the monitored area based on the soil score and the environmental score;

[0062] The early warning module and the second evaluation module are used to obtain the historical wasteland scores of the monitoring area in adjacent time periods, and determine the early warning level of the monitoring area based on the wasteland score difference between the wasteland score and the historical wasteland score.

[0063] It is understandable that the desert ecological environment monitoring and early warning method and system in the above-mentioned embodiments of the present invention have the same beneficial effects and will not be described in detail. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0065] Figure 1 A flowchart of a desert ecological environment monitoring and early warning method provided by an embodiment of the present invention;

[0066] Figure 2 This is a functional block diagram of a desert ecological environment monitoring and early warning system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0067] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0068] like Figure 1 As shown, in some embodiments of the present application, this embodiment provides a desert ecological environment monitoring and early warning method, including:

[0069] Step S100: Acquire an aerial image of the monitoring area, determine the vegetation index and soil spectral characteristics of the monitoring area based on the aerial image, and evaluate the monitoring score of the monitoring area based on the vegetation index and soil spectral characteristics.

[0070] Specifically, the evaluation of the monitoring score of a monitoring area based on the vegetation index and soil spectral characteristics includes: dividing the aerial image into several areas based on a preset distance R, obtaining the reflection frequency and infrared reflectivity of the red light band in each area of ​​the aerial image, and determining the vegetation index and soil reflectivity characteristics of each area based on the reflection frequency and infrared reflectivity of the red light band. Based on the vegetation index and soil reflectivity characteristics of each area, the vegetation health value of each area is determined, and the vegetation health value of each area is substituted into Formula I to determine the monitoring score, where Formula I is as follows:

[0071]

[0072] Where S is the monitoring score, n is the total number of regions, Vi is the vegetation health value of the i-th region, and Wi is the weight of the i-th region.

[0073] It can be seen that the monitoring area is divided into multiple small areas at preset distances using aerial images, and then the red light band reflection frequency and infrared reflectivity of each area are obtained to calculate the vegetation index and soil reflectivity characteristics. These characteristics reflect the vegetation health status of each area. By combining the vegetation health value of each area with the corresponding weight, the overall monitoring score is calculated using the weighted average method. This process realizes the quantitative assessment of the ecological status of the monitoring area and can effectively reflect the changes in vegetation health and soil conditions.

[0074] As can be understood, aerial imagery is used to divide the monitoring area into multiple small areas at preset distances. The red light reflection frequency and infrared reflectivity of each area are then obtained, from which vegetation indices and soil reflectivity characteristics are calculated. These characteristics reflect the vegetation health of each area and provide important data support for the assessment of the overall monitoring score. Specifically, high-resolution aerial photography technology enables detailed monitoring of a wide area, avoiding the limitations of traditional ground surveys. Secondly, during the implementation process, the acquired aerial imagery is processed and divided into several areas based on a preset distance R. This process ensures that the ecological characteristics of different areas can be analyzed independently, resulting in more accurate data. Within each area, vegetation indices (such as the Normalized Difference Vegetation Index (NDVI)) and soil reflectivity characteristics are obtained by analyzing the red light reflection frequency and infrared reflectivity. The vegetation index is an important indicator of plant growth and is typically calculated from reflectance spectral data. Soil reflectivity reflects the composition and condition of the soil, information that is crucial for assessing land degradation and ecological health. Furthermore, the monitoring score S is calculated by obtaining the vegetation health value of each region and substituting it into Formula I. Here, n represents the total number of regions, Vi represents the vegetation health value of region i, and Wi represents the weight of region i. This weighted average effectively reflects the relative importance of each region in the overall ecological health, ensuring that the final monitoring score accurately reflects the ecological status of the entire monitored area. The weighting can be adjusted based on the importance of the region or the differences in its ecological characteristics to meet different monitoring needs. Finally, by regularly acquiring aerial imagery and calculating the monitoring score, dynamic tracking of ecological and environmental changes can be achieved.

[0075] Step S200: Obtain historical monitoring scores of adjacent time periods in the monitoring area, and determine whether to perform environmental monitoring on the monitoring area based on the relationship between the monitoring score and the historical monitoring score, wherein: when the monitoring score is less than the historical monitoring score, perform environmental monitoring on the monitoring area.

[0076] Step S300: Acquire soil data and environmental data of the monitoring area, determine a soil score of the monitoring area based on the soil data, determine an environmental score of the monitoring area based on the environmental data, and determine a desertification score of the monitoring area based on the soil score and the environmental score.

[0077] Specifically, determining the soil score of a monitored area based on soil data involves: obtaining the soil collection depth and corresponding soil moisture in the soil data, and stratifying the soil based on the soil collection depth and corresponding soil moisture. Obtaining the thickness of the surface soil layer in each soil layer, obtaining the historical soil layer thickness of the surface soil layer in adjacent time periods, and determining the soil score based on the relationship between the soil layer thickness and the historical soil layer thickness: When the soil layer thickness is less than or equal to the historical soil layer thickness, the soil score is determined to be Xmin. When the soil layer thickness is greater than the historical soil thickness, the difference between the soil layer thickness and the historical soil thickness is obtained, and the soil score is determined based on this thickness difference.

[0078] Specifically, determining a soil score based on the thickness difference includes: determining the soil score based on the relationship between the thickness difference and a pre-configured first and second preset thickness differences. When the thickness difference is less than the first preset thickness difference, the soil score is determined to be X1. When the thickness difference is greater than or equal to the first preset thickness difference and less than the second preset thickness difference, the soil score is determined to be X2. When the thickness difference is greater than or equal to the second preset thickness difference, the soil score is determined to be X3. The first preset thickness difference is less than the second preset thickness difference, and 0 < Xmin < X1 < X2 < X3.

[0079] Specifically, when determining a soil score Xi, where i = 1, 2, or 3, the following steps are performed: obtaining the mean soil particle size and the volume of the surface soil collected, and determining the soil porosity of the surface soil based on the mean soil particle size and the volume. Obtaining historical soil porosity values ​​for the surface soil over adjacent time periods, and determining whether to adjust the soil score Xi based on the relationship between the soil porosity value and the historical soil porosity value. If the soil porosity value is less than or equal to the historical soil porosity value, no adjustment is made to the soil score Xi. If the soil porosity value is greater than the historical soil porosity value, an adjustment coefficient is determined based on the porosity difference between the soil porosity value and the historical soil porosity value, and the soil score Xi is adjusted based on the adjustment coefficient.

[0080] Specifically, when determining the adjustment coefficient based on the pore value difference between the soil porosity value and the historical soil porosity value, the adjustment coefficient is determined based on the relationship between the pore value difference and a pre-configured first preset pore value difference and a second preset pore value difference. When the pore value difference is less than the first preset pore value difference, the adjustment coefficient is determined to be K1. When the pore value difference is greater than or equal to the first preset pore value difference and less than the second preset pore value difference, the adjustment coefficient is determined to be K2. When the pore value difference is greater than or equal to the second preset pore value difference, the adjustment coefficient is determined to be K3. The first preset pore value difference is less than the second preset pore value difference, and 1<K1<K2<K3.

[0081] It can be seen that different scoring criteria are set according to the relationship between the soil layer thickness and the historical soil layer thickness to determine the soil scores Xmin, X1, X2 and X3. This process takes into account the changes in soil layer thickness and can effectively reflect the actual situation of the soil. In addition, by analyzing the mean particle size and collection volume of the surface soil, the soil porosity value is calculated and compared with the historical data to decide whether to adjust the soil score. The setting of the adjustment coefficient is based on the relationship between the porosity value difference and the preset threshold, ensuring the dynamic adaptability of the soil score. This method comprehensively considers the influence of soil layer thickness, porosity and historical data, realizes the accurate assessment of soil conditions, reflects the changes in soil health and stability, and provides a scientific basis for desertification monitoring and ecological management.

[0082] It can be understood that the soil data, including the soil sampling depth and corresponding moisture content, can reflect the actual soil moisture status. By stratifying the soil, a more detailed understanding of the physical properties of different soil layers is provided, which is crucial for assessing soil quality. Secondly, by analyzing the relationship between the thickness of the surface soil layer and the thickness of historical soil layers, multiple threshold scoring criteria were established, including Xmin, X1, X2, and X3. This approach not only considers the influence of historical data but also promptly reflects soil changes, ensuring the scoring is highly timely and adaptable. Furthermore, when determining the soil score, the soil porosity value is calculated by taking the mean particle size of the surface soil layer and the sampling volume. This metric is a key factor in assessing soil water retention and air permeability. By comparing the soil porosity value with historical porosity values, the soil health status can be determined and, based on this, the score can be adjusted. The advantage of this process lies in not only basing the assessment on absolute values ​​but also in incorporating historical data, making the scoring more scientific and accurate. Finally, the adjustment coefficient is determined based on the relationship between the porosity value difference and the preset threshold. By categorizing the porosity difference into different levels, the soil score can be dynamically adjusted based on actual conditions. For example, when the porosity difference is less than the preset first threshold, a lower adjustment factor, K1, is applied; when the difference is larger, it is increased to K2 or K3. This hierarchical adjustment mechanism ensures the flexibility of soil scoring, enabling it to promptly reflect changing soil conditions and meet the needs of dynamic monitoring.

[0083] Specifically, determining the environmental score for a monitored area based on environmental data involves obtaining the number of sandstorms, total precipitation, and average temperature in the monitored area during a preset time period, and determining the environmental score based on the relationship between the average temperature and the preset temperature value. When the average temperature is less than the preset temperature value, the environmental score is determined to be Jmin. When the average temperature is greater than or equal to the preset temperature value, the number of sandstorms, total precipitation, and average temperature are substituted into Formula II to determine the environmental score, as shown in Formula II: Ji = z1 × a + z2 × d + z3 × f. Here, Ji is the environmental score, i = 1, 2, or 3, a is the number of sandstorms, d is the total precipitation, f is the average temperature, and z1 - z3 are weight coefficients, with the sum of z1 - z3 being 1.

[0084] As can be understood, an environmental scoring model is established by comprehensively analyzing environmental data from the monitored area (including the number of sandstorms, total precipitation, and average temperature) to assess the ecological and environmental status of the region. Specifically, two scoring criteria are set based on the comparison of average temperature values ​​with preset temperature values: when the average temperature is below the preset value, the environmental score is set to the minimum value Jmin, reflecting potential ecological risks; when the average temperature is above or equal to the preset value, a more detailed score calculation is performed using Formula II. This formula weights the number of sandstorms, total precipitation, and average temperature to form a comprehensive environmental score, Ji. The weight coefficients z1, z2, and z3 are set to quantify the impact of different factors on the environmental score, ensuring the scientific and rationality of the score. In this way, environmental changes and potential threats in the monitored area can be effectively reflected, providing data support for ecological management and decision-making.

[0085] Specifically, when determining the wasteland score of the monitored area based on the soil score and the environmental score, the method includes: determining a correction coefficient based on the relationship between the environmental score and a pre-set first preset environmental score and a pre-set second preset environmental score; correcting the soil score based on the correction coefficient; and determining the corrected soil score as the wasteland score of the monitored area, wherein: when the environmental score is less than or equal to the first preset environmental score, the correction coefficient is determined to be P1. When the environmental score is greater than the first preset environmental score, and the first preset environmental score is less than or equal to the second preset environmental score, the correction coefficient is determined to be P2. When the environmental score is greater than the second preset environmental score, the correction coefficient is determined to be P3. The first preset environmental score is less than the second preset environmental score, and 1<P1<P2<P3.

[0086] It can be understood that by integrating environmental changes with soil quality and dynamically adjusting the correction coefficient, the overall ecological status of the monitored area can be reflected. Specifically, the environmental score plays a central role in the assessment of desertification scores. When the environmental score is high, it indicates that the area may face severe ecological challenges, such as persistent drought, frequent sandstorms, or soil erosion. Therefore, a significant correction of the soil score is necessary to ensure timely and effective ecological management measures. At this stage, the setting of correction coefficient P3 is crucial, as it guides decision-makers to take timely action to prevent further ecological deterioration. When the environmental score is at an intermediate level (between the first and second preset environmental scores), the introduction of correction coefficient P2 provides a relatively flexible response mechanism. In this case, while the soil score needs to be corrected, the correction is small, indicating that the ecological environment is improving and that the ecological restoration potential of the monitored area remains. In this case, relevant departments can use this score to develop appropriate management and restoration plans, encouraging sustainable land use while protecting the existing ecosystem. Finally, when the environmental score is higher than the second preset environmental score, the use of correction coefficient P1 indicates that the ecosystem in the monitored area is relatively healthy, and the soil score remains unchanged, providing a good foundation for continued ecological protection and management. This assessment process not only focuses on soil quality itself but also emphasizes the impact of environmental factors on soil health, promoting the development of a comprehensive ecological monitoring system. Through this comprehensive assessment mechanism, the barrenness score of the monitored area can promptly reflect changes in the soil and environment, enabling relevant decision-makers to formulate more scientific and effective ecological protection measures and promote the achievement of sustainable development goals.

[0087] Step S400: Obtain historical desertification scores of the monitored area during adjacent time periods, and determine the warning level of the monitored area based on the difference between the desertification score and the historical desertification score.

[0088] Specifically, when determining the early warning level of a monitored area based on the difference between the wasteland score and the historical wasteland score, the method includes: pre-configuring a first preset wasteland score difference and a second preset wasteland score difference, and determining the early warning level of the monitored area based on the relationship between the wasteland score difference and the first preset wasteland score difference and the second preset wasteland score difference. When the wasteland score difference is less than the first preset wasteland score difference, the early warning level of the monitored area is determined to be low. When the wasteland score difference is greater than or equal to the first preset wasteland score difference, and the wasteland score difference is less than the second preset wasteland score difference, the early warning level of the monitored area is determined to be medium. When the wasteland score difference is greater than or equal to the second preset wasteland score difference, the early warning level of the monitored area is determined to be high. The first preset wasteland score difference is less than the second preset wasteland score difference, and low level < medium level < high level.

[0089] As you can see, by comparing the desertification score difference with a preset difference, trends in ecological change can be clearly identified. This approach is not only simple and easy to implement, but also allows for the formulation of management measures by setting different warning levels. For example, if the desertification score difference in a monitored area is low, relevant departments can choose to conduct routine monitoring and maintenance to prevent further deterioration of the problem. When the difference reaches a medium level, more proactive intervention measures, such as implementing vegetation restoration and soil improvement projects, are necessary to reduce ecological risks. A high level indicates the need for immediate action and the mobilization of additional resources to prevent ecological collapse. Secondly, the dynamic nature of ecological monitoring makes the early warning mechanism more adaptable. By combining real-time monitoring with historical data, the health of the ecosystem can be more accurately assessed. This dynamic assessment method can help decision-makers adjust strategies promptly and avoid misjudgments caused by information lags. For example, if the desertification score difference detected by monitoring increases sharply within a certain period of time, relevant departments can quickly implement targeted measures, such as strengthening soil and water conservation and implementing targeted planting strategies, thereby slowing the progression of desertification. Finally, the successful implementation of early warning mechanisms relies not only on scientific assessment methods but also on effective data support and technical means. With the rapid development of remote sensing technology and big data analysis, environmental changes in monitored areas can be captured in real time using high-resolution satellite imagery and automated monitoring equipment. The combination of these technologies enables ecological monitoring to move beyond traditional manual surveys and provide a more comprehensive and accurate picture of ecological status. Through the analysis and processing of big data, decision makers can gain deeper insights, providing data support for the development of long-term, sustainable ecological management plans.

[0090] In the above-mentioned embodiment, aerial imagery can be used to quickly capture vegetation growth and soil characteristics over a large area. This data can reflect key ecological indicators such as vegetation coverage and health, as well as soil moisture and nutrient status, helping scientists fully understand the ecological health of the monitored area. Compared to traditional ground-based monitoring methods, aerial photography not only saves significant manpower and material resources but also reduces data bias caused by human interference, making ecological monitoring results more objective and reliable. Furthermore, by combining historical monitoring data, current monitoring scores can be compared with historical scores to determine the current trend of ecological status. This dynamic comparison method eliminates the need for isolated monitoring and integrates it into time series analysis, effectively identifying potential risks of ecological deterioration. For example, when the monitoring score falls below the historical monitoring score, an environmental monitoring alert is automatically triggered. This allows for timely response to environmental changes, ensuring the implementation of necessary management measures to prevent further desertification. Furthermore, by integrating soil and environmental data to calculate soil and environmental scores, desertification scores can be assessed. Soil and environmental factors are important factors influencing ecological health. By scientifically calculating these scores, a comprehensive understanding of the multiple factors influencing the ecology of the monitored area can be achieved. This multi-dimensional assessment not only identifies potential ecological problems but also provides more targeted interventions for environmental management. Finally, by comparing the scores with historical desertification scores, the current warning level for the monitored area can be determined. This mechanism ensures continuous monitoring and assessment of desertification risks, enabling monitors to promptly identify changes in the ecosystem and adjust management strategies accordingly.

[0091] In another preferred embodiment based on the above embodiment, Figure 2 As shown, this embodiment provides a desert ecological environment monitoring and early warning system, including: a first evaluation module, a central control module, a second evaluation module and an early warning module.

[0092] Specifically, the first evaluation module is configured to obtain aerial images of the monitored area, determine the vegetation index and soil spectral characteristics of the monitored area based on the aerial images, and assess the monitoring score of the monitored area based on the vegetation index and soil spectral characteristics. The central control module is electrically connected to the first evaluation module and is configured to obtain historical monitoring scores of the monitored area for adjacent time periods. Based on the relationship between the monitoring score and the historical monitoring scores, the central control module determines whether to conduct environmental monitoring of the monitored area. When the monitoring score is less than the historical monitoring score, the central control module conducts environmental monitoring of the monitored area. The second evaluation module is electrically connected to the central control module and is configured to obtain soil and environmental data of the monitored area, determine a soil score for the monitored area based on the soil data, determine an environmental score for the monitored area based on the environmental data, and determine a wasteland score for the monitored area based on the soil and environmental scores. The early warning module is also configured to obtain historical wasteland scores for the monitored area for adjacent time periods and determine the early warning level of the monitored area based on the difference between the wasteland score and the historical wasteland score.

[0093] It is understandable that the desert ecological environment monitoring and early warning method and system in the above-mentioned embodiments of the present invention have the same beneficial effects and will not be described in detail.

[0094] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0095] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0096] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0097] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A desert ecological environment monitoring and early warning method, characterized in that: include: Acquiring aerial images of the monitoring area, determining a vegetation index and soil spectral characteristics of the monitoring area based on the aerial images, and evaluating a monitoring score of the monitoring area based on the vegetation index and soil spectral characteristics; Obtain historical monitoring scores of the monitoring area during adjacent time periods, and determine whether to perform environmental monitoring on the monitoring area based on a relationship between the monitoring score and the historical monitoring scores, wherein: When the monitoring score is less than the historical monitoring score, environmental monitoring is performed on the monitoring area; Acquiring soil data and environmental data of the monitoring area, determining a soil score of the monitoring area based on the soil data, determining an environmental score of the monitoring area based on the environmental data, and determining a wasteland score of the monitoring area based on the soil score and the environmental score; Obtaining historical wasteland scores of the monitoring area during adjacent time periods, and determining a warning level for the monitoring area based on a wasteland score difference between the wasteland score and the historical wasteland score; Determining the soil score of the monitoring area based on the soil data includes: Obtaining a soil collection depth and a corresponding soil moisture in the soil data, and stratifying the soil according to the soil collection depth and the corresponding soil moisture; Obtaining the thickness of the surface soil layer in each of the soil layers, obtaining the historical soil layer thickness of the surface soil layer in adjacent time periods, and determining the soil score based on the relationship between the soil layer thickness and the historical soil layer thickness; When the soil layer thickness is less than or equal to the historical soil layer thickness, the soil score is determined to be Xmin; When the soil layer thickness is greater than the historical soil layer thickness, obtaining a thickness difference between the soil layer thickness and the historical soil layer thickness, and determining the soil score based on the thickness difference; Determining the soil score based on the thickness difference includes: determining the soil score according to a relationship between the thickness difference and a preconfigured first preset thickness difference and a second preset thickness difference; When the thickness difference is less than the first preset thickness difference, the soil score is determined to be X1; When the thickness difference is greater than or equal to the first preset thickness difference and the thickness difference is less than the second preset thickness difference, determining the soil score to be X2; When the thickness difference is greater than or equal to the second preset thickness difference, determining the soil score to be X3; The first preset thickness difference is smaller than the second preset thickness difference, and 0<Xmin<X1<X2<X3.

2. The desert ecological environment monitoring and early warning method according to claim 1, characterized in that: When evaluating the monitoring score of the monitoring area based on the vegetation index and soil spectral characteristics, it includes: Dividing the aerial image into a plurality of regions based on a preset distance R, obtaining a reflection frequency of a red light band and an infrared reflectivity of each region in the aerial image, and determining a vegetation index and soil reflectivity characteristic of each region based on the reflection frequency of the red light band and the infrared reflectivity; The vegetation health value of each of the regions is determined based on the vegetation index and soil reflectance characteristics of each of the regions, and the vegetation health value of each of the regions is substituted into Formula I to determine the monitoring score, wherein Formula I is as follows: Wherein, S is the monitoring score, n is the total number of the regions, Vi is the vegetation health value of the i-th region, and Wi is the weight of the i-th region.

3. The desert ecological environment monitoring and early warning method according to claim 1, characterized in that: When the soil score is determined to be Xi, i=1, 2, or 3, the method further includes: obtaining a soil particle size average of the surface soil and a collection volume of the collected surface soil, and determining a soil porosity value of the surface soil based on the soil particle size average and the collection volume; Obtaining historical soil porosity values ​​of surface soil in adjacent time periods, and determining whether to adjust the soil score Xi based on the relationship between the soil porosity value and the historical soil porosity value; When the soil porosity value is less than or equal to the historical soil porosity value, determining not to adjust the soil score Xi; When the soil porosity value is greater than the historical soil porosity value, an adjustment coefficient is determined according to the porosity value difference between the soil porosity value and the historical soil porosity value, and the soil score Xi is adjusted according to the adjustment coefficient.

4. The desert ecological environment monitoring and early warning method according to claim 3, characterized in that: When determining the adjustment coefficient based on the porosity difference between the soil porosity value and the historical soil porosity value, the adjustment coefficient includes: determining the adjustment coefficient according to a relationship between the pore value difference and a preconfigured first preset pore value difference and a second preset pore value difference; When the pore value difference is less than the first preset pore value difference, the adjustment coefficient is determined to be K1; When the pore value difference is greater than or equal to the first preset pore value difference, and the pore value difference is less than the second preset pore value difference, the adjustment coefficient is determined to be K2; When the pore value difference is greater than or equal to the second preset pore value difference, the adjustment coefficient is determined to be K3; The first preset pore value difference is smaller than the second preset pore value difference, and 1<K1<K2<K3.

5. The desert ecological environment monitoring and early warning method according to claim 4, characterized in that: Determining the environmental score of the monitoring area based on the environmental data includes: Obtaining the number of sandstorms, total precipitation, and average temperature values ​​in the monitoring area within a preset period, and determining the environmental score based on the relationship between the average temperature value and a preset temperature value; When the average temperature value is less than the preset temperature value, the environmental score is determined to be Jmin; When the average temperature value is greater than or equal to the preset temperature value, the number of sandstorms, the total precipitation, and the average temperature value are substituted into Formula II to determine the environmental score, wherein Formula II is as follows: Ji=z1×a+z2×d+z3×f; Wherein, Ji is the environmental score, i=1, 2, 3, a is the number of sandstorms, d is the total precipitation, f is the average temperature value, z1-z3 are weight coefficients, and the sum of z1-z3 is 1.

6. The desert ecological environment monitoring and early warning method according to claim 1, characterized in that: Determining the wasteland score of the monitored area based on the soil score and the environmental score includes: determining a correction coefficient based on a relationship between the environmental score and a first preset environmental score and a second preset environmental score, correcting the soil score based on the correction coefficient, and determining the corrected soil score as the wasteland score of the monitored area, wherein: when the environmental score is less than or equal to the first preset environmental score, determining the correction coefficient to be P1; When the environmental score is greater than the first preset environmental score, and the first preset environmental score is less than or equal to the second preset environmental score, determining the correction coefficient to be P2; When the environmental score is greater than the second preset environmental score, the correction coefficient is determined to be P3; The first preset environment score is smaller than the second preset environment score, and 1<P1<P2<P3.

7. The desert ecological environment monitoring and early warning method according to claim 1, characterized in that: When determining the early warning level of the monitoring area according to the difference between the wasteland score and the historical wasteland score, the method includes: pre-configuring a first preset wasteland score difference and a second preset wasteland score difference, and determining the early warning level of the monitoring area according to a relationship between the wasteland score difference and the first preset wasteland score difference and the second preset wasteland score difference; When the wasteland scoring difference is less than the first preset wasteland scoring difference, the warning level of the monitoring area is determined to be a low level; When the wasteland score difference is greater than or equal to the first preset wasteland score difference, and the wasteland score difference is less than the second preset wasteland score difference, the warning level of the monitoring area is determined to be medium; When the wasteland scoring difference is greater than or equal to the second preset wasteland scoring difference, the warning level of the monitoring area is determined to be high; The first preset wasteland score difference is smaller than the second preset wasteland score difference, and low level < medium level < high level.

8. A desert ecological environment monitoring and early warning system, adapted to execute a desert ecological environment monitoring and early warning method according to any one of claims 1 to 7, characterized in that: include: a first evaluation module, configured to obtain an aerial image of a monitoring area, determine a vegetation index and soil spectral characteristics of the monitoring area based on the aerial image, and evaluate a monitoring score of the monitoring area based on the vegetation index and soil spectral characteristics; a central control module electrically connected to the first evaluation module, the central control module being configured to obtain historical monitoring scores of the monitoring area during adjacent time periods, and determine whether to perform environmental monitoring on the monitoring area based on a relationship between the monitoring score and the historical monitoring score, wherein: when the monitoring score is less than the historical monitoring score, the central control module performs environmental monitoring on the monitoring area; a second evaluation module electrically connected to the central control module, the second evaluation module being configured to obtain soil data and environmental data of the monitored area, determine a soil score of the monitored area based on the soil data, determine an environmental score of the monitored area based on the environmental data, and determine a wasteland score of the monitored area based on the soil score and the environmental score; The early warning module and the second evaluation module are used to obtain the historical wasteland scores of the monitoring area in adjacent time periods, and determine the early warning level of the monitoring area based on the wasteland score difference between the wasteland score and the historical wasteland score.

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