Automatic simple maintenance method and system for re-greening of drought valley side slope

Abstract

The application belongs to the field of green land maintenance, and provides a dry valley slope re-greening automatic simple maintenance method and system, which comprises the following steps: collecting soil data and historical meteorological data of a re-greening area before re-greening of the dry valley slope; selecting a first plant suitable for re-greening according to the soil data and the meteorological data, and uniformly laying the first plant on the slope in different dimensions; taking a first image of the first plant by a camera; judging a water shortage degree of the first plant according to the first image, and supplementing water to the first plant according to the water shortage degree; judging a fertilizer deficiency degree of the first plant according to the first image, and fertilizing the first plant according to the fertilizer deficiency degree. The above scheme can efficiently perform dry valley slope re-greening automatic simple maintenance.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of green land maintenance, and specifically relates to an automatic and simple maintenance method and system for dry valley slope re-greening. BACKGROUND

[0002] With global warming, desertification intensification and the continuous impact of human activities on the ecological environment, the ecosystems in many regions have been severely damaged, especially in dry valley and steep slope environments. Due to the dry climate, poor soil and lack of water resources, the vegetation coverage rate is decreasing and the soil erosion is serious, leading to further deterioration of the ecological balance. In this context, how to implement effective re-greening and ecological restoration in these special environments has become a global challenge.

[0003] Traditional slope re-greening techniques rely on artificial vegetation restoration, but due to the harsh climate and soil conditions of dry valley slopes, traditional re-greening methods have various limitations. First, the soil structure of the slope is loose, and water is easily lost, making it difficult for plants to survive and grow slowly. Second, artificial irrigation and fertilization require a lot of manpower and resources, and due to unstable climate conditions, artificial intervention cannot respond to the water and nutrient needs of plants in real time. In addition, due to the drought-tolerant and poor-tolerant characteristics of plants in these environments, it is particularly important to scientifically select plant species suitable for the local environment. Therefore, how to achieve effective, water-saving and automated re-greening technology in the dry valley slope environment has become a problem to be solved.

[0004] In the prior art, some automated irrigation and fertilization systems have been applied in the agricultural field, but these systems are often designed based on conventional humid climate environments and cannot effectively respond to the special needs of dry valley slope environments. For example, although the existing drip irrigation system can save water resources, it usually requires frequent human intervention, and it is difficult to achieve precise and real-time water replenishment in slope re-greening. Existing monitoring systems also rely on regular manual observation and cannot meet the needs of automated monitoring. SUMMARY

[0005] To solve the problems in the prior art, the present application provides an automatic and simple maintenance method for dry valley slope re-greening, which comprises the following steps:

[0006] Before the dry valley slope re-greening, collect soil data and historical meteorological data of the re-greening area;

[0007] According to the soil data and meteorological data, select a first plant suitable for re-greening, and uniformly lay the first plant on the slope in different dimensions;

[0008] Take a first image of the first plant by a camera;

[0009] According to the first image, the water shortage degree of the first plant is determined, and the first plant is watered according to the water shortage degree.

[0010] According to the first image, the fertilizer deficiency degree of the first plant is determined, and the first plant is fertilized according to the fertilizer deficiency degree.

[0011] Another aspect of the present application also provides an automatic simple maintenance system for re-greening of a dry valley slope, which comprises the following modules:

[0012] The acquisition module is used to collect soil data and historical meteorological data of the re-greening area before the re-greening of the dry valley slope;

[0013] The planting module is used to select the first plant suitable for re-greening according to the soil data and meteorological data, and uniformly lay the first plant on the slope in different dimensions;

[0014] The image module is used to shoot the first image of the first plant through a camera;

[0015] The watering module is used to determine the water shortage degree of the first plant according to the first image, and to water the first plant according to the water shortage degree;

[0016] The fertilization module is used to determine the fertilizer deficiency degree of the first plant according to the first image, and to fertilize the first plant according to the fertilizer deficiency degree.

[0017] The above technical solution has the following specific beneficial effects:

[0018] The present application can automatically determine the water shortage and fertilizer deficiency degree of the plant by installing a camera and a sensor to monitor the growth state of the plant, soil humidity and meteorological data in real time, and timely trigger the irrigation and fertilization system, thereby reducing the frequency of manual intervention and realizing intelligent management of the slope re-greening process.

[0019] The present application uses precise drip irrigation, sprinkler irrigation or underground seepage irrigation system to water according to the actual water shortage degree of the plant, thereby avoiding water resource waste in the traditional irrigation mode, significantly improving water utilization rate, and being particularly suitable for dry and water resource scarce environments.

[0020] Through real-time monitoring and automatic maintenance measures for drought-tolerant plants such as cushion stonecrop, precise irrigation and fertilization can be carried out according to the actual growth state of the plant, which greatly improves the survival rate and growth efficiency of the plant and guarantees the long-term effect of re-greening.

[0021] The present application realizes real-time monitoring and automatic irrigation and fertilization through an automatic system, which not only reduces the workload of manual patrol and maintenance, but also reduces the uncertainty of manual operation, reduces the labor input and maintenance cost.

[0022] The present application realizes real-time monitoring and automatic irrigation and fertilization functions by using an automated system. The system can not only develop routine maintenance processes and strategies according to preset standards, but also dynamically monitor according to weather fluctuations and specific scenarios. The data obtained by monitoring is fed back to the maintenance module in real time, triggering automatic irrigation and fertilization operations, and then dynamically adjusting and optimizing the maintenance processes and strategies. This process continues to iterate, effectively reducing the consumption of human resources and maintenance costs.

[0023] In summary, the present application can efficiently and resource-savingly realize the greening maintenance of the drought valley slope, and provides an ecological restoration solution suitable for extreme environments. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0025] Figure 1 is a flowchart of the method of the present application. DETAILED DESCRIPTION

[0026] Next, the preferred description of the present application will be made in combination with the drawings and specific embodiments.

[0027] The present embodiment solves the above problems by the following steps:

[0028] In one embodiment, referring to Figure 1 The present application provides an automatic and simple maintenance method for the greening of the drought valley slope. The method can realize long-term and efficient maintenance and management of the greening area of the slope according to the special ecological environment of the drought valley slope by intelligent monitoring and automatic maintenance equipment. Specifically, the method comprises the following steps:

[0029] Before the greening of the drought valley slope, the soil data and historical meteorological data of the greening area are collected.

[0030] Before the implementation of the re-greening of the dry valley slope, a comprehensive data collection of the re-greening area is required, including but not limited to soil data and historical meteorological data. The soil data includes information such as soil aggregate structure, pH value, water content, and soil nutrient fertility status, which are used to evaluate the soil's water retention capacity, nutrient content, and conditions suitable for plant growth. The historical meteorological data includes information such as rainfall, temperature, wind speed, evaporation, and drought cycle in the region. By analyzing these meteorological data, the climatic characteristics of the slope area can be obtained, providing data support for subsequent plant species selection, irrigation cycle, and fertilization plan, ensuring that the re-greening process can adapt to the local ecological environment conditions and achieve scientific and efficient slope re-greening.

[0031] According to the soil data and meteorological data, a first plant suitable for re-greening is selected and uniformly laid on the slope in different dimensions, such as the upper, middle, and lower parts of the slope.

[0032] According to the analysis results of the soil data and meteorological data, a first plant suitable for re-greening in the ecological environment of the dry valley slope is selected. The first plant is preferably a plant species with drought tolerance, poor tolerance, and developed root system to improve the ecological stability and soil and water conservation capacity of the slope. Specifically, the first plant that can be selected includes but is not limited to Selaginella pulvinata, Tamarix or Calligonum, etc. These plants can still maintain strong survival ability and growth rate in extreme drought and poor soil conditions, and have the characteristics of tolerating long-term drought and poor soil.

[0033] In the process of re-greening the slope, the first plant is uniformly distributed in different dimensions of the slope, including the upper, middle, and lower parts of the slope, to ensure that the plant coverage is extensive and fully plays its ecological function in different terrain conditions. For example, in the upper part of the slope, due to the large slope, thin soil, and fast water loss, Selaginella pulvinata with stronger drought tolerance and shallower root system can be planted first to reduce water and soil loss; in the middle part of the slope, the soil condition is relatively good and the water is slightly more, so Calligonum with deeper root system and strong soil improvement ability can be selected to enhance the soil fixation capacity of the middle part; in the lower part of the slope, the water is relatively abundant but is prone to waterlogging, so Tamarix with strong water tolerance and flood resistance can be planted to prevent waterlogging in local areas and ensure the effect of soil and water conservation.

[0034] By uniformly laying the first plant in different dimensions of the slope, the ecological conditions of different positions of the slope can be effectively adapted, ensuring the balance and integrity of the re-greening work, and through the distribution and growth characteristics of the plant roots, the purpose of improving the ecological re-greening effect of the slope, reducing water and soil loss, and enhancing the stability of the slope can be achieved.

[0035] For example, take the cushion-like Selaginella as an example. In actual operation, the cushion-like Selaginella is evenly laid along the upper part of the slope. Through its good coverage and rapid recovery ability, it ensures that the plants can still survive and play an ecological role even during long-term drought. For example, the cushion-like Selaginella is planted at an interval of 5 meters, and an ecological blanket or other water-retaining materials are laid to assist in maintaining soil moisture, further enhancing the stability of the vegetation.

[0036] A first image of the first plant is captured by a camera.

[0037] Through cameras installed at different positions on the slope of the arid valley, the growth images of the first plant are automatically collected. The specific steps include: setting the cameras to monitor different areas of the slope to ensure comprehensive monitoring of the growth conditions of the plants in each area. The cameras capture the growth of the first plants such as cushion-like Selaginella, Calligonum, and Tamarix through timed or real-time shooting, obtain image data at different time points, and generate the first image.

[0038] The first image is mainly used to reflect key ecological parameters such as the color, size, leaf curling degree, and overall coverage rate of the plants. For example, when shooting the cushion-like Selaginella, the camera will capture the change in leaf color. The transition from dark green to light yellow can reflect the change in soil moisture, and then determine whether irrigation is needed in this area. Similarly, the image of Calligonum can be used to monitor whether its root system is well developed and whether its overall growth height meets the set standard. For Tamarix, image data will be used to monitor whether its leaves show wilting or other physiological stress reactions to assess whether the water accumulation or soil conditions of the lower slope are suitable for plant growth.

[0039] During image acquisition, the camera can adjust the shooting frequency according to the growth cycle of different plants and environmental changes. For example, during the dry season, the camera can increase the shooting frequency and shoot multiple times a day to track the growth status of the first plant in real time. During the rainy season or periods of stable climate, the shooting frequency can be appropriately reduced. The collected first images are transmitted to the data processing module through wireless transmission or memory card. The system compares and analyzes the first images with the preset normal plant growth pattern.

[0040] According to the first image, the degree of water shortage of the first plant is determined, and the first plant is watered according to the degree of water shortage.

[0041] Through the camera installed on the slope of the arid valley, leaf images at the same position at different time points are captured regularly, forming a sequence of leaf images. These images reflect the growth and state changes of plant leaves over a period of time. The preprocessing steps include:

[0042] Image alignment: Due to the slight changes in camera angle or plant leaf position over time, the image sequence needs to be aligned first (e.g., using image registration algorithms) to ensure that the same leaf region is in the same position in different images.

[0043] De-noising: Remove noise in the image through algorithms such as Gaussian filtering to reduce environmental factors that interfere with leaf detection.

[0044] In each image, the leaf region is segmented to accurately identify the leaf contour. Specifically, the present application segments the leaf region by color-based threshold segmentation (green).

[0045] For each segmented leaf region in each image, its area is calculated. The actual area of the leaf can be estimated using the pixel count method. Assuming the image resolution is known, the leaf area A i (unit: square millimeter or other units) can be calculated by the following formula:

[0046] A i = N p × r 2

[0047] where N p is the number of pixels in the leaf region, and r is the actual length unit represented by each pixel.

[0048] Calculate the average area of multiple leaves

[0049]

[0050] where

[0051] A avg represents the average value of the area of the leaves, A1, A2, …, A n are the areas of each leaf, and n is the total number of leaves.

[0052] By comparing the area changes of the leaves at the same location at different time points, the degree of leaf curling is identified. Generally, leaves will gradually curl in a water-deficient state, resulting in a smaller projected area. Define the change rate of leaf area

[0053]

[0054] where A avgt represents the average area of the leaf at time t, and A avg0 is the leaf area at the initial time point. According to the size of R, the degree of leaf curling can be determined:

[0055] When R≥1, it means that the leaf has no significant curling, and the plant is in a healthy state.

[0056] When 0.7 ≤ R < 1, it indicates that the leaves start to curl, and the plant may be in a mild water deficit state.

[0057] When 0.4 ≤ R < 0.7, it indicates that the leaves are moderately curled, and the plant is in a moderate water deficit state.

[0058] When R < 0.4, it indicates that the leaves are severely curled, and the plant is in a severe water deficit state.

[0059] Combined with the degree of leaf curling, the water deficit state of the plant is determined, and classified according to the degree of water deficit:

[0060] Healthy state: The leaves are not significantly curled, and the water deficit is relatively light, and no water needs to be added.

[0061] Mild water deficit: The leaves are slightly curled, and appropriate water needs to be added.

[0062] Moderate water deficit: The leaves are moderately curled, and the amount of water needs to be increased.

[0063] Severe water deficit: The leaves are severely curled, and emergency water needs to be added, and the amount and frequency of water should be significantly increased.

[0064] According to the degree of water deficit, the system automatically triggers different water supplement strategies:

[0065] Mild water deficit: Implement appropriate irrigation to keep the soil moist.

[0066] Moderate water deficit: Increase the amount of water and irrigation frequency.

[0067] Severe water deficit: Take emergency water supplement measures, add water in small amounts and multiple times to ensure that water gradually penetrates deep into the soil, preventing further curling of the leaves.

[0068] Once it is determined that the plant needs water, the system will automatically trigger the irrigation equipment to perform the water supplement operation. The automatic irrigation equipment includes the following forms:

[0069] a. Drip irrigation system

[0070] Drip irrigation is a precise water-saving irrigation technology that directly delivers water to the roots of plants through drip irrigation pipes installed at different positions on the slope. The drip irrigation system is characterized by high water use efficiency and can accurately control the amount of water according to the water deficit of the plant. The system controls the opening and closing of the water flow through electromagnetic valves. According to the sensor data, the amount of water is calculated, and the drip irrigation speed is adjusted.

[0071] b. Sprinkler irrigation system

[0072] Sprinkler systems distribute water evenly across the plant surface by arranging sprinklers on the slope. It is suitable for large-area slope greening. When the plant is detected to be curled or the soil moisture is low, the sprinkler system starts to spray an appropriate amount of water. By adjusting the spray radius and angle of the sprinkler, it can ensure that the water covers the entire plant area.

[0073] c. Subsurface Drip Irrigation System

[0074] Subsurface drip irrigation systems use buried pipes to deliver water to plant roots. This system can avoid water evaporation loss and keep the soil deep moist. According to the feedback of soil moisture sensors, the subsurface drip irrigation system will start when the soil water content is too low, and accurately supplement water. The amount of water in the drip irrigation pipe is adjusted by the flow control device in the system.

[0075] According to the first image, determine the degree of lack of fertilizer of the first plant, and fertilize the first plant according to the degree of lack of fertilizer.

[0076] Periodically take images of the first plant through cameras or other image acquisition devices. To ensure accurate analysis, the image needs to be pre-processed first:

[0077] De-noising: Use a Gaussian filter to de-noise the image to reduce noise interference in the environment.

[0078] Image alignment: Align images at different time points through image registration algorithms (such as feature point-based registration) to ensure consistent growth calculation of the same plant.

[0079] Background segmentation: Use semantic segmentation models (such as U-Net or Mask R-CNN) to segment the plant area from the background, ensuring that the analysis area only contains cushioned pteridium.

[0080] Use image processing algorithms to extract plant growth parameters from pre-processed images, including height, leaf number, and leaf area. The specific steps are as follows:

[0081] a. Plant height monitoring

[0082] The height of the first plant, such as cushioned pteridium, is one of the important indicators for judging the growth amount. The height of the cushioned pteridium is measured by the vertical size of the image, and the specific steps are as follows:

[0083] Edge detection: Use Canny edge detection algorithm to identify the outline of the plant.

[0084] Height calculation: Calculate the height of the plant by calculating the difference between the vertical coordinates of the top and bottom of the plant.

[0085] b. Leaf number monitoring

[0086] Leaf number is another important growth monitoring indicator. The specific steps are as follows:

[0087] Leaf region segmentation: Use semantic segmentation algorithm to separate each leaf from the whole plant.

[0088] Leaf counting: Calculate the number of segmented leaves in the image through contour analysis algorithm (such as findContours function in OpenCV), and get the leaf number.

[0089] c. Leaf area monitoring

[0090] The growth of leaf area is also an important indicator of plant growth. Leaf area can be measured by the following steps:

[0091] Leaf region segmentation: Use semantic segmentation model to separate the area of each leaf.

[0092] Area calculation: Calculate the average area of the leaf by counting the number of pixels in the leaf area and combining the image resolution. The specific algorithm can refer to the previous steps of the invention.

[0093] d. Monitoring of total growth

[0094] According to the measured plant height, leaf number and leaf area, etc. Parameters, combined with weight calculation of the comprehensive growth of the mat-shaped Selaginella uncinata:

[0095] G total = w1 × H + w2 × N leaf + w3 × A total

[0096] Where:

[0097] G total is the comprehensive growth, H is the plant height, N leaf is the number of leaves, A total is the total area of all leaves.

[0098] w1, w2, w3 are weight coefficients, which can be adjusted according to specific needs (such as manual adjustment according to actual measurement data during monitoring).

[0099] By comparing the growth G total at different times, the growth trend of Selaginella uncinata can be determined:

[0100] ΔG = G total (t2) - G total (t1)

[0101] Where: G total (t1) is the comprehensive growth at the previous time, G total(t2) is the current comprehensive growth amount, and AG is the growth amount increment. If AG is less than a preset normal growth threshold, the system judges that the growth is slow, and fertilization may be needed.

[0102] When it is judged that fertilization is needed, the fertilization amount is calculated according to the growth amount deficiency degree AG and the coverage area A of the first plants. plant The fertilization amount is calculated as follows:

[0103]

[0104] wherein Q is the fertilization amount, A is the coverage area of the first plants, G is the normal growth threshold, K is the fertilization coefficient, and G is the growth amount. fertilizer plant threshold fertilizer

[0105] Through the above algorithm, the system can accurately monitor the growth amount of the Selaginella martensii and automatically judge whether fertilization is needed according to the growth amount change, so as to ensure the normal growth of the plants in the arid valley slope environment.

[0106] On the other hand, the present application also provides an automatic and simple maintenance system for re-greening of an arid valley slope, comprising:

[0107] An acquisition module is configured to collect soil data and historical meteorological data of a re-greening area before re-greening of the arid valley slope.

[0108] A planting module is configured to select a first plant suitable for re-greening according to the soil data and the meteorological data, and to uniformly lay the first plant on the slope in different dimensions.

[0109] An image module is configured to capture a first image of the first plant by using a camera.

[0110] A water supplementing module is configured to judge a water deficiency degree of the first plant according to the first image, and to supplement water to the first plant according to the water deficiency degree.

[0111] A fertilization module is configured to judge a fertilizer deficiency degree of the first plant according to the first image, and to fertilize the first plant according to the fertilizer deficiency degree.

[0112] The modules not specifically described in the present application are subject to the contents described in the prior art. The prior art mentioned in the foregoing background section and the specific embodiment section of the present application can be used as a part of the present application to understand the meanings of some technical features or parameters.​​​​

Claims

1. A kind of automatic simple maintenance method of drought valley side slope greening, it is characterized in that, The method comprises the following steps: Before the slope of the arid valley is greened, collecting soil data and historical meteorological data of the greening area; According to the soil data and historical meteorological data, selecting a first plant suitable for greening, and uniformly laying the first plant on the slope in different dimensions of upper, middle and lower; Taking a first image of the first plant by a camera; According to the first image, judging the water shortage degree of the first plant, and supplementing water to the first plant according to the water shortage degree; According to the first image, judging the fertilizer deficiency degree of the first plant, and fertilizing the first plant according to the fertilizer deficiency degree; The fertilizing of the first plant according to the fertilizer deficiency degree comprises: When it is judged that fertilization is needed, the amount of fertilization is calculated based on the increment of the growth amount and the coverage area of the plant ， wherein: is the amount of fertilizer, is the area of coverage of the plant, is the threshold for normal growth, is the fertilizer coefficient, set based on the plant species and soil fertility, , is the integrated growth amount of the previous time, is the integrated growth amount of the current time.

2. The automatic simple maintenance method for reviving the slope of the dry valley according to claim 1, characterized in that, The first plant is a cushion-like Selaginella.

3. The automatic simple maintenance method for reviving the slope of the dry valley according to claim 1, characterized in that, The judging of the water shortage degree of the first plant according to the first image comprises: Taking leaf images at the same position at different time points by a camera installed on the slope of the arid valley to form an image sequence of the leaves; Aligning the image sequence to ensure that the positions of the same leaf area in different images are consistent; Removing noise in the image by a Gaussian filtering algorithm; Segmenting the leaf area in each image to accurately identify the leaf contour; Using the pixel counting method to calculate the average actual area of the leaf; By comparing the area changes of the leaves at the same position at different time points, the curling degree of the leaves is identified, and the water shortage degree is judged according to the curling degree.

4. The automatic simple maintenance method for reviving the slope of the dry valley according to claim 1, characterized in that, The judging of the fertilizer deficiency degree of the first plant according to the first image comprises: Periodically taking images of the first plant by an image acquisition device; Pretreating the image; Using an image processing algorithm to extract the growth parameters of the plant from the pretreated image, including height, leaf number and leaf area; According to the measured plant height, leaf number and leaf area parameters, the comprehensive growth of the first plant is calculated by combining the weight; By comparing the growth at different periods, the growth trend of the first plant is judged, and the fertilizer deficiency degree is judged according to the growth trend.

5. A kind of automatic simple maintenance system of dry river valley side slope re-greening, it is characterized in that, The system comprises the following modules: An acquisition module for collecting soil data and historical meteorological data of the greening area before the slope of the arid valley is greened; A planting module for selecting a first plant suitable for greening according to the soil data and meteorological data, and uniformly laying the first plant on the slope in different dimensions of upper, middle and lower; An image module for taking a first image of the first plant by a camera; A water supplementing module for judging the water shortage degree of the first plant according to the first image, and supplementing water to the first plant according to the water shortage degree; A fertilizing module for judging the fertilizer deficiency degree of the first plant according to the first image, and fertilizing the first plant according to the fertilizer deficiency degree; The fertilizing of the first plant according to the fertilizer deficiency degree comprises: When it is judged that fertilization is needed, the amount of fertilization is calculated based on the increment of the growth amount and the coverage area ​ ， wherein: is the amount of fertilizer, is the area of coverage of the plant, is the threshold for normal growth, is the fertilizer coefficient, set based on the plant species and soil fertility, , is the integrated growth amount of the previous time, is the integrated growth amount of the current time.

6. The automatic simple maintenance system for reviving the slope of the dry valley according to claim 5, characterized in that, The first plant is a cushion-like Selaginella.

7. The automatic simple maintenance system for reviving the slope of the dry valley according to claim 5, characterized in that, The judging of the water shortage degree of the first plant according to the first image comprises: Taking leaf images at the same position at different time points by a camera installed on the slope of the arid valley to form an image sequence of the leaves; Aligning the image sequence to ensure that the positions of the same leaf area in different images are consistent; The noise in the image is removed by a Gaussian filter algorithm; In each image, the leaf area is segmented to accurately identify the leaf outline; The average actual area of the leaf is calculated using a pixel counting method; By comparing the area changes of the leaf at the same position at different time points, the degree of leaf curling is identified.

8. The automatic simple maintenance system for reviving the slope of the dry valley according to claim 5, characterized in that, The method comprises the following steps: Periodically capturing images of the first plant by an image acquisition device; Preprocessing the images; Using image processing algorithms to extract plant growth parameters, including height, leaf number, and leaf area, from the preprocessed images; Calculating the comprehensive growth of the first plant based on the measured plant height, leaf number, and leaf area parameters, combined with weights; By comparing the growth at different periods, the growth trend of the first plant is determined.

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