A remote telemetry collection system and method for land management

Abstract

The present application belongs to the technical field of land information collection, and discloses a remote telemetry collection system and method for land management, the method comprising: a fixed-point sampling mechanism collects soil parameter information at a fixed point; a random sampling point planning module arranges sampling points; a route planning module plans the flight route; a random sampling mechanism collects soil information according to the planned route; an image acquisition module collects images of the land; an image preprocessing module preprocesses the collected images; an anomaly detection module identifies and analyzes the image after feature extraction; when an abnormality in the soil is detected and sampling and analysis is required, soil samples are collected by a sampling mechanism to facilitate subsequent analysis and processing. The present invention combines fixed-point and random monitoring to remotely monitor land parameters in all directions; soil samples are collected by a sampling mechanism; a box can be placed to place multiple sampling tubes, soil samples at multiple locations can be continuously collected, and the samples can be automatically sealed.

Description

Technical Field

[0001] The present application relates to the technical field of land information collection, and more specifically, to a remote telemetry collection system and method for land management. Background Art

[0002] The invasion of mining or industrial waste or agricultural chemicals deteriorates the original physical and chemical properties of the soil, reduces the land production potential, deteriorates product quality and causes harm to humans, animals and plants. In the process of land management, land data needs to be collected. The collection system can analyze and collect land information.

[0003] The document with the prior art publication number CN114296367A provides a remote telemetry collection device for land management, including several land information collection boxes installed on the managed land and using solar power generation, a drone system, a remote server, and a wireless charging device that enables the land information collection boxes and the drone system to supply power to each other; the land information collection box obtains its own remaining capacity data, i.e., first capacity data, in real time during the land data collection, and sends the first capacity data to the remote server. The invention can collect land information at multiple points by setting several land information collection boxes in the managed land and connect and communicate with the remote server through a wireless communication base station. In this process, drones are used to patrol and inspect the land information collection boxes and the managed land, and the stable operation of the entire collection device is guaranteed by combining solar power generation technology and wireless charging technology.

[0004] Although the above-mentioned prior art solutions can achieve relevant beneficial effects through the structure of the prior art, they still have the following defects: 1. It is impossible to collect information and conduct random inspections of land in a timely manner. 2. It is impossible to find abnormal conditions of the land in a timely manner; 3. When abnormal conditions of the soil are detected, it is impossible to collect soil samples in a timely manner, and special personnel are required to go to the site for sampling, which wastes manpower and material resources.

[0005] In view of this, we propose a remote telemetry collection system and method for land management. Summary of the invention

[0006] 1. Technical problems to be solved

[0007] 1. The purpose of this application is to provide a remote telemetry collection system and method for land management, which solves the technical problems raised in the above background technology, and realizes remote monitoring of land parameters in an all-round way through a combination of fixed-point and random monitoring; when abnormal conditions in the land are detected, soil samples can be collected through a sampling mechanism; multiple sampling tubes can be placed in a sampling tube placement box, and soil samples at multiple locations can be collected continuously. The sealing plug can be sealed to the sampling tube through a propulsion mechanism, a switching component and a sealing plug placement box, and the sample can be sealed to ensure the technical effect of the sample being intact.

[0008] 2. Technical solution

[0009] The technical solution of this application provides a remote telemetry collection system for land management, including:

[0010] Data collection module: collect a large amount of data information about the relevant land, including maps, the shape, size, purpose and nature of use of the land, etc., and mark the land information of each location on the map in detail as labels; collect a large number of photos of the land, including normal pictures and abnormal pictures, and mark them as reference samples.

[0011] Fixed-point sampling mechanism: including soil parameter sensors, which are fixedly arranged at different locations on the land to collect soil parameter information at fixed points. These sensors can work stably for a long time, collect soil parameter information at fixed points, and provide accurate soil data.

[0012] Random sampling mechanism: including drones, soil parameter collection mechanism and sampling mechanism; drones are used to fly to different sampling points to collect soil information; multi-parameter soil detector: collects soil information and multiple soil parameters; when abnormal soil conditions are detected and sampling and analysis is required, the sampling mechanism is activated to collect soil samples for subsequent analysis and processing;

[0013] Random sampling point planning module: According to the land label map, the sampling points for soil information sampling are arranged. The sampling points need to be arranged evenly and cover all the land that needs to be sampled to ensure the comprehensiveness and representativeness of the data.

[0014] Route planning module: Based on the land label map and multiple preset soil information sampling points, the flight route of the drone is planned to make the total flight distance of the drone the shortest, so as to improve work efficiency.

[0015] Image acquisition module: including a high-definition camera to collect high-definition images of the land;

[0016] Image preprocessing module: preprocess the collected images; including denoising, enhancement and other operations to improve the accuracy of subsequent analysis. The enhancement operation can highlight the important features in the image, making these features easier to capture by the subsequent analysis algorithm. Contrast enhancement can increase the contrast between different areas in the image, making the edges, textures and other features in the image more obvious; sharpening operations can enhance the details of the image, making the target objects in the image more prominent.

[0017] Feature extraction module: extracts features from the preprocessed image. The extracted features include color, texture, shape and other features;

[0018] Abnormal detection module: Identify and analyze the image after feature extraction; timely discover abnormal conditions on the land, including illegal occupation of land, illegal construction, destruction of cultivated land, soil pollution, etc. At the same time, according to the soil parameter monitoring results of fixed-point sampling agencies and random sampling agencies, timely identify abnormal soil parameters;

[0019] Remote control center: including remote controller, display screen and wireless signal transmission system;

[0020] PLC control module: connected to the UAV, soil parameter collection mechanism, sampling mechanism and remote control center network through wireless signals.

[0021] As an optional solution of the present invention, the features extracted by the feature extraction module include color, texture, shape, etc.;

[0022] Color features: Color is one of the most intuitive and significant features in an image. In land management, color features can be used to distinguish different types of land cover (such as vegetation, water bodies, buildings, etc.). Commonly used color feature extraction methods include color histogram, color moment, color set, etc. These methods can capture the distribution and statistical information of different color components in an image.

[0023] Texture features: Texture features describe the pattern or structure of a local area in an image, and are usually related to the surface characteristics of an object. In land management, texture features can be used to identify soil type, land conditions (such as cultivated, barren, etc.) or vegetation density. Commonly used texture feature extraction methods include gray level co-occurrence matrix (GLCM), autoregressive model, wavelet transform, etc. These methods can capture the pixel relationship or frequency distribution information of a local area in an image.

[0024] Shape features: Shape features describe the boundary or regional shape of objects in an image. In land management, shape features can be used to identify specific types of objects (such as buildings, roads, lakes, etc.) or detect abnormal areas on the land (such as illegal buildings, damaged farmland, etc.). Commonly used shape feature extraction methods include boundary feature methods (such as Fourier descriptors, chain codes, etc.) and regional feature methods (such as moment features, geometric features, etc.). These methods can capture the boundary contours of objects in an image or the structural information inside a region.

[0025] As an optional solution of the present invention, the anomaly detection module plays an important role in land management, and can detect abnormal conditions on the land in a timely manner, providing strong support for land management. With the continuous development of technology, the accuracy and efficiency of the anomaly detection module will be further improved, bringing more convenience and benefits to land management.

[0026] The anomaly detection module combines advanced algorithms and models to identify and analyze anomalies in images. It includes:

[0027] Model training unit: The model training unit uses machine learning algorithms (such as support vector machines (SVMs), random forests, etc.) or deep learning models to train a classification or detection model from known normal land images. This model can learn and recognize the features of normal land images, which may include color, texture, shape, etc., which together define the appearance and state of normal land. During the training process, the model will continuously learn and adjust its parameters to minimize prediction errors and improve classification or detection accuracy. After training, the model has the ability to recognize normal land images and can be used for subsequent anomaly detection tasks.

[0028] Anomaly Detection Unit: The anomaly detection unit compares the newly input image with the trained model to determine whether there are any anomalies. When a new image is input, the anomaly detection module first extracts the key features of the image and then matches these features with the trained model. If the features of the input image are significantly different from those of the normal model, that is, they exceed the threshold range that the model can tolerate, then the image is marked as anomaly. This means that the image may contain anomalies such as illegal occupation of land, destruction of arable land, and soil pollution.

[0029] Identifying illegally occupied land: By comparing land features such as color, texture, and shape, the anomaly detection module can identify illegally occupied land. For example, a new building or road may change the color and texture features of the land.

[0030] Identifying damaged farmland: When farmland is damaged, its characteristics such as color, texture, and shape may change. The anomaly detection module can capture these changes and identify damaged farmland.

[0031] Identifying soil contamination: Soil contamination may cause abnormal soil color or changes in soil structure. The anomaly detection module can identify soil contamination by analyzing the color and texture characteristics of the soil.

[0032] Model optimization: By continuously collecting new data and adjusting model parameters, the performance of the model can be optimized to improve the accuracy and efficiency of anomaly detection. For images marked as abnormal by the model, manual verification can be performed to ensure the accuracy of the detection results. At the same time, manual verification can also provide feedback for model optimization.

[0033] As an optional solution of the present invention, the route planning module operation includes the following steps:

[0034] Data input: includes a labeled map of the land, which is usually a detailed map containing geographic coordinates, land type (such as forest land, cultivated land, water area, etc.), terrain (such as plains, mountains, hills, etc.), and possible obstacles (such as buildings, trees, etc.).

[0035] Soil information sampling points: multiple preset points, indicating the locations where the drone needs to perform soil information sampling.

[0036] Path planning algorithm: Path planning algorithms including Dijkstra algorithm are used to find the shortest path from the starting point to the end point (or a series of points) while taking into account factors such as terrain and obstacles.

[0037] Flight route optimization: After finding a preliminary path, the route planning module may also need to optimize it. This includes considering the flight characteristics of the drone (such as maximum flight speed, maximum climb / descent angle, endurance, etc.), as well as environmental factors during the flight (such as wind direction, wind speed, etc.). Optimization may involve adjusting parameters such as flight altitude, speed, and steering angle to ensure that the drone can complete the sampling mission efficiently and safely.

[0038] Generate flight instructions: Once the flight route is determined and optimized, the route planning module will generate detailed flight instructions, including take-off point, landing point, flight altitude, speed, turning point, etc. These instructions will be passed to the UAV's flight control system to guide the UAV to fly and sample according to the planned route.

[0039] Real-time monitoring and adjustment: During the flight of the drone, the route planning module may need to communicate with the drone’s flight control system in real time to monitor the drone’s position and status.

[0040] If unexpected situations occur (such as obstacles, weather changes, etc.), the route planning module may need to recalculate the flight route and generate new flight instructions to ensure that the drone can safely complete the sampling mission.

[0041] As an optional solution of the present invention, the random sampling mechanism includes: a drone, a soil parameter collection mechanism and a sampling mechanism;

[0042] A soil parameter collection mechanism is fixedly arranged at the lower end of the drone, and the soil parameter collection mechanism is used to collect soil parameters;

[0043] A sampling mechanism is fixedly arranged on the drone; the sampling mechanism is used to sample the soil;

[0044] The soil parameter collection mechanism includes a motor A, a shaft rod, an electric push rod A and a multi-parameter soil detector;

[0045] A motor A is fixedly arranged on the drone, and a shaft rod is coaxially fixedly arranged on the output end of the motor A; an electric push rod A is fixedly arranged on the shaft rod; a multi-parameter soil detector is fixedly arranged on the movable rod of the electric push rod A; an inclinometer is fixedly arranged on the electric push rod A for monitoring the angle of the electric push rod A.

[0046] Through the above technical solution, the starting motor A drives the electric push rod A and the multi-parameter soil detector to rotate, and the electric push rod A drives the multi-parameter soil detector to move, so that the multi-parameter soil detector is inserted into the soil to collect parameters.

[0047] As an optional solution of the present invention, the sampling mechanism includes a sampling tube placement box, a sealing plug placement box, a propulsion mechanism, a switching assembly, a transposition drive mechanism and a sampling tube;

[0048] A sampling tube placement box is detachably fixed at the lower end of the drone; a plurality of sampling tubes are slidably and evenly arranged in the sampling tube placement box; two adjacent sampling tubes are arranged in contact;

[0049] A sealing plug placement box is detachably fixedly arranged on the sampling tube placement box; a plurality of sealing plugs are slidably and evenly arranged in the sealing plug placement box; two adjacent sealing plugs are arranged in contact with each other;

[0050] The UAV is fixedly provided with a propulsion mechanism; the propulsion mechanism is movably connected with the sampling tube;

[0051] A switching component is fixedly arranged on the sampling tube placement box;

[0052] A transposition driving mechanism is fixedly arranged on the sampling tube placement box.

[0053] Through the above technical scheme, the propulsion mechanism is plugged and fixed with the corresponding sampling cylinder below it; the propulsion mechanism drives the sampling cylinder to move downward, insert it into the soil, and collect soil samples; then the propulsion mechanism drives the sampling cylinder upward; the sampling cylinder is placed above the switching component, and the switching component is actuated to rotate a sealing plug to the bottom of the sampling cylinder, and the propulsion mechanism drives the sampling cylinder downward, so that the sealing plug is stuck to the lower end of the sampling cylinder to seal the sampling cylinder; then the transposition drive mechanism is actuated to move the sampling cylinder containing the soil sample forward, and at the same time, the next empty sampling cylinder is rotated to the bottom of the propulsion mechanism.

[0054] As an optional solution of the present invention, a slideway is provided on the sealing plug placement box, and a plurality of sealing plugs are slidably arranged in the slideway, and one end of the slideway is an open structure;

[0055] A pulling rod is rotatably arranged on the sealing plug placement box, and a coil spring is fixedly arranged on the sealing plug placement box; one end of the coil spring is fixedly connected to the pulling rod.

[0056] Through the above technical solution, the sealing plug is automatically moved forward by the coil spring and the pulling rod.

[0057] As an optional solution of the present invention, a placement slot is provided on the sampling tube placement box; the placement slot is a closed mechanism; a plurality of sampling tubes are slidably arranged in the placement slot;

[0058] A round hole is provided on the placement groove; the propulsion mechanism is slidably matched with the round hole.

[0059] As an optional solution of the present invention, the propulsion mechanism includes an electric push rod B, an insertion rod, an electromagnet and a clamping block;

[0060] The electric push rod B is fixedly set on the drone;

[0061] The movable rod of the electric push rod B is fixedly provided with an insertion rod, and a clamping block is slidably provided on the insertion rod; the clamping block is made of iron material; a spring is provided on the clamping block; the insertion rod is movably plugged and matched with the sampling tube;

[0062] An electromagnet is fixedly arranged inside the insertion rod;

[0063] Through the above technical solution, the electric push rod B is started to drive the insertion rod to move, so that the insertion rod is inserted into the sampling tube, and the electromagnet is closed, so that the card block is stuck on the sampling tube for limiting.

[0064] As an optional solution of the present invention, the switching assembly includes a motor B, a rotating disk, a top disk and a motor fixing plate;

[0065] A motor fixing plate is fixedly arranged on the drone, and a motor B is fixedly arranged on the motor fixing plate; a turntable is coaxially fixedly arranged on the output end of the motor B; a top plate is slidably arranged on the turntable; a spring is connected between the top plate and the turntable; and a rounded corner is arranged on the edge of the top plate;

[0066] The turntable is provided with through holes, a card slot and a top plate slot;

[0067] The sealing plug can be stuck in the slot; the top plate can be slidably arranged in the top plate slot;

[0068] Through the above technical solution, the motor B is started to drive the turntable to rotate, so that the through holes, the card slots and the top plate slots are spaced directly below the insertion rod; the sampling cylinder can be supported by the top plate, and after the sampling cylinder has completed sampling, the sealing plug can be stuck on the sampling cylinder for sealing.

[0069] As an optional solution of the present invention, the transposition drive mechanism includes a motor C, a rotating rod and an arc plate;

[0070] A motor C is fixedly arranged on the sampling tube placement box;

[0071] A rotating rod is coaxially fixedly arranged at the output end of the motor C; four arc-shaped plates are evenly distributed and fixedly arranged on the rotating rod; and the arc-shaped plates are arranged in sliding contact with the corresponding sampling tubes.

[0072] Through the above technical solution, the motor C is started to drive the rotating rod to rotate, and the rotating rod drives the four arc plates to rotate simultaneously. The arc plates move the corresponding sampling cylinder forward and move the next empty sampling cylinder to the bottom of the insertion rod.

[0073] Referring to the figure, a slot is provided at one end of the sampling tube; the slot is plugged into and matched with the plug rod;

[0074] The slot is provided with an annular groove, which is slidably plugged with the card block; the card block can slide in the annular groove.

[0075] Through the above technical solution, the sampling tube can be quickly installed, fixed and released through the plug-in cooperation between the plug rod and the slot, and the sliding plug-in cooperation between the annular groove and the clamping block, thereby improving work efficiency.

[0076] The present invention provides a remote telemetry collection method for land management, comprising the following steps:

[0077] S1, the fixed-point sampling mechanism collects soil parameter information at a fixed point and transmits it to the remote control center;

[0078] S2, random sampling point planning module arranges sampling points for soil information sampling according to the land label map;

[0079] S3, the route planning module plans the flight route of the UAV according to the land label map and multiple preset soil information sampling points to make the total flight distance of the UAV as short as possible;

[0080] S4, random sampling agencies fly to different sampling points according to the planned routes to collect soil information;

[0081] S5. At the same time, the image acquisition module collects high-definition images of the land;

[0082] S6, the image preprocessing module preprocesses the collected image, including operations such as denoising and enhancement; the feature extraction module extracts features from the preprocessed image, and the extracted features include color, texture, shape and other features;

[0083] S7, the anomaly detection module recognizes and analyzes the image after feature extraction; compares and analyzes with the marked reference samples; promptly discovers abnormal conditions on the land, including illegal occupation of land, illegal construction, destruction of cultivated land, soil pollution, etc.; at the same time, according to the soil parameter monitoring results of the fixed-point sampling agency and the random sampling agency, promptly identifies abnormal soil parameters;

[0084] S8. When abnormal conditions in the soil are detected and need to be sampled and analyzed, soil samples are collected through a sampling mechanism to facilitate subsequent analysis and processing;

[0085] S81. When the random sampling mechanism detects that the soil parameters are abnormal, the sampling mechanism collects soil samples immediately;

[0086] S82. When the fixed-point sampling mechanism detects that the soil parameters have a fixed-point abnormality, the sampling mechanism collects soil samples;

[0087] S821. When the random sampling mechanism is not working, the sampling mechanism collects soil samples when the drone flies to the location of the fixed abnormal situation;

[0088] S822. When the random sampling mechanism is working, after the UAV flies to the random sampling point closest to the abnormal situation location and completes information collection, the UAV flies to the fixed abnormal situation location and collects soil samples through the sampling mechanism.

[0089] 3. Beneficial effects

[0090] One or more technical solutions provided in the technical solution of this application have at least the following technical effects or advantages:

[0091] 2. The present invention collects soil parameter information at fixed points over a long period of time through fixed-point sampling mechanisms and transmits it to a remote control center; performs random sampling of soil parameters through random sampling mechanisms; and remotely monitors land parameters in an all-round manner through a combination of fixed-point and random monitoring.

[0092] 3. When abnormal conditions are detected in the land, soil samples can be collected by sampling agencies to facilitate subsequent specific analysis of the soil samples.

[0093] 4. Multiple sampling tubes can be placed in the sampling tube placement box to continuously collect soil samples from multiple locations.

[0094] 5. The sealing plug can be sealed onto the sampling tube through the pushing mechanism, the switching assembly and the sealing plug placement box to seal the sample and ensure that the sample is intact.

[0095] 6. The sampling cylinder can be automatically replaced through the propulsion mechanism and the transposition drive mechanism, so that the sampling cylinder that has collected the soil sample can be automatically advanced to improve work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] Figure 1 This is an overall schematic diagram of a remote telemetry collection system for land management disclosed in a preferred embodiment of the present application;

[0097] Figure 2 A schematic diagram of the cooperation of a soil parameter collection mechanism, a transposition drive mechanism and a sampling tube placement box of a remote telemetry collection system for land management disclosed in a preferred embodiment of the present application;

[0098] Figure 3 A schematic diagram of a sealing plug placement box of a remote telemetry collection system for land management disclosed in a preferred embodiment of the present application;

[0099] Figure 4 A schematic diagram of a soil parameter collection mechanism of a remote telemetry collection system for land management disclosed in a preferred embodiment of the present application;

[0100] Figure 5 A schematic diagram of a sampling tube placement box of a remote telemetry collection system for land management disclosed in a preferred embodiment of the present application;

[0101] Figure 6 A schematic diagram of a propulsion mechanism of a remote telemetry collection system for land management disclosed in a preferred embodiment of the present application;

[0102] Figure 7 A schematic diagram of a switching component of a remote telemetry collection system for land management disclosed in a preferred embodiment of the present application;

[0103] Figure 8 A schematic diagram of a transposition drive mechanism of a remote telemetry collection system for land management disclosed in a preferred embodiment of the present application;

[0104] Fig. 9 A schematic diagram of a sampling tube of a remote telemetry collection system for land management disclosed in a preferred embodiment of the present application.

[0105] Reference numerals:

[0106] 1. UAV; 2. Soil parameter collection mechanism; 3. Sampling tube placement box; 4. Sealing plug placement box; 5. Propulsion mechanism; 6. Switching assembly; 7. Transposition drive mechanism; 8. Sampling tube; 9. Sealing plug; 21. Motor A; 22. Shaft; 23. Electric push rod A; 24. Multi-parameter soil detector; 31. Placement slot; 32. Round hole; 41. Slide; 42. Pull rod; 51. Electric push rod B; 52. Insert rod; 53. Electromagnet; 54. Block; 61. Motor B; 62. Turntable; 621. Through hole; 622. Card slot; 623. Top plate slot; 63. Top plate; 64. Motor fixing plate; 71. Motor C; 72. Turntable; 73. Arc plate; 81. Slot; 82. Annular groove. DETAILED DESCRIPTION

[0107] The present application is further described in detail below in conjunction with the accompanying drawings.

[0108] Reference Figure 1 The present application embodiment provides a remote telemetry collection system for land management, including:

[0109] Data collection module: collects a large amount of data information about the relevant land, including maps, the shape, size, purpose and use of the land, etc., and marks the land information of each location in detail on the map as a label to facilitate subsequent query and reference; collects a large number of photos of the land, including normal pictures and abnormal pictures, and marks them as reference samples.

[0110] Fixed-point sampling mechanism: including soil parameter sensors, which are fixedly arranged at different locations on the land to collect soil parameter information at fixed points. These sensors can work stably for a long time, collect soil parameter information at fixed points, and provide accurate soil data.

[0111] Random sampling mechanism: including drones, soil parameter collection mechanism and sampling mechanism; drones are used to fly to different sampling points to collect soil information; multi-parameter soil detector: collects soil information and multiple soil parameters; when abnormal soil conditions are detected and sampling and analysis is required, the sampling mechanism is activated to collect soil samples for subsequent analysis and processing;

[0112] Random sampling point planning module: According to the land label map, the sampling points for soil information sampling are arranged. The sampling points need to be arranged evenly and cover all the land that needs to be sampled to ensure the comprehensiveness and representativeness of the data.

[0113] Route planning module: Based on the land label map and multiple preset soil information sampling points, the flight route of the drone is planned to make the total flight distance of the drone the shortest, so as to improve work efficiency.

[0114] Image acquisition module: including a high-definition camera to collect high-definition images of the land;

[0115] Image preprocessing module: preprocess the collected images; including denoising, enhancement and other operations to improve the accuracy of subsequent analysis. Enhancement operations can highlight important features in the image, making these features easier to capture by subsequent analysis algorithms. For example, contrast enhancement can increase the contrast between different areas in the image, making the edges, textures and other features in the image more obvious; sharpening operations can enhance the details of the image, making the target object in the image more prominent.

[0116] Feature extraction module: extracts features from the preprocessed image. The extracted features include color, texture, shape and other features;

[0117] Abnormal detection module: Identify and analyze the image after feature extraction; timely discover abnormal conditions on the land; for example: illegal occupation of land, illegal construction, destruction of cultivated land, soil pollution, etc. At the same time, according to the soil parameter monitoring results of fixed-point sampling agencies and random sampling agencies, timely identify abnormal soil parameters;

[0118] Remote control center: including remote controller, display screen and wireless signal transmission system; this is already available and will not be described in detail here;

[0119] PLC control module: connected to the remote control center network through wireless signals. Receives instructions sent by the remote controller and controls the operation of related equipment. The soil parameter sensor is connected to the PLC control module network through wireless signals. The PLC control module is connected to the drone, soil parameter collection mechanism, sampling mechanism and remote control center network through wireless signals.

[0120] Furthermore, the soil parameter sensor preferably adopts the soil parameter sensor model PHWSD-T produced by Wuhan Xinpuhui Technology Co., Ltd., which is a three-in-one soil moisture content, conductivity and temperature. The soil moisture / conductivity / temperature sensor has stable performance and high sensitivity. It is an important tool for observing and studying the occurrence, evolution, improvement and water-salt dynamics of saline soil. By measuring the dielectric constant of the soil, the true moisture content of various soils can be directly and stably reflected. The soil moisture sensor can measure the volume percentage of soil moisture, which is a soil moisture measurement method that meets the current international standards. It is suitable for soil moisture monitoring, scientific experiments, water-saving irrigation, greenhouses, flowers and vegetables, grasslands, soil rapid testing, plant cultivation, sewage treatment, precision agriculture and other occasions.

[0121] Furthermore, the multi-parameter soil detector can detect whether the soil is polluted; it can quickly, accurately and in real time measure a variety of soil parameters, including soil moisture, conductivity, temperature, pH value, nutrients such as nitrogen, phosphorus and potassium, and pollutants such as heavy metals. By detecting these parameters, the multi-parameter soil detector can provide soil managers with a scientific basis for decision-making, effectively reduce the pollution of horticultural products and the residual amount of harmful substances, and protect the health and safety of consumers. In terms of environmental protection, the multi-parameter soil detector can also be used as a tool for detecting pollution from chemical substances such as heavy metals and pesticides, helping land users to quickly and accurately detect various pollutants in the land, thereby ensuring the health and safety of the environment.

[0122] Furthermore, the features extracted by the feature extraction module include color, texture, and shape;

[0123] Color features: Color is one of the most intuitive and significant features in an image. In land management, color features can be used to distinguish different types of land cover (such as vegetation, water bodies, buildings, etc.). Commonly used color feature extraction methods include color histogram, color moment, color set, etc. These methods can capture the distribution and statistical information of different color components in an image.

[0124] Texture features: Texture features describe the pattern or structure of a local area in an image, and are usually related to the surface characteristics of an object. In land management, texture features can be used to identify soil type, land conditions (such as cultivated, barren, etc.) or vegetation density. Commonly used texture feature extraction methods include gray level co-occurrence matrix (GLCM), autoregressive model, wavelet transform, etc. These methods can capture the pixel relationship or frequency distribution information of a local area in an image.

[0125] Shape features: Shape features describe the boundary or regional shape of objects in an image. In land management, shape features can be used to identify specific types of objects (such as buildings, roads, lakes, etc.) or detect abnormal areas on the land (such as illegal buildings, damaged farmland, etc.). Commonly used shape feature extraction methods include boundary feature methods (such as Fourier descriptors, chain codes, etc.) and regional feature methods (such as moment features, geometric features, etc.). These methods can capture the boundary contours of objects in an image or the structural information inside a region.

[0126] Furthermore, the anomaly detection module plays an important role in land management, and can detect abnormal conditions on the land in a timely manner, providing strong support for land management. With the continuous development of technology, the accuracy and efficiency of the anomaly detection module will be further improved, bringing more convenience and benefits to land management.

[0127] The anomaly detection module combines advanced algorithms and models to identify and analyze anomalies in images. It includes:

[0128] Model training unit: The model training unit uses machine learning algorithms (such as support vector machines (SVMs), random forests, etc.) or deep learning models to train a classification or detection model from known normal land images. This model can learn and recognize the features of normal land images, which may include color, texture, shape, etc., which together define the appearance and state of normal land. During the training process, the model will continuously learn and adjust its parameters to minimize prediction errors and improve classification or detection accuracy. After training, the model has the ability to recognize normal land images and can be used for subsequent anomaly detection tasks.

[0129] Anomaly Detection Unit: The anomaly detection unit compares the newly input image with the trained model to determine whether there are any anomalies. When a new image is input, the anomaly detection module first extracts the key features of the image and then matches these features with the trained model. If the features of the input image are significantly different from those of the normal model, that is, they exceed the threshold range that the model can tolerate, then the image is marked as anomaly. This means that the image may contain anomalies such as illegal occupation of land, destruction of arable land, and soil pollution.

[0130] For example: Identifying illegal occupation of land: By comparing the land’s color, texture, and shape, the anomaly detection module can identify illegally occupied land. For example, a new building or road may change the land’s color and texture characteristics.

[0131] Identifying damaged farmland: When farmland is damaged, its characteristics such as color, texture, and shape may change. The anomaly detection module can capture these changes and identify damaged farmland.

[0132] Identifying soil contamination: Soil contamination may cause abnormal soil color or changes in soil structure. The anomaly detection module can identify soil contamination by analyzing the color and texture characteristics of the soil.

[0133] Model optimization: By continuously collecting new data and adjusting model parameters, the performance of the model can be optimized to improve the accuracy and efficiency of anomaly detection. For images marked as abnormal by the model, manual verification can be performed to ensure the accuracy of the detection results. At the same time, manual verification can also provide feedback for model optimization.

[0134] The route planning module works in the following steps:

[0135] Data input: includes a labeled map of the land, which is usually a detailed map containing geographic coordinates, land type (such as forest land, cultivated land, water area, etc.), terrain (such as plains, mountains, hills, etc.), and possible obstacles (such as buildings, trees, etc.).

[0136] Soil information sampling points: multiple preset points, indicating the locations where the drone needs to perform soil information sampling.

[0137] Path planning algorithm: Path planning algorithms including Dijkstra algorithm are used to find the shortest path from the starting point to the end point (or a series of points) while taking into account factors such as terrain and obstacles.

[0138] Flight route optimization: After finding a preliminary path, the route planning module may also need to optimize it. This includes considering the flight characteristics of the drone (such as maximum flight speed, maximum climb / descent angle, endurance, etc.), as well as environmental factors during the flight (such as wind direction, wind speed, etc.). Optimization may involve adjusting parameters such as flight altitude, speed, and steering angle to ensure that the drone can complete the sampling mission efficiently and safely.

[0139] Generate flight instructions: Once the flight route is determined and optimized, the route planning module will generate detailed flight instructions, including take-off point, landing point, flight altitude, speed, turning point, etc. These instructions will be passed to the UAV's flight control system to guide the UAV to fly and sample according to the planned route.

[0140] Real-time monitoring and adjustment: During the flight of the drone, the route planning module may need to communicate with the drone’s flight control system in real time to monitor the drone’s position and status.

[0141] If unexpected situations occur (such as obstacles, weather changes, etc.), the route planning module may need to recalculate the flight route and generate new flight instructions to ensure that the drone can safely complete the sampling mission.

[0142] Furthermore, when using the Dijkstra algorithm to plan the shortest path for the drone from the take-off point to each sampling point and then back to the landing point, the specific steps include:

[0143] (1) Construction of the graph, including:

[0144] Define nodes: Define the take-off point, landing point, and all preset soil information sampling points as nodes in the graph.

[0145] Define edges and weights: Create edges between nodes to represent possible paths for the drone to fly from one point to another. Set weights for each edge based on the actual terrain, obstacles, and flight conditions. Weights usually represent the cost of the flight, such as distance, time, or energy consumption. In areas with obstacles or complex terrain, weights should be increased accordingly.

[0146] (2) Initialization:

[0147] Create a distance array dist[] to store the shortest distance from the take-off point to each node. Initialize the distances of all nodes to infinity (or a large value) and the distance of the take-off point to 0.

[0148] Create a visited[] array to mark whether a node has been visited. Initialize the visited status of all nodes to unvisited (such as false).

[0149] (3) Dijkstra algorithm process: Add the take-off point to a priority queue (or minimum heap) and set its distance to 0.

[0150] When the priority queue is not empty, perform the following steps:

[0151] Take the node u with the shortest distance from the priority queue (that is, the node with the currently known shortest path).

[0152] Mark node u as visited.

[0153] For each unvisited node v adjacent to node u, do the following:

[0154] If the distance from node u to node v (dist[u]+weight(u,v)) is less than dist[v], update dist[v] to the new shorter distance. dist[u] represents the currently known shortest distance from the starting point to node u. weight(u,v) represents the weight of the edge from node u to node v, which usually represents the actual distance, flight time, or energy consumption between the two nodes.

[0155] If node v is not already in the priority queue, or the new distance is shorter than the distance in the queue, then update the distance of node v in the queue.

[0156] Repeat step 2 until all nodes have been visited or the shortest path from the take-off point to all sampling points and the landing point has been found.

[0157] (4) Output results: Based on the output of the algorithm, the flight instructions of the drone are generated, including the take-off point, landing point, the order of sampling points visited, and the flight path between these points.

[0158] Reference Figure 1 , Figure 2 , Figure 3 and Figure 4 , the random sampling mechanism includes: a drone 1, a soil parameter collection mechanism 2 and a sampling mechanism;

[0159] A soil parameter collection mechanism 2 is fixedly provided at the lower end of the drone 1, and the soil parameter collection mechanism 2 is used to collect soil parameters; a PGS locator is fixedly provided on the drone 1, which can automatically record the location information of the sampling;

[0160] The drone 1 is fixedly provided with a sampling mechanism; the sampling mechanism is used to sample the soil;

[0161] The soil parameter acquisition mechanism 2 includes a motor A21, a shaft 22, an electric push rod A23 and a multi-parameter soil detector 24;

[0162] The drone 1 is fixedly provided with a motor A21, and a shaft 22 is coaxially fixedly provided at the output end of the motor A21; an electric push rod A23 is fixedly provided on the shaft 22; a multi-parameter soil detector 24 is fixedly provided on the movable rod of the electric push rod A23; the multi-parameter soil detector 24 is preferably a multi-parameter soil detector of model JZ-192 produced by Beijing Jiuzhou Shengxin Technology Co., Ltd. An inclinometer is fixedly provided on the electric push rod A23 for monitoring the angle of the electric push rod A23.

[0163] In this technical solution, the starting motor A21 drives the electric push rod A23 and the multi-parameter soil detector 24 to rotate, and the electric push rod A23 drives the multi-parameter soil detector 24 to move, so that the multi-parameter soil detector 24 is inserted into the soil to collect parameters.

[0164] The sampling mechanism includes a sampling tube placement box 3, a sealing plug placement box 4, a propulsion mechanism 5, a switching assembly 6, a transposition drive mechanism 7 and a sampling tube 8;

[0165] A sampling tube placement box 3 is detachably fixed at the lower end of the drone 1; a plurality of sampling tubes 8 are slidably and evenly arranged in the sampling tube placement box 3; two adjacent sampling tubes 8 are arranged in contact with each other;

[0166] The sampling tubes 8 are all fixedly provided with electronic tags; the electronic tags correspond one to one with the sampling tubes 8;

[0167] A sealing plug placement box 4 is detachably fixed on the sampling tube placement box 3; a plurality of sealing plugs 9 are slidably and evenly arranged in the sealing plug placement box 4; two adjacent sealing plugs 9 are arranged in contact with each other;

[0168] The drone 1 is fixedly provided with a propulsion mechanism 5; the propulsion mechanism 5 is movably connected with the sampling tube 8;

[0169] A switching assembly 6 is fixedly arranged on the sampling tube placement box 3;

[0170] A transposition driving mechanism 7 is fixedly arranged on the sampling tube placement box 3 .

[0171] In this technical solution, the propulsion mechanism 5 is plugged and fixed with the corresponding sampling tube 8 below it; the propulsion mechanism 5 drives the sampling tube 8 to move downward, insert it into the soil, and collect soil samples; then the propulsion mechanism 5 drives the sampling tube 8 to move upward; the sampling tube 8 is placed above the switching component 6, and the switching component 6 is actuated to rotate a sealing plug 9 to the bottom of the sampling tube 8, and the propulsion mechanism 5 drives the sampling tube 8 to move downward, so that the sealing plug 9 is stuck to the lower end of the sampling tube 8 to seal the sampling tube 8; then the transposition drive mechanism 7 is actuated to move the sampling tube 8 containing the soil sample forward, and at the same time, the next empty sampling tube 8 is rotated to the bottom of the propulsion mechanism 5.

[0172] A slideway 41 is provided on the sealing plug placement box 4, and a plurality of sealing plugs 9 are slidably arranged in the slideway 41, and one end of the slideway 41 is an open structure;

[0173] A pulling rod 42 is rotatably provided on the sealing plug placement box 4 , and a coil spring is fixedly provided on the sealing plug placement box 4 ; one end of the coil spring is fixedly connected to the pulling rod 42 .

[0174] In this technical solution, the sealing plug 9 is automatically advanced by the coil spring and the pulling rod 42 .

[0175] Reference Figure 5 The sampling tube placement box 3 is provided with a placement slot 31; the placement slot 31 is a closed mechanism; a plurality of sampling tubes 8 are slidably arranged in the placement slot 31;

[0176] A circular hole 32 is formed on the placement groove 31 ; the pushing mechanism 5 is slidably matched with the circular hole 32 .

[0177] Reference Figure 6 The propulsion mechanism 5 includes an electric push rod B51, an insert rod 52, an electromagnet 53 and a clamping block 54;

[0178] The electric push rod B51 is fixedly arranged on the drone 1;

[0179] The movable rod of the electric push rod B51 is fixedly provided with an insertion rod 52, and a clamping block 54 is slidably provided on the insertion rod 52; the clamping block 54 is made of iron material; a spring is provided on the clamping block 54; the insertion rod 52 is movably plugged and matched with the sampling tube 8;

[0180] An electromagnet 53 is fixedly disposed inside the insertion rod 52;

[0181] In this technical solution, the electric push rod B51 is started to drive the insertion rod 52 to move, so that the insertion rod 52 is inserted into the sampling tube 8, and the electromagnet 53 is closed, so that the block 54 is stuck on the sampling tube 8 to limit the position.

[0182] Reference Figure 7 , the switching assembly 6 includes a motor B61, a rotating disk 62, a top disk 63 and a motor fixing plate 64;

[0183] The drone 1 is fixedly provided with a motor fixing plate 64, on which a motor B61 is fixedly provided; a turntable 62 is coaxially fixedly provided at the output end of the motor B61; a top plate 63 is slidably provided on the turntable 62; a spring is provided between the top plate 63 and the turntable 62; and the edge of the top plate 63 is provided with a rounded corner;

[0184] The rotating disk 62 is provided with a through hole 621, a clamping slot 622 and a top disk slot 623;

[0185] The sealing plug 9 can be stuck in the slot 622; the top plate 63 can be slidably arranged in the top plate slot 623;

[0186] In this technical solution, the starter motor B61 drives the turntable 62 to rotate, so that the through hole 621, the card slot 622 and the top plate slot 623 are spaced directly below the insertion rod 52; the sampling tube 8 can be supported by the top plate 63, and after the sampling tube 8 completes sampling, the sealing plug 9 can be stuck onto the sampling tube 8 for sealing.

[0187] Reference Figure 8 , the transposition driving mechanism 7 includes a motor C71, a rotating rod 72 and an arc plate 73;

[0188] A motor C71 is fixedly arranged on the sampling tube placement box 3;

[0189] A rotating rod 72 is coaxially fixedly disposed at the output end of the motor C71 ; four arc-shaped plates 73 are evenly distributed and fixedly disposed on the rotating rod 72 ; the arc-shaped plates 73 are disposed in sliding contact with the corresponding sampling tubes 8 .

[0190] In this technical solution, the starting motor C71 drives the rotating rod 72 to rotate, and the rotating rod 72 drives the four arc plates 73 to rotate simultaneously. The arc plates 73 move the corresponding sampling tube 8 forward and move the next empty sampling tube 8 to the bottom of the insertion rod 52 at the same time.

[0191] Reference Fig. 9 A slot 81 is provided at one end of the sampling tube 8; the slot 81 is plugged into and matched with the plug rod 52;

[0192] The slot 81 is provided with an annular groove 82 , which is slidably plugged into and matched with the clamping block 54 ; the clamping block 54 can slide in the annular groove 82 .

[0193] In this technical solution, by means of the plug-in fit between the plug rod 52 and the slot 81 and the sliding plug-in fit between the annular groove 82 and the clamping block 54 , the sampling tube 8 can be quickly installed, fixed and released, thereby improving work efficiency.

[0194] The present invention provides a remote telemetry collection method for land management, comprising the following steps:

[0195] S1, the fixed-point sampling mechanism collects soil parameter information at a fixed point and transmits it to the remote control center;

[0196] S2, random sampling point planning module arranges sampling points for soil information sampling according to the land label map;

[0197] S3, the route planning module plans the flight route of the UAV according to the land label map and multiple preset soil information sampling points to make the total flight distance of the UAV as short as possible;

[0198] S4, random sampling agencies fly to different sampling points according to the planned routes to collect soil information;

[0199] S5. At the same time, the image acquisition module collects high-definition images of the land;

[0200] S6, the image preprocessing module preprocesses the collected image, including operations such as denoising and enhancement; the feature extraction module extracts features from the preprocessed image, and the extracted features include color, texture, shape and other features;

[0201] S7, the anomaly detection module recognizes and analyzes the image after feature extraction; compares and analyzes with the marked reference samples; promptly discovers abnormal conditions on the land, including illegal occupation of land, illegal construction, destruction of cultivated land, soil pollution, etc.; at the same time, according to the soil parameter monitoring results of the fixed-point sampling agency and the random sampling agency, promptly identifies abnormal soil parameters;

[0202] S8. When an abnormality in the soil is detected and sampling and analysis is required, soil samples are collected through the sampling mechanism, and the sampling position coordinate information of the sampling tube 8 is recorded and corresponds to the electronic tag one by one; this is convenient for subsequent analysis and processing;

[0203] S81. When the random sampling mechanism detects that the soil parameters are abnormal, the sampling mechanism collects soil samples immediately;

[0204] S82. When the fixed-point sampling mechanism detects that the soil parameters have a fixed-point abnormality, the sampling mechanism collects soil samples;

[0205] S821, when the random sampling mechanism is not working, the drone 1 flies to the location of the fixed abnormal situation and collects soil samples through the sampling mechanism;

[0206] S822. When the random sampling mechanism is working, after the drone 1 flies to the random sampling point closest to the abnormal situation location and completes information collection, the drone 1 flies to the fixed abnormal situation location and collects soil samples through the sampling mechanism.

[0207] The working principle of the remote telemetry collection system for land management of the present invention is as follows: a fixed-point sampling mechanism collects soil parameter information at a fixed point for a long time and transmits it to a remote control center; as needed, a random sampling point planning module arranges sampling points for soil information sampling according to a label map of the land; a route planning module plans the flight route of the UAV according to the label map of the land and a plurality of preset soil information sampling points to make the total flight distance of the UAV as short as possible; the random sampling mechanism flies to different sampling points according to the planned route to collect soil information; at the same time, an image acquisition module collects high-definition images of the land; an image preprocessing module preprocesses the collected images, including operations such as denoising and enhancement; a feature extraction module extracts features from the preprocessed images, and the extracted features include features such as color, texture and shape; an anomaly detection module identifies and analyzes the images after feature extraction, and compares and analyzes them with identified reference samples ; Timely discover abnormal conditions on the land; including illegal occupation of land, illegal construction, destruction of arable land, soil pollution, etc.; at the same time, according to the soil parameter monitoring results of the fixed-point sampling agency and the random sampling agency, timely identify abnormal soil parameters; when it is detected that the soil has abnormal conditions and needs to be sampled and analyzed, soil samples are collected by the sampling agency to facilitate subsequent analysis and processing; when the random sampling agency monitors that the soil parameters have abnormal conditions, soil samples are immediately collected by the sampling agency; when the fixed-point sampling agency monitors that the soil parameters have fixed-point abnormal conditions, soil samples are collected by the sampling agency; when the random sampling agency is not working, the drone 1 flies to the fixed-point abnormal situation location, and the soil samples are collected by the sampling agency; when the random sampling agency is working, after the drone 1 flies to the random sampling point closest to the abnormal situation location to complete information collection, the drone 1 flies to the fixed-point abnormal situation location and collects soil samples by the sampling agency.

[0208] The present invention collects soil parameter information at a fixed point for a long time through a fixed-point sampling mechanism and transmits it to a remote control center; randomly checks soil parameters through a random sampling mechanism; and remotely monitors land parameters in an all-round manner by combining fixed-point and random monitoring. When an abnormal situation is detected in the land, soil samples can be collected through the sampling mechanism to facilitate subsequent specific analysis of the soil samples. Multiple sampling tubes 8 can be placed in the sampling tube placement box 3, and soil samples at multiple positions can be collected continuously. The sealing plug 9 can be sealed to the sampling tube 8 through the propulsion mechanism 5, the switching component 6 and the sealing plug placement box 4, and the sample is sealed to ensure that the sample is intact. The sampling tube 8 can be automatically replaced by the propulsion mechanism 5 and the transposition drive mechanism 7, so that the sampling tube 8 that has collected the soil sample is automatically advanced, thereby improving work efficiency.

[0209] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A remote telemetry collection method for land management, characterized in that: The following steps are involved: S1, the fixed-point sampling mechanism collects soil parameter information at a fixed point and transmits it to the remote control center; S2, random sampling point planning module arranges sampling points for soil information sampling according to the land label map; S3, the route planning module plans the flight route of the UAV according to the land label map and multiple preset soil information sampling points to make the total flight distance of the UAV as short as possible; S4, random sampling agencies fly to different sampling points according to the planned routes to collect soil information; S5. At the same time, the image acquisition module collects high-definition images of the land; S6, the image preprocessing module preprocesses the collected image; S7, the anomaly detection module recognizes and analyzes the image after feature extraction; compares and analyzes it with the marked reference sample; promptly discovers abnormal conditions on the land; and promptly identifies abnormal conditions of soil parameters based on the soil parameter monitoring results of the fixed-point sampling agency and the random sampling agency; S8. When abnormal conditions in the soil are detected and need to be sampled and analyzed, soil samples are collected through a sampling mechanism to facilitate subsequent analysis and processing; The random sampling mechanism includes: a drone, a soil parameter collection mechanism and a sampling mechanism; the lower end of the drone is fixedly provided with the soil parameter collection mechanism; the drone is fixedly provided with the sampling mechanism; the sampling mechanism is used to sample the soil; the soil parameter collection mechanism includes a motor A, a shaft, an electric push rod A and a multi-parameter soil detector; the drone is fixedly provided with a motor A, and the output end of the motor A is coaxially fixed with a shaft; the electric push rod A is fixedly provided on the shaft; the multi-parameter soil detector is fixedly provided on the movable rod of the electric push rod A; the electric push rod A is fixedly provided with an angle meter; The sampling mechanism includes a sampling tube placement box, a sealing plug placement box, a propulsion mechanism, a switching assembly, a transposition drive mechanism and a sampling tube; a sampling tube placement box is detachably fixedly provided at the lower end of the drone; a plurality of sampling tubes are slidably and evenly provided in the sampling tube placement box; a sealing plug placement box is detachably and fixedly provided on the sampling tube placement box; a plurality of sealing plugs are slidably and evenly provided in the sealing plug placement box; a propulsion mechanism is fixedly provided on the drone; the propulsion mechanism is movably plugged with the sampling tube; a switching assembly is fixedly provided on the sampling tube placement box; a transposition drive mechanism is fixedly provided on the sampling tube placement box; The sealing plug placement box is provided with a slideway, a plurality of sealing plugs are slidably arranged in the slideway, and one end of the slideway is an open structure; a pulling rod is rotatably arranged on the sealing plug placement box, and a coil spring is fixedly arranged on the sealing plug placement box; one end of the coil spring is fixedly connected to the pulling rod; a placement slot is provided on the sampling tube placement box; the placement slot is a closed mechanism; a plurality of sampling tubes are slidably arranged in the placement slot; a round hole is provided on the placement slot; the pushing mechanism slidably cooperates with the round hole; The propulsion mechanism includes an electric push rod B, an insertion rod, an electromagnet and a block; the electric push rod B is fixedly arranged on the drone; the insertion rod is fixedly arranged on the movable rod of the electric push rod B, and the block is slidably arranged on the insertion rod; the block is made of iron material; a spring is arranged on the block; the insertion rod is movably plugged and matched with the sampling tube; an electromagnet is fixedly arranged inside the insertion rod; The switching assembly includes a motor B, a rotating disk, a top disk and a motor fixing plate; A motor fixing plate is fixedly arranged on the drone, and a motor B is fixedly arranged on the motor fixing plate; a turntable is coaxially fixedly arranged on the output end of the motor B; a top plate is slidably arranged on the turntable; a spring is connected between the top plate and the turntable; a through hole, a card slot and a top plate slot are arranged on the turntable; The transposition drive mechanism includes a motor C, a rotating rod and an arc plate; the motor C is fixedly arranged on the sampling tube placement box; the rotating rod is coaxially fixedly arranged on the output end of the motor C; four arc plates are evenly distributed and fixedly arranged on the rotating rod; the arc plates are arranged in sliding contact with the corresponding sampling tubes; a slot is arranged at one end of the sampling tube; the slot is plugged in with the plug rod; an annular groove is opened on the slot, and the annular groove is slidably plugged in with the clamping block; the clamping block can slide in the annular groove.

2. The remote telemetry data collection method for land management according to claim 1, characterized in that: The step S8 comprises the following steps: S81. When the random sampling mechanism detects abnormal soil parameters, soil samples are collected through the sampling mechanism; S82. When the fixed-point sampling mechanism detects that the soil parameters have a fixed-point abnormality, the sampling mechanism collects soil samples; S821. When the random sampling mechanism is not working, the sampling mechanism collects soil samples when the drone flies to the location of the fixed abnormal situation; S822. When the random sampling mechanism is working, after the UAV flies to the random sampling point closest to the abnormal situation location and completes information collection, the UAV flies to the fixed abnormal situation location and collects soil samples through the sampling mechanism.

3. The remote sensing data collection method for land management according to claim 1 is characterized in that: The route planning module includes the following: Data input: Includes a labeled map of the land, including geographic coordinates, land type, and topography; Soil information sampling points: multiple preset points, indicating the locations where the drone needs to perform soil information sampling; Path planning algorithm: The path planning Dijkstra algorithm is used to find the shortest path from the starting point to the end point while taking into account terrain and obstacles; Flight route optimization: After finding the preliminary path, the path is optimized based on the flight characteristics of the drone; Generate flight instructions: Once the flight route is determined and optimized, the route planning module will generate detailed flight instructions, including take-off point, landing point, flight altitude, speed and turning point; Real-time monitoring and adjustment: During the flight of the drone, the route planning module communicates with the drone's flight control system in real time to monitor the drone's position and status.

4. A remote telemetry collection system for land management, comprising: The data collection module, the fixed-point sampling mechanism, the random sampling mechanism, the random sampling point planning module, the route planning module, the image acquisition module, the image preprocessing module, the feature extraction module, the anomaly detection module, the remote control center and the PLC control module are characterized by: Data collection module: collect a large amount of data information about the relevant land, including maps, the shape, size, purpose and nature of the land, and mark the land information in detail on the map as a label; collect a large number of photos of the land, including normal pictures and abnormal pictures, and mark them as reference samples; Fixed-point sampling mechanism: including soil parameter sensors, which are fixedly arranged at different locations on the land and used to collect soil parameter information at fixed points; Random sampling mechanism: including drones, soil parameter collection mechanism and sampling mechanism; drones drive multi-parameter soil detectors to fly to different sampling points to collect soil information; when abnormal conditions in the soil are detected, the sampling mechanism is activated to collect soil samples for subsequent analysis and processing; Random sampling point planning module: arrange sampling points for soil information sampling according to the land label map; Route planning module: based on the land label map and multiple preset soil information sampling points; plan the flight route of the drone to make the total flight distance of the drone as short as possible; Image acquisition module: including a high-definition camera to collect high-definition images of the land; Image preprocessing module: preprocess the collected images, including denoising and enhancement operations; Feature extraction module: extracts features from the preprocessed image. The extracted features include color, texture and shape features. Abnormal detection module: Identify and analyze the image after feature extraction; timely discover abnormal conditions on the land; and timely identify abnormal conditions of soil parameters based on the soil parameter monitoring results of fixed-point sampling agencies and random sampling agencies; Remote control center: including remote controller, display screen and wireless signal transmission system; PLC control module: connected to the UAV, soil parameter collection mechanism, sampling mechanism and remote control center network through wireless signals.

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