Method and system for evaluating measurement accuracy of soil moisture sensor based on remote sensing technology

Abstract

The application discloses a kind of soil moisture sensor measurement precision evaluation method and system based on remote sensing technology, it is related to agricultural water and soil engineering and remote sensing monitoring technical field, the method first completes sensor selection and system construction, standardization plot layout, sensor and remote sensing control point layout, then through standardization irrigation establishes field water capacity, utilizes unmanned plane remote sensing monitoring waterlogging dynamic, after water redistribution rest, sensor data and multi-temporal remote sensing image are synchronously collected, finally with field water capacity as benchmark to evaluate static precision, combine waterlogging and sensor response curve Quantitative dynamic sensitivity.The application fuses ground sensing, standardization field water capacity establishment and unmanned plane remote sensing, realizes static precision and dynamic sensitivity collaborative evaluation, solves the problem that traditional method is difficult to reflect real field condition and dynamic response, and evaluation result system is traceable, suitable for soil moisture sensor field performance selection and precision agriculture application.

Description

Technical Field

[0001] This invention relates to the fields of agricultural water and soil engineering and remote sensing monitoring technology, and in particular to a method and system for evaluating the measurement accuracy of soil moisture sensors based on remote sensing technology. Background Technology

[0002] Soil moisture is a core parameter for agricultural production, and soil moisture sensors are the core devices for field water sensing in smart agriculture. Their measurement accuracy and response performance directly determine the reliability of moisture data and the effectiveness of irrigation decisions. Current sensor accuracy evaluations largely rely on indoor soil column calibration, limited-point drying comparisons, or static error analysis of a single reference sensor. Indoor calibration cannot simulate actual field conditions such as soil variability, temperature, salinity, and root disturbance. Traditional field evaluations only focus on static deviations in water equilibrium, lacking a systematic assessment of response sensitivity and tracking performance during dynamic water transport, making it difficult to adapt to the monitoring needs of moisture changes in different soil textures such as sandy soil, loam, and clay. UAV remote sensing can achieve macroscopic visualization and tracking of soil moisture transport through surface water stain characteristics, providing technical support for multi-scale fusion evaluation. Therefore, there is an urgent need for a soil moisture sensor evaluation method and system that integrates ground sensing, standardized field water holding capacity establishment, and UAV remote sensing dynamic monitoring, capable of simultaneously evaluating static accuracy and dynamic sensitivity. Summary of the Invention

[0003] In order to overcome the shortcomings of the existing technology, the purpose of this invention is to provide a method and system for evaluating the measurement accuracy of soil moisture sensors based on remote sensing technology.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] This invention provides a method for evaluating the measurement accuracy of a soil moisture sensor based on remote sensing technology, comprising:

[0006] S1: Sensor selection and system construction, configuring soil moisture sensors to be evaluated, high-precision reference sensors and UAV remote sensing platforms equipped with high-resolution imaging equipment, and constructing a multi-source data synchronous acquisition system;

[0007] S2: Plot selection and standardized plot layout: Select flat plots with typical soil texture, construct embankment plots that include test areas and protection areas to ensure vertical one-dimensional infiltration of water.

[0008] S3: Sensor installation and remote sensing ground control point deployment. The sensor to be evaluated and the high-precision reference sensor are buried in the test area, and ground control markers for geometric correction of remote sensing images are deployed to achieve spatial registration of ground measurement data and UAV remote sensing images.

[0009] S4: Establishment of standardized field water holding capacity and remote sensing monitoring of irrigation process. Based on the water balance formula, the irrigation volume is calculated and designed. The test area and the protected area are irrigated in layers. At the same time, the soil surface water stains are collected at high frequency by UAV to invert the water infiltration and transport process.

[0010] S5: Surface cover and moisture redistribution: Double-layer cover of straw and plastic film is used to block soil evaporation and precipitation interference, and the soil is left to stand until the soil moisture reaches the stable state of field water holding capacity.

[0011] S6: Multi-source data acquisition, synchronously acquire profile moisture data of the sensor under evaluation and high-precision reference sensor, acquire multi-temporal UAV remote sensing water stain fading images according to the set time phase, and supplement with drying method measurement values ​​as the true moisture value.

[0012] S7: Comprehensive evaluation of sensor accuracy and response sensitivity. The static measurement error of the sensor under evaluation is calculated based on the high-precision reference sensor data during the stable period of field water holding capacity. The dynamic response sensitivity of the sensor under evaluation is quantified by the correlation analysis between the water stain receding rate and the sensor response curve, and the comprehensive performance evaluation is completed.

[0013] Furthermore, the standardized area mentioned in step S2 is as follows: a 2m×2m square outer embankment is constructed with the sensor installation point as the center. The embankment is 30cm high and 30cm wide at the bottom. A 1m×1m inner frame with a soil depth of 20cm is set in the center of the outer embankment. The area inside the frame is the test area, and the area outside the frame to the outer embankment is the protection area.

[0014] Furthermore, the water balance formula in step S4 is: Q = K × (θ_f) c -θ1)×S×H / 100, where Q is the design irrigation volume, K is the water guarantee coefficient, and θ_f c The empirical field water holding capacity is θ1, the weighted average soil profile moisture content before irrigation is θ1, the area of ​​the test area is S, and the measurement depth is H. During irrigation, a 5cm water layer is first established in the protected area, and then water is slowly poured into the test area until the designed water volume is used up while maintaining a 5cm water layer.

[0015] Furthermore, in step S4, the drone collects data at an altitude of 20–50 meters with a collection interval of 30 minutes. The distribution, boundaries, and grayscale values ​​of water stain areas are extracted through image recognition, and a model for inverting water stain image features and surface soil moisture content is constructed.

[0016] Furthermore, the settling time in step S5 is set according to the soil texture: 1-2 days for sandy soil, 2-3 days for loam, and 3-4 days for clay, with the daily change rate of soil moisture <1% as the criterion for stability.

[0017] Furthermore, in step S6, the high-precision reference sensor uses bidirectional measurement to take the average value, the sensor to be evaluated is high-frequency automatic acquisition, and the UAV remote sensing time phase is set to 6h, 12h, 24h, 48h, and 72h after watering.

[0018] Furthermore, in step S7, the static accuracy qualification criterion is that the volumetric moisture content measurement error is ≤±3%; the dynamic response sensitivity is quantitatively evaluated by calculating the correlation coefficient between the water stain fading rate and the sensor response rate, and the response time lag.

[0019] This invention also provides a soil moisture sensor measurement accuracy evaluation system based on remote sensing technology, comprising:

[0020] Building Module: Used for sensor selection and system construction, configuring the soil moisture sensor to be evaluated, the high-precision reference sensor, and the UAV remote sensing platform equipped with high-resolution imaging equipment, and building a multi-source data synchronous acquisition system;

[0021] Selection module: Used for sample plot selection and standardized plot layout. Select flat plots with typical soil texture, construct embankment plots that include test areas and protection areas, and ensure vertical one-dimensional water infiltration.

[0022] Deployment module: used for sensor installation and remote sensing ground control point deployment. It embeds the sensor to be evaluated and the high-precision reference sensor in the test area, and deploys ground control markers for geometric correction of remote sensing images to achieve spatial registration of ground measurement data and UAV remote sensing images.

[0023] Detection module: Used for establishing standardized field water holding capacity and remote sensing monitoring of irrigation process. Based on the water balance formula, it calculates and designs irrigation volume, and irrigates the test area and protection area in layers. At the same time, it uses UAVs to collect images of water stains on the soil surface at high frequency to invert the water infiltration and transport process.

[0024] Redistribution module: Used for surface covering and water redistribution, it uses a double layer of straw and plastic film to block soil evaporation and precipitation interference, and is left to stand until the soil moisture reaches a stable field water holding capacity.

[0025] Acquisition module: Used for multi-source data acquisition, synchronously acquiring profile moisture data from the sensor under evaluation and the high-precision reference sensor, acquiring multi-temporal UAV remote sensing water stain fading images according to the set time phase, and supplementing the drying method measurement values ​​as the true moisture value;

[0026] Evaluation module: Used for comprehensive evaluation of sensor accuracy and response sensitivity. It calculates the static measurement error of the sensor under evaluation based on high-precision reference sensor data during the stable period of field water holding capacity, and quantifies the dynamic response sensitivity of the sensor under evaluation through correlation analysis between water stain receding rate and sensor response curve, thus completing the comprehensive performance evaluation.

[0027] Compared with the prior art, the technical solution disclosed in this invention has the following beneficial effects:

[0028] This invention constructs a controllable field water environment by standardizing the layout of plots and establishing standardized field water holding capacity, eliminating interference from lateral seepage, evaporation, and precipitation, ensuring a unified and stable evaluation benchmark, and improving the accuracy of static precision evaluation.

[0029] This invention integrates UAV remote sensing dynamic monitoring with continuous data acquisition from ground sensors, achieving a breakthrough from point-scale static evaluation to spatiotemporal multidimensional dynamic evaluation. It can quantify the sensor's response sensitivity to water transport in soils of different textures, filling the gap in traditional methods that lack dynamic assessment.

[0030] This invention employs multi-source data fusion and correlation analysis, making the evaluation process traceable and the results quantifiable, thus forming a complete field evaluation system and providing standardized technical support for the selection of soil moisture sensor performance and the application of precision agriculture. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the method for evaluating the measurement accuracy of soil moisture sensors based on remote sensing technology, provided in an embodiment of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0035] This invention provides an evaluation method and system that integrates ground sensor networks, standardized field water holding capacity establishment, and UAV remote sensing dynamic monitoring to collaboratively evaluate the static measurement accuracy and dynamic response sensitivity of soil moisture sensors.

[0036] This invention provides a method for evaluating the measurement accuracy of soil moisture sensors based on remote sensing technology, including:

[0037] S1: Sensor selection and system construction, configuring soil moisture sensors to be evaluated, high-precision reference sensors and UAV remote sensing platforms equipped with high-resolution imaging equipment, and constructing a multi-source data synchronous acquisition system;

[0038] Specifically, S1 involves: First, configuring soil moisture sensors to be evaluated, including tubular multi-layer fixed automatic monitoring instruments and probe-type sensors, among other main types. Simultaneously, configuring a high-precision reference sensor, preferably a Trime tubular TDR sensor, as a mobile measurement benchmark during the stable period of field water holding capacity. Based on this, an unmanned aerial vehicle (UAV) remote sensing system is integrated, equipped with a high-resolution visible light or multispectral camera, capable of preset flight paths, automatic fixed-point image acquisition, and real-time transmission. The system construction process aims for simultaneous acquisition of multi-source data, ensuring spatiotemporal matching between ground-level point-scale measurements and low-altitude surface-scale remote sensing data.

[0039] S2: Plot selection and standardized plot layout: Select flat plots with typical soil texture, construct embankment plots that include test areas and protection areas to ensure vertical one-dimensional infiltration of water.

[0040] The standardized area mentioned in step S2 is as follows: a 2m×2m square outer embankment is constructed with the sensor installation point as the center. The embankment is 30cm high and 30cm wide at the bottom. A 1m×1m inner frame with a soil depth of 20cm is set in the center of the outer embankment. The area inside the frame is the test area, and the area outside the frame to the outer embankment is the protection area.

[0041] Specifically, S2 involves selecting a flat plot of land with typical soil texture (including sandy soil, loam, clay, etc.) as the test plot. A 2m × 2m square outer embankment is constructed centered on the location of the tubular automatic monitoring instrument. The embankment is 30cm high and 30cm wide at the base, and the soil used for its construction is taken from outside the embankment to avoid disturbing the soil within the test area. A 1m × 1m square wooden frame is installed in the center of the inner embankment, buried 20cm deep. The area inside the frame is the test area, and the area between the frame and the outer embankment is the protection area. This standardized plot structure ensures vertical one-dimensional infiltration of water into the test area during irrigation, preventing lateral seepage interference and providing boundary conditions for the accurate establishment of field capacity.

[0042] S3: Sensor installation and remote sensing ground control point deployment. The sensor to be evaluated and the high-precision reference sensor are buried in the test area, and ground control markers for geometric correction of remote sensing images are deployed to achieve spatial registration of ground measurement data and UAV remote sensing images.

[0043] S3 specifically involves: burying the tubular automatic monitoring instrument to be evaluated within the test area, ensuring its measurement area is centered within the test area. Simultaneously, burying 2-3 Trime tubes within the test area as technical repeaters to obtain independent reference values ​​for soil moisture profiles. Probe-type sensors can be optionally buried within the test area. Ground control markers for remote sensing image geometric correction are placed at the four corners of the test area to ensure spatial registration accuracy between UAV imagery and ground measurement data is better than pixel-level. After all sensors are buried, initial readings are recorded, and the area is allowed to settle until soil disturbance recovers.

[0044] S4: Establishment of standardized field water holding capacity and remote sensing monitoring of irrigation process. Based on the water balance formula, the irrigation volume is calculated and designed. The test area and the protected area are irrigated in layers. At the same time, the soil surface water stains are collected at high frequency by UAV to invert the water infiltration and transport process.

[0045] The water balance formula mentioned in step S4 is: Q = K × (θ_f) c -θ1)×S×H / 100, where Q is the design irrigation volume, K is the water guarantee coefficient, and θ_f c The empirical field water holding capacity is θ1, the weighted average soil profile moisture content before irrigation is θ1, the area of ​​the test area is S, and the measurement depth is H. During irrigation, a 5cm water layer is first established in the protected area, and then water is slowly poured into the test area until the designed water volume is used up while maintaining a 5cm water layer.

[0046] In step S4, the drone collects data at a height of 20–50 meters and at a time interval of 30 minutes. The distribution, boundaries, and grayscale values ​​of water stain areas are extracted through image recognition, and a model for inverting water stain image features and surface soil moisture content is constructed.

[0047] S4 specifically involves: First, measuring the soil moisture content θ1 of each layer in the soil profile before irrigation using an embedded automatic monitoring instrument, and calculating the weighted average value within the measurement depth H. Then, selecting the empirical field capacity θ_f based on the target soil texture. c The modified water balance formula Q=K×(θ_f) is adopted. cThe design irrigation volume is calculated as -θ1)×S×H / 100, where S is the area of ​​the test area (1m²), and K is the water guarantee coefficient (taken as 2.0) to ensure sufficient saturation of the profile. Before irrigation, dry grass or straw is evenly laid on the surface of the test area and the protected area to prevent erosion. First, water is rapidly irrigated into the protected area to establish a 5cm water layer, and then water is slowly irrigated into the test area until all water is used up, maintaining a 5cm water layer in the test area. The key feature is that after the irrigation begins and before the surface water recedes completely, a drone is launched to acquire aerial images of the test area at a specific altitude (20-50 meters) and fixed shooting position along a preset route at a high frequency (e.g., once every 30 minutes). The distribution range, boundary contour, and shadow depth gray value of the water stain area on the soil surface are extracted by image recognition technology, and an empirical inversion model of water stain image features and surface soil moisture content is constructed to realize the spatiotemporal dynamic tracking of the surface soil water infiltration and horizontal transport process.

[0048] S5: Surface cover and moisture redistribution: Double-layer cover of straw and plastic film is used to block soil evaporation and precipitation interference, and the soil is left to stand until the soil moisture reaches the stable state of field water holding capacity.

[0049] In step S5, the settling time is set according to the soil texture: 1-2 days for sandy soil, 2-3 days for loam, and 3-4 days for clay. The stability criterion is that the daily change rate of soil moisture is <1%.

[0050] S5 specifically involves: After irrigation and initial aerial photography, covering the test and protected areas with dry grass / straw and then plastic film in sequence. The plastic film can be covered with more straw to enhance insulation and prevent evaporation. This covering measure is used to completely block soil evaporation and external precipitation interference. Afterwards, a water redistribution and settling phase is initiated, allowing soil moisture to naturally tend towards a stable field capacity under the influence of gravity and matrix potential gradients. Depending on the soil texture, the settling time is generally 1-2 days for sandy soil, 2-3 days for loam, and 3-4 days for clay. Stability is determined by a moisture change rate below a set threshold (e.g., daily change rate <1%).

[0051] S6: Multi-source data acquisition, synchronously acquire profile moisture data of the sensor under evaluation and high-precision reference sensor, acquire multi-temporal UAV remote sensing water stain fading images according to the set time phase, and supplement with drying method measurement values ​​as the true moisture value.

[0052] In step S6, the high-precision reference sensor uses bidirectional measurement to take the average value, the sensor to be evaluated is high-frequency automatic acquisition, and the UAV remote sensing time phase is set to 6h, 12h, 24h, 48h, and 72h after watering.

[0053] S6 specifically involves: The initial measurement time is determined based on soil texture, using the Trime sensor to measure field water holding capacity daily starting 24 hours after irrigation, until the moisture content of each layer stabilizes. The Trime sensor performs bidirectional measurements in both east-west and north-south directions each time it measures, and the arithmetic mean of the two readings is taken as the representative value of the moisture content for that layer to eliminate the influence of soil spatial variability and sensor directionality. The tubular automatic monitoring instrument is set to a high-frequency automatic acquisition mode (e.g., once per hour) to completely record data from the start of irrigation to the stabilization of water redistribution. The probe-type sensor requires data to be read only after the soil has undergone at least one crop growing season of natural settling to eliminate the influence of installation disturbance. Simultaneously, layered soil samples obtained by drying are used as the ultimate standard for determining the "true value" of soil moisture content, used to calibrate and verify all sensors. The key feature is that during the water redistribution process, multiple UAV remote sensing monitoring time phases (e.g., 6h, 12h, 24h, 48h, and 72h after irrigation) are set according to the water infiltration and receding patterns, simultaneously acquiring image sequences of the water receding process on the soil surface at different times. By comparing and analyzing multi-temporal remote sensing images, characteristic parameters of the soil surface water stain area decay curve and the surface soil moisture receding rate were extracted.

[0054] S7: Comprehensive evaluation of sensor accuracy and response sensitivity. The static measurement error of the sensor under evaluation is calculated based on the high-precision reference sensor data during the stable period of field water holding capacity. The dynamic response sensitivity of the sensor under evaluation is quantified by the correlation analysis between the water stain receding rate and the sensor response curve, and the comprehensive performance evaluation is completed.

[0055] In step S7, the static accuracy qualification criterion is that the volumetric moisture content measurement error is ≤±3%; the dynamic response sensitivity is quantitatively evaluated by calculating the correlation coefficient between the water stain fading rate and the sensor response rate, and the response time lag.

[0056] S7 specifically involves calibrating the Trime reference sensor's measurements using soil moisture content measured by the oven-drying method as a benchmark. Using multi-layer measurements from the Trime sensor during the stable field water holding capacity period as a reference standard, the absolute and relative errors of the water content in each layer of the tubular automatic monitoring instrument are calculated. A measurement error threshold of ±3% (volume water content) under field water holding capacity conditions is set as the criterion for sensor static accuracy qualification. The key feature is the introduction of remote sensing dynamic evaluation indicators. Multi-temporal soil surface water stain regression characteristic parameters acquired by UAVs (such as water stain area decay coefficient and surface water regression half-life) are correlated with the time-varying curves of water content in each layer of the profile monitored by the sensor. By calculating the correlation coefficient between the water stain regression rate and the sensor's response rise / fall rate, as well as the response time lag, the sensor's dynamic response sensitivity to the water infiltration and redistribution process of different soil types (sandy, loam, clay) is quantitatively evaluated. Based on the combined static accuracy and dynamic sensitivity evaluation results, a sensor performance grading standard is established to achieve a systematic evaluation of the comprehensive field performance of the soil moisture sensor.

[0057] To achieve the above method, this invention also provides a soil moisture sensor measurement accuracy evaluation system based on remote sensing technology, comprising: a standardized field test plot unit, including an outer embankment, an inner frame / inner embankment, a test area, and a protection area structure, for establishing a controllable field water holding capacity (FBC) environment; a ground sensor network, including at least one sensor to be evaluated, a high-precision reference sensor, and a data acquisition unit, for acquiring dynamic soil moisture data at point and profile scales; a UAV low-altitude remote sensing platform, equipped with high-resolution imaging equipment and a flight path planning module, for acquiring multi-temporal soil surface images of the irrigation process and water redistribution process; and a data processing and analysis module, integrating an automatic field water holding capacity calculation model, a remote sensing image water stain recognition and grayscale inversion model, a sensor error calculation model, a response sensitivity correlation analysis model, and a comprehensive evaluation and grading module; the data processing and analysis module is connected to the ground sensor network and the UAV remote sensing platform respectively, receives and fuses multi-source data, and finally outputs sensor static accuracy indicators, dynamic sensitivity indicators, and a comprehensive performance evaluation report.

[0058] Based on the same idea, this invention also provides a soil moisture sensor measurement accuracy evaluation system based on remote sensing technology, comprising:

[0059] Building Module: Used for sensor selection and system construction, configuring the soil moisture sensor to be evaluated, the high-precision reference sensor, and the UAV remote sensing platform equipped with high-resolution imaging equipment, and building a multi-source data synchronous acquisition system;

[0060] Selection module: Used for sample plot selection and standardized plot layout. Select flat plots with typical soil texture, construct embankment plots that include test areas and protection areas, and ensure vertical one-dimensional water infiltration.

[0061] Deployment module: used for sensor installation and remote sensing ground control point deployment. It embeds the sensor to be evaluated and the high-precision reference sensor in the test area, and deploys ground control markers for geometric correction of remote sensing images to achieve spatial registration of ground measurement data and UAV remote sensing images.

[0062] Detection module: Used for establishing standardized field water holding capacity and remote sensing monitoring of irrigation process. Based on the water balance formula, it calculates and designs irrigation volume, and irrigates the test area and protection area in layers. At the same time, it uses UAVs to collect images of water stains on the soil surface at high frequency to invert the water infiltration and transport process.

[0063] Redistribution module: Used for surface covering and water redistribution, it uses a double layer of straw and plastic film to block soil evaporation and precipitation interference, and is left to stand until the soil moisture reaches a stable field water holding capacity.

[0064] Acquisition module: Used for multi-source data acquisition, synchronously acquiring profile moisture data from the sensor under evaluation and the high-precision reference sensor, acquiring multi-temporal UAV remote sensing water stain fading images according to the set time phase, and supplementing the drying method measurement values ​​as the true moisture value;

[0065] Evaluation module: Used for comprehensive evaluation of sensor accuracy and response sensitivity. It calculates the static measurement error of the sensor under evaluation based on high-precision reference sensor data during the stable period of field water holding capacity, and quantifies the dynamic response sensitivity of the sensor under evaluation through correlation analysis between water stain receding rate and sensor response curve, thus completing the comprehensive performance evaluation.

[0066] The basic principles of the present invention have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in the present invention are merely examples and not limitations, and should not be considered as essential features of each embodiment of the present invention. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the present invention to the necessity of employing the aforementioned specific details.

[0067] The block diagrams of devices, apparatuses, devices, and systems involved in this invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0068] It should also be noted that in the apparatus, device, and method of the present invention, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions of the present invention.

[0069] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the invention. Therefore, the invention is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0070] It should be understood that the qualifying terms "first", "second", "third", "fourth", "fifth" and "sixth" used in the description of the embodiments of the present invention are only used to more clearly illustrate the technical solutions and are not intended to limit the scope of protection of the present invention.

[0071] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the invention to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method and system for evaluating the measurement accuracy of soil moisture sensors based on remote sensing technology, characterized in that, include: S1: Sensor selection and system construction, configuring soil moisture sensors to be evaluated, high-precision reference sensors, and UAV remote sensing platforms equipped with high-resolution imaging equipment, and constructing a multi-source data synchronous acquisition system; S2: Plot selection and standardized plot layout: Select flat plots with typical soil texture, construct embankment plots that include test areas and protection areas to ensure vertical one-dimensional infiltration of water. S3: Sensor installation and remote sensing ground control point deployment. The sensor to be evaluated and the high-precision reference sensor are buried in the test area, and ground control markers for geometric correction of remote sensing images are deployed to achieve spatial registration of ground measurement data and UAV remote sensing images. S4: Establishment of standardized field water holding capacity and remote sensing monitoring of irrigation process. Based on the water balance formula, the irrigation volume is calculated and designed. Irrigation is carried out in layers in the test area and the protected area. At the same time, high-frequency images of soil surface water stains are collected by UAVs to invert the water infiltration and transport process. S5: Surface cover and moisture redistribution: Double-layer cover of straw and plastic film is used to block soil evaporation and precipitation interference, and the soil is left to stand until the soil moisture reaches the stable state of field water holding capacity. S6: Multi-source data acquisition, synchronously acquire profile moisture data of the sensor under evaluation and high-precision reference sensor, acquire multi-temporal UAV remote sensing water stain fading images according to the set time phase, and supplement with drying method measurement values ​​as the true moisture value. S7: Comprehensive evaluation of sensor accuracy and response sensitivity. The static measurement error of the sensor under evaluation is calculated based on the high-precision reference sensor data during the stable period of field water holding capacity. The dynamic response sensitivity of the sensor under evaluation is quantified by the correlation analysis between the water stain receding rate and the sensor response curve, and the comprehensive performance evaluation is completed.

2. The evaluation method according to claim 1, characterized in that, The standardized area mentioned in step S2 is as follows: a 2m×2m square outer embankment is constructed with the sensor installation point as the center. The embankment is 30cm high and 30cm wide at the bottom. A 1m×1m inner frame with a soil depth of 20cm is set in the center of the outer embankment. The area inside the frame is the test area, and the area outside the frame to the outer embankment is the protection area.

3. The evaluation method according to claim 1, characterized in that, The water balance formula mentioned in step S4 is: Q = K × (θ_f) c -θ1)×S×H / 100, where Q is the design irrigation volume, K is the water guarantee coefficient, and θ_f c The empirical field water holding capacity is θ1, the weighted average soil profile moisture content before irrigation is θ1, the area of ​​the test area is S, and the measurement depth is H. During irrigation, a 5cm water layer is first established in the protected area, and then water is slowly poured into the test area until the designed water volume is used up while maintaining a 5cm water layer.

4. The evaluation method according to claim 1, characterized in that, In step S4, the drone collects data at a height of 20–50 meters with a collection interval of 30 minutes. The distribution, boundaries, and grayscale values ​​of water stain areas are extracted through image recognition, and a model for inverting water stain image features and surface soil moisture content is constructed.

5. The evaluation method according to claim 1, characterized in that, In step S5, the settling time is set according to the soil texture: 1-2 days for sandy soil, 2-3 days for loam, and 3-4 days for clay. The stability criterion is that the daily change rate of soil moisture is <1%.

6. The evaluation method according to claim 1, characterized in that, In step S6, the high-precision reference sensor uses bidirectional measurement to take the average value, the sensor to be evaluated is high-frequency automatic acquisition, and the UAV remote sensing time phase is set to 6h, 12h, 24h, 48h, and 72h after watering.

7. The evaluation method according to claim 1, characterized in that, In step S7, the static accuracy qualification criterion is that the volumetric moisture content measurement error is ≤±3%; the dynamic response sensitivity is quantitatively evaluated by calculating the correlation coefficient between the water stain fading rate and the sensor response rate, and the response time lag.

8. A soil moisture sensor measurement accuracy evaluation system based on remote sensing technology, characterized in that, include: Building Module: Used for sensor selection and system construction, configuring the soil moisture sensor to be evaluated, the high-precision reference sensor, and the UAV remote sensing platform equipped with high-resolution imaging equipment, and building a multi-source data synchronous acquisition system; Selection module: Used for sample plot selection and standardized plot layout. Select flat plots with typical soil texture, construct embankment plots that include test areas and protection areas, and ensure vertical one-dimensional water infiltration. Deployment module: used for sensor installation and remote sensing ground control point deployment. It embeds the sensor to be evaluated and the high-precision reference sensor in the test area, and deploys ground control markers for geometric correction of remote sensing images to achieve spatial registration of ground measurement data and UAV remote sensing images. Detection module: Used for establishing standardized field water holding capacity and remote sensing monitoring of irrigation process. Based on the water balance formula, it calculates and designs irrigation volume, and irrigates the test area and protection area in layers. At the same time, it uses UAVs to collect images of water stains on the soil surface at high frequency to invert the water infiltration and transport process. Redistribution module: Used for surface cover and water redistribution and static setting. It uses a double layer of straw and plastic film to block soil evaporation and precipitation interference, and is set static until the soil moisture reaches a stable field water holding capacity. Acquisition module: Used for multi-source data acquisition, synchronously acquiring profile moisture data from the sensor under evaluation and the high-precision reference sensor, acquiring multi-temporal UAV remote sensing water stain fading images according to the set time phase, and supplementing the drying method measurement values ​​as the true moisture value; Evaluation module: Used for comprehensive evaluation of sensor accuracy and response sensitivity. It calculates the static measurement error of the sensor under evaluation based on high-precision reference sensor data during the stable period of field water holding capacity, and quantifies the dynamic response sensitivity of the sensor under evaluation through correlation analysis between water stain receding rate and sensor response curve, thus completing the comprehensive performance evaluation.

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