A method for arranging a soil moisture device in a crop irrigation area in a typical hilly terrain in the south of China

Abstract

The application discloses a kind of south typical hilly terrain irrigation area crop soil moisture condition equipment layout method, comprising the following steps: obtaining south hilly terrain irrigation area remote sensing image, carry out semi-supervised classification in combination with field sampling results, interpret and form irrigation area crop structure distribution map A;According to irrigation area crop structure distribution map A, adopt field investigation and handling, form fine irrigation area crop structure distribution map B;South hilly terrain irrigation area crop is subdivided, and the distribution of each partition typical crop is counted;According to block crop planting importance order, according to primary classification, successively guarantee block crop soil moisture condition monitoring station site layout;According to soil moisture condition equipment layout distribution diagram, site location that meets layout requirement is found;Field detection station site communication signal, guarantee data transmission;The application focuses on soil moisture condition equipment layout work, forms differentiated results in the field of soil moisture condition site selection and planning, provides certain reference value for newly-built irrigation area soil moisture condition site selection.

Description

A method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China Technical Field

[0001] This invention relates to the field of soil moisture monitoring equipment deployment technology, and in particular to a method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China. Background Technology

[0002] Soil moisture refers to the water content in the topsoil layer of crops. Soil moisture is influenced by atmospheric conditions, soil type, and vegetation, reflecting the water supply to crops at various growth stages. It directly affects crop growth and harvest. Therefore, studying and analyzing the distribution and variation patterns of soil moisture in the crop root zone is of significant reference value for the rational allocation of water resources, ensuring high and stable crop yields, and constructing water-saving, modern irrigation districts.

[0003] Currently, existing technologies have the following drawbacks and shortcomings: For example, the "A method, device and storage medium for planning soil moisture monitoring stations considering hydrological characteristics" [application number: CN202310026778.9] extracts basic geomorphological features of the watershed, obtains watershed zoning maps, draws soil moisture content zoning maps based on satellite remote sensing and soil moisture data, and then plans the site selection of soil moisture monitoring stations. It also optimizes the site selection of soil moisture monitoring stations by combining the underlying soil type and land use type. However, it requires a large amount of basic data to be obtained in the early stage and needs to have historical data of soil moisture monitoring stations. It is suitable for continued construction of supporting irrigation areas, but not for newly built smart irrigation areas. The application "A Comprehensive Agricultural Monitoring System and Device Based on GNSS and Multi-Sensor Fusion" [Application No.: CN202211445025.3] proposes using multi-source sensors to collect data and transmitting it via BeiDou satellite. However, BeiDou coverage in the hilly and mountainous areas of southern China is mainly concentrated in natural settlements in villages and towns, while soil moisture monitoring equipment is mostly deployed in remote fields. Furthermore, due to the complex underlying surface structure in mountainous areas, full coverage is difficult to achieve, and the cost is considerable. The application "An Online Soil Moisture Monitor Equipped with 5G Communication" [Application No.: CN202320834524.5] proposes using 5G communication for data transmission, but it does not consider the problem of insufficient base station signal coverage in the hilly and mountainous areas of southern China, resulting in data transmission failures after actual equipment deployment. Summary of the Invention

[0004] The purpose of this invention is to overcome the above-mentioned shortcomings and provide a method for the layout of crop moisture monitoring equipment in irrigation areas with typical hilly terrain in southern China. This method focuses on the layout of moisture monitoring equipment and achieves differentiated results in the field of moisture monitoring station site selection and planning, providing certain reference value for the site selection of moisture monitoring stations in newly built irrigation areas.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China, comprising the following steps:

[0006] Step 1: Acquire remote sensing images of irrigation areas in the hilly terrain of southern China, combine them with field sampling results to carry out semi-supervised classification, and interpret them to form crop structure distribution map A of the irrigation area;

[0007] Step 2: Based on the crop structure distribution map A of the irrigation area, conduct on-site surveys to generate a detailed crop structure distribution map B of the irrigation area;

[0008] Step 3: Based on the existing engineering zoning of the irrigation area and the existing basic conditions of the agricultural demonstration base, the crops in the southern hilly irrigation area are subdivided, and the typical crops and their distribution in each zone are statistically analyzed.

[0009] Step 4: Based on the importance of crop planting in each block, ensure the deployment of soil moisture monitoring stations for crops in each block according to the first-level classification.

[0010] Step 5: Based on the general map of soil moisture monitoring equipment deployment, locate the sites that meet the deployment requirements on-site;

[0011] Step 6: On-site testing of the station's communication signal. If there is no signal or a weak signal, which cannot meet the requirements, use a wireless bridge, repeater, or signal amplifier to bridge the signal and ensure data transmission.

[0012] Preferably, in step 1, after acquiring remote sensing images of the irrigation area in the hilly terrain of southern China, data collection and preprocessing are carried out, and crop sampling and labeling are performed in all major crop planting areas of the irrigation area. The sampling area is selected with a crop coverage of not less than 5 mu and flat plots with clear boundaries.

[0013] Preferably, the preprocessing involves radiometric calibration, atmospheric correction, orthorectification, image fusion, image mosaicking, and image cropping steps to form preprocessed data, including:

[0014] Radiometric calibration converts the digital quantization (DN) value of an image into a radiance value. The calculation formula is as follows:

[0015] L λ =Gain × DN + Offset

[0016] In the formula: L λ The radiance value is W / (m²). 2 (μm·sr); Gain is the sensor incremental correction coefficient; Offset is the sensor correction deviation; DN is the pixel gray value;

[0017] Atmospheric correction eliminates the influence of water vapor, oxygen, and carbon dioxide in the surface atmosphere on the reflection of surface features in images. The calculation formula is as follows:

[0018]

[0019] Where: L is the total radiance received by the sensor processing element; ρ is the pixel surface reflectivity; ρ e Let S be the average surface reflectance around the pixel, and L be the albedo of the balloon surface. α This refers to the atmospheric backscattered emissivity, i.e., atmospheric path radiation.

[0020] Orthorectification is used to perform geometric correction on remote sensing images, eliminating geometric distortion and achieving accurate matching with the actual location of ground targets.

[0021] Image fusion combines low spatial resolution multispectral images with high spatial resolution panchromatic images to generate high spatial resolution multispectral images, improving the visual effect of the images and facilitating visual interpretation and analysis.

[0022] The mosaicking process involves stitching together multiple remote sensing images of the project's coverage area using geographic coordinate-based image mosaicking.

[0023] Image preprocessing is completed by cropping the mosaicked image using the boundary vector file of the study area.

[0024] Preferably, in step 1, the semi-supervised classification based on field sampling results to interpret and form the crop structure distribution map A of the irrigation area includes the following process:

[0025] The vegetation index is calculated using the Normalized Difference Vegetation Index (NDVI) to eliminate radiation errors and enhance the response capability of vegetation. The NDVI calculation formula is as follows:

[0026]

[0027] In the formula: NIR is the reflectance value in the near-infrared band, and R is the reflectance value in the infrared band;

[0028] Training samples should be typical and representative, and should contain as few mixed pixels as possible. The number of training samples should meet the minimum sample size, and the sample reference data and classification data should be as close as possible in time.

[0029] The sample classification was evaluated using the Kappa coefficient. For samples with a coefficient less than 0.85, the samples were retrained until the Kappa coefficient was not lower than 0.85.

[0030] Preferably, step 2 specifically involves: based on the crop structure distribution map A of the irrigation area, conducting on-site surveys of the crop structure in the irrigation area, verifying the accuracy of crop labeling and distribution, correcting any incorrect crop distributions, and generating a refined crop structure distribution map B of the irrigation area.

[0031] Preferably, in step 3, the crops in the irrigation areas of the southern hilly terrain are subdivided into conventional crops and cash crops. Conventional crops are dryland crops, and cash crops are seedlings and agricultural demonstration bases.

[0032] Preferably, when ranking the importance of crops planted in a block, the importance ranking is: agricultural demonstration base > seedling crops > dryland crops. The classification principle is as follows: for agricultural demonstration bases with a concentrated area of ​​more than 5,000 mu, the principle is to set up no less than one set of soil moisture monitoring equipment per 1,000 mu, and to distribute them evenly according to the proportion of crop planting area. For seedling crops, according to the engineering zoning, the principle is to ensure that no less than one set of soil moisture monitoring equipment is set up per 10,000 mu in each zone, and to distribute them evenly. For dryland crops, according to the engineering zoning, the principle is to ensure that no less than one typical crop soil moisture monitoring station is set up in each zone, and to distribute them evenly. Finally, the number of soil moisture monitoring stations and their preset locations are determined.

[0033] Preferably, during the layout, since the boundaries of the fields are uneven, the geometric center is used as the center point for uniform layout. The formula for calculating the geometric center is:

[0034]

[0035]

[0036] In the formula, Aix represents the x-coordinate of the i-th vertex, and Aiy represents the y-coordinate of the i-th vertex.

[0037] Preferably, step 5 specifically comprises:

[0038] Within the irrigation district, locations within a 1km coverage area that are flat, with little variation in soil type and topographic conditions, and more than 200m away from tall buildings, roads, rivers, reservoirs, and large canals are identified to form a distribution map of potential locations for soil moisture monitoring stations.

[0039] Elevation and slope maps are generated based on DEM data with a resolution of 30m or higher for the study area. Vector files S1 are then cropped from areas with elevation fluctuations not exceeding 10m and slope changes not exceeding 1.5 degrees.

[0040] Generate overlay vector graphics of buildings, roads, rivers, and hydraulic structures, and sequentially generate buffer vector files with a radius of 200m, namely S2, S3, S4, and S5;

[0041] A 1km buffer zone S6 is generated centered on a preset location. The intersection of S6 with S2, S3, S4, and S5 is inverted to generate S7. The intersection of S7 with S1 generates S8. S8 is a distribution map of optional locations for soil moisture monitoring stations.

[0042] Preferably, step 6 specifically comprises:

[0043] When conducting signal testing of soil moisture monitoring equipment, if the signal is too weak to meet the transmission rate, the signal coverage area can be expanded by a base station near the village using signal amplifiers and repeaters, with an effective area of ​​up to 5km. If the soil moisture monitoring station is far from the village or the signal base station area of ​​the communication service provider, a wireless bridge can be used for medium- and long-distance signal transmission, with an effective area of ​​5-30km. If there is no signal and the surrounding area is far from the base station signal, Beidou equipment can be used for signal transmission to ensure data transmission quality. Finally, the location where the signal meets the transmission rate is selected as the deployment location of the soil moisture monitoring station.

[0044] Beneficial effects of this invention:

[0045] 1. This method focuses on the deployment of soil moisture monitoring equipment, and has achieved differentiated results in the field of soil moisture monitoring station site selection and planning, providing certain reference value for soil moisture monitoring site selection in newly built irrigation areas.

[0046] 2. This method proposes a reference path for the site selection and implementation of soil moisture monitoring stations. It is easy to implement and can easily form relevant site selection guidance documents. It can be effectively implemented in the work process and improve work efficiency.

[0047] 3. This method is simple in principle and has a wide range of applications, and can be widely promoted in the hilly irrigation areas of southern China. Attached Figure Description

[0048] Figure 1 is a flowchart illustrating a method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China. Detailed Implementation

[0049] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0050] As shown in Figure 1, a method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China includes the following steps:

[0051] Step 1: Acquire remote sensing images of irrigation areas in the hilly terrain of southern China, combine them with field sampling results to carry out semi-supervised classification, and interpret them to form crop structure distribution map A of the irrigation area;

[0052] Step 2: Based on the crop structure distribution map A of the irrigation area, conduct on-site surveys to generate a detailed crop structure distribution map B of the irrigation area;

[0053] Step 3: Based on the existing engineering zoning of the irrigation area and the existing basic conditions of the agricultural demonstration base, the crops in the southern hilly irrigation area are subdivided according to the format in Table 1, and the typical crops and distribution of each zone are statistically analyzed.

[0054] Table 1 Crop Structure Classification Table

[0055] Primary Classification: Dryland Crops (Conventional Crops), Seedling Crops (Cash Crops), Agricultural Demonstration Bases (Cash Crops) Secondary Classification: Z 11 Z 12 Z 13 Z 14 Z 15 Wait for Z 21 Z 22 Z 23 Z 24 Z 25 Wait for Z 31 Z 32 Z 33 Z 34 Z 35 surface

[0056] Step 4: Based on the importance of crop planting in each block, ensure the deployment of soil moisture monitoring stations for crops in each block according to the first-level classification.

[0057] Step 5: Based on the general map of soil moisture monitoring equipment deployment, locate the sites that meet the deployment requirements on-site;

[0058] Step 6: On-site testing of the station's communication signal. If there is no signal or a weak signal, which cannot meet the requirements, use a wireless bridge, repeater, or signal amplifier to bridge the signal and ensure data transmission.

[0059] Preferably, in step 1, after acquiring remote sensing images of the irrigation area in the hilly terrain of southern China, data collection and preprocessing are carried out, and crop sampling and labeling are performed in all major crop planting areas of the irrigation area. The sampling area is selected with a crop coverage of not less than 5 mu and flat plots with clear boundaries.

[0060] Preferably, the preprocessing involves radiometric calibration, atmospheric correction, orthorectification, image fusion, image mosaicking, and image cropping steps to form preprocessed data, including:

[0061] Radiometric calibration converts the digital quantization (DN) value of an image into a radiance value. The calculation formula is as follows:

[0062] L λ =Gain × DN + Offset

[0063] In the formula: L λ The radiance value is W / (m²). 2 (μm·sr); Gain is the sensor incremental correction coefficient; Offset is the sensor correction deviation; DN is the pixel gray value;

[0064] Atmospheric correction eliminates the influence of water vapor, oxygen, and carbon dioxide in the surface atmosphere on the reflection of surface features in images. The calculation formula is as follows:

[0065]

[0066] Where: L is the total radiance received by the sensor processing element; ρ is the pixel surface reflectivity; ρ e Let S be the average surface reflectance around the pixel, and L be the albedo of the balloon surface. α This refers to the atmospheric backscattered emissivity, i.e., atmospheric path radiation.

[0067] Orthorectification is used to perform geometric correction on remote sensing images, eliminating geometric distortion and achieving accurate matching with the actual location of ground targets.

[0068] Image fusion combines low spatial resolution multispectral images with high spatial resolution panchromatic images to generate high spatial resolution multispectral images, improving the visual effect of the images and facilitating visual interpretation and analysis.

[0069] The mosaicking process involves stitching together multiple remote sensing images of the project's coverage area using geographic coordinate-based image mosaicking.

[0070] Image preprocessing is completed by cropping the mosaicked image using the boundary vector file of the study area.

[0071] Preferably, in step 1, the semi-supervised classification based on field sampling results to interpret and form the crop structure distribution map A of the irrigation area includes the following process:

[0072] The vegetation index is calculated using the Normalized Difference Vegetation Index (NDVI) to eliminate radiation errors and enhance the response capability of vegetation. The NDVI calculation formula is as follows:

[0073]

[0074] In the formula: NIR is the reflectance value in the near-infrared band, and R is the reflectance value in the infrared band;

[0075] Training samples should be typical and representative, and should contain as few mixed pixels as possible. The number of training samples should meet the minimum sample size, and the sample reference data and classification data should be as close as possible in time.

[0076] The sample classification was evaluated using the Kappa coefficient. For samples with a coefficient less than 0.85, the samples were retrained until the Kappa coefficient was not lower than 0.85.

[0077] Preferably, step 2 specifically involves: based on the crop structure distribution map A of the irrigation area, conducting on-site surveys of the crop structure in the irrigation area, verifying the accuracy of crop labeling and distribution, correcting any incorrect crop distributions, and generating a refined crop structure distribution map B of the irrigation area.

[0078] Preferably, in step 3, the crops in the irrigation area of ​​the southern hilly terrain are subdivided into conventional crops and cash crops. Conventional crops are dryland crops, and cash crops are seedling crops and agricultural demonstration bases. For example, Irrigation area M is located in the southern region. The irrigation area generally presents a typical erosion-structured hilly and mountainous landform. The irrigation area has carried out water-saving irrigation area construction and agricultural demonstration bases in many places. In terms of engineering, it presents a management model of zoned management and unified scheduling. The crops are mainly divided into dryland conventional crops, seedling cash crops and greenhouse cash crops (i.e., agricultural demonstration bases). Dryland cash crops mainly include sweet potatoes and peanuts, seedling cash crops mainly include navel oranges and hawthorns, and greenhouse cash crops mainly include peppers, tomatoes and strawberries, as shown in Table 2. The typical crops and their distribution are further subdivided according to the zones.

[0079] Table 2M Irrigation District Crop Structure Classification Table

[0080] Primary Classification: Dryland Crops (Conventional Crops), Seedling Crops (Cash Crops), Agricultural Demonstration Bases (Cash Crops) Secondary Classification: Rice, Peanuts, Sweet Potatoes, Navel Oranges, Hawthorns, Peppers, Tomatoes, Strawberries surface

[0081] Preferably, when ranking the importance of crops planted in a block, the importance ranking is: agricultural demonstration base > seedling crops > dryland crops. The classification principle is as follows: for agricultural demonstration bases with a concentrated area of ​​more than 5,000 mu, the principle is to set up no less than one set of soil moisture monitoring equipment per 1,000 mu, and to distribute them evenly according to the proportion of crop planting area. For seedling crops, according to the engineering zoning, the principle is to ensure that no less than one set of soil moisture monitoring equipment is set up per 10,000 mu in each zone, and to distribute them evenly. For dryland crops, according to the engineering zoning, the principle is to ensure that no less than one typical crop soil moisture monitoring station is set up in each zone, and to distribute them evenly. Finally, the number of soil moisture monitoring stations and their preset locations are determined.

[0082] Preferably, during the layout, since the boundaries of the fields are uneven, the geometric center is used as the center point for uniform layout. The formula for calculating the geometric center is:

[0083]

[0084]

[0085] In the formula, Aix represents the x-coordinate of the i-th vertex, and Aiy represents the y-coordinate of the i-th vertex.

[0086] Preferably, step 5 specifically comprises:

[0087] Within the irrigation district, locations within a 1km coverage area that are flat, with little variation in soil type and topographic conditions, and more than 200m away from tall buildings, roads, rivers, reservoirs, and large canals are identified to form a distribution map of potential locations for soil moisture monitoring stations.

[0088] Elevation and slope maps are generated based on DEM data with a resolution of 30m or higher for the study area. Vector files S1 are then cropped from areas with elevation fluctuations not exceeding 10m and slope changes not exceeding 1.5 degrees.

[0089] Generate overlay vector graphics of buildings, roads, rivers, and hydraulic structures, and sequentially generate buffer vector files with a radius of 200m, namely S2, S3, S4, and S5;

[0090] A 1km buffer zone S6 is generated centered on a preset location. The intersection of S6 with S2, S3, S4, and S5 is inverted to generate S7. The intersection of S7 with S1 generates S8. S8 is a distribution map of optional locations for soil moisture monitoring stations.

[0091] Preferably, step 6 specifically comprises:

[0092] When conducting signal testing of soil moisture monitoring equipment, if the signal is too weak to meet the transmission rate, the signal coverage area can be expanded by a base station near the village using signal amplifiers and repeaters, with an effective area of ​​up to 5km. If the soil moisture monitoring station is far from the village or the signal base station area of ​​the communication service provider, a wireless bridge can be used for medium- and long-distance signal transmission, with an effective area of ​​5-30km. If there is no signal and the surrounding area is far from the base station signal, Beidou equipment can be used for signal transmission to ensure data transmission quality. Finally, the location where the signal meets the transmission rate is selected as the deployment location of the soil moisture monitoring station.

[0093] The above embodiments are merely preferred technical solutions of the present invention and should not be considered as limitations on the present invention. The scope of protection of the present invention should be limited to the technical solutions described in the claims, including equivalent substitutions of the technical features described in the claims. That is, equivalent substitutions and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China, characterized by: The process includes the following steps: Step 1: Acquire remote sensing images of the irrigation area in the hilly terrain of southern China, and conduct semi-supervised classification based on field sampling results to interpret and generate a crop structure distribution map A for the irrigation area; Step 2: Based on the crop structure distribution map A, conduct field surveys to generate a refined crop structure distribution map B for the irrigation area; Step 3: Based on the existing engineering zoning of the irrigation area and the existing basic conditions of the agricultural demonstration base, further subdivide the crops in the irrigation area of ​​the hilly terrain of southern China, and statistically analyze the typical crops and their distribution in each zone; Step 4: According to the importance of crop planting in each block, monitor soil moisture in each block according to the first-level classification. Step 5: Based on the general distribution map of soil moisture monitoring equipment, locate site locations that meet the deployment requirements; Step 6: Test the communication signal of the sites on-site. If there is no signal or a weak signal, it is difficult to meet the requirements. Use wireless bridges, repeaters, or signal amplifiers to bridge the signal and ensure data transmission; Step 2 specifically involves: Based on the crop structure distribution map A of the irrigation area, conduct an on-site survey of the crop structure of the irrigation area, verify the accuracy of crop labeling and distribution, correct any incorrect crop distributions, and form a refined crop structure distribution map B of the irrigation area; In Step 3, the southern hill The crops in the hilly irrigation area are subdivided into conventional crops and cash crops. Conventional crops are dryland crops, while cash crops include seedlings and agricultural demonstration bases. When ranking crops by importance in a block, the order is: agricultural demonstration bases > seedlings > dryland crops. The classification principle is as follows: For agricultural demonstration bases of 5,000 mu or more, at least one soil moisture monitoring station should be installed per 1,000 mu, evenly distributed according to the proportion of crop planting area. For seedlings, the system should be evenly distributed according to engineering zones, ensuring at least one soil moisture monitoring station per 10,000 mu within each zone. For dryland crops… For crops, according to the engineering zones, ensure that each zone has at least one typical crop soil moisture monitoring station and that they are evenly distributed, and finally determine the number of moisture monitoring stations and their preset locations; Step 5 specifically involves: finding locations within the irrigation area that are flat, with basically unchanged soil type and terrain conditions, and more than 200m away from tall buildings, roads, rivers, reservoirs and large canals, within a 1km coverage area, to form a distribution map of possible moisture monitoring station locations; generating elevation and slope maps based on DEM data of 30m resolution and above for the study area, cropping elevation fluctuations not exceeding 10m and slope changes not exceeding 1.A vector file S1 for a 5-degree area is generated; a vector map overlaid with buildings, roads, rivers, and hydraulic structures is generated, and buffer vector files with a radius of 200m are generated sequentially, namely S2, S3, S4, and S5; a buffer zone S6 with a preset location is generated with a 1km center; S6 and S2, S3, S4, and S5 are intersected and inverted to generate S7; S7 and S1 are intersected to generate S8; S8 is the distribution map of optional locations for soil moisture monitoring stations; Step 6 specifically involves: conducting signal testing of soil moisture monitoring equipment. When the signal is weak and the transmission rate is difficult to meet, the signal coverage area can be expanded by a base station near the natural village through signal amplifiers and repeater equipment, with an effective area of ​​up to 5km. When the soil moisture monitoring station is far from the natural village or the signal base station area of ​​the communication service provider, a wireless bridge can be used for medium and long-distance signal transmission, with an effective area of ​​5-30km. When there is no signal and the surrounding area is far from the base station signal, Beidou equipment can be used for signal transmission to ensure data transmission quality. Finally, a location where the signal meets the transmission rate is selected as the deployment location of the soil moisture monitoring station. .

2. The method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China according to claim 1, characterized in that: In step 1, after acquiring remote sensing images of irrigation areas in hilly terrain in southern China, data collection and preprocessing are carried out. Crop sampling and labeling are performed in all major crop categories planted in the irrigation area. The sampling area is selected with a crop coverage of no less than 5 mu (approximately 0.33 hectares) and with flat plots and clear boundaries.

3. The method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China according to claim 2, characterized in that: Preprocessing involves radiometric calibration, atmospheric correction, orthorectification, image fusion, image mosaicking, and image cropping to generate preprocessed data. This includes converting the digital quantization (DN) values ​​of the image into radiance values ​​through radiometric calibration, calculated using the following formula: In the formula: L λ The radiance value is W / (m²). 2 (·μm·sr); Gain is the sensor incremental correction coefficient; Offset is the sensor correction deviation; DN is the pixel gray value; Atmospheric correction eliminates the influence of water vapor, oxygen, and carbon dioxide in the surface atmosphere on the reflection of surface features in the image. The calculation formula is as follows: In the formula: L is the total radiance received by the sensor processing element; The surface reflectance of a pixel; Let S be the average surface reflectance around the pixel, and S be the albedo of the balloon surface. The atmospheric backscattered radiance, or atmospheric path radiance, is used. Orthorectification is applied to the remote sensing images to perform geometric correction, eliminating geometric distortion and achieving accurate matching with the actual locations of ground targets. Image fusion combines low spatial resolution multispectral images with high spatial resolution panchromatic images to generate high spatial resolution multispectral images, improving the visual effect and facilitating visual interpretation and analysis. Geographic coordinate-based image mosaicking stitches together multiple remote sensing images of the project coverage area. Finally, the mosaicked images are cropped using the boundary vector file of the study area, completing the image preprocessing.

4. The method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China according to claim 1, characterized in that: In step 1, the semi-supervised classification based on field sampling results is interpreted to form the crop structure distribution map A of the irrigation area, which includes the following process: The vegetation index is calculated using the Normalized Difference Vegetation Index (NDVI) to eliminate radiation errors and enhance the response capability of vegetation. The NDVI calculation formula is as follows: In the formula: NIR is the reflectance value of the near-infrared band, and R is the reflectance value of the infrared band; Sample training should be carried out. The training samples should be typical and representative, and should contain no other mixed pixels as much as possible. The training samples should meet the minimum number of samples, and the sample reference data and classification data should be as close as possible in time; Sample classification evaluation should be carried out, and the classification results should be evaluated by using the Kappa coefficient. For the classification samples with a coefficient less than 0.85, the samples should be retrained until the kappa coefficient is not lower than 0.

85.

5. The method for deploying crop soil moisture monitoring equipment in a typical hilly irrigation area in southern China according to claim 1, characterized in that: During the layout process, since the boundaries of the fields are irregular, the geometric center is used as the center point for uniform layout. The formula for calculating the geometric center is: ； In the formula, Aix represents the x-coordinate of the i-th vertex, and Aiy represents the y-coordinate of the i-th vertex.

Images