An apparatus and method for monitoring arable land degradation

Abstract

This invention discloses an apparatus and method for monitoring farmland degradation. The apparatus includes a field domain, a mobile domain, and a central domain. The method involves: acquiring the vegetation cover index T; acquiring the soil fertility index M; acquiring the land environment index S; calculating the degraded farmland monitoring index TH; and assessing the farmland degradation status. This invention constructs a three-level node system for farmland degradation monitoring: a central domain, a mobile domain, and a field domain, collecting and storing farmland monitoring data from multiple perspectives, thus improving the long-term and real-time nature of data acquisition. Using the collected and stored farmland monitoring data, a farmland degradation monitoring model is built to calculate the vegetation cover index, soil fertility index, and land environment index of the farmland, and based on this, a final farmland degradation index is formed, enabling an assessment of the latest status of degraded farmland.

Description

Technical Field

[0001] This invention relates to the field of agricultural scientific research technology, and in particular to an apparatus and method for monitoring farmland degradation. Background Technology

[0002] Currently, monitoring of degraded arable land refers to the dynamic observation and evaluation of the distribution, type, degree, causes, and impacts of degraded arable land using methods such as remote sensing, geographic information systems, and soil surveys.

[0003] However, due to the lack of a unified definition and standard for degraded arable land, the methods and indicators used for monitoring vary greatly, the monitoring indicators are not comprehensive, and the data is difficult to integrate and compare. This results in insufficient ability to integrate and analyze multi-source monitoring data, making it impossible to comprehensively collect various indicators of arable land from multiple dimensions such as "sky, air, and land," and consequently, it is impossible to accurately reveal the mechanism and factors of arable land degradation.

[0004] In addition, due to the power consumption limitations of monitoring equipment, monitoring cannot be carried out continuously in remote and isolated areas where infrastructure construction such as electricity is lagging behind. Furthermore, since most existing solutions have sensors with built-in Internet connection modules, the price is relatively high, making land monitoring expensive. The sensors also have poor stability, and due to funding constraints, large-scale promotion is not possible. This results in limited data acquisition and insufficient continuity of farmland monitoring. Consequently, the continuity of monitoring data is limited, and without long-term, continuous data, it is difficult to reflect the spatiotemporal changes and dynamic evolution of farmland. Summary of the Invention

[0005] The purpose of this invention is to provide an apparatus and method for monitoring arable land degradation. This invention has the advantage of enabling comprehensive and long-term monitoring and acquisition of arable land data for evaluation.

[0006] The technical solution of the present invention: a device for monitoring farmland degradation, comprising a field domain, a mobile domain, and a central domain;

[0007] The field area is the data acquisition section, used to collect various field data; the field area is located in the field and includes various sensors for data acquisition, corresponding controllers and data transmission modules;

[0008] The mobile domain is the transportation section, used to move between various field domains to conduct data interaction and information collection. The mobile domain includes data collection equipment installed on the mobile device.

[0009] The central domain is the control section, which is used to process the collected data and issue corresponding instructions as needed. The central domain includes a data processing and calculation module and a network communication module.

[0010] In the aforementioned device for monitoring farmland degradation, the field area can collect data on the local plot, including soil temperature, moisture, runoff, and pH value, and record the working status of the sensors.

[0011] The mobile domain can move within the corresponding field domain using mobile devices, connect to the field domain, and collect data gathered from the field domain; it can also use its onboard multispectral equipment to collect near-ground remote sensing data, including crop cover and soil organic matter distribution.

[0012] The central domain can communicate and interact with the mobile domain in real time, make decisions and issue relevant control commands, periodically acquire MODIS and FY3D satellite remote sensing data of the local land, store the collected data, and calculate and predict the farmland degradation situation in the region based on the data.

[0013] A method for monitoring farmland degradation is characterized by: using a degraded farmland monitoring index model to quantitatively assess the farmland degradation status; the degraded farmland monitoring index model includes a vegetation cover index, a soil fertility index, and a land environment index; the degraded farmland monitoring index value obtained from the degraded farmland monitoring index model is a weighted sum of the vegetation cover index, the soil fertility index, and the land environment index.

[0014] The aforementioned method for monitoring arable land degradation includes the following steps:

[0015] A. Obtaining the vegetation cover index T;

[0016] B. Obtaining the soil fertility index M;

[0017] C. Acquisition of the Land Environment Index S;

[0018] D. Calculate the degraded farmland monitoring index TH;

[0019] E. Assess the status of farmland degradation.

[0020] In the aforementioned method for monitoring farmland degradation, the specific steps for obtaining the vegetation cover index T in step A are as follows:

[0021] A1. Using regularly acquired MODIS and FY3D satellite remote sensing images of the central area, calculate the normalized vegetation index (NDI) of the plots within the field area. The formula is as follows:

[0022]

[0023] Among them, NVI i For the normalized vegetation index (PR) of the field area numbered i, i R represents the near-infrared reflectance of the plot of land in the field area with sign i; i Reflectivity in the red band;

[0024] A2. Using the bare soil vegetation constant and total vegetation cover constant of the study plot estimated empirically, calculate the vegetation cover index of the plot in the field area. The formula is:

[0025]

[0026] Among them, T i NVI is the vegetation cover index of the field area numbered i. i Let σ be the normalized vegetation index of the field plot numbered i, and σ be the bare soil vegetation constant. Total vegetation cover constant, σ and The value was estimated based on historical remote sensing images of the site.

[0027] A3. Calculate the overall vegetation cover index of the study area using the following formula:

[0028]

[0029] Where T is the vegetation cover index of the study area, and n is the number of field plots in the study area. i is the vegetation cover index of the field area numbered i.

[0030] In the aforementioned method for monitoring farmland degradation, the specific steps for obtaining the soil fertility index M in step B are as follows:

[0031] B1. Using data from multispectral equipment acquired in the mobile domain, calculate the soil fertility index for each plot in a single field area. The formula is as follows:

[0032] M i =X0 + X1 × A i +X2×B i

[0033] Among them, M i A represents the soil fertility index of the plot located in field area numbered i. i B represents the near-infrared reflectance of organic carbon in the soil of field plot i; i X0 represents the reflectance of soil organic carbon in the red light band of field area i; X1, X2 are regression coefficients.

[0034] B2. Calculate the overall soil fertility index of the study area, using the following formula:

[0035]

[0036] Where M is the soil fertility index of the study area, and n is the number of field plots in the study area. iThe soil fertility index is the soil fertility index of the field area numbered i.

[0037] In the aforementioned method for monitoring farmland degradation, the acquisition of the land environmental index S in step C is specifically carried out as follows:

[0038] C1. Using sensor data acquired in the field area, calculate the land environment index of the plot where the individual field area is located, using the following formula:

[0039]

[0040] Among them, C i D i F i H i The values ​​are temperature, moisture, runoff, and soil pH of the plot obtained from field area i; C0, D0, F0, and H0 are the baseline values ​​of temperature, moisture, runoff, and soil pH of the plot in field area i; α is the regression coefficient.

[0041] C2. Calculate the overall land environment index for the study area, using the following formula:

[0042]

[0043] Where S is the land environment index of the study area, and n is the number of field plots in the study area. i The land environmental index is the plot of land in the field area numbered i.

[0044] In the aforementioned method for monitoring farmland degradation, the specific steps for obtaining the degraded farmland monitoring index TH in step D are as follows:

[0045] Based on the vegetation cover index T, soil fertility index M, and land environment index S, the degraded arable land index of the study area is calculated using the following formula:

[0046] TH=γT+βM+δS

[0047] Where TH is the monitoring index of degraded farmland in the study area, T is the vegetation cover index, M is the soil fertility index, S is the land environment index, and γ, β, and δ are weighting coefficients.

[0048] In the aforementioned method for monitoring farmland degradation, the evaluation is based on the obtained farmland degradation monitoring index TH. If the TH value is greater than or equal to the set threshold, the study area can be evaluated as a farmland degradation insignificant area, and the farmland condition is predicted to improve in the future.

[0049] If the TH value is less than the development threshold, the study area can be evaluated as a region of significant farmland degradation, and the farmland condition is predicted to deteriorate in the future.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] 1. The device includes a field domain, a mobile domain, and a central domain. It collects comprehensive data on farmland degradation and has a highly flexible monitoring architecture. Each domain (field domain, mobile domain, and central domain) is independent of the others and uses the cloud for data interaction. The number of domains can be increased, decreased, or merged at will without affecting the overall monitoring performance.

[0052] 2. The design of the monitoring index overcomes the problems of traditional farmland monitoring data analysis being singular and fragmented, and the analysis objectives being one-sided. It can measure the farmland status from multiple aspects such as vegetation, fertility, and environment, quantitatively determine the farmland degradation trend, and realize a more standardized, universal, and easily expandable farmland degradation monitoring data analysis and processing specification. This is of great significance for improving the accuracy and adaptability of farmland degradation monitoring.

[0053] 3. Good economic benefits: Traditional farmland degradation monitoring schemes are based on the model of "sensors with Internet connection modules + remote cloud servers", which is expensive in large-scale monitoring scenarios. In this application, field sensors and field areas do not require Internet connection modules. Monitoring can be carried out using only traditional sensors. The sensor cost is low and no special supporting software is required. The cost of deploying each plot is much lower than the traditional model, which has good economic benefits and can be promoted and applied on a large scale.

[0054] 4. It has good energy efficiency and is suitable for monitoring farmland degradation in remote and isolated areas, thus expanding the monitoring range. Since the field domain and its associated sensors at the end of the monitoring do not require frequent remote communication, they have low power demand. They are particularly suitable for deployment in remote, isolated areas with poor infrastructure, enhancing the data collection capability for areas that could not be continuously monitored in the past and expanding the monitoring range. As for the mobile domain, since it is located on transportation vehicles and is constantly moving, the power supply is provided by the transportation vehicles. The central domain is located in a large data center facility, so there is no power supply problem for either of them. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the structure of the device of the present invention;

[0056] Figure 2 This is a schematic diagram of the operation of the data acquisition device in an embodiment of the present invention;

[0057] Figure 3 This is a schematic diagram of the zoning of a demonstration plot in an embodiment of the present invention;

[0058] Figure 4 This is a schematic diagram of the field site layout in an embodiment of the present invention;

[0059] Figure 5This is a schematic diagram of the farmland degradation monitoring results of a demonstration plot in an embodiment of the present invention. Detailed Implementation

[0060] The present invention will be further described below with reference to the accompanying drawings and embodiments, but this should not be construed as limiting the present invention.

[0061] Example. A device for monitoring farmland degradation, such as... Figure 1 and 2 As shown, it includes the field domain, the mobile domain, and the central domain;

[0062] The field area is the data acquisition section, used to collect various field data; the field area is located in the field and includes various sensors for data acquisition, corresponding controllers and data transmission modules;

[0063] The mobile domain is the transportation section, used to move between various field domains to conduct data interaction and information collection. The mobile domain includes data collection equipment installed on the mobile device.

[0064] The central domain is the control section, which is used to process the collected data and issue corresponding instructions as needed. The central domain includes a data processing and calculation module and a network communication module.

[0065] The field area is the data collection link for the cultivated land environment of the data acquisition device, and it is set up in the field. The field area is a regional data collection device, which is responsible for collecting data collected by various sensors in the field, controlling the working status of the sensors, and initially integrating and screening monitoring data. The field area is connected to each sensor in the form of wired or wireless local area network. It mainly collects data such as soil temperature, moisture, runoff, and pH value of the local plot, records the working status of the sensors, controls the sensor location, and clears obstacles.

[0066] In the construction of field domains, various field devices can be general sensor devices, which do not necessarily have the ability to connect to the Internet. Each device can connect to the field domain via wired or wireless (Bluetooth, local area network) methods. The field domain itself acts as a data repeater and does not necessarily need to be connected to the Internet. It only needs to have a wireless data transmission module (Bluetooth or local area network) to exchange information with the mobile domain. This setup can greatly reduce the deployment cost and energy consumption of field devices.

[0067] The mobile domain is the transport component of the data acquisition device, typically mounted on vehicles or other means of transportation and constantly moving within a defined area; the function of the mobile domain is:

[0068] 1) Use transportation to move to the vicinity of various field areas in the area, connect the field areas, and collect the data gathered from the field areas;

[0069] 2) Transmit the latest instructions to the sensors controlled in the field area, thereby achieving unified control of various sensors in the area;

[0070] 3) Equipped with multispectral equipment, it can collect near-ground remote sensing data such as crop cover and soil organic matter distribution in the field.

[0071] The mobile domain operates in a manner similar to vehicle-to-everything (V2X) communication, and the devices it carries need to be connected to the internet.

[0072] Field data collected by the mobile domain can be stored using an autocorrelation method because the data format is relatively uniform, and a special field can be set to identify different field domains.

[0073] Because mobile domains are located on vehicles, the energy supply environment is relatively good, the cost of obtaining energy is relatively low, and safety and stability can be guaranteed.

[0074] Typically, within a given area, multiple mobile domains may be set up (but fewer than the number of field domains) to ensure that mobile domains can collect data in all directions within the area, thus avoiding data loss.

[0075] The central domain is the control section of the data acquisition device, located at its logical center. The functions of the central domain are:

[0076] 1) It integrates multiple communication protocols such as self-organizing network WIFI, 4G, 5G, and IP-MESH, which can realize real-time data interaction with the mobile domain at regular intervals;

[0077] 2) Intelligent decision-making on control information from the field domain and sensors, and transmission of instructions from the mobile domain to the field domain;

[0078] 3) Regularly acquire MODIS and FY3D satellite remote sensing data of the land parcel;

[0079] 4) Store data collected in mobile and field domains;

[0080] 5) Equipped with a data processing and calculation module, it processes various sensor data, multi-channel spectral data, and remote sensing data, calculates various farmland monitoring indices based on preset models, and finally calculates the farmland degradation index value of the region. It quantitatively assesses the location, degree, and rate of soil degradation, visualizes the monitoring information, and provides corresponding prevention and control suggestions and measures.

[0081] Central domains are typically located within large data center server rooms. Generally, one to two central domains can be set up in a single region, depending on the situation.

[0082] A method for monitoring farmland degradation utilizes a degraded farmland monitoring index model to quantitatively assess the status of farmland degradation. The degraded farmland monitoring index model includes a vegetation cover index, a soil fertility index, and a land environment index. The degraded farmland monitoring index value obtained from the degraded farmland monitoring index model is a weighted sum of the vegetation cover index, soil fertility index, and land environment index.

[0083] A method for monitoring arable land degradation includes the following steps:

[0084] A. Obtaining the vegetation cover index T;

[0085] B. Obtaining the soil fertility index M;

[0086] C. Acquisition of the Land Environment Index S;

[0087] D. Calculate the degraded farmland monitoring index TH;

[0088] E. Assess the status of farmland degradation.

[0089] The vegetation cover index T obtained in step A is as follows:

[0090] A1. Using regularly acquired MODIS and FY3D satellite remote sensing images of the central area, calculate the normalized vegetation index (NDI) of the plots within the field area. The formula is as follows:

[0091]

[0092] Among them, NVI i For the normalized vegetation index (PR) of the field area numbered i, i R represents the near-infrared reflectance of the plot of land in the field area with sign i; i Reflectivity in the red band;

[0093] A2. Using the bare soil vegetation constant and total vegetation cover constant of the study plot estimated empirically, calculate the vegetation cover index of the plot in the field area. The formula is:

[0094]

[0095] Among them, T i NVI is the vegetation cover index of the field area numbered i. i Let σ be the normalized vegetation index of the field plot numbered i, and σ be the bare soil vegetation constant. Total vegetation cover constant, σ and The value was estimated based on historical remote sensing images of the site.

[0096] A3. Calculate the overall vegetation cover index of the study area using the following formula:

[0097]

[0098] Where T is the vegetation cover index of the study area, and n is the number of field plots in the study area. i is the vegetation cover index of the field area numbered i.

[0099] The soil fertility index M obtained in step B is as follows:

[0100] B1. Using data from multispectral equipment acquired in the mobile domain, calculate the soil fertility index for each plot in a single field area. The formula is as follows:

[0101] M i =X0 + X1 × A i +X2×B i

[0102] Among them, M i A represents the soil fertility index of the plot located in field area numbered i. i B represents the near-infrared reflectance of organic carbon in the soil of field plot i; i X0 represents the reflectance of soil organic carbon in the red light band of field area i; X1, X2 are regression coefficients (determined by experts based on historical measurements of soil composition in this area);

[0103] B2. Calculate the overall soil fertility index of the study area, using the following formula:

[0104]

[0105] Where M is the soil fertility index of the study area, and n is the number of field plots in the study area. i The soil fertility index is the soil fertility index of the field area numbered i.

[0106] The land environmental index S obtained in step C is as follows:

[0107] C1. Using sensor data acquired in the field area, calculate the land environment index of the plot where the individual field area is located, using the following formula:

[0108]

[0109] Among them, C i D i F i H iThese represent the temperature, moisture, runoff, and soil pH of the plot obtained from field area i; C0, D0, F0, and H0 are the baseline values ​​(average values ​​of soil hydrological data over the years) for the plot in field area i; α is the regression coefficient (determined by experts based on historical measurements of the climate and hydrological conditions of the region).

[0110] C2. Calculate the overall land environment index for the study area, using the following formula:

[0111]

[0112] Where S is the land environment index of the study area, and n is the number of field plots in the study area. i The land environmental index is the plot of land in the field area numbered i.

[0113] The specific steps for obtaining the degraded arable land monitoring index TH as described in step D are as follows:

[0114] Based on the vegetation cover index T, soil fertility index M, and land environment index S, the degraded arable land index of the study area is calculated using the following formula:

[0115] TH=γT+βM+δS

[0116] Where TH is the monitoring index of degraded farmland in the study area, T is the vegetation cover index, M is the soil fertility index, S is the land environment index, and γ, β, and δ are weighting coefficients.

[0117] The assessment is based on the obtained degraded farmland monitoring index TH. If the TH value is greater than or equal to the set threshold, the study area can be evaluated as a farmland area with insignificant degradation, and the farmland condition is predicted to improve in the future.

[0118] If the TH value is less than the development threshold, the study area can be evaluated as a region of significant farmland degradation, and the farmland condition is predicted to deteriorate in the future.

[0119] Demonstration field verification

[0120] In 2024, this invention was demonstrated and tested at the Fengshou Branch of Chahayang Farm in Gannan County, Qiqihar City, Heilongjiang Province. The demonstration area covered 294 mu (approximately 19.6 hectares) and was divided into 8 plots, as shown in the diagram. Figure 3 As shown (numbered ①-⑧).

[0121] Each plot has 4-5 field zones, with mobile zones for data collection and central zones located in the upper left and lower right corners of the plot, totaling 36 field zones, 8 mobile zones, and 2 central zones. Each field zone has 5 sensor locations. A sensor distribution diagram is shown below. Figure 4 As shown.

[0122] Based on historical hydrological data and on-site scoring results from the expert panel, the degraded farmland monitoring index for each field area was calculated. The obtained farmland degradation monitoring index was then interpolated and expanded using Lagrange interpolation to obtain a set of degraded farmland monitoring indices for 30*30m plots within the demonstration area. The farmland degradation status was then mapped as follows: Figure 5 .

[0123] The calculated overall farmland degradation monitoring index for the study area is 0.33, which is higher than the set threshold of 0.25. Therefore, it can be determined that the farmland degradation status in this area is within an acceptable range.

[0124] Based on on-site sampling and verification, the reliability check value of this application is 0.788, which is between 0.7 and 0.8, demonstrating good reliability and meeting the actual needs of local degraded farmland monitoring.

Claims

1. A method for monitoring of degradation of arable land, characterized by: The method comprises a device for monitoring farmland degradation, which comprises a field area, a mobile area and a central area; the field area, the mobile area and the central area are three levels of nodes for monitoring farmland degradation in multiple dimensions; The field area is a data acquisition part for acquiring various field data in the field; the field area is arranged at a field site and comprises various sensors for data acquisition, corresponding controllers and a data transmission module; The mobile area is a transportation part for moving between field areas to exchange data and collect information; the mobile area comprises a data acquisition device arranged on a mobile device; The central area is a control part for processing the collected data and issuing corresponding instructions as needed; the central area comprises a data processing and calculation module and a network communication module; The field area is a regional data collection device connected with various sensors in the form of wired or wireless local area network; it is used to collect soil temperature, moisture, runoff and pH value data of the local plot, record the working state of the sensor and control the orientation of the sensor; each sensor does not have the function of connecting to the Internet; the field area itself is also not connected to the Internet and has a wireless data transmission module to exchange information with the mobile area; The mobile area can move in the corresponding field area by using a mobile device, connect to the field area and collect the data collected by the field area; the multi-spectral device carried thereon is used to collect near-earth remote sensing data including the coverage of crops in the field and the distribution of soil organic matter; The central area can communicate with the mobile area in real time to exchange data, process the collected data, decide the control information of the field area and the sensor and issue relevant control instructions; the instructions are transmitted from the mobile area to the field area; MODIS and FY3D satellite remote sensing data of the local plot are regularly obtained; the collected data are stored; the data are calculated to predict the relevant conditions of farmland degradation; The method uses a farmland degradation monitoring index model to quantitatively evaluate the farmland degradation condition; the farmland degradation monitoring index model comprises a vegetation coverage index, a soil fertility index and a land environment index; the farmland degradation monitoring index value obtained by the farmland degradation monitoring index model is the weighted sum of the vegetation coverage index, the soil fertility index and the land environment index; The method comprises the following steps, A, Vegetation Cover Index Acquisition; B, obtaining a soil fertility index M; C, obtaining a land environment index S; D, calculating a farmland degradation monitoring index TH; E, evaluating the farmland degradation condition.

2. A method for monitoring the degradation of arable land according to claim 1, characterized in that, The vegetation cover index described in step A Acquisition, in particular as follows: A1, using the MODIS and FY3D satellite remote sensing images of the local area regularly obtained by the central area, calculating the normalized vegetation index of the plot of the field area, the formula being wherein, is the normalized difference vegetation index for the field zone at block i, is the near infrared band reflectance for the field zone at block i; is the red band reflectance; A2, using the bare soil vegetation constant and the full vegetation coverage constant, calculating the vegetation coverage index of the plot of the field area, the formula being wherein, is the vegetation cover index for the field parcel in which the field zone numbered i is located, is the normalized difference vegetation index for the field parcel in which the field zone numbered i is located, is the bare soil vegetation constant, is the full vegetation cover constant; A3, calculating the overall vegetation coverage index of the study area, the formula being wherein, is a vegetation cover index for the study area, is a number of field parcels in the study area, is a vegetation cover index for the parcel in which the field parcel numbered i is located.

3. A method for monitoring of cropland degradation according to claim 1, wherein, The soil fertility index described in step B Acquisition, the specific steps are as follows: B1, using the data of the multi-spectral device obtained by the mobile area, calculating the soil fertility index of the plot of the single field area, the formula being wherein, is the soil fertility index for the field parcel in which the field zone numbered i is located, is the reflectance of the organic carbon in the soil of the field parcel in which the field zone numbered i is located in the near infrared waveband; is the reflectance of the organic carbon in the soil of the field parcel in which the field zone numbered i is located in the red waveband; , , is the regression coefficient; B2, calculating the overall soil fertility index of the study area, the formula being wherein, is a soil fertility index for the study area, is a number of field parcels in the study area, is a soil fertility index for the parcel in which the field parcel numbered i is located.

4. The method according to claim 1, wherein, The land environment index described in step C Acquisition, the specific steps are as follows: C1, using the sensor data obtained by the field area, calculating the land environment index of the plot of the single field area, the formula being wherein, T, W, Q, and pH are the temperature, water, runoff, and soil pH, respectively, of the field section numbered i; T, W, Q, and pH are the temperature, water, runoff, and soil pH, respectively, of the field section numbered i; is the regression coefficient; C2, calculating the overall land environment index of the research area, the formula is where S is a land environment index of a research area, is the number of field areas in the research area, is a land environment index of a plot where a field area numbered i is located.

5. The method according to claim 1, wherein, The degradation farmland monitoring index TH described in step D is obtained, and the specific steps are as follows: Based on the vegetation cover index , the soil fertility index M and the land environment index , the degraded farmland index of the study area is calculated, and the formula is where TH is the degradation farmland monitoring index of the study area, is the vegetation coverage index, M is the soil fertility index, is the land environment index, is the weight coefficient.

6. The method according to claim 1, wherein: Based on the obtained degradation farmland monitoring index TH, if the TH value is greater than or equal to a set threshold, the research area can be evaluated as a farmland degradation not significant area, and the future farmland condition is predicted to be good; If the TH value is less than the set threshold, the research area can be evaluated as a farmland degradation significant area, and the future farmland condition is predicted to develop in a bad trend.

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