Analysis system and method for agricultural multi-source heterogeneous data

Abstract

The invention relates to the technical field of agricultural application, in particular to an analysis system and method for agricultural multi-source heterogeneous data, and the method comprises the steps: obtaining the topographic data of an agricultural cultivation area, and obtaining the rainfall data and crop canopy data of the agricultural cultivation area in a monitoring period; evaluating the rainfall erosion degree in the monitoring period according to the rainfall data and the crop canopy data; evaluating the soil loss risk in the monitoring period according to the rainfall erosion degree evaluation result and the topographic data; and performing soil loss risk early warning according to the soil loss risk assessment result in the monitoring period. According to the method, the soil loss risk is evaluated by quantifying the rainfall erosion degree of the agricultural cultivation area, and the accuracy and reliability of farmland water and soil loss risk early warning are effectively improved.

Description

Technical Field

[0001] The present application relates to the field of agricultural application technology, and in particular to an analysis system and method for agricultural multi-source heterogeneous data. Background Art

[0002] As an important natural resource, the quality of arable land is closely related to land production potential and crop production capacity. High-quality arable land can provide sufficient nutrients and a suitable growth environment for crops, thereby ensuring high and stable yields of crops. Therefore, the quality of arable land is crucial to maintaining national food security and promoting stable growth of the agricultural economy.

[0003] Soil and water loss on cultivated land is not only directly related to the sustainable use of soil resources, but also has a profound impact on agricultural economic development and ecological environmental balance. From the perspective of agricultural economy, soil and water loss on cultivated land will lead to a decline in soil fertility, a large loss of key nutrients such as nitrogen, phosphorus and potassium in the soil, and thus affect the yield and quality of crops.

[0004] In the actual production process, crop rotation, harvesting and other crop planting intervals will cause the surface soil of cultivated land to be exposed. The cultivated land during the crop planting interval has the characteristics of long soil exposure time and low vegetation coverage, which increases the risk of soil erosion in cultivated land. The existing soil erosion risk assessment method of cultivated land ignores the impact of the interval period before crop harvesting or planting on soil erosion in cultivated land, reducing the accuracy of soil erosion risk warning of cultivated land. Summary of the invention

[0005] In order to overcome the defects and shortcomings of the existing technology, the present application provides an analysis system and method for agricultural multi-source heterogeneous data, which quantifies the degree of rainfall erosion in agricultural farming areas and then assesses the risk of soil loss, effectively improving the accuracy and reliability of soil and water loss risk warning for cultivated land.

[0006] In order to achieve the above objectives, this application adopts the following technical solutions:

[0007] In a first aspect, the present application provides an analysis method for agricultural multi-source heterogeneous data, comprising the following steps:

[0008] Obtain topographic data of agricultural farming areas, and obtain rainfall data and crop canopy data of agricultural farming areas during the monitoring period;

[0009] Assess the extent of rainfall erosion during the monitoring period based on rainfall data and crop canopy data;

[0010] Assess soil loss risk during the monitoring period based on rainfall erosion assessment results combined with topographic data;

[0011] Soil loss risk warning will be issued based on the soil loss risk assessment results within the monitoring period.

[0012] Preferably, the specific steps of evaluating the degree of rainfall erosion within the monitoring period include:

[0013] Obtain rainfall data and crop canopy data for agricultural farming areas during the monitoring period;

[0014] Calculate the rainfall uniformity index of agricultural farming areas during the monitoring period through rainfall data;

[0015] The temporal consistency index between soil exposure date and rainfall date in agricultural cultivated areas during the monitoring period was calculated using rainfall data and crop canopy data.

[0016] The rainfall erosion index is calculated by combining the rainfall uniformity index and the time consistency index. The rainfall erosion index is used to evaluate the degree of rainfall erosion during the monitoring period. The calculation formula of the rainfall erosion index is:

[0017]

[0018] Where E represents the rainfall uniformity index, T represents the time consistency index, represents the rainfall uniformity weight, represents the time consistency weight, and I represents the rainfall erosion index.

[0019] Preferably, the calculation formula of the rainfall uniformity index is:

[0020]

[0021] Where R i represents the rainfall in the agricultural farming area on the ith monitoring date within the monitoring period, R j represents the rainfall in the agricultural farming area on the jth monitoring date within the monitoring period, It represents the mean rainfall in the agricultural farming area during the monitoring period, n represents the number of monitoring dates during the monitoring period, and E represents the rainfall uniformity index.

[0022] Preferably, the specific steps of calculating the time consistency index of soil exposure date and rainfall date in the agricultural farming area within the monitoring period include:

[0023] The crop canopy coverage of agricultural farming areas during the monitoring period was calculated using crop canopy data;

[0024] The dates when the crop canopy coverage in the agricultural farming area during the monitoring period is less than the preset crop canopy coverage threshold are marked as soil exposure dates, and a soil exposure date set is constructed;

[0025] Extract the rainfall date from the rainfall data within the monitoring period and construct a rainfall date set;

[0026] The temporal consistency index is calculated through the soil exposure date set and the rainfall date set. The temporal consistency index is used to evaluate the overlap between the soil exposure date and the rainfall date during the monitoring period. The calculation formula of the temporal consistency index is:

[0027]

[0028] Where T E represents the set of soil exposure dates within the monitoring period, T R Represents the set of rainfall dates within the monitoring period, CT E ∩T R | indicates the calculation of soil exposure date set T E With the rainfall date set T R The number of elements in the intersection, CT E ∪T R | represents the calculation of the soil exposure date set T E With the rainfall date set T R The number of elements in the union, T represents the temporal consistency index.

[0029] Preferably, the specific steps of assessing the soil loss risk within the monitoring period include:

[0030] Obtain topographic data and rainfall erosion index for agricultural cultivation areas;

[0031] Extract the terrain slope of agricultural farming areas through terrain data and count the area of ​​sloping farmland with a terrain slope range of [2°, 25°);

[0032] The soil loss risk index is calculated by the area of ​​sloping farmland and the rainfall erosion index. The soil loss risk index is used to assess the soil loss risk in agricultural farming areas during the monitoring period. The soil loss risk index calculation formula is:

[0033]

[0034] Where A s A represents the area of ​​sloping farmland in the agricultural cultivation area. t represents the area of ​​agricultural cultivation area, I represents the rainfall erosion index, and R represents the soil loss risk index.

[0035] Preferably, the specific steps of carrying out soil loss risk warning according to the soil loss risk assessment results within the monitoring period include:

[0036] Obtain a soil loss risk index, and when the soil loss risk index is greater than a preset soil loss risk threshold, issue a soil loss risk warning;

[0037] When the soil loss risk index is less than or equal to the preset soil loss risk threshold, no soil loss risk warning will be issued.

[0038] It should be noted here that the rainfall uniformity weight, time consistency weight, preset crop canopy coverage threshold and preset soil loss risk threshold are determined as follows: 5,000 sets of terrain data, rainfall data and crop canopy data of agricultural farming areas are collected to distinguish whether there is a risk of soil loss in the agricultural farming areas, and the terrain data, rainfall data and crop canopy data are substituted into the soil loss risk index calculation formula for calculation, and the calculated soil loss risk index and the distinction results are simultaneously imported into the fitting software, and the optimal rainfall uniformity weight, time consistency weight, preset crop canopy coverage threshold and preset soil loss risk threshold that meet the distinction accuracy of the distinction results are output.

[0039] In a second aspect, the present application provides an analysis system for agricultural multi-source heterogeneous data, comprising:

[0040] A data acquisition module is used to acquire terrain data of agricultural farming areas, and to acquire rainfall data and crop canopy data of agricultural farming areas within a monitoring period;

[0041] The rainfall erosion assessment module is used to assess the extent of rainfall erosion during the monitoring period based on rainfall data and crop canopy data;

[0042] The soil loss assessment module is used to assess the soil loss risk within the monitoring period based on the rainfall erosion assessment results and combined with terrain data;

[0043] The soil loss early warning module is used to issue a soil loss risk early warning based on the soil loss risk assessment results within the monitoring period;

[0044] The control module is used to control the operation of the data acquisition module, the rainfall erosion assessment module, the soil loss assessment module and the soil loss early warning module.

[0045] In a third aspect, the present application provides an electronic device comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes an analysis method for agricultural multi-source heterogeneous data by calling the computer program stored in the memory.

[0046] In a fourth aspect, the present application provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute an analysis method for agricultural multi-source heterogeneous data.

[0047] Compared with the prior art, this application has the following advantages and beneficial effects:

[0048] This application first quantifies the rainfall uniformity in the agricultural farming area and the temporal consistency between the soil exposure date and the rainfall date to monitor the degree of rainfall erosion within the period, then evaluates the soil loss risk within the monitoring period based on the rainfall erosion degree assessment results combined with the terrain data, and finally issues a soil loss risk warning based on the soil loss risk assessment results, thereby effectively improving the accuracy and reliability of the soil and water loss risk warning for cultivated land. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0050] Figure 1 It is a schematic diagram of the overall process of an analysis method for agricultural multi-source heterogeneous data provided by an embodiment of the present application;

[0051] Figure 2 It is a structural schematic diagram of an analysis system for agricultural multi-source heterogeneous data provided by an embodiment of the present application;

[0052] Figure 3 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] The technical solution of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0054] See also Figure 1 , Figure 1 This is a schematic diagram of the overall process of an analysis method for agricultural multi-source heterogeneous data provided by an embodiment of the present application, which specifically includes the following steps:

[0055] S110: Acquire terrain data of the agricultural farming area, and acquire rainfall data and crop canopy data of the agricultural farming area within a monitoring period;

[0056] Agricultural multi-source heterogeneous data refers to agricultural data with different sources, types or structures. In the embodiment of the present application, the terrain data includes DEM (Digital Elevation Model) elevation data of the agricultural farming area, and the DEM elevation data is obtained through the National Geospatial Data Cloud. The rainfall data includes the rainfall date and corresponding rainfall amount in the agricultural farming area during the monitoring period. The crop canopy data includes crop canopy images, and the crop canopy images are obtained by drone photography.

[0057] S120: Evaluate the extent of rainfall erosion during the monitoring period based on rainfall data and crop canopy data;

[0058] The rainfall erosion index combines the rainfall uniformity index with the temporal consistency index of soil exposure date and rainfall date to comprehensively evaluate the erosion potential of rainfall in terms of spatial and temporal distribution. The rainfall erosion index can quantify the coupling effect of rainfall concentration and insufficient vegetation cover. The specific steps for evaluating the degree of rainfall erosion during the monitoring period include:

[0059] Obtain rainfall data and crop canopy data for agricultural farming areas during the monitoring period;

[0060] Calculate the rainfall uniformity index of agricultural farming areas during the monitoring period through rainfall data;

[0061] The temporal consistency index between soil exposure date and rainfall date in agricultural cultivated areas during the monitoring period was calculated using rainfall data and crop canopy data.

[0062] The rainfall erosion index is calculated by combining the rainfall uniformity index and the time consistency index. The rainfall erosion index is used to evaluate the degree of rainfall erosion during the monitoring period. The calculation formula of the rainfall erosion index is:

[0063]

[0064] Where E represents the rainfall uniformity index, T represents the time consistency index, represents the rainfall uniformity weight, represents the time consistency weight, I represents the rainfall erosion index;

[0065] The uniformity of rainfall has an important impact on the risk of soil loss. When rainfall is evenly distributed, the soil has more time to absorb water, and the risk of runoff generation and erosion is lower. When rainfall is highly concentrated, heavy rainfall in a short period of time will cause a sharp increase in runoff, especially in areas with steep terrain or low vegetation cover, which will aggravate soil erosion and nutrient loss. The calculation formula of the rainfall uniformity index is:

[0066]

[0067] Where R i represents the rainfall in the agricultural farming area on the ith monitoring date within the monitoring period, R j represents the rainfall in the agricultural farming area on the jth monitoring date within the monitoring period, It means calculating the rainfall difference between any two monitoring dates within the monitoring period. Since the rainfall difference is double counted during the calculation, it needs to be divided by 2 to balance the repeated count. represents the mean rainfall in the agricultural farming area during the monitoring period, n represents the number of monitoring dates during the monitoring period, and E represents the rainfall uniformity index;

[0068] By calculating the temporal consistency index of soil exposure date and rainfall date, we can reveal the degree of overlap of rainfall date during soil exposure period. When the temporal consistency index is high, it means that rainfall is mostly concentrated in the period of insufficient vegetation coverage, and the risk of soil loss due to rainfall erosion is significantly increased. The specific steps for calculating the temporal consistency index of soil exposure date and rainfall date in agricultural farming areas during the monitoring period include:

[0069] The crop canopy coverage of the agricultural farming area during the monitoring period is calculated through crop canopy data. The crop canopy coverage refers to the ratio of the crop canopy coverage area to the total cultivated land area. The crop canopy coverage area is the orthographic projection area of ​​the crop canopy on the cultivated land. The crop canopy is separated from the background of the crop canopy image by the color threshold segmentation method based on the difference in canopy and background colors. Since the camera lens of the drone is perpendicular to the ground when collecting crop canopy images, the crop canopy coverage area is calculated by counting the number of crop canopy pixels and multiplying the actual area corresponding to the pixels.

[0070] The dates when the crop canopy coverage in the agricultural farming area during the monitoring period is less than the preset crop canopy coverage threshold are marked as soil exposure dates, and a soil exposure date set is constructed;

[0071] Extract the rainfall date from the rainfall data within the monitoring period and construct a rainfall date set;

[0072] The temporal consistency index is calculated through the soil exposure date set and the rainfall date set. The temporal consistency index is used to evaluate the overlap between the soil exposure date and the rainfall date during the monitoring period. The calculation formula of the temporal consistency index is:

[0073]

[0074] Where T E represents the set of soil exposure dates within the monitoring period, T R Represents the set of rainfall dates within the monitoring period, CT E ∩T R | represents the calculation of the soil exposure date set T E With the rainfall date set T R The number of elements in the intersection, that is, the soil exposure date set T E and the rainfall date set T R The number of overlapping dates in the two sets, CT E ∪T R | represents the calculation of the soil exposure date set T E With the rainfall date set TR The number of elements in the union is the total number of all soil exposure dates and rainfall dates (removing duplicate dates). T represents the temporal consistency index, which is used to quantify the degree of overlap between soil exposure dates and rainfall dates. The larger the temporal consistency index, the more rainfall occurs during the soil exposure period, which means a higher risk of soil loss.

[0075] S130: Evaluate the soil loss risk during the monitoring period based on the rainfall erosion assessment results and combined with terrain data;

[0076] The terrain slope is one of the important factors affecting soil loss. The greater the terrain slope, the faster the surface runoff speed driven by gravity, and the stronger its ability to carry soil particles, resulting in a significant increase in the risk of soil erosion. In areas with smaller slopes, the water flow speed is slower and the soil erosion risk is relatively low. The specific steps for assessing the soil loss risk during the monitoring period include:

[0077] Obtain topographic data and rainfall erosion index for agricultural cultivation areas;

[0078] The terrain slope of the agricultural cultivation area is extracted through terrain data, and the area of ​​sloping cultivated land with a terrain slope range of [2°, 25°) is counted. The terrain slope range of sloping cultivated land is [2°, 25°), 2° is the starting slope for soil erosion, and a slope greater than or equal to 25° is not suitable for crop planting. The terrain slope range of sloping cultivated land refers to the cultivated land slope classification in the "Technical Regulations for Land Use Status Survey" issued by the National Agricultural Zoning Committee;

[0079] The specific steps of extracting the terrain slope of the agricultural farming area include: (1) obtaining the DEM elevation data of the agricultural farming area through the National Geospatial Data Cloud; (2) using ArcGIS software to project the DEM elevation data into slope raster data; (3) clipping the generated slope raster data to the scope of the agricultural farming area to obtain the terrain slope of the agricultural farming area;

[0080] The soil loss risk index is calculated by the area of ​​sloping farmland and the rainfall erosion index. The soil loss risk index is used to assess the soil loss risk in agricultural farming areas during the monitoring period. The soil loss risk index calculation formula is:

[0081]

[0082] Where A s A represents the area of ​​sloping farmland in the agricultural cultivation area. t represents the area of ​​agricultural cultivation area, It represents the proportion of sloping cultivated land to agricultural cultivated land. The larger the proportion of sloping cultivated land, the greater the risk of soil loss in agricultural cultivated land. I represents the rainfall erosion index, and R represents the soil loss risk index.

[0083] S140: Provide soil loss risk warning based on the soil loss risk assessment results within the monitoring period;

[0084] The specific steps for early warning of soil loss risk based on the soil loss risk assessment results within the monitoring period include:

[0085] Obtain a soil loss risk index, and when the soil loss risk index is greater than a preset soil loss risk threshold, issue a soil loss risk warning;

[0086] When the soil loss risk index is less than or equal to the preset soil loss risk threshold, no soil loss risk warning will be issued.

[0087] See also Figure 2 , Figure 2 : is a structural diagram of an analysis system for agricultural multi-source heterogeneous data provided by an embodiment of the present application. This embodiment provides an analysis system for agricultural multi-source heterogeneous data, including:

[0088] The data acquisition module 210 is used to acquire the terrain data of the agricultural farming area, and acquire the rainfall data and crop canopy data of the agricultural farming area within the monitoring period;

[0089] A rainfall erosion assessment module 220 is used to assess the degree of rainfall erosion within a monitoring period based on rainfall data and crop canopy data;

[0090] A soil loss assessment module 230 is used to assess the soil loss risk within the monitoring period based on the rainfall erosion assessment results and combined with terrain data;

[0091] A soil loss early warning module 240 is used to issue a soil loss risk early warning according to the soil loss risk assessment results within the monitoring period;

[0092] The control module 250 is used to control the operation of the data acquisition module, the rainfall erosion assessment module, the soil loss assessment module and the soil loss early warning module.

[0093] In the embodiment of the present application, the rainfall erosion assessment module 220 is used to assess the degree of rainfall erosion within the monitoring period according to rainfall data and crop canopy data. The specific steps of assessing the degree of rainfall erosion within the monitoring period include:

[0094] Obtain rainfall data and crop canopy data for agricultural farming areas during the monitoring period;

[0095] Calculate the rainfall uniformity index of agricultural farming areas during the monitoring period through rainfall data;

[0096] The temporal consistency index between soil exposure date and rainfall date in agricultural cultivated areas during the monitoring period was calculated using rainfall data and crop canopy data.

[0097] The rainfall erosion index is calculated by combining the rainfall uniformity index and the time consistency index. The rainfall erosion index is used to evaluate the degree of rainfall erosion during the monitoring period. The calculation formula of the rainfall erosion index is:

[0098]

[0099] Where E represents the rainfall uniformity index, T represents the time consistency index, represents the rainfall uniformity weight, represents the time consistency weight, I represents the rainfall erosion index;

[0100] The calculation formula of rainfall uniformity index is:

[0101]

[0102] Where R i represents the rainfall in the agricultural farming area on the ith monitoring date within the monitoring period, R j represents the rainfall in the agricultural farming area on the jth monitoring date within the monitoring period, represents the mean rainfall in the agricultural farming area during the monitoring period, n represents the number of monitoring dates during the monitoring period, and E represents the rainfall uniformity index;

[0103] The specific steps for calculating the temporal consistency index between soil exposure date and rainfall date in agricultural cultivation areas during the monitoring period include:

[0104] The crop canopy coverage of agricultural farming areas during the monitoring period was calculated using crop canopy data;

[0105] The dates when the crop canopy coverage in the agricultural farming area during the monitoring period is less than the preset crop canopy coverage threshold are marked as soil exposure dates, and a soil exposure date set is constructed;

[0106] Extract the rainfall date from the rainfall data within the monitoring period and construct a rainfall date set;

[0107] The temporal consistency index is calculated through the soil exposure date set and the rainfall date set. The temporal consistency index is used to evaluate the overlap between the soil exposure date and the rainfall date during the monitoring period. The calculation formula of the temporal consistency index is:

[0108]

[0109] Where T E represents the set of soil exposure dates within the monitoring period, T R Represents the set of rainfall dates within the monitoring period, CT E ∩T R | represents the calculation of the soil exposure date set T E With the rainfall date set T R The number of elements in the intersection, C|T E ∪T R | represents the calculation of the soil exposure date set T E With the rainfall date set T R The number of elements in the union, T represents the temporal consistency index.

[0110] In the embodiment of the present application, the soil loss assessment module 230 is used to assess the soil loss risk within the monitoring period according to the rainfall erosion degree assessment result and in combination with the terrain data. The specific steps of assessing the soil loss risk within the monitoring period include:

[0111] Obtain topographic data and rainfall erosion index for agricultural cultivation areas;

[0112] Extract the terrain slope of agricultural farming areas through terrain data and count the area of ​​sloping farmland with a terrain slope range of [2°, 25°);

[0113] The soil loss risk index is calculated by the area of ​​sloping farmland and the rainfall erosion index. The soil loss risk index is used to assess the soil loss risk in agricultural farming areas during the monitoring period. The soil loss risk index calculation formula is:

[0114]

[0115] Where A s A represents the area of ​​sloping farmland in the agricultural cultivation area. t represents the area of ​​agricultural cultivation area, I represents the rainfall erosion index, and R represents the soil loss risk index.

[0116] In the embodiment of the present application, the soil loss early warning module 240 is used to perform a soil loss risk early warning according to the soil loss risk assessment result within the monitoring period. The specific steps of performing a soil loss risk early warning according to the soil loss risk assessment result within the monitoring period include:

[0117] Obtain a soil loss risk index, and when the soil loss risk index is greater than a preset soil loss risk threshold, issue a soil loss risk warning;

[0118] When the soil loss risk index is less than or equal to the preset soil loss risk threshold, no soil loss risk warning will be issued.

[0119] The above-mentioned parameters and steps for each unit module to implement corresponding functions in an analysis system for agricultural multi-source heterogeneous data of the present application can refer to the parameters and steps in the embodiment of an analysis method for agricultural multi-source heterogeneous data above, and will not be repeated here.

[0120] like Figure 3 As shown, an embodiment of the present invention further provides an electronic device 300, including a memory 310, a processor 320 and a communication bus 330; the memory 310 and the processor 320 are connected via the communication bus 330. The memory 310 stores a method for analyzing agricultural multi-source heterogeneous data provided in the above embodiment, which can be loaded and executed by the processor 320.

[0121] The memory 310 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 310 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing an analysis method for agricultural multi-source heterogeneous data provided in the above embodiment, etc.; the data storage area may store data involved in an analysis method for agricultural multi-source heterogeneous data provided in the above embodiment, etc.

[0122] The processor 320 may include one or more processing cores. The processor 320 calls the data stored in the memory 310 by running or executing the instructions, programs, code sets or instruction sets stored in the memory 310, and performs various functions and processes data of the present application. The processor 320 may be at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller and a microprocessor. It is understandable that for different devices, the electronic device used to implement the above-mentioned processor 320 function can also be other, and the embodiment of the present application is not specifically limited.

[0123] The communication bus 330 may include a path to transmit information between the above components. The communication bus 330 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The communication bus 330 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one double arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0124] An embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executes a method for analyzing agricultural multi-source heterogeneous data as provided in the above embodiment.

[0125] In this embodiment, the computer-readable storage medium may be a tangible device that holds and stores instructions used by the instruction execution device. The computer-readable storage medium may be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof. Specifically, the computer-readable storage medium may be a portable computer disk, a hard disk, a USB flash drive, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a podium random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, an optical disk, a magnetic disk, a mechanical encoding device, and any combination thereof.

[0126] The terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or also includes elements inherent to such process, method, article, or apparatus.

[0127] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of application involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned application concept. For example, the above features are replaced with (but not limited to) technical features with similar functions applied in the present application.

Claims

1. A method for analyzing agricultural multi-source heterogeneous data, characterized in that: The steps include: Obtain topographic data of agricultural farming areas, and obtain rainfall data and crop canopy data of agricultural farming areas during the monitoring period; Assess the extent of rainfall erosion during the monitoring period based on rainfall data and crop canopy data; Assess soil loss risk during the monitoring period based on rainfall erosion assessment results combined with topographic data; Soil loss risk warning will be issued based on the soil loss risk assessment results within the monitoring period.

2. The method for analyzing agricultural multi-source heterogeneous data according to claim 1, characterized in that: The specific steps of evaluating the degree of rainfall erosion during the monitoring period include: Obtain rainfall data and crop canopy data for agricultural farming areas during the monitoring period; Calculate the rainfall uniformity index of agricultural farming areas during the monitoring period through rainfall data; The temporal consistency index between soil exposure date and rainfall date in agricultural cultivated areas during the monitoring period was calculated using rainfall data and crop canopy data. The rainfall erosion index is calculated by combining the rainfall uniformity index and the time consistency index. The rainfall erosion index is used to evaluate the degree of rainfall erosion during the monitoring period. The calculation formula of the rainfall erosion index is: Where E represents the rainfall uniformity index, T represents the time consistency index, represents the rainfall uniformity weight, represents the time consistency weight, and I represents the rainfall erosion index.

3. The method for analyzing agricultural multi-source heterogeneous data according to claim 2, characterized in that: The calculation formula of the rainfall uniformity index is: Where R i represents the rainfall in the agricultural farming area on the ith monitoring date within the monitoring period, R j represents the rainfall in the agricultural farming area on the jth monitoring date within the monitoring period, It represents the mean rainfall in the agricultural farming area during the monitoring period, n represents the number of monitoring dates during the monitoring period, and E represents the rainfall uniformity index.

4. The method for analyzing agricultural multi-source heterogeneous data according to claim 2, characterized in that: The specific steps of calculating the time consistency index between the soil exposure date and the rainfall date in the agricultural farming area within the monitoring period include: The crop canopy coverage of agricultural farming areas during the monitoring period was calculated using crop canopy data; The dates when the crop canopy coverage in the agricultural farming area during the monitoring period is less than the preset crop canopy coverage threshold are marked as soil exposure dates, and a soil exposure date set is constructed; Extract the rainfall date from the rainfall data within the monitoring period and construct a rainfall date set; The temporal consistency index is calculated through the soil exposure date set and the rainfall date set. The temporal consistency index is used to evaluate the overlap between the soil exposure date and the rainfall date during the monitoring period. The calculation formula of the temporal consistency index is: Where T E represents the set of soil exposure dates within the monitoring period, T R Represents the set of rainfall dates within the monitoring period, CT E ∩T R | indicates the calculation of soil exposure date set T E With the rainfall date set T R The number of elements in the intersection, C|T E ∪T R | indicates the calculation of soil exposure date set T E With the rainfall date set T R The number of elements in the union, T represents the temporal consistency index.

5. The method for analyzing agricultural multi-source heterogeneous data according to claim 1, characterized in that: The specific steps for assessing soil loss risk during the monitoring period include: Obtain topographic data and rainfall erosion index for agricultural cultivation areas; Extract the terrain slope of agricultural farming areas through terrain data and count the area of ​​sloping farmland with a terrain slope range of [2°, 25°); The soil loss risk index is calculated by the area of ​​sloping farmland and the rainfall erosion index. The soil loss risk index is used to assess the soil loss risk in agricultural farming areas during the monitoring period. The soil loss risk index calculation formula is: Where A s A represents the area of ​​sloping farmland in the agricultural cultivation area. t represents the area of ​​agricultural cultivation area, I represents the rainfall erosion index, and R represents the soil loss risk index.

6. The method for analyzing agricultural multi-source heterogeneous data according to claim 1, characterized in that: The specific steps of carrying out soil loss risk early warning according to the soil loss risk assessment results within the monitoring period include: Obtain a soil loss risk index, and when the soil loss risk index is greater than a preset soil loss risk threshold, issue a soil loss risk warning; When the soil loss risk index is less than or equal to the preset soil loss risk threshold, no soil loss risk warning will be issued.

7. An analysis system for agricultural multi-source heterogeneous data, applied to an analysis method for agricultural multi-source heterogeneous data as claimed in any one of claims 1 to 6, characterized in that: The system comprises: A data acquisition module is used to acquire terrain data of agricultural farming areas, and to acquire rainfall data and crop canopy data of agricultural farming areas within a monitoring period; The rainfall erosion assessment module is used to assess the extent of rainfall erosion during the monitoring period based on rainfall data and crop canopy data; Soil loss assessment module, which is used to assess soil loss risk within the monitoring period based on the rainfall erosion assessment results combined with terrain data; The soil loss early warning module is used to issue a soil loss risk early warning based on the soil loss risk assessment results within the monitoring period; The control module is used to control the operation of the data acquisition module, the rainfall erosion assessment module, the soil loss assessment module and the soil loss early warning module.

8. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes an analysis method for agricultural multi-source heterogeneous data as described in any one of claims 1-6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes an analysis method for agricultural multi-source heterogeneous data as described in any one of claims 1 to 6.

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