A remote sensing monitoring system for corn waterlogging early warning

Abstract

The invention belongs to the field of corn waterlogging early warning, relates to remote sensing monitoring technology, and is used to solve the problem that the accuracy of corn waterlogging early warning cannot be guaranteed and the early warning process cannot be optimized. Specifically, it is a remote sensing monitoring system for corn waterlogging early warning, comprising a waterlogging early warning module, a waterlogging alarm module and a waterlogging early warning optimization module, wherein the waterlogging early warning module comprises a planting site monitoring unit and a precipitation monitoring unit; the waterlogging early warning module, the waterlogging alarm module and the waterlogging early warning optimization module are sequentially connected for communication; the water body and corn state of the corn planting site are monitored through a remote sensing platform, and waterlogging early warning and waterlogging alarm are performed on the corn planting site in combination with precipitation information, and the waterlogging early warning process is optimized according to the early warning level and the alarm level; the invention can combine the water body state, precipitation information and the growth coefficient of corn to ensure the timeliness of corn waterlogging early warning and improve the accuracy of corn waterlogging early warning.

Description

Technical Field

[0001] The invention belongs to the field of corn waterlogging early warning, relates to remote sensing monitoring technology, and specifically is a remote sensing monitoring system for corn waterlogging early warning. Background Art

[0002] Corn is one of the main food crops in my country and an important feed and industrial raw material. Corn has many varieties and high nutritional value. It is rich in carbohydrates, dietary fiber, vitamins and minerals. The planting and harvesting of corn usually rely on mechanized operations to improve efficiency and yield.

[0003] The existing corn flood prediction system often warns of floods based on precipitation information from the weather system, but does not provide comprehensive warnings based on the actual water conditions in the corn-growing areas, resulting in the inability to guarantee the accuracy of corn flood warnings. In addition, the existing technology is unable to warn of floods based on the actual growth status of corn, and is even unable to provide feedback and optimize the warning process based on the alarm results. Summary of the invention

[0004] The purpose of the present invention is to provide a remote sensing monitoring system for corn waterlogging early warning, which is used to solve the problem that the accuracy of corn waterlogging early warning cannot be guaranteed and the early warning process cannot be fed back and optimized according to the alarm results;

[0005] The technical problem to be solved by the present invention is: how to provide a remote sensing monitoring system for corn waterlogging early warning which can ensure the accuracy of corn waterlogging early warning and can provide feedback and optimization on the early warning process according to the alarm results.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A remote sensing monitoring system for corn waterlogging early warning includes a waterlogging early warning module, a waterlogging alarm module and a waterlogging early warning optimization module. The waterlogging early warning module includes a planting site monitoring unit and a precipitation monitoring unit. The waterlogging early warning module, the waterlogging alarm module and the waterlogging early warning optimization module are sequentially connected in communication.

[0008] The planting site monitoring unit is used to monitor the water body and corn growth status of the corn planting site: mark a fixed time point of each natural day as a monitoring time point, obtain high-resolution remote sensing image data of the water body and corn in the corn planting site at the monitoring time point, pre-process, feature extract and invert the high-resolution remote sensing image data, and obtain the actual water body depth DS and the growth coefficient SZ of the corn planting site; compare the actual water body depth DS with a preset water accumulation depth threshold ZX, and mark the water body status of the water body as a water accumulation state or a non-water accumulation state;

[0009] The precipitation monitoring unit is used to monitor the precipitation information of the corn planting land: obtaining the precipitation information of the corn planting land through the meteorological platform at the monitoring time point;

[0010] The waterlogging warning module is used to warn of waterlogging according to the precipitation information of the corn planting land: at the monitoring time point, by combining the precipitation information with the actual water depth DS, the necessity of waterlogging warning for the corn planting land is analyzed; if a warning is needed, the waterlogging warning level of the corn planting land is analyzed and a warning is issued;

[0011] The waterlogging alarm module is used to alarm for waterlogging according to the influence of water on corn growth in the corn planting land: the water state of the corn planting land is checked at the monitoring time point, and if the water state of the corn planting land is waterlogged, an alarm signal is triggered, and the alarm level is analyzed by comparing the value of the corn growth variation coefficient SB;

[0012] The waterlogging warning optimization module is used to optimize the warning according to the results of the verification analysis of the warning level and the alarm level.

[0013] Furthermore, the process of monitoring the water body in the corn-planting land includes: dividing the corn-planting land into several monitoring areas, obtaining high-resolution remote sensing image data of the water body in the monitoring area at the monitoring time point, preprocessing, feature extraction and physical model inversion of the high-resolution remote sensing image data to obtain the water body depth of the monitoring area, summing and averaging the water body depths of each monitoring area to obtain the actual water body depth DS of the corn-planting land; marking the water depth of a certain height as the water depth threshold ZX, if the actual water depth DS is greater than or equal to the water depth threshold ZX, then the water state of the corn-planting land is marked as a waterlogged state, and the current monitoring time point is marked as the waterlogging existence time JC; if the actual water depth DS is less than the water depth threshold ZX, then the water state of the corn-planting land is marked as a non-waterlogged state, and the accumulated waterlogging time JT is cleared.

[0014] Furthermore, the process of monitoring the growth status of corn includes: preprocessing the high-resolution remote sensing data of corn in the monitoring area acquired at the monitoring time point, extracting features and inverting the physical model to obtain the corn leaf length and plant height, summing up the leaf length and plant height of the corn in each monitoring area and taking the average value to calculate the average leaf length YC and the average plant height ZG of the corn in the corn planting field, and numerically calculating the growth coefficient SZ of the corn in the corn planting field through the formula SZ=k1*YC+k2*ZG.

[0015] Furthermore, the precipitation information includes the expected 24-hour precipitation YJ, the precipitation start time, and the actual 24-hour precipitation SJ; the precipitation start time on the day when the corn planting land is in a waterlogging state is recorded as the waterlogging start time JK.

[0016] Furthermore, the process of analyzing the necessity of waterlogging warning for corn-planting land includes: summing the actual water body depth DS and the expected 24-hour precipitation YJ to obtain the expected water body depth YS at the next monitoring time point; if the expected water body depth YS is less than or equal to the water accumulation depth threshold ZX, the water body state of the corn-planting land is set to a non-water accumulation state, and no warning is required; if the expected water body depth YS is greater than the water accumulation depth threshold ZX, the water body state of the corn-planting land is set to a water accumulation state, and a warning signal is issued.

[0017] Furthermore, the process of analyzing the waterlogging warning level of the corn-planting land includes: obtaining the flooding depth NS and flooding duration NT of corn; numerically calculating the waterlogging start time JK and the waterlogging existence time JC through the formula JT=JC-JK to obtain the cumulative waterlogging duration JT; if the expected water body depth YS is greater than or equal to the flooding depth NS and the cumulative waterlogging duration JT is greater than or equal to the flooding duration NT, a first-level warning signal is triggered; if the expected water body depth YS is less than or equal to the flooding depth NS and the cumulative waterlogging duration JT is less than or equal to the flooding duration NT, a third-level warning signal is triggered; if the expected water body depth YS is greater than the flooding depth NS but the cumulative waterlogging duration JT is less than the flooding duration NT or the expected water body depth YS is less than the flooding depth NS but the cumulative waterlogging duration JT is greater than the flooding duration NT, a second-level warning signal is triggered; if the expected water body depth YS is greater than the water depth danger threshold SSmax, a special-level warning signal is triggered: the severity of waterlogging disasters is from severe to mild, namely special, first, second and third levels.

[0018] Furthermore, the process of alarming for waterlogging based on the impact of water on corn growth in corn planting areas includes: checking the water status of the corn planting areas at the monitoring time point. If the water status of the corn planting areas is a non-waterlogged state, there is no waterlogging risk and no alarm is required; if the water status of the corn planting areas is a waterlogged state, there is a waterlogging risk, an alarm signal is triggered, and an alarm level analysis is performed; the corn growth coefficient SZ1 at the current monitoring time point and the corn growth coefficient SZ0 at the previous monitoring time point are obtained, and the growth variation coefficient SB of the corn is obtained by numerical calculation using the formula SB=(SZ1-SZ0) / SZ0; the maximum alarm threshold BJmax and the minimum alarm threshold BJmin of the corn waterlogging are obtained, and if the growth variation coefficient SB of the corn is greater than or equal to the maximum alarm threshold BJmax, a first-level alarm signal is triggered; if the growth variation coefficient SB of the corn is less than the maximum alarm threshold BJmax and greater than the minimum alarm threshold BJmin, a second-level alarm signal is triggered; if the growth variation coefficient SB of the corn is less than the minimum alarm threshold BJmin, a third-level alarm signal is triggered.

[0019] Furthermore, the process of optimizing the early warning according to the results of the verification analysis of the early warning level and the alarm level includes: when the alarm signal is triggered at the current monitoring time point, the early warning signal at the previous monitoring time point is obtained. If the early warning signal is not triggered at the previous monitoring time point, it is judged that the threshold for triggering the early warning signal does not meet the requirements, and the water accumulation depth threshold ZX is lowered; if the early warning signal is triggered at the previous monitoring time point, the early warning level and the alarm level are compared. If the early warning level is less than or equal to the alarm level, it is judged that the early warning level meets the requirements and no optimization is required; if the early warning level is greater than the alarm level, it is judged that the early warning level does not meet the requirements, and the optimization decision analysis is triggered: the actual 24-hour precipitation SJ and the expected 24-hour precipitation YJ are analyzed for differences: the actual 24-hour precipitation SJ and the expected 24-hour precipitation YJ are calculated by difference to obtain the precipitation deviation value JP. If the precipitation deviation value JP is greater than or equal to the difference threshold CY, it is judged that the actual and expected precipitation are different, and the data collection method of the waterlogging early warning module needs to be optimized; if the precipitation deviation value JP is less than the difference threshold CY, it is judged that the actual and expected precipitation are not different, and the processing means after the early warning signal is triggered needs to be optimized.

[0020] The present invention has the following beneficial effects:

[0021] 1. By preprocessing and extracting features from high-resolution remote sensing data of water bodies in the monitoring area, the actual water depth and water status of the corn planting area are obtained. Combined with the precipitation information obtained from the meteorological platform at the monitoring time point, the timeliness of corn waterlogging warning is guaranteed and the accuracy of corn waterlogging warning is improved;

[0022] 2. By preprocessing and extracting features from high-resolution remote sensing data of corn in the monitoring area, the growth status of corn in the corn planting area is obtained. Combined with the water status obtained at the monitoring time point, waterlogging alarms are issued to the corn planting area in a timely manner, and feedback is provided on the accuracy of the warning at the previous monitoring time point;

[0023] 3. Verify and analyze the warning level and alarm level. By reasonably adjusting the threshold for triggering the warning signal, optimizing the data collection method of the waterlogging warning module and the processing means after the warning signal is triggered, the accuracy of the warning level is improved, ensuring that different levels of waterlogging can be handled accordingly, so as to use reasonable resources to reduce disaster losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 The figure is a system block diagram of the present invention as a whole. DETAILED DESCRIPTION

[0026] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] like Figure 1 As shown, a remote sensing monitoring system for corn waterlogging early warning includes a waterlogging early warning module, a waterlogging alarm module and a waterlogging early warning optimization module. The waterlogging early warning module includes a planting site monitoring unit and a precipitation monitoring unit. The waterlogging early warning module, the waterlogging alarm module and the waterlogging early warning optimization module are communicatively connected in sequence.

[0028] The planting site monitoring unit is used to monitor the water body and corn growth status of the corn planting site: the corn planting site is divided into several monitoring areas, and the fixed time point of each natural day is marked as the monitoring time point. At the monitoring time point, high-resolution remote sensing image data of the water body in the monitoring area is obtained, and the reflectivity data and water body index of the water body in different bands are extracted after radiation correction and geometric correction of the high-resolution remote sensing image data of the water body. The water body depth of the monitoring area is obtained by inversion of the physical model, and the water body depth of each monitoring area is summed and averaged to obtain the actual water body depth DS of the corn planting site; the water depth of a certain height is marked as the water depth threshold ZX, if the actual water depth DS is greater than or equal to the water depth threshold ZX, the water state of the corn planting site is marked as a waterlogged state, and the current monitoring time point is marked as the waterlogged existence time JC; if the actual water depth DS is less than the water depth threshold ZX, the water state of the corn planting site is marked as a non-waterlogged state, and the accumulated waterlogging time JT is cleared.

[0029] The high-resolution remote sensing data of corn in the monitoring area obtained at the monitoring time point were subjected to noise reduction, radiation correction and geometric correction to obtain reflectance data, leaf area index and vegetation index in different bands. The corn leaf length and plant height were inverted by the physical model. The leaf length and plant height of corn in each monitoring area were summed and averaged to obtain the average leaf length YC and plant height ZG of corn in the corn planting area. The growth coefficient SZ of corn in the corn planting area was obtained through numerical calculation using the formula SZ=k1*YC+k2*ZG, where k1 and k2 are proportional coefficients, and k2>k1>1.

[0030] The precipitation monitoring unit is used to monitor the precipitation information of the corn planting land: at the monitoring time point, the precipitation information of the corn planting land is obtained through the meteorological platform, and the precipitation information includes the expected 24-hour precipitation YJ, the precipitation start time and the actual 24-hour precipitation SJ; the precipitation start time on the day when the corn planting land is in a non-waterlogging state is recorded as the waterlogging start time JK.

[0031] The waterlogging warning module is used to warn of waterlogging according to the precipitation information of corn-planting areas: the necessity of waterlogging warning for corn-planting areas is analyzed at the monitoring time point: the actual water body depth DS is summed with the expected 24-hour precipitation YJ to obtain the expected water body depth YS at the next monitoring time point; if the expected water body depth YS is less than or equal to the water accumulation depth threshold ZX, the water body state of the corn-planting area is set to a non-water accumulation state, and no warning is required; if the expected water body depth YS is greater than the water accumulation depth threshold ZX, the water body state of the corn-planting area is set to a water accumulation state, and a warning signal is issued.

[0032] When the warning signal is issued, the waterlogging warning level of the corn planting area is analyzed: the flooding depth NS and flooding duration NT of the corn are obtained; the waterlogging start time JK and the waterlogging existence time JC are numerically calculated by the formula JT=JC-JK to obtain the cumulative waterlogging duration JT; if the expected water body depth YS is greater than or equal to the flooding depth NS and the cumulative waterlogging duration JT is greater than or equal to the flooding duration NT, the first-level warning signal is triggered; if the expected water body depth YS is less than or equal to the flooding depth NS and the cumulative waterlogging duration JT is less than or equal to the flooding duration NT, the third-level warning signal is triggered; if the expected water body depth YS is less than or equal to the flooding depth NS and the cumulative waterlogging duration JT is less than or equal to the flooding duration NT, the third-level warning signal is triggered; If the estimated water depth YS is greater than the flood-resistant depth NS but the cumulative water accumulation time JT is less than the flood-resistant time NT, or the estimated water depth YS is less than the flood-resistant depth NS but the cumulative water accumulation time JT is greater than the flood-resistant time NT, a second-level warning signal is triggered; if the estimated water depth YS is greater than the water depth danger threshold SSmax, a special warning signal is triggered; among them, the severity of waterlogging is ranked from special, level one, level two and level three from severe to mild; combining the actual water depth DS with precipitation information to warn of corn waterlogging, ensures the timeliness of corn waterlogging warning and improves the accuracy of corn waterlogging warning.

[0033] The waterlogging alarm module is used to alarm for waterlogging according to the impact of water on corn growth in the corn planting area: check the water status of the corn planting area at the monitoring time point. If the water status of the corn planting area is no water accumulation, there is no waterlogging risk and no alarm is needed; if the water status of the corn planting area is water accumulation, there is a waterlogging risk, triggering an alarm signal and performing an alarm level analysis; obtain the corn growth coefficient SZ1 at the current monitoring time point and the corn growth coefficient SZ0 at the previous monitoring time point, perform numerical calculations using the formula SB=(SZ1-SZ0) / SZ0, and obtain the corn growth change coefficient SB; obtain the corn The maximum alarm threshold BJmax and the minimum alarm threshold BJmin for waterlogging. If the growth variation coefficient SB of corn is greater than or equal to the maximum alarm threshold BJmax, a first-level alarm signal is triggered; if the growth variation coefficient SB of corn is less than the maximum alarm threshold BJmax and greater than the minimum alarm threshold BJmin, a second-level alarm signal is triggered; if the growth variation coefficient SB of corn is less than the minimum alarm threshold BJmin, a third-level alarm signal is triggered; by combining the growth variation coefficient SB of corn and the water state in the corn planting field, the corn planting field is promptly given a waterlogging alarm, and feedback is given on the accuracy of the warning at the previous monitoring time point.

[0034] The waterlogging warning optimization module is used to optimize the warning according to the results of the verification analysis of the warning level and the alarm level: when the alarm signal is triggered at the current monitoring time point, the warning signal of the previous monitoring time point is obtained. If the warning signal is not triggered at the previous monitoring time point, it is judged that the threshold for triggering the warning signal does not meet the requirements, and the water depth threshold ZX is lowered; if the warning signal is triggered at the previous monitoring time point, the warning level is compared with the alarm level. If the warning level is less than or equal to the alarm level, it is judged that the warning level meets the requirements and no optimization is required; if the warning level is greater than the alarm level, it is judged that the warning level does not meet the requirements, triggering the optimization decision analysis: the actual 24-hour precipitation SJ is compared with the expected Difference analysis of 24-hour precipitation YJ: The difference between the actual 24-hour precipitation SJ and the expected 24-hour precipitation YJ is calculated to obtain the precipitation deviation value JP. If the precipitation deviation value JP is greater than or equal to the difference threshold CY, it is judged that the actual and expected precipitation are different, and the data collection method of the waterlogging warning module needs to be optimized; if the precipitation deviation value JP is less than the difference threshold CY, it is judged that the actual and expected precipitation are not different, and the processing means after the warning signal is triggered needs to be optimized; the warning level and the alarm level are verified and analyzed to improve the accuracy of the warning and ensure that different levels of waterlogging can be handled accordingly, so as to use reasonable resources to reduce disaster losses.

[0035] A remote sensing monitoring system for corn waterlogging early warning, when in operation, monitors and analyzes the water body and corn growth status of a corn planting site through a remote sensing platform at a monitoring time point, and carries out daily waterlogging early warning and waterlogging alarm for the corn planting site based on precipitation information obtained from a meteorological platform, and optimizes the waterlogging early warning process by verifying and analyzing the waterlogging alarm level with the warning level at the previous monitoring time point.

[0036] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0037] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula SZ=k1*YC+k2*ZG; technicians in this field collect multiple groups of sample data and set corresponding growth coefficients for each group of sample data; substitute the set growth coefficients and the collected sample data into the formula, any two formulas constitute a binary linear equation system, the calculated coefficients are screened and averaged, and the values ​​of k1 and k2 are 3.65 and 2.39 respectively;

[0038] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding growth coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the growth coefficient is proportional to the average value of the plant height.

[0039] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0040] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A remote sensing monitoring system for early warning of corn waterlogging, characterized in that: It includes a waterlogging early warning module, a waterlogging alarm module and a waterlogging early warning optimization module, wherein the waterlogging early warning module includes a planting site monitoring unit and a precipitation monitoring unit; the waterlogging early warning module, the waterlogging alarm module and the waterlogging early warning optimization module are sequentially connected in communication; The planting site monitoring unit is used to monitor the water body and corn growth status of the corn planting site: mark a fixed time point of each natural day as a monitoring time point, obtain the actual water body depth DS and the corn growth coefficient SZ of the corn planting site at the monitoring time point; mark the water body status of the water body as a waterlogging state or a non-waterlogging state according to the value of the actual water body depth DS; The precipitation monitoring unit is used to monitor the precipitation information of the corn planting land: obtaining the precipitation information of the corn planting land through the meteorological platform at the monitoring time point; The waterlogging warning module is used to warn of waterlogging according to the precipitation information of the corn planting area: at the monitoring time point, by combining the precipitation information with the actual water depth DS, the necessity of waterlogging warning for the corn planting area is judged. If a warning is needed, the warning level of the waterlogging is analyzed and a warning is issued; The waterlogging alarm module is used to alarm for waterlogging according to the influence of water on corn growth in the corn planting land: the water state of the corn planting land is checked at the monitoring time point, and if the water state of the corn planting land is a waterlogging state, an alarm signal is triggered, and the growth coefficient SZ of the corn is numerically calculated to obtain the growth change coefficient SB, and the alarm level is analyzed according to the value of the growth change coefficient SB and an alarm is issued; The waterlogging early warning optimization module is used to optimize the early warning according to the results of the early warning level and the alarm level verification analysis; The process of monitoring the water body in the corn planting area includes: dividing the corn planting area into several monitoring areas, obtaining high-resolution remote sensing image data of the water body in the monitoring area at the monitoring time point, preprocessing, feature extraction and physical model inversion of the high-resolution remote sensing image data to obtain the water body depth of the monitoring area, summing and averaging the water body depths of each monitoring area to obtain the actual water body depth DS of the corn planting area; comparing the actual water body depth DS with the preset water accumulation depth threshold ZX: if the actual water body depth DS is greater than or equal to the water accumulation depth threshold ZX, then the water body state of the corn planting area is marked as a water accumulation state, and the current monitoring time point is marked as the water accumulation existence time JC; if the actual water body depth DS is less than the water accumulation depth threshold ZX, then the water body state of the corn planting area is marked as a non-water accumulation state, and the accumulated water accumulation time JT is cleared; The process of monitoring the growth status of corn includes: preprocessing the high-resolution remote sensing data of corn in the monitoring area obtained at the monitoring time point, extracting features and inverting the physical model to obtain the corn leaf length and plant height, summing up the leaf length and plant height of corn in each monitoring area and taking the average value to calculate the average leaf length YC and the average plant height ZG of corn in the corn planting field, and numerically calculating the growth coefficient SZ of corn in the corn planting field through the formula SZ=k1*YC+k2*ZG, wherein k1 and k2 are both proportional coefficients, and k2>k1>1; The process of alarming against waterlogging according to the influence of water bodies on corn growth in corn planting lands includes: checking the water state of corn planting lands at the monitoring time point, if the water state of the corn planting lands is a state without water accumulation, there is no risk of waterlogging and no need to alarm; if the water state of the corn planting lands is a state with water accumulation, there is a risk of waterlogging, an alarm signal is triggered, and an alarm level analysis is performed; the corn growth coefficient SZ1 at the current monitoring time point and the corn growth coefficient SZ0 at the previous monitoring time point are obtained, and the growth variation coefficient SB of corn is obtained by numerical calculation using the formula SB=(SZ1-SZ0) / SZ0; the maximum alarm threshold BJmax and the minimum alarm threshold BJmin of corn waterlogging are obtained, and if the growth variation coefficient SB of corn is greater than or equal to the maximum alarm threshold BJmax, a first-level alarm signal is triggered; if the growth variation coefficient SB of corn is less than the maximum alarm threshold BJmax and greater than the minimum alarm threshold BJmin, a second-level alarm signal is triggered; if the growth variation coefficient SB of corn is less than the minimum alarm threshold BJmin, a third-level alarm signal is triggered; The process of optimizing the early warning according to the results of the verification analysis of the early warning level and the alarm level includes: when the alarm signal is triggered at the current monitoring time point, the early warning signal at the previous monitoring time point is obtained. If the early warning signal is not triggered at the previous monitoring time point, it is judged that the threshold for triggering the early warning signal does not meet the requirements, and the water accumulation depth threshold ZX is lowered; if the early warning signal is triggered at the previous monitoring time point, the early warning level and the alarm level are compared. If the early warning level is less than or equal to the alarm level, it is judged that the early warning level meets the requirements and no optimization is required; if the early warning level is greater than the alarm level, it is judged that the early warning level does not meet the requirements, and the optimization decision analysis is triggered: the difference analysis of the actual 24-hour precipitation SJ and the expected 24-hour precipitation YJ is performed: the difference between the actual 24-hour precipitation SJ and the expected 24-hour precipitation YJ is calculated to obtain the precipitation deviation value JP. If the precipitation deviation value JP is greater than or equal to the difference threshold CY, it is judged that the actual and expected precipitation are different, and the data collection method of the waterlogging early warning module needs to be optimized; if the precipitation deviation value JP is less than the difference threshold CY, it is judged that the actual and expected precipitation are not different, and the processing means after the early warning signal is triggered need to be optimized.

2. A remote sensing monitoring system for corn waterlogging early warning according to claim 1, characterized in that: The precipitation information includes the expected 24-hour precipitation YJ, the precipitation start time and the actual 24-hour precipitation SJ; the precipitation start time on the day when the corn planting land is in a waterlogging state is recorded as the waterlogging start time JK.

3. A remote sensing monitoring system for corn waterlogging early warning according to claim 2, characterized in that: The process of analyzing the necessity of waterlogging warning for corn-planting areas includes: summing the actual water depth DS and the expected 24-hour precipitation YJ to obtain the expected water depth YS at the next monitoring time point; if the expected water depth YS is less than or equal to the water accumulation depth threshold ZX, the water state of the corn-planting area is set to a non-water accumulation state, and no warning is required; if the expected water depth YS is greater than the water accumulation depth threshold ZX, the water state of the corn-planting area is set to a water accumulation state, and a warning signal is issued.

4. A remote sensing monitoring system for corn waterlogging early warning according to claim 3, characterized in that: The process of analyzing the waterlogging warning level of corn planting areas includes: obtaining the flooding tolerance threshold of corn: flooding tolerance depth NS and flooding tolerance time NT; numerically calculating the waterlogging start time JK and the waterlogging existence time JC through the formula JT=JC-JK to obtain the cumulative waterlogging time JT; if the expected water body depth YS is greater than or equal to the flooding tolerance depth NS and the cumulative waterlogging time JT is greater than or equal to the flooding tolerance time NT, a first-level warning signal is triggered; if the expected water body depth YS is less than or equal to the flooding tolerance depth NS and the cumulative waterlogging time JT is less than or equal to the flooding tolerance time NT, a third-level warning signal is triggered; if the expected water body depth YS is greater than the flooding tolerance depth NS but the cumulative waterlogging time JT is less than the flooding tolerance time NT or the expected water body depth YS is less than the flooding tolerance depth NS but the cumulative waterlogging time JT is greater than the flooding tolerance time NT, a second-level warning signal is triggered; if the expected water body depth YS is greater than the water depth danger threshold SSmax, a special-level warning signal is triggered: the severity of waterlogging disasters is from severe to mild, namely special, first, second and third levels.

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