A farmland intelligent protection real-time dynamic monitoring method applied to a multi-cloud and multi-fog area

Abstract

The application belongs to the technical field of cultivated land protection, and particularly relates to a real-time dynamic monitoring method for cultivated land protection applied to a cloudy and foggy area. The application can evaluate the best cultivated land area according to historical crop yield, compare the best cultivated land area with a real-time state cultivated land area, so as to determine whether the cultivated land is infringed, and can also monitor an increased area and a reduced area in a cultivated land change process, respectively calculate the change trend of the increased area and the reduced area, finally predict the cultivated land change result in combination with a change period, and optimize the reduced area according to the situation of occupying additional cultivated land, so that no extra cultivated land is occupied in the cultivated land change process, and the cultivated land in the monitoring area is effectively protected.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of cultivated land protection, and particularly relates to a real-time dynamic monitoring method for cultivated land protection applied to a cloudy and foggy area. BACKGROUND

[0002] Cultivated land refers to land for planting crops, including cultivated land, newly developed and reclaimed land, idle land, rotation land and grassland, with the rapid economic development, more and more civil buildings or industrial buildings cover the original cultivated land, resulting in a continuous decrease in the cultivated land area in China, and a large decrease in the cultivated land area will directly threaten the agricultural development, so it can be seen that real-time mandatory cultivated land protection is very necessary, which is a global strategic problem related to the sustainable development of the economy and society in China, and with the development of information technology, an intelligent protection system for cultivated land emerges as the times require, so that the way for people to protect cultivated land is changed from on-site operation to remote operation, especially for the cloudy and foggy area, artificial survey is extremely laborious, and it is difficult to prevent the occurrence of cultivated land invasion time, but the remote monitoring method can solve this problem, for example, low-altitude cruising of the unmanned aerial vehicle, which can not only collect ground information, but also quickly survey regardless of the terrain, thereby saving manpower and enabling more rapid and comprehensive monitoring.

[0003] The existing cultivated land protection system only has a cruising function and processes the cultivated land invasion event when it is found, but during the cultivated land change process, the cultivated land may be changed and cannot be restored, so the upper limit of the change is reduced, and the change period is also reduced accordingly, but the occupation of the cultivated land is still continued, obviously, this will cause the occupation of the redundant cultivated land, based on this, the present application provides a real-time dynamic monitoring method for cultivated land protection applied to a cloudy and foggy area. SUMMARY

[0004] The application aims to provide a real-time dynamic monitoring method for cultivated land protection applied to a cloudy and foggy area, which can monitor the increased area and the decreased area in real time during the cultivated land change process, and avoid the occurrence of additional occupied cultivated land during the change process.

[0005] The technical scheme adopted by the application is as follows:

[0006] A real-time dynamic monitoring method for cultivated land protection applied to a cloudy and foggy area, comprising:

[0007] acquiring a monitoring area, wherein the monitoring area comprises a cultivated land area and a non-cultivated land area;

[0008] acquiring the areas of the cultivated land area and the non-cultivated land area, inputting the areas into a calculation model, obtaining the proportion of the cultivated land area, and marking the proportion as a to-be-evaluated parameter;

[0009] acquiring a normal parameter of the cultivated land area in the to-be-detected region and comparing the normal parameter with the to-be-evaluated parameter;

[0010] if the normal parameter is less than or equal to the to-be-evaluated parameter, determining that the cultivated land area of the monitoring region is normal, and acquiring a change region of the cultivated land area in real time and summarizing the change region into a to-be-evaluated data set;

[0011] if the normal parameter is greater than the to-be-evaluated parameter, determining that the cultivated land area of the monitoring region is reduced, and generating an alarm signal;

[0012] classifying the change region of the cultivated land area in the to-be-evaluated data set to obtain an increase region and a decrease region;

[0013] inputting the increase region and the decrease region into a trend analysis model respectively to obtain a change trend of the increase region and the decrease region respectively, and labeling the change trend of the increase region and the change trend of the decrease region as an increase trend value and a decrease trend value respectively;

[0014] if the increase trend value is less than the decrease trend value, generating a pre-warning signal;

[0015] if the increase trend value is greater than the decrease trend value, determining that the cultivated land area is normal;

[0016] acquiring a change period of the increase region and the decrease region respectively, and combining and operating the increase trend value and the decrease trend value to obtain a terminal increase region and a terminal decrease region, and comparing the terminal increase region with the terminal decrease region;

[0017] if the terminal increase region is less than the terminal decrease region, issuing a pre-warning signal and generating a correction plan for the decrease region;

[0018] if the terminal increase region is greater than or equal to the terminal decrease region, determining that the cultivated land area is normal.

[0019] In a preferred scheme, the step of acquiring the area of the cultivated land area and the non-cultivated land area and inputting the area into a calculation model to obtain the proportion of the cultivated land area comprises:

[0020] acquiring the area of the cultivated land area and the non-cultivated land area;

[0021] acquiring a standard function from the evaluation model;

[0022] inputting the area of the cultivated land area and the non-cultivated land area into the standard function, and labeling a calculation result as the proportion of the cultivated land area.

[0023] In a preferred scheme, the step of acquiring the normal parameter of the cultivated land area in the to-be-detected region comprises:

[0024] constructing a sampling period, the sampling period comprising a plurality of statistical nodes;

[0025] Obtaining historical crop yields under the statistical node and sorting them according to occurrence time;

[0026] Obtaining a standard yield and comparing it with all the historical crop yields, screening all the historical crops greater than or equal to the standard yield and marking them as qualified yields;

[0027] Obtaining the farmland areas corresponding to all the qualified yields and arranging them in descending order, and marking the smallest farmland area as a temporary parameter;

[0028] Obtaining the statistical node under the temporary parameter and all the historical crop yields and inputting them into a judgment model to determine whether the temporary parameter can be used as a rated parameter;

[0029] If yes, directly marking the temporary parameter as a rated parameter;

[0030] If no, continuing to obtain the farmland area next in order and greater than the qualified yield and inputting it into the judgment model as a temporary parameter.

[0031] In a preferred embodiment, when obtaining the statistical node under the temporary parameter, the following steps are included:

[0032] Obtaining the number of statistical nodes under the temporary parameter;

[0033] Obtaining a standard evaluation number and comparing it with the number of statistical nodes, wherein the value of the standard evaluation number is n and n≥5;

[0034] If the standard evaluation number is greater than the number of statistical nodes, it is determined that the historical crop yields under the temporary parameter cannot be input into the judgment model, and the farmland area next in order and greater than the qualified yield is continuously obtained;

[0035] If the standard evaluation number is less than or equal to the number of statistical nodes, it is determined that the historical crop yields under the temporary parameter can be input into the judgment model.

[0036] In a preferred embodiment, the step of inputting all the historical crop yields under the temporary parameter into the judgment model to determine whether the temporary parameter can be used as a rated parameter includes:

[0037] Obtaining all the historical crop yields under the temporary parameter and determining whether there is a historical crop yield less than the standard yield;

[0038] If yes, calculating the proportion of the historical crop yield less than the standard yield;

[0039] If the ratio of the historical crop yield less than the standard yield is less than or equal to 80%, it is determined that the temporary parameter cannot be used as the rated parameter;

[0040] If the ratio of the historical crop yield less than the standard yield is greater than 80%, it is determined that the temporary parameter can be used as the rated parameter;

[0041] If not, it is directly determined that the temporary parameter can be used as the rated parameter.

[0042] In a preferred embodiment, the step of inputting the increase area and the decrease area into the trend analysis model respectively to obtain the change trend of the increase area and the decrease area respectively, and labeling the increase trend value and the decrease trend value respectively, comprises:

[0043] Obtaining the starting node and the current monitoring node of the cultivated land change in the monitoring area to obtain the measurement period;

[0044] Constructing a plurality of sampling nodes in the measurement period, and obtaining the increase area and the decrease area under each sampling node respectively, wherein the sampling nodes are provided with m, and m≥10;

[0045] Obtaining the trend analysis function from the trend analysis model, and inputting the increase area and the decrease area under each sampling node into the trend analysis function respectively to obtain the increase trend value and the decrease trend value.

[0046] In a preferred embodiment, when obtaining the increase area and the decrease area under each sampling node respectively, the increase area and the decrease area under adjacent sampling nodes are compared, and the instantaneous change amount of the increase area and the decrease area is screened out, and the specific process is as follows:

[0047] Obtaining the difference value of the increase area and the decrease area under adjacent sampling, and labeling it as the to-be-evaluated change amount;

[0048] Obtaining the allowable change interval, and comparing it with the to-be-evaluated change amount one by one;

[0049] If the to-be-evaluated change amount is in the allowable change interval, it is determined that the to-be-evaluated change amount is a normal change amount, and it is added to the trend analysis function;

[0050] If the to-be-evaluated change amount is not in the allowable change interval, it is determined that the to-be-evaluated change amount is an instantaneous change amount, and the corresponding increase area or decrease area is screened out.

[0051] In a preferred embodiment, the step of obtaining the change period of the increase area and the decrease area respectively, and combining and operating the increase trend value and the decrease trend value to obtain the terminal increase area and the terminal decrease area comprises:

[0052] respectively, and compare them;

[0053] If the change period of the increase area is greater than or equal to the change period of the decrease area, it is directly determined that the terminal increase area is greater than the terminal decrease area;

[0054] If the change period of the increase area is less than the change period of the decrease area, a calculation function is obtained;

[0055] The change period, the increase trend value and the decrease trend value are input into the calculation function to obtain the terminal increase area and the terminal decrease area.

[0056] The application also provides a farmland intelligent protection real-time dynamic monitoring system applied to a multi-cloud and multi-fog area, which is applied to the multi-cloud and multi-fog area farmland intelligent protection real-time dynamic monitoring method.

[0057] A data acquisition module is configured to acquire a monitoring area, wherein the monitoring area includes a farmland area and a non-farmland area;

[0058] A calculation module is configured to acquire areas of the farmland area and the non-farmland area, input the areas into a calculation model, obtain an area ratio of the farmland area, and mark the area ratio as an evaluation parameter;

[0059] A determination module is configured to acquire a rated parameter of the farmland area in a detection area and compare the rated parameter with the evaluation parameter;

[0060] If the rated parameter is less than or equal to the evaluation parameter, it is determined that the farmland area of the monitoring area is normal, and a change area of the farmland area is acquired in real time and summarized as an evaluation data set;

[0061] If the rated parameter is greater than the evaluation parameter, it is determined that the farmland area of the monitoring area is reduced, and an alarm signal is generated;

[0062] A classification module is configured to classify the change area of the farmland area in the evaluation data set to obtain an increase area and a decrease area;

[0063] A first evaluation module is configured to input the increase area and the decrease area into a trend analysis model respectively to obtain a change trend of the increase area and the decrease area respectively, and mark the change trend of the increase area as an increase trend value and the change trend of the decrease area as a decrease trend value;

[0064] If the increase trend value is less than the decrease trend value, a warning signal is generated;

[0065] If the increase trend value is greater than the decrease trend value, it is determined that the farmland area is normal;

[0066] a second evaluation module for obtaining a change period of the increased area and the decreased area respectively, and combining the increased trend value and the decreased trend value to obtain a terminal increased area and a terminal decreased area, and comparing the terminal increased area with the terminal decreased area;

[0067] if the terminal increased area is less than the terminal decreased area, a warning signal is sent, and a correction plan for the decreased area is generated;

[0068] if the terminal increased area is greater than or equal to the terminal decreased area, it is determined that the cultivated land area is normal.

[0069] and a cultivated land intelligent protection real-time dynamic monitoring terminal applied to a multi-cloud and multi-fog area, comprising:

[0070] at least one processor;

[0071] and a memory in communication connection with the at least one processor;

[0072] wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the above-mentioned multi-cloud and multi-fog area cultivated land intelligent protection real-time dynamic monitoring method.

[0073] The technical effects obtained by the present application are:

[0074] The present application can evaluate the optimal cultivated land area according to the historical crop yield, and compare it with the real-time state of the cultivated land area to determine whether the cultivated land is infringed, and can also monitor the increased area and the decreased area in the process of cultivated land change, calculate the change trend of the increased area and the decreased area respectively, and finally predict the cultivated land change result by combining the change period, and optimize the decreased area according to the situation of occupying additional cultivated land, so that there is no extra cultivated land occupied in the process of cultivated land change, and the cultivated land in the monitoring area is effectively protected. BRIEF DESCRIPTION OF DRAWINGS

[0075] Figure 1 is a method flowchart provided by the present application;

[0076] Figure 2 is a system module diagram provided by the present application. DETAILED DESCRIPTION

[0077] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0078] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be appreciated that the present application can be practiced in a variety of ways beyond the specific details set forth herein, assuming that the fundamental underlying principles are maintained. It should also be appreciated that the description set forth herein is not intended as a limitation on the scope of the present application but is intended to provide a description of one or more implementations thereof.

[0079] Secondly, the "one embodiment" or "an embodiment" referred to herein means a specific feature, structure, or characteristic under discussion. Thus, "in one preferred embodiment" at one location does not necessarily mean the same embodiment as "in one preferred embodiment" at another location. Moreover, "in one preferred embodiment" does not necessarily mean that all embodiments leading to that preferred embodiment are preferred or even possible.

[0080] Referring to FIGS. 1-3, Figure 1 and Figure 2 The present application provides a farmland intelligent protection real-time dynamic monitoring method for a multi-cloud and multi-fog area, which comprises the following steps:

[0081] S1, acquiring a monitoring area, wherein the monitoring area comprises a farmland area and a non-farmland area;

[0082] S2, acquiring the areas of the farmland area and the non-farmland area, and inputting the areas into a calculation model to obtain a proportion of the farmland area, and marking the proportion as an evaluation parameter;

[0083] S3, acquiring a rated parameter of the farmland area in the monitoring area, and comparing the rated parameter with the evaluation parameter;

[0084] If the rated parameter is less than or equal to the evaluation parameter, it is determined that the farmland area of the monitoring area is normal, and a change area of the farmland area is acquired in real time, and the change area is summarized as an evaluation data set;

[0085] If the rated parameter is greater than the evaluation parameter, it is determined that the farmland area of the monitoring area is reduced, and an alarm signal is generated;

[0086] S4, classifying the change area of the farmland area in the evaluation data set to obtain an increased area and a reduced area;

[0087] S5, inputting the increased area and the reduced area into a trend analysis model respectively to obtain a change trend of the increased area and the reduced area respectively, and marking the change trend of the increased area as an increased trend value and the change trend of the reduced area as a reduced trend value respectively;

[0088] If the increased trend value is less than the reduced trend value, a warning signal is generated;

[0089] If the increased trend value is greater than the reduced trend value, it is determined that the farmland area is normal;

[0090] S6、respectively acquire the change period of the increase area and the decrease area, and combine and operate with the increase trend value and the decrease trend value, to obtain the terminal increase area and the terminal decrease area, and compare them;

[0091] If the terminal increase area is less than the terminal decrease area, an early warning signal is sent out, and a correction plan for the decrease area is generated;

[0092] If the terminal increase area is greater than or equal to the terminal decrease area, it is determined that the cultivated land area is normal.

[0093] As described in steps S1-S6 above, farmland protection is a global strategic issue related to the sustainable development of China's economy and society. A large reduction in farmland area will directly threaten agricultural development, so it is necessary to implement farmland protection measures compulsorily. However, some people will still cause harm to farmland, such as building tombs, houses and factories in violation of regulations, which will lead to a continuous reduction in the area of farmland in China over a long period of time. This is obviously not in line with the global strategy of sustainable development. However, China has a wide land area, and it is obviously not desirable to rely solely on human monitoring. With the advent of the information age, it is obviously very convenient to use camera and other image capture devices for remote monitoring to ensure the timeliness of data and to enable timely discovery of farmland infringement events and the taking of appropriate measures. However, in actual situations, each region has a corresponding economic development plan, so farmland will be expropriated and some dilapidated building areas will be planned for the restoration of farmland. In the present embodiment, the region to be monitored is first determined, and then the farmland area and non-farmland area in the region are counted. The farmland area mainly includes crop land, and the non-farmland area includes building land and industrial land, etc. The proportion of the farmland area in the monitored region can be calculated by a calculation model, and then combined with a rated parameter to determine whether the farmland area in the monitored region is normal. For abnormal situations, an alarm signal is generated to notify the regulatory department, which can then re-plan the farmland area and the non-farmland area in the region. However, for farmland areas with normal results, there will still be a situation of a reduction in farmland, i.e. the change area of the farmland area in the present embodiment. This can be divided into an increase area and a decrease area, and on the premise that the increase area is greater than the decrease area, a trend analysis model is used to analyze the change trend of the increase area and the decrease area to determine whether the change area of the farmland area is showing a decreasing trend. If there is a decreasing trend, a warning signal is sent to notify the regulatory department, which can intervene and curb the decreasing trend. This method only provides data support for the regulatory department and does not participate in decision-making, which is determined and implemented by human subjectivity. This embodiment does not limit or excessively elaborate on this. The situation where the increase area is greater than the decrease area is then analyzed to prevent the additional occupation of excess farmland during the change of farmland. For situations where the increase trend value is greater than the decrease trend value, further evaluation is needed according to the change period to avoid a reduction in the area of the farmland area after the completion of the increase area and the decrease area. This realizes a prediction process to help the regulatory department develop a corresponding correction plan, such as expanding the increase area and reducing the area of the decrease area. This will not be elaborated on here. Conversely, at the end of the change period, if the area of the increase area is greater than the area of the decrease area, it means that the farmland is ultimately increased, and then the monitoring work can continue normally.In this way, early warning information can be provided to the regulatory department before the cultivated land area is reduced, and the purpose of protecting the cultivated land can be achieved by timely stopping the cultivated land infringement.

[0094] In a preferred embodiment, the step of obtaining the area of the cultivated land region and the non-cultivated land region and inputting the area into the calculation model to obtain the proportion of the cultivated land region comprises:

[0095] S201, obtaining the area of the cultivated land region and the non-cultivated land region;

[0096] S202, obtaining the standard function from the evaluation model;

[0097] S203, inputting the area of the cultivated land region and the non-cultivated land region into the standard function, and marking the calculation result as the proportion of the cultivated land region.

[0098] As described above in steps S201-S203, when calculating the proportion of the cultivated land region, the region can be globally scanned by a camera carried by a drone, or fixed cameras for collecting the cultivated land region can be arranged at intervals to extract the area of the cultivated land region and the non-cultivated land region, respectively, and then the standard function P=G a / (G a +G b ) is used, wherein P represents the proportion of the cultivated land region, i.e., the evaluation parameter proposed in this embodiment, G a represents the area of the cultivated land region, and G b represents the area of the non-cultivated land region. For different monitoring regions, the above formula can be used to calculate the proportion of the cultivated land region to obtain the real-time status of the cultivated land, and after outputting the calculation result, the result is compared with the rated parameter, and it is determined whether to send an alarm signal.

[0099] In a preferred embodiment, the step of obtaining the rated parameter of the cultivated land region in the region to be detected comprises:

[0100] S301, constructing a sampling period, the sampling period comprising a plurality of statistical nodes;

[0101] S302, obtaining the historical crop yield under the statistical node and sorting according to the occurrence time;

[0102] S303, obtaining the standard yield and comparing with all the historical crop yields to screen out all the historical crops greater than or equal to the standard yield and mark them as qualified yields;

[0103] S304, obtaining the cultivated land area corresponding to all the qualified yields and arranging them in descending order, and marking the minimum cultivated land area as a temporary parameter;

[0104] S305, acquire the statistical nodes under the temporary parameters, and all the historical crop yields, and input into the determination model to determine whether the temporary parameters can be used as the rated parameters;

[0105] If yes, directly determine the temporary parameters as the rated parameters;

[0106] If no, continue to acquire the next place and the farmland area greater than the qualified yield, and input into the determination model as the temporary parameters.

[0107] As described in the above steps S301-S305, with the development of agriculture, people are gradually improving the varieties of crops, so that they can achieve high yield in the inherent farmland, thereby reducing the corresponding farmland for economic development. Of course, the standard yield in each region is fixed, and when determining the standard yield, it should be determined according to the population number in China. After determining the standard yield, compare it with the historical crop yield, and select all the historical crops greater than or equal to the standard yield as the qualified yield. In this embodiment, the minimum farmland area corresponding to the qualified yield is selected and determined as the temporary parameter. Generally, the change of farmland is a long-term and slow process, and after the change of farmland, it will be ensured that it will not change for a period of time, or the historical crop yield in this stage is input into the determination model to determine whether the temporary parameter can be used as the rated parameter.

[0108] In a preferred embodiment, when acquiring the statistical nodes under the temporary parameters, the following steps are included:

[0109] Stp1, acquire the number of statistical nodes under the temporary parameters;

[0110] Stp2, acquire the standard evaluation number and compare it with the number of statistical nodes, wherein the value of the standard evaluation number is n, and n≥5;

[0111] If the standard evaluation number is greater than the number of statistical nodes, it is determined that the historical crop yield under the temporary parameters cannot be input into the determination model, and the next place and the farmland area greater than the qualified yield are continuously acquired;

[0112] If the standard evaluation number is less than or equal to the number of statistical nodes, it is determined that the historical crop yield under the temporary parameters can be input into the determination model.

[0113] As described in the above steps Stpl-step Stp2, the continuity of the temporary parameters analyzed in this embodiment mainly analyzes the continuity of the temporary parameters, for example, the cultivated land area under the temporary parameters only corresponds to two sets of historical crop yields, and one set of historical crop yields is less than the qualified yield. It cannot be determined whether it reaches the qualified yield due to the influence of external factors (such as climate, rainwater is of high quality), nor can it be determined whether it is lower than the qualified yield due to the influence of external factors (heavy rain, drought, etc.). Therefore, it is necessary to determine whether the temporary parameters meet the conditions for inputting into the determination model.

[0114] In a preferred embodiment, all historical crop yields under the temporary parameters are input into the determination model to determine whether the temporary parameters can be used as the rated parameters, including:

[0115] Stp3, obtaining all historical crop yields under the temporary parameters, and determining whether there is a historical crop yield less than the standard yield;

[0116] Stp4, if there is, calculating the proportion of historical crop yields less than the standard yield;

[0117] If the proportion of historical crop yields less than the standard yield is less than or equal to 80%, it is determined that the temporary parameters cannot be used as the rated parameters;

[0118] If the proportion of historical crop yields less than the standard yield is more than 80%, it is determined that the temporary parameters can be used as the rated parameters;

[0119] Stp5, if not, it is directly determined that the temporary parameters can be used as the rated parameters.

[0120] As described in the above steps Stpl-step Stp2, the continuity of the temporary parameters analyzed in this embodiment mainly analyzes the continuity of the temporary parameters, for example, the cultivated land area under the temporary parameters only corresponds to two sets of historical crop yields, and one set of historical crop yields is less than the qualified yield. It cannot be determined whether it reaches the qualified yield due to the influence of external factors (such as climate, rainwater is of high quality), nor can it be determined whether it is lower than the qualified yield due to the influence of external factors (heavy rain, drought, etc.). Therefore, it is necessary to determine whether the temporary parameters meet the conditions for inputting into the determination model.

[0121] In a preferred embodiment, the increasing area and the decreasing area are respectively input into the trend analysis model to obtain the change trend of the increasing area and the decreasing area respectively, and the step of marking the increasing trend value and the decreasing trend value respectively comprises:

[0122] S501, obtaining the starting node and the current monitoring node of the cultivated land change in the monitoring area to obtain the measurement period;

[0123] S502, constructing a plurality of sampling nodes in the measurement period, and obtaining the increasing area and the decreasing area under each sampling node respectively, wherein the sampling nodes are provided with m, and m≥10;

[0124] S503, obtaining a trend analysis function from the trend analysis model, and inputting the increasing area and the decreasing area under each sampling node into the trend analysis function to obtain the increasing trend value and the decreasing trend value.

[0125] As described in the above steps S501-S503, when the cultivated land change occurs in the monitoring area, the measurement period is constructed accordingly, and the cultivated land change is a long-term process, so the measurement period has a long period. Before the trend analysis is performed, a plurality of sampling nodes are constructed in the measurement period, and the trend analysis can be performed only after the number of sampling nodes exceeds m, otherwise it is easy to have the problem that the accurate analysis result cannot be obtained due to less data. Of course, the larger the value of m is, the more accurate the result of the trend analysis is. When the interval of the sampling nodes is determined, it can be set according to the specific requirements, wherein the trend analysis function is: In the formula, Q j represents the increasing trend value or the decreasing trend value, t represents the measurement period, r represents the total amount of the sampling nodes, M jh represents the area of the increasing area or the area of the decreasing area in the interval 1-r, h represents the number of the area of the increasing area and the area of the decreasing area in the measurement period, and j represents the number of the increasing area and the decreasing area, for example, j=1, 2, wherein the number 1 is the increasing area, and the number 2 represents the decreasing area, which is only a substitute symbol and does not participate in and affect the operation of the formula.

[0126] In a preferred embodiment, when the increasing area and the decreasing area under each sampling node are obtained, the increasing area and the decreasing area under adjacent sampling nodes are compared to screen out the instantaneous change amount of the increasing area and the decreasing area, and the specific process is as follows:

[0127] Step 1, obtaining the difference value of the increasing area and the decreasing area under adjacent sampling, and marking it as the to-be-evaluated change amount;

[0128] Step 2, obtaining the allowable change interval, and comparing it with the to-be-evaluated change amount one by one;

[0129] If the to-be-evaluated change amount is within the allowable change interval, the to-be-evaluated change amount is determined to be a normal change amount, and is added to the trend analysis function;

[0130] If the to-be-evaluated change amount is not within the allowable change interval, the to-be-evaluated change amount is determined to be a transient change amount, and the corresponding increase area or decrease area is excluded.

[0131] As described in steps 1 to 2 above, when the cultivated area changes, transient changes will inevitably occur. For example, under heavy rain, the increase process and decrease process of the cultivated area will be affected accordingly. Conversely, a temporary and significant increase in the work efficiency of the increase area or the decrease area will also cause a large fluctuation in the change of the cultivated area. This fluctuation will have a greater impact on the trend analysis process, and ultimately will cause the calculation error of the increase trend value and the decrease trend value to increase. In this embodiment, the to-be-evaluated change amount is analyzed by pre-setting the allowable deviation interval, and the increase area and the decrease area that produce the transient change amount are excluded. Accordingly, the corresponding sampling nodes are also excluded, which will divide the measurement period into multiple discontinuous short-term periods. Based on this situation, the trend analysis function is optimized accordingly, and the optimization result is: t1, t2 represent short-term periods, f represents the number of short-term periods, M ji , M jk represents the area of the increase area or the area of the decrease area in the short-term period. The meaning of M jh is the same, i and k represent the number of the area of the increase area or the area of the decrease area in different short-term periods, x and y represent the number of sampling nodes in each short-term period, which is only a substitute symbol and can be accurate to a specific value during specific operation. It needs to be analyzed according to the specific situation, and is not limited here. Based on this formula, the accurate increase trend value and the decrease trend value can be calculated.

[0132] In a preferred embodiment, the step of obtaining the change period of the increase area and the decrease area respectively and combining the increase trend value and the decrease trend value to obtain the terminal increase area and the terminal decrease area comprises:

[0133] S601, respectively obtaining the change period of the increase area and the decrease area, and comparing;

[0134] S602, if the change period of the increase area is greater than or equal to the change period of the decrease area, directly determining that the terminal increase area is greater than the terminal decrease area;

[0135] S603, if the change period of the increase area is less than the change period of the decrease area, obtaining a measurement function;

[0136] S604, input the change period, the increase trend value and the decrease trend value into the calculation function to obtain a terminal increase area and a terminal decrease area.

[0137] As described in the above steps S601-S604, for the change of the increase area and the decrease area in the monitoring area, it is carried out under the premise of reporting to the supervision department, and for the case of illegal encroachment on cultivated land, an alarm signal is immediately sent out when this case is monitored, and the supervision department can carry out targeted processing according to the alarm signal, and the change period of the increase area and the decrease area may be inconsistent, and under the premise that the increase area is greater than the decrease area and the increase trend value is greater than the decrease trend value, the change period is obtained, and then the calculation function is: Z = T * (A + B) / 2 j indicates the terminal increase area or the terminal decrease area, T indicates the change period, indicates the area of the increase area or the area of the decrease area in the current state, based on this, the cultivated land area under the stop node of the increase area is taken as a reference to set the change upper limit of the decrease area, so as to avoid the occurrence of additional occupied cultivated land in the process of cultivated land change.

[0138] The application also provides a cultivated land intelligent protection real-time dynamic monitoring system applied to a multi-cloud and multi-fog area, which is applied to the multi-cloud and multi-fog area cultivated land intelligent protection real-time dynamic monitoring method, and comprises:

[0139] A data acquisition module is configured to acquire a monitoring area, wherein the monitoring area comprises a cultivated land area and a non-cultivated land area.

[0140] A calculation module is configured to acquire the areas of the cultivated land area and the non-cultivated land area, input the areas into a calculation model, obtain the proportion of the cultivated land area, and label the proportion as an evaluation parameter.

[0141] A determination module is configured to acquire a rated parameter of the cultivated land area in the monitoring area and compare the rated parameter with the evaluation parameter.

[0142] If the rated parameter is less than or equal to the evaluation parameter, it is determined that the cultivated land area of the monitoring area is normal, and a change area of the cultivated land area is acquired in real time and is summarized as an evaluation data set.

[0143] If the rated parameter is greater than the evaluation parameter, it is determined that the cultivated land area of the monitoring area is reduced, and an alarm signal is generated.

[0144] A classification module is configured to classify the change area of the cultivated land area in the evaluation data set to obtain an increase area and a decrease area.

[0145] The first evaluation module is configured to input the increased area and the decreased area into a trend analysis model respectively to obtain a change trend of the increased area and the decreased area respectively, and to label the change trend of the increased area as an increased trend value and the change trend of the decreased area as a decreased trend value respectively;

[0146] If the increased trend value is less than the decreased trend value, a warning signal is generated;

[0147] If the increased trend value is greater than the decreased trend value, it is determined that the cultivated land area is normal.

[0148] The second evaluation module is configured to obtain a change period of the increased area and the decreased area respectively, and to combine the increased trend value and the decreased trend value to obtain a terminal increased area and a terminal decreased area, and to compare the terminal increased area with the terminal decreased area.

[0149] If the terminal increased area is less than the terminal decreased area, a warning signal is generated, and a correction plan for the decreased area is generated.

[0150] If the terminal increased area is greater than or equal to the terminal decreased area, it is determined that the cultivated land area is normal.

[0151] As described above, in real-time monitoring of cultivated land, first, the cultivated land area and the non-cultivated land area in the monitoring area are obtained by the data acquisition module, then the proportion of the cultivated land area is calculated by the calculation module, and it is determined by the determination module whether there is a decrease in the cultivated land area. In order to make full use of land, cultivated land change is a very common situation, for example, new buildings and the restoration of dilapidated buildings to cultivated land. Based on this, the changed area in the cultivated land area is labeled as an increased area and a decreased area, then the first evaluation module is used to determine the increased trend and the decreased trend, to determine whether the change trend of the cultivated land meets the standard, and finally the second evaluation module is used to determine the actual area after the change of the cultivated land, and to predict whether the terminal increased area is greater than the terminal decreased area, to prevent the occupation of additional cultivated land in the change of cultivated land.

[0152] And a cultivated land intelligent protection real-time dynamic monitoring terminal applied to a multi-cloud and multi-fog area comprises:

[0153] at least one processor;

[0154] and a memory in communication connection with the at least one processor;

[0155] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the above-mentioned multi-cloud and multi-fog area cultivated land intelligent protection real-time dynamic monitoring method.

[0156] It has to be noted that, as used herein, the terms "includes" and / or "contains", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to those elements, but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0157] The above description is only the preferred embodiment of the present application, it should be pointed out that, for those skilled in the art, without departing from the principles of the present application, can make a number of improvements and refinements, these improvements and refinements should also be considered as the protection scope of the present application. The structure, device and operation method not specifically described and explained in the present application, such as no special description and limitation, are implemented according to the conventional means in the art.

Claims

1. A method for real-time dynamic monitoring of farmland for intelligent protection in cloudy and foggy areas, characterized in that: include: The monitoring area is obtained, wherein the monitoring area includes cultivated land areas and non-cultivated land areas; The areas of cultivated land and non-cultivated land are obtained and input into the calculation model to obtain the proportion of cultivated land, which is then calibrated as the parameter to be evaluated. Obtain the rated parameters of the cultivated land area in the region to be detected, and compare them with the parameters to be evaluated; If the rated parameter is less than or equal to the parameter to be evaluated, the cultivated land area of ​​the monitored area is determined to be normal, and the changes in the cultivated land area are acquired in real time and summarized into a dataset to be evaluated. If the rated parameter is greater than the parameter to be evaluated, it is determined that the cultivated land area of ​​the monitored area has decreased, and an alarm signal is generated. The changed areas of cultivated land in the dataset to be evaluated are classified into areas of increase and areas of decrease. The increasing and decreasing regions are respectively input into the trend analysis model to obtain the changing trends of the increasing and decreasing regions, and are respectively labeled as increasing trend value and decreasing trend value; If the increasing trend value is less than the decreasing trend value, an early warning signal is generated; If the increasing trend value is greater than the decreasing trend value, then the cultivated land area is determined to be normal; The change cycles of the increased and decreased regions are obtained respectively, and combined with the increase trend value and decrease trend value to obtain the terminal increased region and the terminal decreased region, and then compared. If the area where the terminal increases is smaller than the area where the terminal decreases, an early warning signal is issued and a correction plan for the decreased area is generated. If the area where the terminal increases is greater than or equal to the area where the terminal decreases, then the cultivated land area is determined to be normal.

2. The method for real-time dynamic monitoring of farmland protection in cloudy and foggy areas according to claim 1, characterized in that: The step of obtaining the area of ​​the cultivated land area and the non-cultivated land area, and inputting it into the calculation model to obtain the proportion of cultivated land area, includes: Obtain the area of ​​the cultivated land area and the non-cultivated land area; Obtain the standard function from the evaluation model; The areas of cultivated land and non-cultivated land are input into a standard function, and the calculation results are calibrated as the proportion of cultivated land.

3. The method for real-time dynamic monitoring of farmland protection in cloudy and foggy areas according to claim 1, characterized in that: The step of obtaining the rated parameters of the cultivated land area in the area to be detected includes: A sampling period is constructed, which includes multiple statistical nodes; Obtain the historical crop yields under the statistical nodes and sort them according to the time of occurrence; Obtain the standard yield and compare it with the yields of all historical crops. Select all historical crops that have a yield greater than or equal to the standard yield and mark them as qualified yields. Obtain the cultivated land area corresponding to all the qualified yields, arrange them in descending order, and mark the minimum cultivated land area as a temporary parameter; Obtain the statistical nodes under the temporary parameters and all historical crop yields, and input them into the judgment model to determine whether the temporary parameters can be used as the rated parameters. If so, then directly set the temporary parameter to the rated parameter; If not, continue to obtain the next rank of cultivated land area that is greater than the qualified yield, and input it as a temporary parameter into the judgment model.

4. The method for real-time dynamic monitoring of farmland protection in cloudy and foggy areas according to claim 3, characterized in that: When obtaining the statistical nodes under the temporary parameters, the following steps are included: Get the number of nodes under temporary parameters; Obtain the standard evaluation quantity and compare it with the number of statistical nodes, wherein the standard evaluation quantity is n, and n≥5; If the number of standard evaluations is greater than the number of statistical nodes, it is determined that the historical crop yield under the temporary parameters cannot be input into the judgment model, and the cultivated land area with the next rank and greater than the qualified yield continues to be obtained. If the number of standard evaluations is less than or equal to the number of statistical nodes, then it is determined that the historical crop yield under the temporary parameters can be input into the determination model.

5. The method for real-time dynamic monitoring of farmland protection in cloudy and foggy areas according to claim 3, characterized in that: The step of inputting all historical crop yields under the temporary parameters into the judgment model and determining whether the temporary parameters can be used as the nominal parameters includes: Obtain all historical crop yields under the temporary parameters, and determine whether there are any historical crop yields that are less than the standard yield; If it exists, calculate the percentage of historical crop yields that are less than the standard yield; If the proportion of historical crop yields that are less than the standard yield is less than or equal to 80%, then the temporary parameter cannot be used as the rated parameter. If the proportion of historical crop yields that are less than the standard yield is higher than 80%, then the temporary parameter is determined to be a rated parameter. If it does not exist, then the temporary parameter is directly determined to be a valid parameter.

6. The method for real-time dynamic monitoring of farmland protection in cloudy and foggy areas according to claim 1, characterized in that: The step of inputting the increasing and decreasing regions into the trend analysis model respectively, obtaining the changing trends of the increasing and decreasing regions respectively, and labeling them as increasing trend values ​​and decreasing trend values ​​respectively, includes: The starting node and current monitoring node of farmland changes within the monitoring area are obtained to determine the measurement period; Multiple sampling nodes are constructed during the measurement period, and the increase and decrease regions under each sampling node are obtained respectively. The sampling nodes are set to m, and m≥10. The trend analysis function is obtained from the trend analysis model, and the increasing and decreasing regions under each sampling node are input into the trend analysis function to obtain the increasing trend value and the decreasing trend value.

7. A method for real-time dynamic monitoring of farmland protection in cloudy and foggy areas according to claim 6, characterized in that: When acquiring the increasing and decreasing regions under each sampling node, the increasing and decreasing regions under adjacent sampling nodes are compared, and the instantaneous changes in the increasing and decreasing regions are filtered out. The specific process is as follows: Obtain the difference between the increased and decreased areas under adjacent sampling and label it as the change to be evaluated; Obtain the allowable range of change and compare it with the change amount to be evaluated one by one; If the change to be evaluated is within the allowable range, then the change to be evaluated is determined to be a normal change and is added to the trend analysis function. If the change to be evaluated is not within the allowable range, then the change to be evaluated is determined to be an instantaneous change, and its corresponding increase or decrease area is screened out.

8. The method for real-time dynamic monitoring of farmland protection in cloudy and foggy areas according to claim 1, characterized in that: The step of obtaining the change cycles of the increasing and decreasing regions respectively, and combining them with the increasing and decreasing trend values ​​to obtain the terminal increasing region and the terminal decreasing region includes: The change cycles of the added and reduced regions are obtained and compared respectively; If the change cycle of the added area is greater than or equal to the change cycle of the reduced area, then it is directly determined that the terminal's added area is greater than the terminal's reduced area. If the change cycle of the increased area is less than the change cycle of the decreased area, then the calculation function is obtained; The change cycle, the increasing trend value, and the decreasing trend value are input into the calculation function to obtain the terminal increase area and the terminal decrease area.

9. A real-time dynamic monitoring system for intelligent protection of arable land in cloudy and foggy areas, applied to the real-time dynamic monitoring method for intelligent protection of arable land in cloudy and foggy areas as described in any one of claims 1 to 8, characterized in that: include: A data acquisition module is used to acquire a monitoring area, wherein the monitoring area includes cultivated land areas and non-cultivated land areas; The calculation module is used to obtain the area of ​​the cultivated land area and the non-cultivated land area, and input them into the calculation model to obtain the proportion of cultivated land area, and calibrate it as the parameter to be evaluated. The determination module is used to obtain the rated parameters of the cultivated land area in the area to be detected and compare them with the parameters to be evaluated. If the rated parameter is less than or equal to the parameter to be evaluated, the cultivated land area of ​​the monitored area is determined to be normal, and the changes in the cultivated land area are acquired in real time and summarized into a dataset to be evaluated. If the rated parameter is greater than the parameter to be evaluated, it is determined that the cultivated land area of ​​the monitored area has decreased, and an alarm signal is generated. A classification module is used to classify the changed areas of cultivated land in the dataset to be evaluated, and to obtain the areas of increase and decrease; The first evaluation module is used to input the increasing region and the decreasing region into the trend analysis model respectively, to obtain the changing trends of the increasing region and the decreasing region respectively, and to label them as increasing trend value and decreasing trend value respectively; If the increasing trend value is less than the decreasing trend value, an early warning signal is generated; If the increasing trend value is greater than the decreasing trend value, then the cultivated land area is determined to be normal; The second evaluation module is used to obtain the change cycle of the increasing region and the decreasing region respectively, and combine it with the increasing trend value and the decreasing trend value to obtain the terminal increasing region and the terminal decreasing region, and compare them. If the area where the terminal increases is smaller than the area where the terminal decreases, an early warning signal is issued and a correction plan for the decreased area is generated. If the area where the terminal increases is greater than or equal to the area where the terminal decreases, then the cultivated land area is determined to be normal.

10. A real-time dynamic monitoring terminal for intelligent protection of farmland in cloudy and foggy areas, characterized in that: include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the real-time dynamic monitoring method for intelligent protection of farmland in cloudy and foggy areas as described in any one of claims 1 to 8.

Images