Solenopsis invicta monitoring and data analysis method based on GIS and GPS technologies

Abstract

The invention provides a Solenopsis invicta monitoring and data analysis method based on GIS and GPS technologies, and relates to the technical field of biological control, the method comprises the following steps: arranging GPS equipment in a target area, and collecting the distribution position data of Solenopsis invicta in real time; performing spatial visualization display on the acquired data by utilizing a GIS technology to form a solenopsis invicta distribution thermodynamic diagram; deploying a sensor or an image recognition technology to dynamically monitor the solenopsis invicta, and obtaining the activity frequency and behavior mode of the solenopsis invicta; based on the distribution data and the dynamic monitoring data of the solenopsis invicta, an activity mode of the solenopsis invicta is analyzed, and an activity thermodynamic diagram is generated; predicting the diffusion trend of the solenopsis invicta through the diffusion prediction model in combination with environmental factors; and according to a prediction result, a targeted prevention and control strategy is formulated, and accurate prevention and control are implemented. By combining the GIS and GPS technologies, accurate monitoring and dynamic prevention and control of the solenopsis invicta are realized, the prevention and control efficiency and accuracy are improved, and the system has important ecological protection and agricultural production values.

Description

Technical Field

[0001] The present invention relates to the field of biological control technology, and in particular to a red imported fire ant monitoring and data analysis method based on GIS and GPS technology. Background Art

[0002] The red fire ant is an invasive alien species native to South America. Due to its strong adaptability, reproduction and spread ability, the red fire ant has spread rapidly in many regions around the world in recent years, posing a serious threat to agriculture, ecological environment, public safety and other aspects. The red fire ant is highly aggressive and can cause direct harm to plants, animals and even humans, especially crops. In addition, the spread of the red fire ant may also destroy the local ecosystem and lead to the loss of species diversity.

[0003] At present, the prevention and control methods of red fire ants mainly include physical control, chemical control and biological control. However, these traditional control methods often have problems such as unstable control effects, negative impacts on the environment, and inability to accurately strike during implementation. Especially when the red fire ant population is large and widely distributed, traditional control methods often cannot be accurately implemented, resulting in waste of resources and unsatisfactory control effects.

[0004] In order to solve this problem, many researchers have tried to improve the accuracy of red fire ant monitoring and prevention through modern technology. GIS (Geographic Information System) technology and GPS (Global Positioning System) technology have been widely used in ecological monitoring, environmental protection, and agricultural pest management. Through GIS technology, spatial data can be visualized to help researchers analyze the distribution characteristics and diffusion trends of red fire ants. GPS technology can provide high-precision location information and provide basic data for red fire ant monitoring. However, existing red fire ant monitoring methods are mostly focused on static distribution monitoring, lacking real-time tracking of the dynamic behavior of red fire ants, making it difficult to form effective diffusion prediction and prevention strategies.

[0005] In addition, current red fire ant control technology also faces problems such as difficulty in evaluating control effects and poor real-time monitoring capabilities. In the process of red fire ant control, the formulation and implementation of control strategies often depend on the distribution density and activity range of red fire ants, but due to the lack of efficient data fusion and analysis methods, it is difficult to formulate control measures accurately and individually.

[0006] Therefore, there is an urgent need for a new red fire ant monitoring and control method that comprehensively applies GIS, GPS, sensor networks and data analysis technologies, which can monitor the dynamic behavior of red fire ants in real time, accurately identify their activity hotspots, predict their spread trends, and formulate effective prevention and control strategies based on the prediction results, so as to achieve precise prevention and control of red fire ants and protection of the ecological environment. Summary of the invention

[0007] In order to solve the technical problems in the prior art of red fire ant monitoring and prevention, such as insufficient accuracy, weak dynamic monitoring and prediction capabilities, waste of resources and unstable prevention and control effects, the present invention provides a red fire ant monitoring and data analysis method based on GIS and GPS technology.

[0008] The technical solution provided by the present invention is as follows: The present invention provides a red imported fire ant monitoring and data analysis method based on GIS and GPS technology, comprising: S1. Collecting the distribution location data of red fire ants in the target area using a GPS device, wherein the GPS device can provide high-precision geographic coordinate information, and obtaining at least two spatial coordinate points, wherein each spatial coordinate point represents the location of a red fire ant colony; S2. Combining GIS technology to perform spatial visualization on the red fire ant distribution location data, the GIS system marks the collected GPS data on a map and generates a red fire ant distribution layer, the distribution layer presents the density and regional distribution trend of the red fire ant distribution through different color codes or annotation methods; S3. Obtaining dynamic monitoring data of red fire ants' activities through sensors or image recognition technology, wherein the dynamic monitoring data includes the activity frequency, activity range and behavioral changes of red fire ants in various time periods; S4, integrating the red fire ant distribution location data acquired by the GPS with the dynamic monitoring data, analyzing the activity pattern of the red fire ants, and generating a red fire ant activity heat map, wherein the heat map can clearly show the high-density areas and frequent activity periods of the red fire ants; S5. Extracting potential danger areas of red fire ants through data analysis, and predicting the spread trend of red fire ants based on the red fire ant activity heat map to generate a red fire ant spread prediction model; S6. According to the red fire ant spread prediction model, a red fire ant prevention and control strategy is formulated through simulation analysis. The prevention and control strategy uses physical, chemical or biological control methods to accurately strike red fire ants according to different prediction results.

[0009] The beneficial effects brought about by the technical solution provided by the present invention include at least: (1) In the present invention, by adopting GPS technology and GIS system, the present invention can realize high-precision spatial positioning of red fire ants and visual display of their distribution. GPS equipment collects the geographic coordinates of red fire ants in real time, and transmits these coordinate data to the GIS platform to form a distribution map of red fire ants. Using the spatial analysis function of GIS, the density distribution and diffusion trend of red fire ants can be clearly displayed, providing researchers with detailed information on the activity areas of red fire ants. This technical means significantly improves the accuracy and timeliness of red fire ant distribution data, avoids the errors of relying on manual records in traditional methods, greatly improves the efficiency and accuracy of monitoring, and provides a reliable basis for subsequent prevention and control decisions.

[0010] (2) In the present invention, dynamic monitoring and real-time behavior analysis of red fire ants are achieved through sensor networks and image recognition technology. The sensor equipment can sense the activities of red fire ants in real time and transmit the data to the central system for processing. At the same time, the deployed high-definition cameras and image recognition algorithms (such as convolutional neural networks (CNNs)) can automatically identify the behaviors of red fire ants, such as foraging and reproduction. By analyzing these dynamic data, the activity patterns and behavior patterns of red fire ants can be revealed, providing real-time basis for the optimization of prevention and control measures. This technical means not only improves the real-time nature of monitoring, but also provides support for precise prevention and control, overcoming the limitations of static monitoring in traditional methods.

[0011] (3) In the present invention, a diffusion prediction model was established by combining red fire ant activity data and climate factors using multivariate regression analysis. By predicting the future activities of red fire ants, a scientific basis is provided for the formulation of prevention and control strategies. The model can predict the diffusion trend of red fire ants in the future based on real-time monitoring data and identify high-risk areas in advance. Control personnel can take targeted prevention and control measures based on the prediction results, such as precise spraying of pesticides or deployment of ant traps. This technical means significantly improves the accuracy of red fire ant prevention and control, avoids the waste of prevention and control resources in traditional methods, and can effectively intervene before red fire ants spread on a large scale, thereby minimizing their harm to the ecological environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0013] Figure 1 A flowchart of a red imported fire ant monitoring and data analysis method based on GIS and GPS technology provided by an embodiment of the present invention; Figure 2 A schematic flow chart of steps for establishing a red fire ant diffusion prediction model in a red fire ant monitoring and data analysis method based on GIS and GPS technology provided in an embodiment of the present invention; Figure 3 A schematic diagram of the K-means algorithm flow chart of a red imported fire ant monitoring and data analysis method based on GIS and GPS technology provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0014] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0015] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0016] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0017] In the embodiments of the present invention, sometimes the subscripts are as follows It may be mistakenly written as a non-subscript form such as W1. When the difference is not emphasized, the meanings they express are the same.

[0018] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0019] Reference Manual Attached Figure 1 , shows a flow chart of a red fire ant monitoring and data analysis method based on GIS and GPS technology provided by an embodiment of the present invention.

[0020] The embodiment of the present invention provides a red imported fire ant monitoring and data analysis method based on GIS and GPS technology, and the processing flow may include the following steps: S1. Collect the distribution location data of red fire ants in the target area using a GPS device, wherein the GPS device can provide high-precision geographic coordinate information and obtain at least two spatial coordinate points, wherein each spatial coordinate point represents the location of a red fire ant colony.

[0021] It should be noted that by deploying GPS equipment in the target area and collecting the distribution location data of red fire ants in real time, high-precision geographic coordinate information can be obtained. Each coordinate point represents the location of the red fire ant colony, ensuring the accuracy of the data and the integrity of the spatial distribution. This step provides basic data for subsequent spatial analysis and behavioral analysis, and ensures the reliability of the positioning results through high-precision GPS equipment, avoiding the impact of errors on subsequent analysis.

[0022] S2. Combining GIS technology to perform spatial visualization on the distribution location data of the red fire ants, the GIS system marks the collected GPS data on the map and generates a red fire ant distribution layer, and the distribution layer presents the density and regional distribution trend of the red fire ants through different color codes or annotation methods.

[0023] It should be noted that the distribution data of red fire ants collected by GPS equipment is combined with GIS technology for spatial visualization. This process can intuitively display the distribution and density changes of red fire ants by marking the distribution locations of red fire ants on the map and presenting them using color scales according to different density levels. The purpose of this step is to visualize the distribution data, help researchers or prevention and control personnel quickly identify high-density areas of red fire ants, determine their diffusion trends, and provide data support for further decision-making.

[0024] S3. Obtain dynamic monitoring data of red fire ants' activities through sensors or image recognition technology, wherein the dynamic monitoring data includes the activity frequency, activity range and behavioral changes of the red fire ants in various time periods.

[0025] It should be noted that by deploying sensors or using image recognition technology to obtain dynamic monitoring data of red fire ants, their activity frequency, activity range and changes in behavior patterns are recorded. Dynamic monitoring data not only provides changes in the time dimension, but also reveals the activity level and activity pattern of red fire ants. By analyzing dynamic data, behavioral changes of red fire ants can be identified in a timely manner, providing more fine-grained information for subsequent analysis and providing a basis for real-time adjustment of prevention and control measures.

[0026] S4. The red fire ant distribution location data acquired by the GPS is integrated with the dynamic monitoring data, the activity pattern of the red fire ants is analyzed, and a red fire ant activity heat map is generated. The heat map can clearly show the high-density areas and frequent activity periods of the red fire ants.

[0027] It should be noted that by integrating the red fire ant distribution location data collected by GPS with the dynamic monitoring data, the activity pattern of the red fire ants was analyzed and an activity heat map was generated. The heat map can clearly show the activity intensity of the red fire ants in different areas and time periods, allowing researchers to clearly see which areas are the peak active periods of the red fire ants and which places are potential areas for their spread. The core role of this step is to present the activity data in a visual way, providing an intuitive basis for subsequent spread prediction and prevention.

[0028] S5. Through data analysis, the potential danger areas of red fire ants are extracted, and the diffusion trend of red fire ants is predicted based on the red fire ant activity heat map to generate a red fire ant diffusion prediction model.

[0029] It should be noted that, combined with data analysis, the activity heat map and distribution data of red fire ants are used to identify potential danger areas and predict the spread trend of red fire ants. By establishing a diffusion prediction model, the future spread range and trend of red fire ants can be accurately determined, and prevention and control measures can be taken in advance. This step provides scientific prediction support for prevention and control strategies, helping prevention and control personnel to effectively foresee the possible expansion path of red fire ants and reduce their harm to the environment.

[0030] S6. According to the red fire ant spread prediction model, a red fire ant prevention and control strategy is formulated through simulation analysis. The prevention and control strategy uses physical, chemical or biological control methods to accurately strike red fire ants according to different prediction results.

[0031] It should be noted that, based on the diffusion prediction model, a targeted red fire ant control strategy is formulated through simulation analysis. This strategy can select appropriate control methods according to different prediction results, such as physical, chemical or biological control measures. Through reasonable control measures, the spread source of red fire ants can be accurately attacked to minimize their impact on the ecosystem. The role of this step is to form a closed-loop red fire ant control strategy by integrating prediction data with actual control measures to ensure its effectiveness and operability.

[0032] like Figure 2 As shown, in a possible implementation manner, the red fire ant spread prediction model further includes: The steps for establishing the red fire ant diffusion prediction model are as follows: S201. Calculating the diffusion rate of red fire ants in different regions based on historical red fire ant distribution data, where the diffusion rate is the change in the distribution area of ​​red fire ants per unit time; S202, establishing a dynamic model of red fire ant diffusion based on the diffusion rate and in combination with climate data, wherein the climate data includes temperature, humidity and wind speed, which are collected in real time by meteorological monitoring equipment; S203, using a time series data analysis algorithm, including a sliding average method or an exponential smoothing method, to smooth the spread rate of red fire ants to reduce the impact of external interference factors on the prediction model; S204. Correct the diffusion path of red fire ants in combination with geographical factors, and output the diffusion path of red fire ants in the predicted area and its future development trend. The geographical factors include land type and vegetation coverage.

[0033] In a possible implementation, the red fire ant spread rate further includes: The calculation method of the red fire ant diffusion speed is as follows: S301. Determine the distribution area of ​​red fire ants at different time points, recorded as ,in is the time variable; S302: Calculate the change in the distribution area of ​​red fire ants in unit time , the calculation formula is: ; S303: Calculate the diffusion rate of red fire ants based on the change amount , the calculation formula is: ; in, Indicates a time interval.

[0034] In a possible implementation, the red fire ant diffusion rate further includes: The spread rate of red fire ants The optimization calculation method is as follows: S401. Use the weighted average method to calculate the impact of historical diffusion rate on future diffusion rate and set the weight function , so that the historical diffusion rate has a higher weight for the prediction at the current moment; S402: The weight function The calculation formula is: ; in, is the attenuation factor, The starting time of historical data; S403, through the weight function , weighted average the historical diffusion rate to obtain the optimized diffusion rate : ; in, is the number of historical data points, For historical moments.

[0035] In a possible implementation, the red fire ant activity heat map includes: The method for generating the red fire ant activity heat map is as follows: S501, spatially clustering the activity positions of red fire ants by a cluster analysis algorithm to obtain activity areas of several red fire ant colonies, wherein the cluster analysis algorithm includes a K-means algorithm; S502: Based on the spatial clustering results, calculate the activity intensity of red fire ants in each area. Calculated by the following formula: ; in, For the i The activity frequency of red fire ants in the area, For Region i The number of samples in S503. According to the intensity of the activity , the corresponding heat map is regenerated in the GIS system, where red represents high-intensity activity areas and blue represents low-intensity activity areas.

[0036] like Figure 3 As shown, in a possible implementation, the K-means algorithm further includes: The calculation steps of the K-means algorithm are as follows: S601, randomly select K initial cluster centers , ; S602. For each red fire ant activity point , calculate its distance to each cluster center distance, and Assigned to the nearest cluster center; S603, update each cluster center The location of all active points in the cluster The mean of S604. Repeat steps S602 to S603 until the clustering results converge.

[0037] In a possible implementation, the activity frequency of red fire ants further includes: The method for calculating the activity frequency of red fire ants includes: S701, within a specified time period, using a wireless sensor network (WSN) to monitor the activities of red fire ants and obtain the movement trajectory of each individual red fire ant; S702: dividing the movement trajectory of the red fire ants into time windows and calculating the activity frequency of the red fire ants in each time window. , and its calculation formula is: ; in, For time window The number of red fire ant activity events monitored within is the length of the time window.

[0038] In a possible implementation manner, the detection data of the red fire ant activity behavior includes: Analysis of the behavioral patterns of red fire ants: Image recognition technology is used to classify the activities of red fire ants and generate behavioral recognition reports including foraging, reproduction, nest migration and other behavioral patterns: S801, automatically classifying the behaviors of red imported fire ants by using an image recognition algorithm, wherein the image recognition algorithm includes a convolutional neural network (CNN); S802: Combining the behavior identification report with the red fire ant distribution layer to generate a behavior heat map of the red fire ants, visually displaying the distribution of various behaviors in different areas.

[0039] In a possible implementation, the method for formulating the red fire ant control strategy includes: S901. Determine the risk of red fire ants spreading in the future based on the red fire ant spread prediction model and red fire ant activity heat map; S902. For high-risk areas, formulate corresponding physical or chemical control measures, the physical control measures include setting up fire ant fences, and the chemical control measures include spraying ant killers; S903. For low-risk areas, adopt biological control methods by introducing natural enemies or biological agents for intervention.

[0040] In a possible implementation, the physical control measures further include: S1001. Set up obstacles and traps in high-risk areas of red fire ants to prevent and control them by limiting their spatial activities; S1002. Use remote sensing technology combined with GIS data to monitor the activity changes of red fire ants in real time and adjust prevention and control strategies in a timely manner.

[0041] In the initial stage of implementation, GPS positioning equipment is first deployed in areas where red fire ants are prone to grow. The equipment can accurately obtain the geographical coordinate information of each monitoring point by connecting with satellite signals. In this embodiment, a specific area can be selected for experimentation, such as a farmland area in a suburb, and 10 GPS sampling points are set to conduct real-time monitoring of the distribution location of red fire ants.

[0042] The specific steps include: selecting a suitable area and deploying at least 10 GPS sensors, with the distance between each sensor being about 50 meters.

[0043] The GPS device sends coordinate information to the central data processing system through a real-time data transmission system.

[0044] The data system aggregates coordinate information and records the location where the red fire ants appear. Each coordinate point not only records the longitude and latitude, but is also bound to a timestamp through a GPS signal to provide spatiotemporal data support for subsequent analysis.

[0045] It should be noted that the purpose of this step is to collect the distribution coordinates of red fire ants through high-precision GPS equipment to ensure the accuracy of the data and lay the foundation for subsequent spatial analysis and behavioral pattern recognition. The record of each coordinate point is the basis for further analysis, and the timestamp represented by each point helps to analyze the activity pattern of red fire ants.

[0046] After the red fire ant distribution coordinate data is obtained, it is spatially visualized through GIS technology. Use GIS platform (such as ArcGIS or QGIS) to map the collected GPS coordinate points onto the geographic map to form a red fire ant distribution layer.

[0047] The specific implementation steps include: importing the red fire ant coordinate data collected by GPS into GIS software.

[0048] In the GIS platform, different symbols or color scales (such as green, yellow, red, etc.) are used to represent the density of red fire ants in different areas.

[0049] Based on the timestamp of each coordinate point, a time change layer is generated to show the activity distribution of red fire ants in different periods of time.

[0050] In the red fire ant distribution layer generated on the map, the depth of color represents the density, red represents high-density areas, and green represents low-density areas.

[0051] It should be noted that this step combines the scattered GPS coordinate data with geographic information through the GIS system to generate a visual map to help monitoring personnel quickly identify the distribution area and density of red fire ants. Through the display of the heat map, it is possible to intuitively observe which areas have a more concentrated distribution of red fire ants, providing an effective basis for subsequent prevention and control strategies.

[0052] After the red fire ant distribution layer is generated, the dynamic behavior of the red fire ants is further monitored in real time through sensor networks or cameras. These dynamic monitoring data include the activity frequency, activity range and behavioral changes of the red fire ants in different time periods.

[0053] The specific implementation process includes: deploying wireless sensor networks (WSNs) in the area, which can sense the presence of red fire ants and record their activities.

[0054] The sensor uploads data every 10 minutes, recording the activity frequency, activity range and location changes of red fire ants.

[0055] In addition to sensors, some monitoring points also deploy image recognition cameras to analyze the behavior of red fire ants through the camera's image data and identify whether the ants are foraging, reproducing, migrating, and other activities.

[0056] Deep learning algorithms, such as convolutional neural networks (CNNs), are used to analyze images, extract the activity behaviors of red fire ants from the images, and generate hourly activity behavior reports.

[0057] It should be noted that the purpose of this step is to obtain real-time activity data of red fire ants through dynamic monitoring, and then analyze the activity patterns of red fire ants. The monitoring frequency and activity pattern can help determine the spread trend of red fire ants and provide dynamic data support for the subsequent generation of red fire ant activity heat maps.

[0058] Based on the previously acquired dynamic monitoring data and red fire ant distribution layer, data fusion technology was used to generate a heat map of red fire ants' activities.

[0059] The specific implementation process includes: Cluster analysis algorithms (such as K-means clustering) are used to spatially cluster the activities of red fire ants and identify high-density activity areas.

[0060] Based on the activity density calculation formula, the activity frequency of each area is mapped to the color intensity of the heat map. Areas with high frequency are displayed in red, and areas with low frequency are displayed in blue.

[0061] The generated activity heat map is merged with the red fire ant distribution layer to obtain a heat map that comprehensively shows the distribution and activity intensity of red fire ants.

[0062] This heat map is updated every 24 hours to reflect the changing trends in the activity of red fire ants.

[0063] It should be noted that the heat map provides a visual means to clearly show the high-density areas and changing trends of red fire ant activities. This heat map provides an intuitive basis for the subsequent prediction of the spread of red fire ants and the formulation of prevention and control strategies.

[0064] Based on the red fire ant activity heat map and combined with climate data (such as temperature, humidity, wind speed, etc.), a red fire ant diffusion prediction model was established. The diffusion prediction model is used to predict the diffusion trend of red fire ants in the future.

[0065] The specific implementation process includes: First, collect climate data in the area, including temperature, humidity, wind speed, etc. The data source is meteorological monitoring equipment.

[0066] Combined with historical data, the multiple linear regression analysis method was used to model the relationship between the spread rate of red fire ants and climate factors.

[0067] The model is used to calculate the spread rate of red fire ants in the next week, and a red fire ant spread path map is generated based on the prediction results.

[0068] The diffusion path map provides the possible direction and range of the spread of red fire ants, and monitoring personnel can take corresponding prevention and control measures in advance based on this information.

[0069] It should be noted that the establishment of the diffusion prediction model is to better predict the diffusion trend of red fire ants. By combining it with climate data and considering the impact of environmental factors on the diffusion of red fire ants, it can provide a scientific basis for subsequent prevention and control strategies.

[0070] Based on the generated diffusion prediction model and the data analysis results of the activity heat map, a targeted red fire ant control strategy can be formulated. The control strategy should be adjusted according to the red fire ant's diffusion area, activity intensity and environmental factors.

[0071] The specific implementation process includes: For areas with a higher tendency to spread, physical prevention and control measures are adopted, such as setting up fire ant fences and using ant traps.

[0072] In areas where the spread is slower, biological control methods are used, natural enemies of red fire ants (such as certain crickets or ants) are introduced, or biological agents are used for intervention.

[0073] In high-risk areas, red fire ant colonies are directly eliminated by spraying suitable anticides.

[0074] After each prevention and control, continue to track and monitor the distribution of red fire ants in the area and adjust the prevention and control strategies in a timely manner.

[0075] It should be noted that based on the diffusion prediction model and activity heat map, the spread of red fire ants and the need for prevention and control can be accurately judged, and targeted prevention and control measures can be formulated to minimize the spread of red fire ants and their impact on the environment.

[0076] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least: (1) In the present invention, by adopting GPS technology and GIS system, the present invention can realize high-precision spatial positioning of red fire ants and visual display of their distribution. GPS equipment collects the geographic coordinates of red fire ants in real time, and transmits these coordinate data to the GIS platform to form a distribution map of red fire ants. Using the spatial analysis function of GIS, the density distribution and diffusion trend of red fire ants can be clearly displayed, providing researchers with detailed information on the activity areas of red fire ants. This technical means significantly improves the accuracy and timeliness of red fire ant distribution data, avoids the errors of relying on manual records in traditional methods, greatly improves the efficiency and accuracy of monitoring, and provides a reliable basis for subsequent prevention and control decisions.

[0077] (2) In the present invention, dynamic monitoring and real-time behavior analysis of red fire ants are achieved through sensor networks and image recognition technology. The sensor equipment can sense the activities of red fire ants in real time and transmit the data to the central system for processing. At the same time, the deployed high-definition cameras and image recognition algorithms (such as convolutional neural networks (CNNs)) can automatically identify the behaviors of red fire ants, such as foraging and reproduction. By analyzing these dynamic data, the activity patterns and behavior patterns of red fire ants can be revealed, providing real-time basis for the optimization of prevention and control measures. This technical means not only improves the real-time nature of monitoring, but also provides support for precise prevention and control, overcoming the limitations of static monitoring in traditional methods.

[0078] (3) In the present invention, a diffusion prediction model was established by combining red fire ant activity data and climate factors using multivariate regression analysis. By predicting the future activities of red fire ants, a scientific basis is provided for the formulation of prevention and control strategies. The model can predict the diffusion trend of red fire ants in the future based on real-time monitoring data and identify high-risk areas in advance. Control personnel can take targeted prevention and control measures based on the prediction results, such as precise spraying of pesticides or deployment of ant traps. This technical means significantly improves the accuracy of red fire ant prevention and control, avoids the waste of prevention and control resources in traditional methods, and can effectively intervene before red fire ants spread on a large scale, thereby minimizing their harm to the ecological environment.

[0079] The above contents are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0080] There are a few points to note: (1) The drawings of the embodiments of the present invention only involve structures related to the embodiments of the present invention. Other structures may refer to conventional designs.

[0081] (2) For the sake of clarity, in the drawings used to describe the embodiments of the present invention, the thickness of layers or regions is exaggerated or reduced, that is, these drawings are not drawn according to the actual scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being "on" or "under" another element, the element may be "directly" "on" or "under" the other element or there may be intermediate elements.

[0082] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to obtain new embodiments.

[0083] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A red imported fire ant monitoring and data analysis method based on GIS and GPS technology, characterized in that: include: S1. Collecting the distribution location data of red fire ants in the target area using a GPS device, wherein the GPS device can provide high-precision geographic coordinate information, and obtaining at least two spatial coordinate points, wherein each spatial coordinate point represents the location of a red fire ant colony; S2. Combining GIS technology to perform spatial visualization on the red fire ant distribution location data, the GIS system marks the collected GPS data on a map and generates a red fire ant distribution layer, the distribution layer presents the density and regional distribution trend of the red fire ant distribution through different color codes or annotation methods; S3. Obtaining dynamic monitoring data of red fire ants' activities through sensors or image recognition technology, wherein the dynamic monitoring data includes the activity frequency, activity range and behavioral changes of red fire ants in various time periods; S4, integrating the red fire ant distribution location data acquired by the GPS with the dynamic monitoring data, analyzing the activity pattern of the red fire ants, and generating a red fire ant activity heat map, wherein the heat map can clearly show the high-density areas and frequent activity periods of the red fire ants; S5. Extracting potential danger areas of red fire ants through data analysis, and predicting the spread trend of red fire ants based on the red fire ant activity heat map to generate a red fire ant spread prediction model; S6. According to the red fire ant spread prediction model, a red fire ant prevention and control strategy is formulated through simulation analysis. The prevention and control strategy uses physical, chemical or biological control methods to accurately strike red fire ants according to different prediction results.

2. The method for monitoring and analyzing red imported fire ants based on GIS and GPS technology according to claim 1, characterized in that: The red fire ant spread prediction model further includes: The steps for establishing the red fire ant diffusion prediction model are as follows: S201. Calculating the diffusion rate of red fire ants in different regions based on historical red fire ant distribution data, where the diffusion rate is the change in the distribution area of ​​red fire ants per unit time; S202, establishing a dynamic model of red fire ant diffusion based on the diffusion rate and in combination with climate data, wherein the climate data includes temperature, humidity and wind speed, which are collected in real time by meteorological monitoring equipment; S203, using a time series data analysis algorithm, including a sliding average method or an exponential smoothing method, to smooth the spread rate of red fire ants to reduce the impact of external interference factors on the prediction model; S204. Correct the diffusion path of red fire ants in combination with geographical factors, and output the diffusion path of red fire ants in the predicted area and its future development trend. The geographical factors include land type and vegetation coverage.

3. The method for monitoring and analyzing red imported fire ants based on GIS and GPS technology according to claim 2, characterized in that: The red fire ant spread rate further includes: The calculation method of the red fire ant diffusion speed is as follows: S301. Determine the distribution area of ​​red fire ants at different time points, recorded as ,in is the time variable; S302: Calculate the change in the distribution area of ​​red fire ants in unit time , the calculation formula is: ； S303: Calculate the diffusion rate of red fire ants based on the change amount , the calculation formula is: ； in, Indicates a time interval.

4. The method for monitoring and analyzing red imported fire ants based on GIS and GPS technology according to claim 3, characterized in that: The red fire ant diffusion rate further includes: The spread rate of red fire ants The optimization calculation method is as follows: S401. Use the weighted average method to calculate the impact of historical diffusion rate on future diffusion rate and set the weight function , so that the historical diffusion rate has a higher weight for the prediction at the current moment; S402: The weight function The calculation formula is: ； in, is the attenuation factor, is the starting time of historical data; S403, through the weight function , weighted average the historical diffusion rate to obtain the optimized diffusion rate : ； in, is the number of historical data points, For historical moments.

5. The method for monitoring and analyzing red imported fire ants based on GIS and GPS technology according to claim 1, characterized in that: The red fire ant activity heat map includes: The method for generating the red fire ant activity heat map is as follows: S501, spatially clustering the activity positions of red fire ants by a cluster analysis algorithm to obtain activity areas of several red fire ant colonies, wherein the cluster analysis algorithm includes a K-means algorithm; S502: Based on the spatial clustering results, calculate the activity intensity of red fire ants in each area. Calculated by the following formula: ； in, For the i The activity frequency of red fire ants in the area, For Region i The number of samples in S503. According to the intensity of the activity , the corresponding heat map is regenerated in the GIS system, where red represents high-intensity activity areas and blue represents low-intensity activity areas.

6. The method for monitoring and analyzing red imported fire ants based on GIS and GPS technology according to claim 5, characterized in that: The K-means algorithm further includes: The calculation steps of the K-means algorithm are as follows: S601, randomly select K initial cluster centers , ; S602. For each red fire ant activity point , calculate its distance to each cluster center distance, and Assigned to the nearest cluster center; S603, update each cluster center The location of all active points in the cluster The mean of S604. Repeat steps S602 to S603 until the clustering results converge.

7. The method for monitoring and analyzing red imported fire ants based on GIS and GPS technology according to claim 1, characterized in that: The activity frequency of red fire ants further includes: The method for calculating the activity frequency of red fire ants includes: S701, within a specified time period, using a wireless sensor network (WSN) to monitor the activities of red fire ants and obtain the movement trajectory of each individual red fire ant; S702: dividing the movement trajectory of the red fire ants into time windows and calculating the activity frequency of the red fire ants in each time window. , and its calculation formula is: ； in, For time window The number of red fire ant activity events monitored within is the length of the time window.

8. The method for monitoring and analyzing red imported fire ants based on GIS and GPS technology according to claim 1, characterized in that: The detection data of the red fire ant activity behavior includes: Analysis of the behavioral patterns of red fire ants: Image recognition technology is used to classify the activities of red fire ants and generate behavioral recognition reports including foraging, reproduction, nest migration and other behavioral patterns: S801, automatically classifying the behaviors of red imported fire ants by using an image recognition algorithm, wherein the image recognition algorithm includes a convolutional neural network (CNN); S802: Combining the behavior identification report with the red fire ant distribution layer to generate a behavior heat map of the red fire ants, visually displaying the distribution of various behaviors in different areas.

9. The method for monitoring and analyzing red imported fire ants based on GIS and GPS technology according to claim 1, characterized in that: The method for formulating the red fire ant control strategy includes: S901. Determine the risk of red fire ants spreading in the future based on the red fire ant spread prediction model and red fire ant activity heat map; S902. For high-risk areas, formulate corresponding physical or chemical control measures, the physical control measures include setting up fire ant fences, and the chemical control measures include spraying ant killers; S903. For low-risk areas, adopt biological control methods by introducing natural enemies or biological agents for intervention.

10. The method for monitoring and analyzing red imported fire ants based on GIS and GPS technology according to claim 9, characterized in that: The physical control measures further include: S1001. Set up obstacles and traps in high-risk areas of red fire ants to prevent and control them by limiting their spatial activities; S1002. Use remote sensing technology combined with GIS data to monitor the activity changes of red fire ants in real time and adjust prevention and control strategies in a timely manner.

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