River and lake behavior recognition method and device, computer equipment and storage medium

Abstract

The application provides a method and device for identifying river and lake behaviors, computer equipment and a storage medium, and relates to the field of data processing. The method comprises: acquiring first satellite remote sensing data and ground road network structure data, and determining a shoreline area of a river and lake based on the first satellite remote sensing data and the ground road network structure data; acquiring signaling data of an electronic device in a first analysis period, and determining a first trajectory feature of a target person carrying the electronic device in the shoreline area based on the signaling data; determining a behavior occurrence position of a river and lake violation behavior of the target person according to the first trajectory feature, and matching the first trajectory feature with pre-stored trajectory features in a trajectory feature library, determining a target trajectory feature matched with the first trajectory feature, and determining a behavior type of the river and lake violation behavior of the target person according to a behavior type corresponding to the target trajectory feature.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular to a method, apparatus, computer device, and readable storage medium for identifying river and lake behavior. Background Technology

[0002] The effective protection and rational utilization of river and lake shorelines play an important role in the ecological civilization and economic and social development of the surrounding areas. Unauthorized occupation, mining, dumping, and construction within the river and lake management area will pose a great threat to the ecological environment and flood control safety of the river and lake.

[0003] To address the aforementioned violations of the "four irregularities," identification can be achieved through manual investigations and review of extensive planning and project approval documents. This process relies heavily on manual judgment, consuming significant manpower and resources. Furthermore, the low level of digitization and standardization in planning and approval documents leads to relatively low efficiency and accuracy. Alternatively, "four irregularities" can be identified using satellite imagery. By establishing rules and models for identifying suspected violations, a comprehensive analysis of discovered clues can be conducted to extract a list of violations, providing precise information for identification and resolution. However, satellite imagery-based identification is limited by factors such as satellite transit time, cloud cover, satellite image resolution, and whether the violations occurred during satellite transit. This results in issues such as failure to identify violations, delayed identification, and interference from natural conditions.

[0004] Therefore, improving the efficiency and accuracy of identifying violations in rivers and lakes has become an urgent problem to be solved. Summary of the Invention

[0005] In view of this, this application provides a method, apparatus, computer device, and readable storage medium for identifying river and lake behavior.

[0006] In a first aspect, embodiments of this application provide a method for identifying river and lake behavior, including: Acquire first satellite remote sensing data and ground road network structure data, and determine the shoreline area of ​​rivers and lakes based on the first satellite remote sensing data and the ground road network structure data; Acquire signaling data of electronic devices during the first analysis period, and based on the signaling data, determine the first trajectory characteristics of the target person carrying the electronic device in the shoreline area; The location of the target person's violation of the river and lake regulations is determined based on the first trajectory feature, and the first trajectory feature is matched with the trajectory features pre-stored in the trajectory feature database to determine the target trajectory feature that matches the first trajectory feature. Based on the behavior type corresponding to the target trajectory feature, the behavior type of the target person's violation of the river and lake regulations is determined.

[0007] The method described in the embodiments of this application may also have the following additional technical features: In the above technical solution, optionally, the shoreline area of ​​rivers and lakes is determined based on the first satellite remote sensing data and the ground road network structure data, including: The scope of the river and lake water areas is determined based on the first satellite remote sensing data and the ground road network structure data; The river and lake shoreline boundaries are determined based on the river and lake water area, and the shoreline areas are divided based on the river and lake shoreline boundaries.

[0008] In any of the above technical solutions, optionally, the shoreline area is delineated based on the river / lake shoreline boundary, including: Based on the river and lake shoreline boundaries, a shoreline core area and a shoreline influence area are divided. The shoreline area includes the shoreline core area and the shoreline influence area. The shoreline core area is the area extending from the river and lake shoreline boundary into the river or lake at a first preset distance, and the shoreline influence area is the area extending from the river and lake shoreline boundary into the river or lake at a second preset distance.

[0009] In any of the above technical solutions, optionally, the behavior type of the target person regarding the violation of river and lake regulations is determined based on the behavior type corresponding to the target trajectory features, including: Acquire the second satellite remote sensing data for the first analysis period; If the second satellite remote sensing data is not obtained, the behavior type corresponding to the target trajectory characteristics will be taken as the behavior type of the target person's violation of regulations in rivers and lakes; If the second satellite remote sensing data is obtained, the behavior type of the target person in violation of river and lake regulations is determined based on the behavior type corresponding to the second satellite remote sensing data and the target trajectory characteristics.

[0010] In any of the above technical solutions, optionally, the behavior type of the target person regarding the violation of river and lake regulations is determined based on the behavior type corresponding to the second satellite remote sensing data and the target trajectory characteristics, including: Extract the first static physical features of the shoreline area from the second satellite remote sensing data; Compare the behavior types corresponding to the first static physical feature with the target trajectory feature; If the two match, the behavior type corresponding to the target trajectory feature will be taken as the behavior type of the target person for the violation of the river and lake regulations. If the two do not match, then historical data will be used to determine the type of behavior of the target personnel in violation of river and lake regulations.

[0011] In any of the above technical solutions, optionally, historical data is used to determine the type of behavior of the target personnel regarding violations of river and lake regulations, including: Determine whether there are any historical river or lake violations within the location and a preset surrounding area of ​​the occurrence of the behavior in the historical data. If so, obtain the similarity between the signaling data and the historical signaling data corresponding to the historical river or lake violations. If the similarity is greater than a preset threshold, then the behavior type corresponding to the target trajectory features is taken as the behavior type of the target person regarding the river or lake violations; and / or, The third satellite remote sensing data within a preset time period prior to the first analysis period is determined from the historical data. A second static physical feature of the shoreline area is extracted from the third satellite remote sensing data. If, based on the second static physical feature, it is determined that there is a violation of regulations concerning the river or lake, the behavior type corresponding to the target trajectory feature is taken as the behavior type of the target person's violation of regulations concerning the river or lake; and / or, The road network distribution information of the shoreline area is determined from the historical data. Based on the road network distribution information, it is determined whether the first trajectory feature is a normal trajectory. If it is not a normal trajectory, the behavior type corresponding to the target trajectory feature is taken as the behavior type of the target person's violation of the river and lake regulations.

[0012] Optionally, in any of the above technical solutions, the method further includes: The trajectory feature library is constructed, which stores multiple mapping relationships between trajectory features and behavior types; wherein, the method of constructing the trajectory feature library includes: The electronic device signaling sampling data during the second analysis period is obtained, as well as the confirmed river and lake violation data during the second analysis period. The electronic device signaling sampling data includes at least one of the following: user ID, timestamp, latitude and longitude, and stay information. Trajectory features are extracted from the signaling sampling data of the electronic device to obtain trajectory features, which include at least one of the following: trajectory movement speed, stop point density, stop duration, and round-trip frequency; The extracted trajectory features are correlated with the behavior types of the river and lake violation data to construct the mapping relationship.

[0013] Secondly, embodiments of this application provide a recognition device for river and lake behavior, comprising: The shoreline area determination module is used to acquire first satellite remote sensing data and ground road network structure data, and determine the shoreline area of ​​rivers and lakes based on the first satellite remote sensing data and the ground road network structure data. The trajectory feature determination module is used to acquire signaling data of electronic devices during the first analysis period, and based on the signaling data, determine the first trajectory features of the target person carrying the electronic device in the shoreline area. The identification module is used to determine the location where the target person's violation of the river and lake regulations occurs based on the first trajectory feature, and to match the first trajectory feature with the trajectory features pre-stored in the trajectory feature database to determine the target trajectory feature that matches the first trajectory feature, and to determine the type of the target person's violation of the river and lake regulations based on the behavior type corresponding to the target trajectory feature.

[0014] Thirdly, embodiments of this application provide a computer device including a processor and a memory, the memory storing programs or instructions that can run on the processor, the programs or instructions implementing the steps of the method as described in the first aspect when executed by the processor.

[0015] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method as described in the first aspect.

[0016] The present application's embodiments of the method, apparatus, computer equipment, and readable storage medium for identifying river and lake behaviors acquire first satellite remote sensing data and ground road network structure data, and determine the shoreline area of ​​the river and lake based on the first satellite remote sensing data and ground road network structure data; acquire signaling data of electronic devices during a first analysis period, and determine the first trajectory characteristics of the target person carrying the electronic device in the shoreline area based on the signaling data; determine the location of the target person's violation of river and lake regulations based on the first trajectory characteristics; match the first trajectory characteristics with pre-stored trajectory characteristics in the trajectory characteristic database to determine the target trajectory characteristics that match the first trajectory characteristics; and determine the type of behavior of the target person in the violation of river and lake regulations based on the behavior type corresponding to the target trajectory characteristics.

[0017] This application, through signaling data from electronic devices, identifies trajectory characteristics within river and lake shoreline areas, thereby identifying illegal activities that damage rivers and lakes, such as unauthorized occupation, mining, dumping, and construction. This application fills the gap in satellite remote sensing for monitoring dynamic behavior, enabling precise differentiation of types of illegal activities in rivers and lakes, improving the accuracy and differentiation of identification types, and enhancing identification efficiency.

[0018] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 A flowchart illustrating the method for identifying river and lake behavior according to an embodiment of this application is shown. Figure 2 A structural block diagram of a river and lake behavior identification device according to an embodiment of this application is shown; Figure 3 A structural block diagram of a computer device according to an embodiment of this application is shown. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0021] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0022] The following description, in conjunction with the accompanying drawings, details the method, apparatus, computer equipment, and readable storage medium for identifying river and lake behavior provided in this application through specific embodiments and application scenarios. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0023] This application provides a method for identifying river and lake behavior, such as... Figure 1 As shown, the method includes: Step 101: Obtain first satellite remote sensing data and ground road network structure data, and determine the shoreline area of ​​rivers and lakes based on the first satellite remote sensing data and ground road network structure data.

[0024] In this step, data preprocessing and shoreline delineation are performed. Specifically, the shoreline areas of rivers and lakes are accurately determined using satellite remote sensing data and ground road network structure data.

[0025] In one embodiment of this application, the shoreline area of ​​a river or lake is determined based on first satellite remote sensing data and ground road network structure data, including: The scope of rivers and lakes was determined based on the first satellite remote sensing data and ground road network structure data; The river and lake shoreline boundaries are determined based on the river and lake water area, and shoreline areas are divided based on these boundaries. The division of shoreline areas based on the river and lake shoreline boundaries includes: dividing the shoreline into a core area and an influence area. The core area is the region extending from the river and lake shoreline boundary into the river or lake at a first predetermined distance, while the influence area is the region extending from the river and lake shoreline boundary into the river or lake at a second predetermined distance.

[0026] In this embodiment, the extent of river and lake water areas is accurately extracted using satellite remote sensing data and ground road network structure data, thereby determining the river and lake shoreline boundaries. Then, based on these boundaries, shoreline areas are delineated. Specifically, the area extending 50 meters inward from the shoreline boundary into the river or lake is designated as the core shoreline area; the area extending 50-200 meters outward from the shoreline boundary is designated as the shoreline influence area. This method allows for the delineation of a suitable shoreline range, enabling the identification of violations in rivers and lakes, preventing omissions, and accurately constraining signaling data within the designated shoreline area, eliminating interference from irrelevant areas and improving identification accuracy.

[0027] In one embodiment, road network distribution information for the shoreline area is obtained simultaneously based on ground road network structure data. This road network distribution information is used to assist in analyzing the transportation routes of illegal activities related to rivers and lakes. For example, the transportation of materials from illegal mining, dumping, and construction relies on surrounding roads. Electronic device signaling trajectories related to these illegal activities are filtered to exclude trajectories of normal commuting vehicles, thereby improving identification efficiency and accuracy.

[0028] Step 102: Obtain signaling data of electronic devices during the first analysis period, and based on the signaling data, determine the first trajectory characteristics of the target personnel carrying electronic devices in the shoreline area.

[0029] In this step, signaling data from electronic devices during the first analysis period is acquired to achieve real-time data collection. Electronic devices can be mobile devices such as mobile phones, tablets, and wearable devices. Signaling data includes, but is not limited to, user ID, timestamp, latitude and longitude, and dwelling information. The user ID can be a vehicle ID, electronic device ID, or personnel ID. Dwelling information includes dwelling location and dwelling duration. Further, the signaling data is mapped to a defined shoreline area, and trajectory features such as the movement speed, dwelling point density, dwelling duration, and round-trip frequency of the target personnel carrying electronic devices are extracted; these are the first trajectory features.

[0030] Step 103: Determine the location of the target person's violation of the river and lake rules based on the first trajectory feature, and match the first trajectory feature with the trajectory features stored in the trajectory feature database to determine the target trajectory feature that matches the first trajectory feature. Then, determine the type of behavior of the target person in violation of the river and lake rules based on the behavior type corresponding to the target trajectory feature.

[0031] In this embodiment, the signaling data contains latitude and longitude data. The location of the target person's illegal behavior in rivers and lakes can be determined using the first trajectory feature. The location of the behavior is the center point of the latitude and longitude of the area where the trajectory features are concentrated, with an accuracy of ≤50 meters. Furthermore, the first trajectory feature is compared with pre-stored trajectory features in a trajectory feature database to determine the trajectory feature that matches the first trajectory feature, which is then used as the target trajectory feature. Each pre-stored trajectory feature in the trajectory feature database has a corresponding behavior type. Based on the behavior type corresponding to the target trajectory feature, the type of illegal behavior of the target person in rivers and lakes is determined. In one embodiment, the behavior types include four types: illegal occupation, illegal mining, illegal dumping, and illegal construction.

[0032] This application, through signaling data from electronic devices, identifies trajectory characteristics within river and lake shoreline areas, thereby identifying illegal activities that damage rivers and lakes, such as unauthorized occupation, mining, dumping, and construction. This application fills the gap in satellite remote sensing for monitoring dynamic behavior, enabling precise differentiation of types of illegal activities in rivers and lakes, improving the accuracy and differentiation of identification types, and enhancing identification efficiency.

[0033] In one embodiment of this application, determining the behavior type of a target person regarding violations of river and lake regulations based on the behavior type corresponding to the target trajectory features includes: Acquire the second satellite remote sensing data for the first analysis period; If the second satellite remote sensing data is not obtained, the behavior type corresponding to the target trajectory characteristics will be taken as the behavior type of the target personnel for their illegal behavior in rivers and lakes. If second satellite remote sensing data is obtained, the behavior type of the target personnel in violation of river and lake regulations can be determined based on the behavior type corresponding to the second satellite remote sensing data and the target trajectory characteristics.

[0034] In this embodiment, a two-way collaborative logic of "spatial anchoring-behavioral verification" is established. This involves cross-verification using the static physical characteristics of satellite remote sensing and the dynamic behavioral characteristics of electronic equipment signaling. When satellite data is missing, the trajectory feature library is directly invoked for independent identification, forming a dual guarantee of "static observation + dynamic behavior." Here, missing satellite data refers to the absence of corresponding satellite data within the analysis period, which may be due to cloud cover, incomplete satellite transit coverage, satellite malfunction, or other reasons.

[0035] Acquire second-satellite remote sensing data for the first analysis period; that is, attempt to collect second-satellite remote sensing data while acquiring signaling data from electronic devices. If second-satellite remote sensing data is not acquired, the identification conclusion for river and lake violations is directly based on the matching results of the trajectory feature database.

[0036] If second satellite remote sensing data is collected, the identification conclusion of river and lake violations is determined jointly based on the second satellite remote sensing data and the behavior type corresponding to the target trajectory characteristics.

[0037] In one embodiment of this application, the behavior type of the target person regarding violations of river and lake regulations is determined based on the behavior type corresponding to the second satellite remote sensing data and the target trajectory characteristics, including: Extract the first static physical features of the shoreline area from the second satellite remote sensing data; Compare the behavior types corresponding to the first static physical features with the target trajectory features; If the two match, the behavior type corresponding to the target trajectory characteristics will be taken as the behavior type of the target person for the violation of the river and lake regulations. If the two do not match, then historical data should be combined to determine the type of behavior of the target personnel in violation of river and lake regulations.

[0038] In this embodiment, if second satellite remote sensing data exists for the same analysis period, a first static physical feature is extracted from the second satellite remote sensing data to determine the location of the violation, such as the outline of a newly constructed building for illegal construction and excavation traces for illegal mining. Then, the first static physical feature is compared with the behavior type corresponding to the target trajectory feature.

[0039] If the identification result of the first static physical feature matches the behavior type corresponding to the target trajectory feature, it indicates that the static physical feature extracted by the satellite remote sensing data is consistent with the behavior type determined by the information data. For example, if the behavior type determined by the information data is illegal construction, and the satellite remote sensing data shows that there is a newly added building outline at the corresponding location, then it is confirmed that the behavior type of the target personnel's illegal behavior in the river and lake is illegal construction.

[0040] If the identification result based on the first static physical feature does not match the behavior type corresponding to the target trajectory feature, for example, if the behavior type determined by the information data is illegal mining, and the satellite remote sensing data shows excavation traces or ore accumulation, then historical data is called for further analysis.

[0041] This application's embodiments, through a spatiotemporal linkage mechanism, effectively circumvent limitations such as satellite remote sensing transit time and cloud cover, enabling all-weather monitoring via signaling data even when satellite data is missing. Simultaneously, bidirectional verification reduces the false positive rate from a single data source, improves the reliability of identification results, and enhances location accuracy, providing precise coordinate guidance for rapid response.

[0042] In one embodiment of this application, historical data is used to determine the type of behavior of the target personnel in violation of river and lake regulations, including: Determine whether there are any historical violations related to rivers and lakes within the predetermined range of the location where the behavior occurred, based on historical data. If so, obtain the similarity between the signaling data and the historical signaling data corresponding to the historical violations. If the similarity is greater than a predetermined threshold, then the behavior type corresponding to the target trajectory features is taken as the behavior type of the target person regarding the river and lake violation; and / or, In historical data, identify third satellite remote sensing data within a preset time period prior to the first analysis period. Extract second static physical features of the shoreline area from the third satellite remote sensing data. If violations of regulations concerning rivers and lakes are determined based on the second static physical features, then the behavior type corresponding to the target trajectory features is taken as the behavior type of the target person's violation of regulations concerning rivers and lakes; and / or, Determine the road network distribution information of the shoreline area from historical data, and judge whether the first trajectory feature is a normal trajectory based on the road network distribution information. If it is not a normal trajectory, the behavior type corresponding to the target trajectory feature is taken as the behavior type of the target person for illegal behavior in rivers and lakes.

[0043] In this embodiment, historical data includes the location of historical river and lake violations, corresponding historical signaling data, satellite remote sensing data for each analysis period, and road network distribution information of the shoreline area.

[0044] Check historical data to see if there are similar records of river and lake violations within the location and a preset surrounding area, such as within 1 kilometer. If so, compare the similarity between the current signaling data and historical signaling data for river and lake violations. If the similarity is greater than a preset threshold, such as ≥80%, then the signaling data's identification result is preferred; that is, the behavior type corresponding to the target trajectory characteristics is taken as the target person's behavior type for river and lake violations.

[0045] Based on the static physical characteristics of satellite remote sensing data before and after the first analysis period, i.e., the static physical characteristics of the third satellite remote sensing data, it is determined whether there are any violations of river and lake regulations in their initial or temporary states. An initial state might be, for example, the foundation construction stage of illegal construction, or the satellite not clearly displaying the building outline. A temporary state might be, for example, a short-term pile of illegally dumped land that has been cleared, or the satellite not capturing the violation. If such violations exist, the identification result of the satellite remote sensing data is also determined to be the existence of the corresponding type of river and lake violation. Therefore, the behavior type corresponding to the target trajectory characteristics is taken as the behavior type of the target personnel regarding the river and lake violation.

[0046] By combining road network distribution information of the shoreline area, this information is used to assist in analyzing the transportation routes of illegal activities in rivers and lakes. For example, the transportation of materials from illegal mining, dumping, and construction relies on surrounding roads. Through road network distribution information, the signaling trajectories of electronic devices related to illegal activities in rivers and lakes can be filtered to exclude trajectories of normal commuting or operational vehicles. For instance, if the signaling trajectory of a vehicle near a highway matches normal freight speeds, it is excluded as an illegal activity. In other words, if the road network distribution information determines that the first trajectory feature is not a normal trajectory, then it is considered an illegal activity. Therefore, the behavior type corresponding to the target trajectory feature is taken as the behavior type of the target personnel involved in the illegal activities in rivers and lakes.

[0047] This application embodiment improves the accurate identification of behavioral types of violations in rivers and lakes by combining historical data.

[0048] In one embodiment of this application, the method further includes: generating and outputting an identification report, which includes the location where the behavior occurred, the type of behavior, the confidence level, signaling feature matching details, and the static physical characteristics of satellite remote sensing data.

[0049] In one embodiment of this application, the method further includes: constructing a trajectory feature library, which stores multiple mapping relationships between trajectory features and behavior types; wherein, the method of constructing the trajectory feature library includes: Obtain electronic device signaling sampling data during the second analysis period, and obtain confirmed river and lake violation data during the second analysis period. The electronic device signaling sampling data includes at least one of the following: user ID, timestamp, latitude and longitude, and dwell information. Trajectory features are extracted from the signaling sampling data of electronic devices to obtain trajectory features, which include at least one of the following: trajectory movement speed, dwell point density, dwell time, and round-trip frequency; The extracted trajectory features are correlated with the behavior types of river and lake violation data to construct a mapping relationship.

[0050] In this embodiment, a trajectory feature library is constructed to store the mapping relationship between trajectory features and behavior types. Specifically, this includes the following steps: (1) Collect sampling data: Collect electronic device signaling sampling data during the second analysis period, including user ID, timestamp, latitude and longitude, stay information, etc., and obtain confirmed river and lake violation data during the second analysis period, including behavior type, behavior location, occurrence time, static physical characteristics, etc.

[0051] (2) Signaling feature extraction: The electronic device signaling sampling data is used to reconstruct the trajectory and calculate the trajectory features such as trajectory movement speed, dwell point density, dwell time, and round-trip frequency per unit time.

[0052] (3) Correlation Analysis: The extracted trajectory features are correlated with the behavior types and corresponding static physical characteristics of river and lake violations to determine the typical characteristics of different behavior types, construct the mapping relationship between trajectory features and behavior types, and achieve dynamic and accurate characterization of behavior types. For example: a) Trajectory characteristics of illegal occupation: People stay for a long time (e.g., stay duration ≥ 72 hours, average stay ≥ 4 hours per day), high density of rest points (e.g., ≥ 5 rest points per 100㎡), and medium frequency of material transport vehicles (e.g., ≥ 3 round trips per day). b) Trajectory characteristics of illegal mining: High frequency of engineering vehicles (e.g., ≥8 round trips per day), stable trajectory movement speed (e.g., speed maintained at 20-40km / h during transportation periods), and personnel gathering during specific mining periods (e.g., 2-6 am and 9-11 am). c) Trajectory characteristics of disorderly stacking behavior: corresponding to short-term gatherings of people (e.g., stay duration ≤ 24 hours, number of people in a single gathering ≥ 10 people) and concentrated round trips of material transport vehicles in a short period of time (e.g., ≥ 5 round trips within 2 hours). d) Trajectory characteristics of illegal construction: It is characterized by long-term residence of personnel (e.g., stay duration ≥15 days, average stay ≥6 hours per day) and frequent traffic of construction vehicles (e.g., concrete trucks, dump trucks) (e.g., ≥6 times per day).

[0053] This application embodiment analyzes historical signaling data corresponding to historical river and lake violations, extracts typical features of different violation types, constructs a fine-grained mapping relationship between trajectory features and behavior types, breaks through the limitation of traditional satellite remote sensing that can only observe static physical forms, deeply mines the unique dynamic trajectory and spatiotemporal attributes of signaling data, and realizes dynamic identification.

[0054] As a specific implementation of the aforementioned method for identifying river and lake behavior, this application provides a device for identifying river and lake behavior. Figure 2 As shown, the identification device 200 for river and lake behavior includes: shoreline area determination module 201, trajectory feature determination module 202, and identification module 203.

[0055] Among them, the shoreline area determination module 201 is used to acquire first satellite remote sensing data and ground road network structure data, and determine the shoreline area of ​​rivers and lakes based on the first satellite remote sensing data and ground road network structure data; The trajectory feature determination module 202 is used to acquire signaling data of electronic devices during the first analysis period, and based on the signaling data, determine the first trajectory features of the target person carrying electronic devices in the shoreline area. The identification module 203 is used to determine the location of the target person's violation of the river and lake regulations based on the first trajectory features, and to match the first trajectory features with the trajectory features stored in the trajectory feature database to determine the target trajectory features that match the first trajectory features, and to determine the type of the target person's violation of the river and lake regulations based on the behavior type corresponding to the target trajectory features.

[0056] Furthermore, the shoreline area determination module 201 is specifically used for: The scope of the river and lake water areas is determined based on the first satellite remote sensing data and the ground road network structure data; The river and lake shoreline boundaries are determined based on the river and lake water area, and the shoreline areas are divided based on the river and lake shoreline boundaries.

[0057] Furthermore, the shoreline area determination module 201 is specifically used for: Based on the river and lake shoreline boundaries, a shoreline core area and a shoreline influence area are divided. The shoreline area includes the shoreline core area and the shoreline influence area. The shoreline core area is the area extending from the river and lake shoreline boundary into the river or lake at a first preset distance, and the shoreline influence area is the area extending from the river and lake shoreline boundary into the river or lake at a second preset distance.

[0058] Furthermore, the identification module 203 is specifically used for: Acquire the second satellite remote sensing data for the first analysis period; If the second satellite remote sensing data is not obtained, the behavior type corresponding to the target trajectory characteristics will be taken as the behavior type of the target person's violation of regulations in rivers and lakes; If the second satellite remote sensing data is obtained, the behavior type of the target person in violation of river and lake regulations is determined based on the behavior type corresponding to the second satellite remote sensing data and the target trajectory characteristics.

[0059] Furthermore, the identification module 203 is specifically used for: Extract the first static physical features of the shoreline area from the second satellite remote sensing data; Compare the behavior types corresponding to the first static physical feature with the target trajectory feature; If the two match, the behavior type corresponding to the target trajectory feature will be taken as the behavior type of the target person for the violation of the river and lake regulations. If the two do not match, then historical data will be used to determine the type of behavior of the target personnel in violation of river and lake regulations.

[0060] Furthermore, the identification module 203 is specifically used for: Determine whether there are any historical river or lake violations within the location and a preset surrounding area of ​​the occurrence of the behavior in the historical data. If so, obtain the similarity between the signaling data and the historical signaling data corresponding to the historical river or lake violations. If the similarity is greater than a preset threshold, then the behavior type corresponding to the target trajectory features is taken as the behavior type of the target person regarding the river or lake violations; and / or, The third satellite remote sensing data within a preset time period prior to the first analysis period is determined from the historical data. A second static physical feature of the shoreline area is extracted from the third satellite remote sensing data. If, based on the second static physical feature, it is determined that there is a violation of regulations concerning the river or lake, the behavior type corresponding to the target trajectory feature is taken as the behavior type of the target person's violation of regulations concerning the river or lake; and / or, The road network distribution information of the shoreline area is determined from the historical data. Based on the road network distribution information, it is determined whether the first trajectory feature is a normal trajectory. If it is not a normal trajectory, the behavior type corresponding to the target trajectory feature is taken as the behavior type of the target person's violation of the river and lake regulations.

[0061] Furthermore, the device is characterized in that it further includes: a construction module, used for: The trajectory feature library is constructed, which stores multiple mapping relationships between trajectory features and behavior types; wherein, the method of constructing the trajectory feature library includes: The electronic device signaling sampling data during the second analysis period is obtained, as well as the confirmed river and lake violation data during the second analysis period. The electronic device signaling sampling data includes at least one of the following: user ID, timestamp, latitude and longitude, and stay information. Trajectory features are extracted from the signaling sampling data of the electronic device to obtain trajectory features, which include at least one of the following: trajectory movement speed, stop point density, stop duration, and round-trip frequency; The extracted trajectory features are correlated with the behavior types of the river and lake violation data to construct the mapping relationship.

[0062] The river and lake behavior identification device 200 in this application embodiment can be a computer device or a component within a computer device, such as an integrated circuit or a chip. The river and lake behavior identification device 200 provided in this application embodiment can achieve... Figure 1 The various processes implemented in the embodiment of the method for identifying river and lake behavior will not be described in detail here to avoid repetition.

[0063] This application also provides a computer device, such as... Figure 3 As shown, the computer device 300 includes a processor 301 and a memory 302. The memory 302 stores a program or instruction that can run on the processor 301. When the program or instruction is executed by the processor 301, it implements the various steps of the above-described embodiment of the method for identifying river and lake behavior and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0064] The memory 302 can be used to store software programs and various data. The memory 302 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 302 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 302 in the embodiments of this application includes, but is not limited to, these and any other suitable types of memory.

[0065] Processor 301 may include one or more processing units; optionally, processor 301 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 301.

[0066] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described method for identifying river and lake behavior and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0067] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0068] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for identifying river and lake behavior, characterized in that, include: Acquire first satellite remote sensing data and ground road network structure data, and determine the shoreline area of ​​rivers and lakes based on the first satellite remote sensing data and the ground road network structure data; Acquire signaling data of electronic devices during the first analysis period, and based on the signaling data, determine the first trajectory characteristics of the target person carrying the electronic device in the shoreline area; The location of the target person's violation of the river and lake regulations is determined based on the first trajectory feature, and the first trajectory feature is matched with the trajectory features pre-stored in the trajectory feature database to determine the target trajectory feature that matches the first trajectory feature. Based on the behavior type corresponding to the target trajectory feature, the behavior type of the target person's violation of the river and lake regulations is determined.

2. The method for identifying river and lake behavior according to claim 1, characterized in that, Based on the first satellite remote sensing data and the ground road network structure data, the shoreline areas of rivers and lakes are determined, including: The scope of the river and lake water areas is determined based on the first satellite remote sensing data and the ground road network structure data; The river and lake shoreline boundaries are determined based on the river and lake water area, and the shoreline areas are divided based on the river and lake shoreline boundaries.

3. The method for identifying river and lake behavior according to claim 2, characterized in that, Based on the aforementioned river and lake shoreline boundaries, the shoreline area is divided, including: Based on the river and lake shoreline boundaries, a shoreline core area and a shoreline influence area are divided. The shoreline area includes the shoreline core area and the shoreline influence area. The shoreline core area is the area extending from the river and lake shoreline boundary into the river or lake at a first preset distance, and the shoreline influence area is the area extending from the river and lake shoreline boundary into the river or lake at a second preset distance.

4. The method for identifying river and lake behavior according to claim 1, characterized in that, Based on the behavior type corresponding to the target trajectory characteristics, determine the behavior type of the target person regarding the violation of river and lake regulations, including: Acquire the second satellite remote sensing data for the first analysis period; If the second satellite remote sensing data is not obtained, the behavior type corresponding to the target trajectory characteristics will be taken as the behavior type of the target person's violation of regulations in rivers and lakes; If the second satellite remote sensing data is obtained, the behavior type of the target person in violation of river and lake regulations is determined based on the behavior type corresponding to the second satellite remote sensing data and the target trajectory characteristics.

5. The method for identifying river and lake behavior according to claim 4, characterized in that, Based on the second satellite remote sensing data and the behavior type corresponding to the target trajectory characteristics, the behavior type of the target personnel regarding violations of river and lake regulations is determined, including: Extract the first static physical features of the shoreline area from the second satellite remote sensing data; Compare the behavior types corresponding to the first static physical feature with the target trajectory feature; If the two match, the behavior type corresponding to the target trajectory feature will be taken as the behavior type of the target person for the violation of the river and lake regulations. If the two do not match, then historical data will be used to determine the type of behavior of the target personnel in violation of river and lake regulations.

6. The method for identifying river and lake behavior according to claim 5, characterized in that, Based on historical data, determine the types of violations committed by the target individuals in relation to rivers and lakes, including: Determine whether there are any historical river or lake violations within the location and a preset surrounding area of ​​the occurrence of the behavior in the historical data. If so, obtain the similarity between the signaling data and the historical signaling data corresponding to the historical river or lake violations. If the similarity is greater than a preset threshold, then the behavior type corresponding to the target trajectory features is taken as the behavior type of the target person regarding the river or lake violations; and / or, The third satellite remote sensing data within a preset time period prior to the first analysis period is determined from the historical data. A second static physical feature of the shoreline area is extracted from the third satellite remote sensing data. If, based on the second static physical feature, it is determined that there is a violation of regulations concerning the river or lake, the behavior type corresponding to the target trajectory feature is taken as the behavior type of the target person's violation of regulations concerning the river or lake; and / or, The road network distribution information of the shoreline area is determined from the historical data. Based on the road network distribution information, it is determined whether the first trajectory feature is a normal trajectory. If it is not a normal trajectory, the behavior type corresponding to the target trajectory feature is taken as the behavior type of the target person's violation of the river and lake regulations.

7. The method for identifying river and lake behavior according to any one of claims 1 to 6, characterized in that, The method further includes: The trajectory feature library is constructed, which stores multiple mapping relationships between trajectory features and behavior types; wherein, the method of constructing the trajectory feature library includes: The electronic device signaling sampling data during the second analysis period is obtained, as well as the confirmed river and lake violation data during the second analysis period. The electronic device signaling sampling data includes at least one of the following: user ID, timestamp, latitude and longitude, and stay information. Trajectory features are extracted from the signaling sampling data of the electronic device to obtain trajectory features, which include at least one of the following: trajectory movement speed, stop point density, stop duration, and round-trip frequency; The extracted trajectory features are correlated with the behavior types of the river and lake violation data to construct the mapping relationship.

8. A device for identifying river and lake behavior, characterized in that, include: The shoreline area determination module is used to acquire first satellite remote sensing data and ground road network structure data, and determine the shoreline area of ​​rivers and lakes based on the first satellite remote sensing data and the ground road network structure data. The trajectory feature determination module is used to acquire signaling data of electronic devices during the first analysis period, and based on the signaling data, determine the first trajectory features of the target person carrying the electronic device in the shoreline area. The identification module is used to determine the location where the target person's violation of the river and lake regulations occurs based on the first trajectory feature, and to match the first trajectory feature with the trajectory features pre-stored in the trajectory feature database to determine the target trajectory feature that matches the first trajectory feature, and to determine the type of the target person's violation of the river and lake regulations based on the behavior type corresponding to the target trajectory feature.

9. A computer device, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that run on the processor, the program or instructions being executed by the processor to implement the steps of the method for identifying river and lake behavior as described in any one of claims 1 to 7.

10. A readable storage medium having a program or instructions stored thereon, characterized in that, When the program or instructions are executed by the processor, they implement the steps of the method for identifying river and lake behavior as described in any one of claims 1 to 7.

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