A three-dimensional GIS flight simulation system for ecological environment monitoring

Abstract

The application discloses a three-dimensional GIS flight simulation system for ecological environment monitoring and relates to the technical fields of geographic information and three-dimensional simulation. The method comprises the following steps: collecting multi-source ecological environment monitoring data by a cloud platform; preprocessing the collected multi-source ecological environment monitoring data, and constructing a three-dimensional simulation flight scene; in the three-dimensional simulation flight scene, smoothing the original flight track according to the preprocessed ecological environment monitoring data, and optimizing the flight track; extracting river data features from the multi-source ecological environment monitoring data, analyzing the river flight track by using the river data features, and optimizing the river flight track; and combining the collected multi-source ecological environment monitoring data, simulating and emulating the optimized flight track in a three-dimensional scene. The application can ensure the flight performance and the fluency of flight browsing.

Description

Technical Field

[0001] This invention relates to the field of geographic information and 3D simulation technology, and in particular to a 3D GIS flight simulation system for ecological environment monitoring. Background Technology

[0002] In recent years, my country has steadfastly pursued a path of ecological priority and green development, making significant strides in building a beautiful China. However, China's green and low-carbon transformation remains a formidable task, ecological and environmental problems remain prominent, and the demand for ecological and environmental monitoring is growing, requiring more precise, efficient, and comprehensive monitoring methods. Ecological and environmental monitoring allows for real-time understanding of the ecological environment, timely detection and resolution of ecological and environmental problems, and provides a scientific basis for ecological and environmental protection. Three-dimensional aerial photography, as an advanced visualization method, provides technical support for ecological and environmental monitoring and management. Through aerial photography and simulation based on three-dimensional ecological and environmental scenes, a comprehensive, three-dimensional, and dynamic perception of the ecological environment can be achieved, helping to promptly identify ecological and environmental problems and improve monitoring efficiency and management levels.

[0003] Currently, flight simulations based on 3D GIS simulation environments generally perform fusion preprocessing of 3D spatial data and determine flight routes by presetting a series of flight points and perspectives. However, existing technologies still lack smoothness when dealing with complex terrains such as multi-segment line connections and turns, which can easily lead to a stiff and disjointed flight experience and fail to effectively support the display and analysis of ecological environment monitoring information.

[0004] In addition, traditional 3D GIS flight simulation technology is not only insufficient for smoothing complex trajectories, but also lacks the processing of key geographic elements and flight routes. The adjustment and setting of flight parameters are difficult, and the display, analysis and interactivity of thematic information during the flight simulation process cannot meet the needs of the industry. It cannot provide a smooth flight browsing and dynamic thematic information display experience, and cannot provide effective technical support for fully reflecting the macro-level ecological environment scene and monitoring business information.

[0005] Based on this, the present invention proposes a three-dimensional GIS flight simulation method and system for ecological environment monitoring scenarios. Summary of the Invention

[0006] This invention provides a three-dimensional GIS flight simulation method for ecological environment monitoring, comprising:

[0007] The cloud platform collects multi-source ecological environment monitoring data;

[0008] The collected multi-source ecological environment monitoring data are preprocessed to construct a three-dimensional simulated flight scenario;

[0009] In a three-dimensional simulated flight scenario, the original flight trajectory is smoothed and optimized based on preprocessed ecological environment monitoring data.

[0010] Extract riverside data features from multi-source ecological environment monitoring data, analyze riverside flight trajectories using these features, and optimize riverside flight trajectories.

[0011] By combining the collected multi-source ecological environment monitoring data, a three-dimensional scene simulation was performed on the optimized flight trajectory.

[0012] The above-mentioned three-dimensional GIS flight simulation method for ecological environment monitoring involves collecting multi-source ecological environment monitoring data. Specifically, based on the ecological environment monitoring area, monitoring elements, and flight path planning requirements, it collects basic geographic data such as river and water body related vector data, topography, POI points, and building models, as well as ecological environment monitoring data such as air quality, water quality, and meteorology, and integrates the multi-source ecological environment information.

[0013] The above-mentioned 3D GIS flight simulation method for ecological environment monitoring includes preprocessing of collected multi-source ecological environment monitoring data, specifically including: unifying spatiotemporal reference, converting multi-source data formats into a unified data format required by the system, data editing and processing according to scene fusion requirements, data lightweighting, data quality inspection, and layer setting and management.

[0014] The three-dimensional GIS flight simulation method for ecological environment monitoring described above includes the following sub-steps for smoothing and optimizing the original flight trajectory:

[0015] Select multiple key control points for the flight path from the map;

[0016] Interpolation optimization was performed on multiple key control points;

[0017] Multiple curve segments defined by adjacent control points are combined after interpolation optimization to form a continuous flight trajectory;

[0018] The resulting flight trajectory is further optimized through interpolation to improve its shape and smoothness.

[0019] The above-described 3D GIS flight simulation method for ecological environment monitoring includes optimizing the river-flying trajectory, specifically comprising the following sub-steps:

[0020] Preprocessing of the flight path along the river;

[0021] The pre-processed riverside flight trajectory was thinned out.

[0022] The riverside flight trajectory, after being thinned, was smoothed.

[0023] The above-described 3D GIS flight simulation method for ecological environment monitoring combines multi-source ecological environment monitoring data to perform 3D scene simulation on the optimized flight trajectory. Specifically, it simulates meteorological lighting and water flow scenes in the 3D ecological environment scene; based on meteorological data and flight simulation time settings, it simulates weather and lighting conditions in the ecological environment spatial scene, simulating sunny, rainy, and snowy weather scenes, as well as daytime and nighttime lighting effects, using real-time weather data; and it generates water surface flow effects for the flight path along the river to enhance the realism of the scene during flight.

[0024] This invention also provides a three-dimensional GIS flight simulation system for environmental monitoring, comprising: a cloud platform, ecological area monitoring equipment, and a GIS system;

[0025] Ecological area monitoring equipment is used to collect ecological environment monitoring data and send the ecological environment monitoring data to the cloud platform;

[0026] The GIS system is used to provide basic geographic data to the cloud platform;

[0027] The cloud platform acquires ecological environment monitoring data from ecological area monitoring equipment and basic geographic data from the GIS system as multi-source ecological environment monitoring data; the cloud platform executes a three-dimensional GIS flight simulation method for ecological environment monitoring as described above.

[0028] The present invention also provides a computer storage medium, characterized in that it comprises: at least one memory and at least one processor;

[0029] The memory is used to store one or more program instructions;

[0030] A processor is used to run one or more program instructions to execute a three-dimensional GIS flight simulation method for ecological environment monitoring as described above.

[0031] The beneficial effects achieved by this invention are as follows:

[0032] (1) This invention uses cubic spline curve interpolation to smooth the set of spatial coordinate points, thus achieving smooth flight transition at the inflection point of the custom trajectory; through appropriate thinning calculation and interpolation calculation, the flight trajectory along the water system is optimized, ensuring flight performance and smoothness of flight browsing, while also taking into account the rationality of the flight browsing range along the line.

[0033] (2) The technical solution of this invention is adopted in the three-dimensional flight simulation module of the Ministry of Ecology and Environment's spatiotemporal data cloud platform. After setting the flight path or selecting the water system along the flight path, it can achieve smooth flight and browse various ecological and environmental monitoring scenarios and information in the simulated three-dimensional space, which significantly improves the realism, smoothness and user experience of flight simulation. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0035] Figure 1 This is a flowchart of a three-dimensional GIS flight simulation method for ecological environment monitoring provided in Embodiment 1 of this application;

[0036] Figure 2 This is a schematic diagram of a three-dimensional GIS flight simulation system for environmental monitoring provided in Embodiment 1 of this application. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Example 1

[0039] like Figure 1 As shown, Embodiment 1 of the present invention provides a three-dimensional GIS flight simulation method for ecological environment monitoring, applied in the spatiotemporal data cloud platform of the Ministry of Ecology and Environment, specifically including:

[0040] Step 110: The cloud platform collects multi-source ecological environment monitoring data;

[0041] Based on the needs of ecological and environmental monitoring areas, monitoring elements, and flight path planning, basic geographic data such as river and water body related vector data, topography, POI points, and building models are collected, as well as ecological and environmental monitoring data such as air quality, water quality, and meteorology. Then, the multi-source ecological and environmental information is aggregated and integrated.

[0042] Among them, river and water body related vector data are used to form the original trajectory of flight along the river; basic geographic data such as terrain, POI points, and building models are used for three-dimensional static scene simulation in flight demonstration; and ecological environment monitoring data such as air quality, water quality, and meteorology are used for information display and user interaction during flight, providing special information support for flight browsing and simulation.

[0043] Step 120: Preprocess the collected multi-source ecological environment monitoring data to construct a three-dimensional simulated flight scenario;

[0044] Specifically, the collected ecological environment monitoring data is preprocessed to construct a three-dimensional simulated flight scenario, providing a data foundation for three-dimensional browsing and flight simulation.

[0045] Data preprocessing specifically includes:

[0046] ① Unified spatiotemporal reference:

[0047] Multi-source flight scene data needs to be displayed under a unified coordinate system. The 2000 National Geodetic Coordinate System (CGCS2000) and the 1985 National Height Datum are used as a unified spatial reference. Coordinate transformation tools are used to perform coordinate transformation and spatial registration of multi-source data, unifying various types of data from different sources under this spatiotemporal reference to ensure coordinate consistency and the accuracy of geographical location information.

[0048] ② Convert multi-source data formats into the unified data format required by the system:

[0049] In order to make full use of existing information resources and improve the efficiency of system data utilization, the multi-source data formats are completely converted into the data format required by the system, realizing the unified format conversion of two-dimensional, three-dimensional and attribute data.

[0050] ③ Perform data editing and processing according to the needs of scene integration:

[0051] Based on the scene fusion requirements of the 3D scene virtual simulation model, the data is edited and processed, including image data registration and mosaicking, 3D model flattening, hole punching, cropping, and precise matching of model positions, etc., to fuse data of different types and time series.

[0052] ④ Lightweight data processing:

[0053] To address issues such as excessive resource consumption and loading lag during rendering of numerous ecological environment monitoring model scenes, an optimized multi-level model data structure was constructed, and the data was instantiated and tiled. Through a series of lightweight processing steps, the loading speed and performance of the full-element 3D scene were improved, meeting the performance requirements for scene rendering, information display, and analysis during flight browsing.

[0054] ⑤ Data quality control and processing:

[0055] Based on the system's quality requirements for 3D scene data, data quality checks are conducted according to standards such as data spatial reference consistency, data format accuracy, and data content completeness to ensure the usability and accuracy of ecological environment scene and monitoring data.

[0056] ⑥ Layer settings and management:

[0057] Various types of ecological environment monitoring data are managed in layers, with thematic element layers such as topography, vegetation, and water system layers set up for data management. The display and hiding of each layer are managed in the flight browsing simulation to meet the information display needs during the flight browsing process.

[0058] Step 130: In the three-dimensional simulated flight scenario, the original flight trajectory is smoothed and optimized based on the preprocessed ecological environment monitoring data;

[0059] The original flight trajectory consists of a series of coordinate points in map space. However, the transitions at the inflection points of the original flight trajectory are abrupt and unsmooth. This application smooths the flight trajectory in three-dimensional space, achieving smooth transitions at inflection points while keeping the inflection points within the flight field of view, thus improving the flight simulation experience.

[0060] Specifically, the original flight trajectory is smoothed and optimized, which includes the following sub-steps:

[0061] Step 131: Select multiple key control points for the flight path from the map;

[0062] In the 3D simulation scenario, a series of key control points are selected on the map to represent the key locations of the flight trajectory, including important nodes on the flight path such as takeoff point, turning point, and landing point.

[0063] The turning point is obtained based on the flight path, using the formula. Calculate whether each flight turning point is a critical control point for turning, where GKZ is the critical control point for turning, and ks is the critical control point for turning. i Let g be the airspeed at the i-th flight turn point, g be the acceleration due to gravity, and θ be the velocity. i Let yd be the turning angle at the i-th flight turning point. i Let hd be the allowable turning radius at the i-th flight turning point. i ,zd i ,jd i Let be the three-dimensional coordinates of the i-th flight turning point, and n be the number of flight turning points in the flight path, with i ranging from [1, n]. Let be the turning radius at the i-th flight turning point. Determine if it is greater than the allowable turning radius at the i-th flight turning point. If it is greater than the allowable turning radius at the i-th flight turning point, then the i-th flight turning point is a critical control point for turning.

[0064] Based on the flight path, the takeoff and landing points where altitude adjustments are needed during flight monitoring are obtained, using the formula... Calculate whether each flight takeoff and landing point is a critical control point, where hd j ,zd j jd j Let hd be the three-dimensional coordinates of the j-th rising / falling point. j+1 ,zd j+1 jd j+1 These are the three-dimensional coordinates of the (j+1)th flight takeoff and landing point, (hd j ,zd j ,jd j ) and (hd j+1 ,zd j+1 ,jd j+1 ) represents two adjacent takeoff and landing points, jl j The flight distance that takes the aircraft to ascend to its normal altitude due to flight inertia, (hd j ,zd j ,jd j Let be the three-dimensional coordinates of the j-th takeoff and landing point, m be the number of takeoff and landing points in the flight path, and j be in the range [1, m-1]. Let j be the distance from the j+1th takeoff and landing point. Determine if it is less than the flight distance from the j+1th takeoff and landing point to the normal ascent altitude due to flight inertia. If it is less, then the jth takeoff and landing point is the critical control point for takeoff and landing.

[0065] The key control points are generated by integrating the key control points for turning and lifting.

[0066] Step 132: Perform interpolation optimization on multiple key control points;

[0067] Specifically, interpolation calculations were performed to optimize the flight path, using the Catmull-RomSpline cubic spline curve interpolation algorithm. Catmull-Rom Spline is a method for generating multi-segment interpolated B-Spline curves, where each curve is defined by four adjacent control points (Pi-2, Pi-1, Pi, Pi+1), where P′... i =τ(P i+1 -P i-1 The calculation is performed using the Catmull-Rom Spline interpolation formula, which is:

[0068]

[0069] Where p(s) is the interpolation point function, representing the curve point at parameter s, used for interpolation along the curve segment; u is a variable, usually ranging from 0 to 1, representing the proportional position of a point on the curve relative to its segment. By changing the value of u, different points can be obtained on the curve; Pi-2, Pi-1, Pi, Pi+1 are control points used to define each curve segment. Pi-2 is the second control point of the previous curve segment, Pi-1 is the end point of the previous curve segment, Pi is the start point of the current segment, and Pi+1 is the end point of the current segment; τ is the tension parameter, used to control the smoothness of the curve, ranging from 0 to 1. The smaller the value, the smoother the curve.

[0070] Step 133: Combine multiple curve segments defined by adjacent control points after interpolation optimization to form a continuous flight trajectory.

[0071] Multiple curve segments defined by adjacent control points are combined to form a continuous flight path. To ensure the smoothness of the path at the connection points, the parameter τ in the interpolation formula is kept consistent between adjacent curve segments when applying the Catmull-Rom Spline interpolation formula to maintain parameter continuity.

[0072] Step 134: Continue to perform interpolation optimization on the formed flight trajectory to optimize the shape and smoothness of the flight trajectory.

[0073] Based on actual needs, the parameter τ in the interpolation formula is adjusted to optimize the shape and smoothness of the flight trajectory. When τ = 0, a standard Uniform Catmull-Rom spline curve is obtained; when τ = 1, a Chordal Catmull-Rom spline curve is obtained; and when τ = 0.5, a Centripetal Catmull-Rom spline curve is obtained. The set parameter τ is then substituted into the formula to obtain the optimized flight trajectory. This optimized trajectory is applied to a 3D simulation scene for flight simulation and verification, evaluating the rationality and applicability of the parameters, and obtaining the optimal parameter values.

[0074] See back Figure 1 Step 140: Extract riverside data features from multi-source ecological environment monitoring data, analyze riverside flight trajectories using riverside data features, and optimize riverside flight trajectories.

[0075] Specifically, the riverside data features include, but are not limited to, river channel and water system vector features. Using these features, a riverside flight path is automatically provided. In response to the dense and complex coordinate points of the river channel and water system vector paths, the characteristics of the riverside flight path data are analyzed, key points are selected, and the main shape features of the path are preserved. The path is then optimized according to thinning calculation rules. The optimized riverside flight path retains the main shape features of the path while reducing redundant points and improving flight performance.

[0076] The optimization process, based on the thinning calculation rules, includes the following sub-steps:

[0077] Step 141: Preprocess the flight path along the river;

[0078] River vector data is merged based on the "name" field, combining river segments with the same name into a continuous polyline to avoid breaks and repetitions in the trajectory segments.

[0079] Step 142: Thin out the preprocessed riverside flight trajectory;

[0080] The Douglas-Peucker algorithm is applied to thin out the merged river trajectory segments. The algorithm assumes the original curve is P(t) = (x(t), y(t)), t ∈ [0, 1], and the key point set is K = {k1, k2, ..., kn}. The goal of the algorithm is to find the minimum K such that for any t ∈ [0, 1], d(P(t), L(t)) ≤ ε. Here, P(t) defines the shape and position of the original curve, x(t) and y(t) represent the x-coordinate and y-coordinate of the curve at time t, respectively; t is used to locate a point on the curve. By changing the value of t, different points on the curve can be obtained. Its value ranges from 0 to 1; K = {k1, k2, ..., kn} is the key point set, which contains some important points on the curve; L(t) is a polygonal line fitted through K points; d(P(t), L(t)) is the vertical distance from P(t) to L(t); and ε is the maximum tolerance value.

[0081] First, a maximum tolerance value ε is set. After testing and verification, ε is set to 200 meters, representing the maximum vertical distance between the curve and the polygonal line fitted through the keypoints. Then, starting from the two endpoints of the curve, the point farthest from the polygonal line is found. If this distance is greater than ε, the point is retained as a keypoint, and the curve is divided into two segments using this point as the boundary. Each segment is processed recursively. This process is repeated until the distance between all points is no greater than ε, finally yielding a simplified curve composed of keypoints.

[0082] Step 143: Smooth the thinned riverside flight path:

[0083] The Snake algorithm is applied to the thinned river trajectory data for smoothing to further reduce discontinuities or uneven transitions caused by thinning. The Snake algorithm is an energy minimization method that adjusts points on the curve to achieve an optimal fit under certain constraints. The Snake curve can be represented as S(u)=(x(u),y(u)), u∈[0,1], and its total energy E consists of internal energy E_int and external energy E_ext: E=E_int+E_ext. Internal energy typically includes elastic energy E_elastic and bending energy E_bend. The Snake algorithm minimizes E by adjusting S(u).

[0084] Where S(u) represents the Snake curve function, x(u) and y(u) represent the x and y coordinates of position u on the curve, respectively, used to describe and adjust the shape of the river trajectory; u is a parameter of the Snake curve, with a value between 0 and 1. By changing the value of u, different points can be located on the Snake curve to adjust the curve shape; E is the total energy of the Snake curve; E_int is the internal energy of the Snake curve; E_ext is the external energy of the Snake curve; E_elastic is the elastic energy of the Snake curve, reflecting the energy change of the curve when stretched or compressed; E_bend is the bending energy of the Snake curve, which reflects the energy change of the curve when bending; δ is a parameter in the Snake algorithm that controls the smoothness of the curve, defining the maximum allowable distance between points on the Snake curve and the original data points.

[0085] For example, the maximum tolerance value δ is set to 100 meters as a parameter to control the smoothness of the curve in the Snake algorithm. The thinned river segment is initialized, and the points on the curve are adjusted iteratively to minimize the total energy (including internal elastic energy and external potential energy) of the curve while ensuring that the distance between the curve and the original data points does not exceed δ.

[0086] Step 150: Combine the collected multi-source ecological environment monitoring data to perform three-dimensional scene simulation of the optimized flight trajectory;

[0087] Specifically, the simulation of three-dimensional ecological environment scenes includes meteorological lighting and water flow. Based on meteorological data and flight simulation time settings, the simulation of weather and lighting conditions in the ecological environment spatial scene is carried out. Real-time weather data is used to simulate weather scenes such as sunny, rainy, and snowy days, as well as lighting effects such as day and night. Furthermore, water flow effects are generated for the flight path along the river to enhance the realism of the scene during the flight.

[0088] According to the formula Calculate the simulation degree of the 3D scene, where MNZ is the simulation degree of the 3D scene; λ1 is the weight value of the simulation data of the flight trajectory; and gj is the weight value of the simulation data. i Let gj be the simulated flight trajectory value for the i-th simulation. max ,gj min λj represents the maximum and minimum values ​​in the simulated flight trajectory, respectively; λ2 represents the weight value of the simulated meteorological and weather conditions data, and xj represents the maximum and minimum values ​​in the simulated flight trajectory data. i Let xj be the simulated meteorological and weather state value for the i-th simulation. max ,xj min λ1 and λ2 are the maximum and minimum values ​​in the simulated meteorological and weather conditions, respectively; λ3 is the weight value of the simulated lighting effect data, zs i Let zs be the simulated lighting effect value for the i-th simulation. max ,zs min λ1 and λ2 are the maximum and minimum values ​​of the simulated lighting effect, respectively; n is the simulation number, and the value of i ranges from [1, n], where λ1 + λ2 + λ3 = 1.

[0089] The degree of monitoring of the flight trajectory on the ecological environment is judged based on the simulation degree of the three-dimensional scene. If the monitoring degree does not reach the predicted monitoring value, the simulation parameters are adjusted and the above steps are repeated to optimize the three-dimensional scene simulation.

[0090] Example 2

[0091] like Figure 2 As shown, Embodiment 2 of the present invention provides a three-dimensional GIS flight simulation system for environmental monitoring, including: a cloud platform 21, an ecological area monitoring device 22, and a GIS system 23;

[0092] The ecological area monitoring equipment 22 is used to collect ecological environment monitoring data and send the ecological environment monitoring data to the cloud platform 21;

[0093] GIS system 23 is used to provide basic geographic data to cloud platform 21;

[0094] The cloud platform 21 acquires the ecological environment monitoring data of the ecological area monitoring equipment 22 and the basic geographic data of the GIS system 23 as multi-source ecological environment monitoring data;

[0095] The cloud platform 21 specifically includes:

[0096] Multi-source data collection module 211 is used to collect multi-source ecological environment monitoring data;

[0097] The three-dimensional simulated flight scenario construction module 212 is used to preprocess the collected multi-source ecological environment monitoring data and construct a three-dimensional simulated flight scenario;

[0098] The flight trajectory optimization module 213 is used to smooth the original flight trajectory and optimize the flight trajectory in a three-dimensional simulated flight scenario based on the pre-processed ecological environment monitoring data; extract river-side data features from multi-source ecological environment monitoring data, analyze the river-side flight trajectory using the river-side data features, and optimize the river-side flight trajectory.

[0099] The 3D scene simulation module 214 is used to simulate the optimized flight trajectory in three dimensions by combining the collected multi-source ecological environment monitoring data.

[0100] Corresponding to the above embodiments, the present invention provides a computer storage medium, including: at least one memory and at least one processor;

[0101] The memory is used to store one or more program instructions;

[0102] A processor is used to run one or more program instructions to execute a three-dimensional GIS flight simulation method for ecological environment monitoring.

[0103] Corresponding to the above embodiments, this embodiment of the invention provides a computer-readable storage medium containing one or more program instructions, which are executed by a processor to provide a three-dimensional GIS flight simulation method for ecological environment monitoring.

[0104] The embodiments disclosed in this invention provide a computer-readable storage medium storing computer program instructions. When the computer program instructions are executed on a computer, the computer performs the above-described three-dimensional GIS flight simulation method for ecological environment monitoring.

[0105] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0106] The various methods, steps, and logic diagrams disclosed in the embodiments of this invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods.

[0107] The storage medium can be memory, such as volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0108] Among them, non-volatile memory can 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.

[0109] Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as 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 linked dynamic random access memory (Synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM).

[0110] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0111] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using a combination of hardware and software. When applied as software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of computer programs from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0112] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A three-dimensional GIS flight simulation method for ecological environment monitoring, characterized in that, include: The cloud platform collects multi-source ecological environment monitoring data; The collected multi-source ecological environment monitoring data are preprocessed to construct a three-dimensional simulated flight scenario; In a three-dimensional simulated flight scenario, the original flight trajectory is smoothed and optimized based on preprocessed ecological environment monitoring data. In the 3D simulation scenario, a series of key control points are selected on the map to represent the key locations of the flight trajectory; The turning point is obtained based on the flight path, using the formula. Calculate whether each flight turning point is a critical control point for turning, where, As a key control point for turning, For the first Airspeed at each flight turning point It is the acceleration due to gravity. For the first The number of turning angles at each flight turning point For the first The permissible turning radius at each flight turning point For the first The three-dimensional coordinates of each flight turning point The number of turning points in the flight path. The range of values ​​is , For the first Determine if the turning radius at the first flight turning point is greater than the first turning radius. The permissible turning radius at the first flight turning point is greater than the first. The permissible turning radius at the first flight turning point is... Each flight turning point is a critical control point for turning; Based on the flight path, the takeoff and landing points where altitude adjustments are needed during flight monitoring are obtained, using the formula... Calculate whether each takeoff and landing point is a critical control point for takeoff and landing, where, , , The first The three-dimensional coordinates of the rising and falling points , , The first The three-dimensional coordinates of each flight takeoff and landing point and For two adjacent takeoff and landing points, The distance traveled to the normal altitude reached due to flight inertia. For the first The three-dimensional coordinates of each flight landing and takeoff point This represents the number of takeoff and landing points along the flight path. The range of values ​​is , For the first The distance from the j+1th flight landing point to the j-th flight landing point is determined to be less than the flight distance from the j-th flight landing point to the j+1th flight landing point for normal ascent altitude due to flight inertia. If it is less, then the j-th flight landing point is the critical control point for ascent and descent. The key control points are generated by integrating the key control points for turning and lifting. Extract riverside data features from multi-source ecological environment monitoring data, analyze riverside flight trajectories using these features, and optimize riverside flight trajectories. By combining the collected multi-source ecological environment monitoring data, a three-dimensional scene simulation was performed on the optimized flight trajectory.

2. The three-dimensional GIS flight simulation method for ecological environment monitoring as described in claim 1, characterized in that, Collect multi-source ecological and environmental monitoring data, specifically: based on the ecological and environmental monitoring areas, monitoring elements, and flight path planning requirements, collect basic geographic data such as vector data related to rivers and water bodies, topography, POI points, and building models, as well as ecological and environmental monitoring data such as air quality, water quality, and meteorology, and integrate multi-source ecological and environmental information.

3. The three-dimensional GIS flight simulation method for ecological environment monitoring as described in claim 1, characterized in that, The collected multi-source ecological environment monitoring data is preprocessed, including: unifying the spatiotemporal benchmark, converting the multi-source data format into the unified data format required by the system, editing and processing the data according to the scenario fusion requirements, lightweight data processing, data quality inspection, and layer setting and management.

4. The three-dimensional GIS flight simulation method for ecological environment monitoring as described in claim 1, characterized in that, The original flight trajectory is smoothed and optimized, which includes the following sub-steps: Select multiple key control points for the flight path from the map; Interpolation optimization is performed on multiple key control points; Multiple curve segments defined by adjacent control points are combined after interpolation optimization to form a continuous flight trajectory; The resulting flight trajectory is further optimized through interpolation to improve its shape and smoothness.

5. The three-dimensional GIS flight simulation method for ecological environment monitoring as described in claim 1, characterized in that, Optimizing the riverside flight path involves the following sub-steps: Preprocessing of the flight path along the river; The pre-processed riverside flight trajectory was thinned out. The riverside flight trajectory, after being thinned, was smoothed.

6. The three-dimensional GIS flight simulation method for ecological environment monitoring as described in claim 1, characterized in that, By combining the collected multi-source ecological environment monitoring data, a three-dimensional scene simulation is performed on the optimized flight trajectory. Specifically, the simulation includes: meteorological lighting and water flow scenes in the three-dimensional ecological environment scene; based on meteorological data and the flight simulation time setting, the weather and lighting conditions of the ecological environment spatial scene are simulated; real-time weather data is used to simulate sunny, rainy, and snowy weather scenes, as well as daytime and nighttime lighting effects; and water flow effects are generated for the flight path along the river to enhance the realism of the scene during the flight.

7. A three-dimensional GIS flight simulation system for environmental monitoring, characterized in that, include: Cloud platform, ecological area monitoring equipment and GIS system; Ecological area monitoring equipment is used to collect ecological environment monitoring data and send the ecological environment monitoring data to the cloud platform; The GIS system is used to provide basic geographic data to the cloud platform; The cloud platform acquires ecological environment monitoring data from ecological area monitoring equipment and basic geographic data from the GIS system as multi-source ecological environment monitoring data; the cloud platform executes a three-dimensional GIS flight simulation method for ecological environment monitoring as described in any one of claims 1-6.

8. A computer storage medium, characterized in that, include: At least one memory and at least one processor; The memory is used to store one or more program instructions; A processor for running one or more program instructions to execute a three-dimensional GIS flight simulation method for ecological environment monitoring as described in any one of claims 1-6.

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