UAV Beach Erosion Mapping With Unified Shoreline Comparison
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Solution Overview
Problem
Conventional beach erosion monitoring methods rely on ground measurement and manual sampling, which are costly, inefficient, and lack real-time data acquisition, making it difficult to accurately assess and manage beach changes due to complex and dynamic beach environments.
Innovation Solution
A beach erosion detection and quantitative calculation method using an unmanned aerial vehicle (UAV) equipped with Livox LIDAR, high-precision inertial navigation, and mapping camera, combined with M300RTK for accurate positioning, and integrated with machine learning models to analyze and predict beach erosion trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional ground measurement and manual sampling methods are used for beach erosion monitoring, then measurement precision can be maintained, but productivity is low and loss of time is high
Solution Approach 1:
The patent replaces conventional mechanical ground measurement systems with an aerial photography system using UAVs equipped with LIDAR and mapping cameras. This substitution enables rapid data acquisition over large beach areas while maintaining high measurement precision through advanced photogrammetry and LIDAR technology, directly resolving the contradiction between measurement precision and productivity
Solution Approach 2:
The patent transitions from two-dimensional ground-based measurement to three-dimensional aerial mapping using LIDAR and photogrammetry. This dimensional change allows simultaneous capture of comprehensive beach topography data across entire monitoring sections, dramatically improving productivity while preserving measurement accuracy through multi-point spatial sampling
2Device complexity
If conventional manual sampling methods are used, then equipment complexity is low, but measurement precision and data completeness are insufficient
Solution Approach 1:
The patent merges LIDAR technology, mapping cameras, inertial navigation systems, and RTK positioning into an integrated UAV monitoring platform. This combination creates a comprehensive data acquisition system that captures both surface morphology and subsurface sedimentation information, achieving high measurement precision while managing system complexity through integrated design
Solution Approach 2:
The UAV monitoring system performs multiple functions including aerial photography, LIDAR scanning, GPS positioning, and real-time data transmission. This multi-functionality allows a single system to address various monitoring needs (topography, sedimentation, erosion patterns) simultaneously, improving measurement precision without proportionally increasing device complexity
3Quantity of substance
If conventional monitoring methods are used, then cost is reduced, but loss of time increases and real-time monitoring capability is lost
Solution Approach 1:
The patent implements continuous monitoring capability through automated UAV flights at regular intervals, with real-time data transmission and processing. This continuous action enables timely detection of beach erosion events and sedimentation changes, reducing loss of time while maintaining cost-effectiveness through automated operation and reduced manual intervention
Solution Approach 2:
The system performs preliminary data processing and erosion prediction during flight operations, generating initial analysis results before ground verification is needed. This preliminary action reduces overall monitoring time by preparing data for immediate analysis, while keeping costs manageable through efficient preprocessing algorithms
4Device complexity
If conventional methods are used for complex beach environment analysis, then device complexity is low, but measurement precision and adaptability are insufficient
Solution Approach 1:
The patent employs machine learning models that dynamically adjust processing parameters based on varying beach conditions, wave patterns, and sediment characteristics. This parameter adaptation enables the system to handle diverse beach environments effectively, improving measurement precision and adaptability while managing computational complexity through intelligent algorithms
Solution Approach 2:
The monitoring system dynamically adapts its operation based on real-time environmental conditions, adjusting flight paths, scanning parameters, and processing priorities according to wave activity, tide levels, and weather conditions. This dynamic behavior enhances adaptability to complex beach environments while maintaining reasonable system complexity through automated decision-making algorithms
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables high-precision beach topography data acquisition, real-time erosion prediction, and future trend simulation, providing scientific data support for effective beach management and protection measures.
Implementation Method 1
selecting an unmanned aerial vehicle equipped with a Livox LIDAR, where the LIDAR is able to measure the distance between the target and the unmanned aerial vehicle and the relative position of the target by emitting laser pulses and receiving their reflected signals
Data Source
AI summary
A beach erosion detection and quantitative calculation method based on unmanned aerial vehicle mapping is provided, including the following steps: S1, configuring unmanned aerial vehicles; S2, obtaining beach aerial image data in different periods by using the unmanned aerial vehicle; S3, delineating a plurality of sections on the beach, and extracting elevation data of the sections from the multi-period data by using the aerial images processed; S4, in order to unify the reference boundary of multi-period aerial photography data, a unified lowest water line is defined, and the upper boundary is the coastline; S5, automatically identifying and predicting factors affecting beach erosion; S6, performing real-time erosion prediction and future erosion trend simulation; S7, calculating the total amount of beach erosion, and comparing the sand amount in each grid to get the distribution characteristics of beach erosion change.