Soil Erosion Rate Monitoring Using UAV Reference Grids
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Solution Overview
Problem
Existing soil erosion monitoring methods in wind-water complex erosion regions face challenges in balancing workload and accuracy, with traditional methods being labor-intensive and susceptible to human error, while modern methods fail to comprehensively consider all factors influencing soil erosion.
Innovation Solution
A method involving grid division based on surface cover, random sampling for soil erodibility, using unmanned aerial vehicles for image data acquisition, and calculating soil erosion volumes using reference grids with erosion pins, corrected by soil erodibility, to improve accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional water measurement method or erosion pin method is used, then direct observation of erosion rate is achieved, but workload increases and human factors affect accuracy
Solution Approach 1:
The patent replaces traditional mechanical measurement methods (erosion pins, manual cross-sectional measurements) with an optical imaging system using drones and cameras. The system captures images of erosion pins and cross-sections, then uses image processing algorithms to automatically calculate erosion rates, eliminating manual measurement work while maintaining measurement accuracy.
Solution Approach 2:
The patent creates visual copies (images) of the erosion pins and cross-sectional profiles using drone photography. These image copies are then processed digitally to extract erosion measurements, replacing the need for direct physical measurement and reducing human intervention while preserving measurement precision.
2Measurement precision
If volumetric measurement method is used to calculate erosion volume by measuring cross-sectional profiles, then gully erosion volume is accurately reflected, but operation becomes complicated
Solution Approach 1:
The patent replaces complex manual cross-sectional measurement operations with automated image processing. Drone-captured images of cross-sections are processed using algorithms that automatically calculate erosion volumes, maintaining accuracy while eliminating the complicated manual measurement process.
Solution Approach 2:
The system enables self-service measurement by allowing the erosion features to be photographed in situ by the drone, with the image processing algorithm automatically extracting the volumetric information without requiring manual surveying equipment or complex field operations.
3Area of stationary object
If hydrological measurement method is used to indirectly reflect soil erosion by measuring sediment accumulation, then watershed scale monitoring is achieved, but comprehensive consideration of all erosion factors is lost
Solution Approach 1:
The patent merges the advantages of direct measurement methods with watershed-scale monitoring by deploying the drone imaging system across multiple locations within the watershed. This allows direct observation of erosion pins and cross-sections at various scales simultaneously, capturing both local erosion details and overall watershed patterns, thereby maintaining factor analysis completeness while expanding coverage area.
Data Source
AI summary
Disclosed is a method for monitoring soil erosion rate in a wind-water complex erosion region, which includes dividing a soil erosion monitoring area into a bare area and a vegetated area, performing grid division, and obtaining soil erodibility of each grid in the bare area and the vegetated area; obtaining a bare area reference grid and a vegetated area reference grid; obtaining image data of both the bare area and the vegetated area at monitoring starting and ending moments; calculating soil erosion volumes of both the bare area reference grid and the vegetated area reference grid; calculating a soil erosion volume corrected by soil erodibility; and calculating the soil erosion rate according to the soil erosion volume corrected by soil erodibility, and completing the monitoring of the soil erosion rate. The problem that the workload and monitoring accuracy of the existing monitoring methods cannot be balanced is solved.