Landslide Volume Estimation Using PCA and Voxel Integration
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Solution Overview
Problem
Existing landslide monitoring methods, including geodetic, photogrammetry, and laser radar technologies, struggle to accurately calculate landslide volume due to low point density, low efficiency, or insufficient precision, particularly in complex terrain and weather conditions.
Innovation Solution
A method combining principal component analysis and voxel integration, involving bi-temporal laser scanning, grid formation, and double integration to calculate volume variations within voxels, correcting abnormal grids for accurate landslide volume estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional geodetic measurement method is used, then measurement precision is improved, but productivity is worsened
Solution Approach 1:
The patent segments the continuous landslide surface into discrete voxel units (grid cells) for individual volume calculation. Each voxel is processed independently through point cloud filtering, plane fitting, and volume integration, enabling parallel computation and significantly improving productivity while maintaining precision through systematic processing of each segment
Solution Approach 2:
The patent replaces traditional mechanical surveying instruments (levels, total stations) with laser radar technology that uses electromagnetic waves (laser beams) to acquire three-dimensional point cloud data. This substitution enables rapid, non-contact, automated data acquisition across the entire landslide surface, dramatically improving productivity while maintaining high measurement precision
2Productivity
If photogrammetry technology is used, then productivity is improved, but measurement precision is worsened
Solution Approach 1:
The patent replaces photogrammetry's optical imaging system with laser radar's direct distance measurement system. The laser radar emits laser beams and measures the time of flight for return signals, directly obtaining precise three-dimensional coordinates without requiring complex image processing and stereo triangulation, thereby improving measurement precision while maintaining high productivity
Solution Approach 2:
The patent changes the fundamental measurement parameter from two-dimensional image coordinates (photogrammetry) to three-dimensional spatial coordinates with direct distance measurement (laser radar). This parameter change enables precise vertical elevation measurement and accurate volume calculation, resolving the precision limitation of photogrammetry while maintaining its high productivity advantage
3Device complexity
If average elevation method is used, then device complexity is reduced, but measurement precision is worsened
Solution Approach 1:
The patent segments the landslide volume calculation into multiple voxel units, each processed with rigorous point cloud filtering and plane fitting. This segmentation allows precise local volume calculation for each voxel and summation to obtain total volume, achieving high measurement precision without requiring overly complex equipment
Solution Approach 2:
The patent replaces the simple but inaccurate average elevation calculation with a more sophisticated voxel-based double integration method using point cloud data. This substitution uses computational mathematics (principal component analysis, plane fitting, integral calculation) instead of simple averaging, achieving high precision while keeping the physical measurement system relatively simple through laser radar
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
Ensures efficient and accurate landslide volume calculation by eliminating unreliable results from average elevation, enhancing precision and applicability through statistical analysis and grid correction.
Implementation Method 1
a laser scanning system emits a laser beam to a target, and then compares the received signal with a transmitted signal to obtain geometric parameters such as a distance, an orientation, and a height of the target
Data Source
AI summary
A landslide volume calculation method fusing principal component analysis and voxel integration, comprising the steps of: collecting and registering bi-temporal point cloud data; establishing grids in a landslide area; calculating a normal vector of a point in each grid and a fitting planar function by using a principal component analysis method; calculating a volume variation of each grid by means of planar function integration; and calculating volume variations of all the grids, identifying an abnormal value by means of statistical analysis, and correcting the abnormal value. In the present disclosure, a landslide volume is efficiently and accurately calculated by using laser radar ranging technology and an acquired point cloud, constructing voxel units, fusing same with a principal component analysis method, and using voxel-based double integration to calculate volume variations inside voxels, thereby solving the problem of a volume result calculated by means of an average elevation being unreliable.