LIDAR Elevation Determination Using Structural Modeling
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Solution Overview
Problem
Traditional methods for determining elevation, particularly for structures, are costly, time-consuming, and lack sufficient accuracy, making them inefficient for generating Flood Elevation Certificates.
Innovation Solution
The use of remote elevation data and measurements, such as LIDAR, combined with computer-assisted on-site inspections, to generate Flood Elevation Certificates quickly, accurately, and at a lower cost than traditional methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional means are used for determining elevation, then elevation data can be obtained, but the process is costly and time-consuming
Solution Approach 1:
The system performs preliminary actions by collecting and processing LIDAR data, satellite imagery, and topographic maps in advance to create a pre-computed elevation model. This allows the elevation determination to be quickly retrieved and applied when needed, eliminating the time-consuming field survey process while maintaining accuracy
Solution Approach 2:
The patent replaces traditional mechanical field surveying methods with automated computational systems that use LIDAR data, satellite imagery, and digital topographic models. This substitution eliminates manual measurement processes, significantly reducing time consumption while maintaining or improving measurement precision through automated image processing and coordinate transformation algorithms
2Measurement precision
If traditional means are used for determining elevation, then elevation data can be obtained, but the cost is high
Solution Approach 1:
The system uses universal data sources such as LIDAR datasets, satellite imagery, and topographic maps that serve multiple purposes. These same data sources can determine elevation for numerous properties simultaneously, distributing the cost across many applications and making each individual elevation determination more cost-effective while maintaining high precision through sophisticated processing algorithms
Solution Approach 2:
The patent creates digital copies of elevation data from LIDAR point clouds and satellite imagery, allowing unlimited replication and distribution of the elevation information. Once the elevation model is computed from the original data sources, it can be copied and applied to multiple properties without additional field work, significantly reducing per-unit cost while preserving measurement precision through consistent digital processing
3Productivity
If automated systems are used, then productivity increases, but measurement precision may be compromised
Solution Approach 1:
The system incorporates feedback mechanisms where the automated processing results are validated against known control points, historical survey data, and quality thresholds. This feedback loop ensures that automated calculations maintain measurement precision by detecting and correcting deviations, allowing high-speed processing without sacrificing accuracy
Solution Approach 2:
The patent combines multiple data sources including LIDAR point clouds, satellite imagery, digital topographic maps, and ground control point data into a composite elevation model. This composite approach leverages the strengths of each data source and uses integrated processing algorithms to maintain high measurement precision while achieving rapid automated determination across multiple properties
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
This approach allows for the production of Flood Elevation Certificates that meet FEMA accuracy standards, reducing costs and time while improving accuracy, thereby facilitating more efficient flood insurance assessments.
Implementation Method 1
The use of remote elevation data and measurements, such as LIDAR
Data Source
AI summary
Systems and methods for determining elevation based on structural modeling and light detection and ranging (LIDAR) data are disclosure. LIDAR bare earth data corresponding to an area within a parcel boundary is obtained as preliminary elevation data. A basis of structure boundary is determined for a structure within the parcel boundary based on an absence of the LIDAR bare earth data within a region in the area. Three-dimensional models are generated based on photographic data, to represent portions of the structure that affect LIDAR signals. A structure boundary for the structure is determined based on the basis of structure boundary in combination with supplemental elevation data generated using the three-dimensional models. Adjacent grade values are determined based on a portion of the preliminary elevation data and supplemental elevation data corresponding to an area between the structure boundary and a buffer boundary.