UAV Forest Survey Routing for Cloud-Aware Point Cloud Resolution
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Solution Overview
Problem
Aerial surveys of forests face challenges due to cloud cover, which leads to gaps in information, increased costs, and reduced resolution, as current methods require rescheduling and higher altitudes, compromising data quality and efficiency.
Innovation Solution
An unmanned aerial vehicle system equipped with an electromagnetic energy sensor and a survey controller that dynamically adjusts routes to fly over areas with minimal cloud cover, generating a point cloud with desired resolution by identifying gaps in cloud cover using multiple sources like satellites and ground-based imagers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the aerial vehicle flies at higher altitudes to survey large areas, then the coverage area increases and cost per acre decreases, but the point cloud density and resolution decrease
Solution Approach 1:
The system dynamically adjusts the flight altitude of the aerial vehicle based on real-time cloud cover conditions. When cloud cover is detected in a region, the system lowers the flight altitude to compensate for signal attenuation and maintain point cloud density, while allowing higher altitudes in cloud-free regions to maximize coverage area.
Solution Approach 2:
The system applies different flight altitudes to different spatial regions based on local cloud cover conditions. Regions with heavy cloud cover receive lower altitude flights for higher resolution data, while cloud-free regions are surveyed at higher altitudes for broader coverage, optimizing the trade-off between coverage area and point cloud density locally.
2Productivity
If the aerial vehicle flies through cloud cover to maintain survey continuity, then productivity increases, but measurement precision deteriorates due to laser reflection and refraction
Solution Approach 1:
The system uses cloud cover detection data from satellites and ground-based imagers as an intermediary information source to predict and avoid regions where laser measurements would be degraded by cloud interference, allowing the aerial vehicle to plan routes that maintain productivity while avoiding precision-loss zones.
Solution Approach 2:
The system performs preliminary cloud cover assessment using satellite and ground-based imaging before the aerial survey begins, identifying regions that will have cloud interference and adjusting the flight plan in advance to avoid those areas or allocate additional survey passes to ensure complete coverage when conditions improve.
3Measurement precision
If cloud cover is avoided by rescheduling surveys, then measurement precision is maintained, but loss of time and productivity increase
Solution Approach 1:
The system implements continuous feedback loops that monitor cloud cover conditions in real-time during the survey operation, using this information to dynamically adjust the flight plan, reroute around developing cloud formations, and optimize survey timing to maintain both precision and productivity without requiring complete rescheduling.
4Measurement precision
If the aerial vehicle flies below cloud cover to maintain resolution, then point cloud density is preserved, but the field of view is reduced and survey efficiency decreases
Solution Approach 1:
The system applies different flight altitudes to different spatial regions based on local cloud cover conditions. Regions with heavy cloud cover receive lower altitude flights for higher resolution data, while cloud-free regions are surveyed at higher altitudes for broader coverage, optimizing the trade-off between coverage area and point cloud density locally.
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 enhances data quality and efficiency by increasing the coverage area of forest surveys, reducing costs, and allowing more frequent data collection while maintaining high resolution, even under cloudy conditions.
Implementation Method 1
The light detection and ranging system measures the distance to points in the forest by measuring the time light takes to return to the light detection and ranging system
Implementation Method 2
measuring the time light takes to return to the light detection and ranging system
Implementation Method 3
The electromagnetic energy sensor system is configured to generate information about a forest
Data Source
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AI summary
A method and apparatus for generating information about a forest (204). A number of locations (236) in the forest (204) are identified over which an electromagnetic energy sensor system (311) in an unmanned aerial vehicle (230) generates the information about the forest (204) by generating a point cloud (234) with a resolution (239) that meets a point cloud threshold (243). A route (232) is generated for the unmanned aerial vehicle (230) to move to the number of locations (236) and generate the information about the forest (204) in the number of locations (236).