uas applications in forestry
TRANSCRIPT
UAS Applications in Forestry
Unmanned Aerial Systems
Abstract
Historical Role of Photogrammetry in Forestry
Different components of the industry that benefits from aerial imagery
Even aged management (tree farms) does not mean every stand is the same age
Uneven aged management decisions are based on structure and composition
Aerial Imagery was flown at intervals (years)
Introduction U.S. covers approximately 2,200 million
acres 23% can be classified as Commercial Timberlands 11% of those timberlands are private Paradigm shift in ownership and strategy of
companies The REIT (publicly traded) tax incentives!▪ Real Estate Investment Trust
The TIMO (diversified portfolios)▪ Timber Management Organization
Greater mosaic of ownership
UAS in Forestry
Smaller continuity in ownership Needs for REIT’s and TIMO’s to know
ages and stages of land tracts for future investments
Flying smaller tracts of land increases expense for imagery
Creates a great niche for UAS in forestry
UAV•Less than 5 pounds•Capable of carrying a camera or sensor•Powered by electric or gas motor•Easily deployed•Provides local high resolution imagery•Qualitative and Quantitative results
Economics
Specific Outputs Permanent record of forest state in time Land use history Baseline for analysis 3D Modeling Triangulation of features
Scale
Scale is a function of altitude and focal length
Greater scale = less detail but more area captured in image
We need smaller scale greater detail
Typical Scale in Forestry 1:12,000 – 1:24,000 1000 – 1320 feet to
the inch
Focal Length
•RF = f / H•RF = Scale (desired)•F = Focal Length of Camera•H = Height AGL
•Standard Focal Lengths in Forestry:
•15 cm (6 inches)•21 cm (8.25 inches)•30 cm (12 inches)
Cost Estimate
Seasonal Considerations
Time of year Time of day (shadows) Low light Poor Weather Wind Affect on vegetation Panchromatic film vs. Electromagnetic
Radiation IR, Thermal IR, Combination Digital Imagery
LiDAR
Light Detection and Ranging Like SONAR but in the air Emits IR pulse Measures reflectance Location of the scanner must be
known Data returned as XYZ coordinates
(3D) Measures: Height, density, inventory,
hydrology, engineering (roads)
LiDAR
Proposed UAV Methodology Low Cost Application High Resolution Imagery Easy Deployment Increased Efficiency in Multi Aspects Fixed Wing vs. Rotor Wing
Forest Applications Planning
Delineation ID Tree Height Density Layout Right of Way
Harvesting Track Progress Timber Sale Administration Prescription Follow thru Monitor Crews
Post Harvest QA/QC SMZ ‘s Regulations Tree Retention Road Decommission Long Term Monitoring Silviculture
Cost
Micro UAV class (under 5 lbs) Turn-key Off the shelve systems Customer Support Integration Known companies
Cost Comparison
Cost Comparison
Timeliness
•Learning Curve•Factory Training Time•Flight Time for given Area•Processing
Mission Planning Requirements Spatial Accuracy
Minimum 30 cm but 15 cm is better (confidence 95%) Output Formats
Orthophoto, DEM, DTM, Georeferenced images Safety
Documentation, Pre-Flight, Sense and Avoid Timeframe
ASAP!!! Platform
Trimble UX5 Sensor
Included 16.2 mega pixel camera. LiDAR option would be nice Personnel
Forester / Analyst Regulatory Concerns
COA / SAC prospects
Mission Plan 300-900 feet AGL (best resolution) Minimum 30% side-lap and 60% end-lap (ensure
accurate 3d modeling) Autonomous flight with preloaded waypoints for flight
plan (beginning and end of each path) Mid afternoon flight (high sun, low shade) Stable atmospheric conditions (less roll / yaw of aircraft) Adequate speed for platform and camera (15-20 mph) Ability to fly low light and inclement weather if need be UAS provides image processing software Adequate workstation (PC) for processing Safe environment (deployment, launch, flight, landing,
post flight sequences
Budget
Analysis Strengths
Cost vs. traditional methods Integration Outputs Ownership Development
Weaknesses Regulations Start Up Cost Risk Logistics
Opportunities Growth Up and Coming Technology Learn From Other Multi Industry
Threats History Perception Vulnerability Social View
Conclusion
Edge of Mainstream in U.S. Highly Applicable in Forestry Very Few Cons Medium For Integration Exceeds Current Industry Standards Sensor Flexibility Data Integrity Wide Range of Options