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