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Rapid Forest Triage by Rapid Forest Triage by

Rapid Forest Triage by - PowerPoint Presentation

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Rapid Forest Triage by - PPT Presentation

Subcanopy MAV Suk Yung Lee Adam Wolf Kelly Caylor Roland Brockers October 3 2014 Overview Project objective Fly a quadcopter through a forest and survey trees autonomously Rationale ID: 568315

canopy fig neighborhood height fig canopy height neighborhood tree error http nearest sensor biomass survey area environmental board mav

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Slide1

Rapid Forest Triage by Sub-canopy MAV

Suk Yung

Lee

Adam Wolf, Kelly

Caylor

, Roland

Brockers

October 3, 2014Slide2

Overview

Project objective: Fly a quadcopter through a forest and survey trees autonomously

Rationale: Microclimate and local competition Determine biomass and carbon sink potentialCost and time effective methodBranch applications (surveillance, etc) Combines fields such as computer vision, controls, and data processing*

Fig 1 – Concept of a forest survey conducted by an MAVSlide3

Manual Surveying

Formulate a ground truth with a manual survey

Rectangular survey grid

Diameter at breast heightTree locationsTree heights Canopy radius and area MetadataNumber of treesGrid size

Survey date & locationGPS coordinates of four grid corners (w/ error margins

Fig 2 – Measuring of tree location, diameter, and height

x

2

a

1

a

2

y

1

y

2

x

1

DBH

Origin

β

h

y

b

1

oSlide4

GPS Error

Polaris Navigation, GPS Status Android apps

Averaged an error margin of ±3.048 meters, but varied Navcom Technology – satpredictorNumber of satellites availableDilution of precision Target specific times of day for best accuracy and precision

Fig 3 – Satellite Availability and DOP (

Navcom

)

Fig 4 – Geometric ErrorSlide5

Ecology Maps

Neighborhood Basal Area Density

Nearest Tree DBH of Nearest Tree Neighborhood Height Standard Deviation of Neighborhood Height Average Distance within Neighborhood

Fig 5 – Nearest Tree Map (m)Slide6

Biomass

Chave

et al 2005

F = 0.06, broadleaf

= 0.59,

Quercus

agrifolia

19,895.54 kg 

Lower

limit

Cone geometry

11,053.08 kg

Upper limit

Cylinder geometry

33,159.23 kgSlide7

Environmental Sensor board

Sensor board, operating in ROS using the asctec_mav_framework

Time stamp Relative humidity IR thermometer Thermistor Short-wave radiation Normalized difference vegetation index1

Fig 5 – Environmental Sensor Board ReadingsSlide8

Website

DemonstrationSlide9

Future Considerations

Above canopy survey

Autonomous height and canopy measurements

More effective biomass estimate2 Leaf area indexDensity of plant canopiesPrimary photosynthetic productionEvapotranspirationImage processing upward-facing hemispherical photos

Fig 7 – Upward facing hemispherical shot of canopySlide10

Acknowledgments

Adam

Wolf

Kelly Caylor Roland Brockers Jet Propulsion Laboratory Princeton Environmental InstituteSlide11

Citations

References

1 - http

://en.wikipedia.org/wiki/Normalized_Difference_Vegetation_Index2 - Chave et al. 2005ImagesFig 1 - http://www-robotics.jpl.nasa.gov/Fig 2 - http://oregonstate.edu/Fig 4 – Richard Langley, http://www.iastate.edu/Fig 7 - Stuart B Weiss