flying low and slow: high resolution imagery for...
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Flying Low and Slow: High Resolution Imagery for
Agricultural Field ResearchEileen Perry, Glenn Fitzgerald, Ian Goodwin, James
Nuttall, Mark O’ Connell
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BackgroundWhy not satellite imagery?
• Resolution, timing, clouds
Why so many pixels?• Separating the canopy from
background soil and vegetation
What’s different about research trials?• Targets vs. continuous coverage• Accuracy (‘quantitative’ remote
sensing)
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Some Trials Using UAS
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AgFACE, ‘Laboratory Without Walls’
530ppm400ppm
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Early Frost Detection
Spectrometer results
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Profitable Pears: Managing Canopy NCanopy Chlorophyll Concentration Index (CCCI)Works for cereals, why not pears?
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Profitable Pears: Managing Canopy N• Target the plots, not the orchard• Don’t depend solely on technology (such as GPS)• Calibration accuracy is key
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Profitable Pears: Managing Canopy N
R2= 0.67RMSE %N = 0.24
NDVI M3CI
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Challenges for Quantitative Remote Sensing
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Challenges for Quantitative RS
Reflectance calibration, what’s good enough?• Multi-band, multi-path• Thermal instability
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Estimating Uncertainty using Error Propagation
• Estimated uncertainty based on simple error propagation
• Reduce NDRE/NDVI toM3CI = (RNIR+Rred-RRE)/(RNIR-Rred+RRE)
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Erro
r in
%N
Erro
r in
Inde
x Va
lue
Error in Reflectance(0-1)
δIndex (M3CI 0.46)δIndex (M3CI 0.77)δ %N (M3CI 0.46)δ %N (M3CI 0.77)
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Challenges for Quantitative RS
• Reflectance calibration, what’s good enough?Multi-band, multi-path• Thermal instability
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MicaSense Red-edge Tetracam MicroMCA
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Challenges for Quantitative RS
• Reflectance calibration, what’s good enough?• Multi-band, multi-pathThermal instability
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5 °C
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Challenges for Quantitative RS
• Reflectance calibration, what’s good enough?• Multi-band, multi-pathThermal instability
• FLIR stated accuracy ± 2.0 °C; precision 0.032 °C• With warm-up ≥ 3 minutes, uncertainty of 43DNs (16 bit),
~0.6°C
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"Genius is one per cent inspiration, ninety-nine per cent perspiration" (Thomas Alva Edison)
If you don’t succeed, fly, fly again…
Ag Research