Making sense of methane fluxes with MATLAB
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Making sense of methane fluxes with MATLAB Gavin McNicol EPS 209 Data source – Jaclyn Hatala & Dennis Baldocchi
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Making sense of methane fluxes with MATLAB. Gavin McNicol EPS 209 Data source – Jaclyn Hatala & Dennis Baldocchi. Field Site & Method. Sherman Island, Sacramento- SJ Bay Delta Collaboration with Baldocchi lab Eddy covariance flux measurements CH 4 CO 2 H 2 O. - PowerPoint PPT Presentation
Transcript of Making sense of methane fluxes with MATLAB
Making sense of methane fluxes with MATLAB
Gavin McNicolEPS 209
Data source – Jaclyn Hatala & Dennis Baldocchi
Field Site & Method
Sherman Island,Sacramento- SJ Bay Delta
Collaboration with Baldocchi lab
Eddy covariance flux measurements CH4 CO2 H2O
Diurnal methane fluxes
Source: Jaclyn Hatala & Dennis Baldocchi
Cow Cam!
Source: Detto et al. (2010)
MATLAB Image Processing
Basic Goals:Find cows in image (color, texture, intensity)Produce vector of ‘cow’ and ‘no cow’ time pointsCan we do more than just presence/absence?
Results so far
• Individual images: can we see the cows?Range Filter
Results
• Individual images: can we see the cows?Mahalanobis distance
Results Range filter method on test images: 59% accuracy (type I error)
Threshold
Results
Unexpected result 18th – 25th January 2010
Next steps1 – Combine mahalanobis distance information with edge
detector
2 – Better to over-predict.
3 – Group photos by day as cows are never there all day and look at deviation from mean intensity.
Questions?
