Making sense of methane fluxes with MATLAB Gavin McNicol EPS 209 Data source – Jaclyn Hatala & Dennis Baldocchi.

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Presentation transcript:

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

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 points Can 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 18 th – 25 th January 2010

Next steps 1 – 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?