VitiCanopy

VitiCanopy (De Bei et al., 2016) uses the front in-built camera and GPS capabilities of the device to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculate relevant canopy architecture parameters.

Through gap fraction analysis VitiCanopy calculates the following parameters of canopy architecture:

• Leaf area index (LAI): total one-sided area of leaf tissue per unit ground area.

• Effective leaf area index (LAIe): LAI corrected by the clumping index.

• Canopy cover: percentage (fraction) of ground area covered by the vertical projection of the canopy. Canopy cover equals 1 when the whole image is covered by leaves, with no gaps.

• Canopy porosity: percentage of gaps within the image (spaces), which can be related to light penetration through the canopy.

• Clumping index: ratio of effective plant or leaf area index to the actual plant or leaf area index (Macfarlane et al., 2007). It equals 1 when foliage is randomly distributed in a canopy and it is less than one when foliage becomes more clustered in lumps. For grapevine this factor is close or equal to 1 (random dispersion), unless there are sections of the image with big gaps where no canopy is present.

The above mentioned parameters are calculated according to the algorithms described in Fuentes et al. (2008, 2014), which were calculated from Macfarlane et al. (2007):

the fractions of foliage projective cover (ff) = 1- tg/tp

crown cover (fc) = 1- lg/tp

crown porosity (Φ) = ff/ fc

Where lg = large gap pixel, tg = total pixels in all gaps, tp = total gap pixels.

LAI is calculated as:

LAI = -fc lnΦ/k

Where k is the light extinction coefficient.

*Please note that for grapevines k has been reported to vary between 0.65 and 0.75. The default k value for the App is set at 0.7 as reported for grapevines in Fuentes et al., (2014), De Bei et al., (2016). Specific k values per image can be obtained by measuring the Photosynthetic Active Radiation (PAR) at the top of the canopy (Io) and from where the image is taken (I) for more accuracy. In this case k = 1 − I/Io (Poblete et al., 2015). LAI for crops other than grapevine can be measured using the App by choosing the appropriate k value.

The App also calculates the clumping index:

Ω(0) = (1- Φ) ln(1-ff)/ln(Φ)ff

The clumping index is a correction factor to obtain effective LAI (LAIe) as the product:

LAIe = LAI x Ω(0)

References

De Bei R.; Fuentes S.; Gilliham M.; Tyerman S.; Edwards E.; Bianchini N.; Smith J.; Collins C. 2016. VitiCanopy: a free computer App to estimate canopy vigor and porosity for grapevine. Sensors 2016, 16, 585.

Fuentes S., Poblete-Echeverria C., Ortega-Farias S., Tyerman S.D., De Bei R. 2014. Automated estimation of leaf area index (LAI) from grapevine canopies using cover photography, video and computational analysis methods. Australian Journal of Grape and Wine Research, 20 (3): 465-473

Fuentes S., Palmer A.R., Taylor D., Zeppel M., Whitley R., Eamus D. 2008. An automated procedure for estimating the leaf area index (LAI) of woodland ecosystems using digital imagery, Matlab® programming and its application to an examination of the relationship between remotely sensed and field measurements of LAI. Functional Plant Biology, 35: 1070-1079

Macfarlane C., Arndt S.K., Livesley S.J., Edgar A.C., White D.A., Adams M.A., Eamus D. 2007. Estimation of leaf area index in eucalypt forest with vertical foliage, using cover and full frame fisheye photography. Forest Ecology and Management, 242(2-3): 756-763

Poblete-Echeverría C., Fuentes S., Ortega-Farias S., Gonzalez-Talice J., Yuri J.A. 2015. Digital cover photography for estimating leaf area index (LAI) in apple trees using a variable light extinction coefficient. Sensors, 15: 2860-2872