Leaf area index (LAI) is used to measure the amount of foliage that is present in a forest canopy. This type of information is important to many scientists’ models, particularly involving carbon cycles.
If you could measure LAI with a high level of precision, repeated measurements could be used to measure the health of forests/trees. This type of data would be useful for farmers as well as scientists.
Unfortunately, present tools to measure LAI are either very expensive or lack the precision to monitor tree health.
Over the last 4 years, I have been working on a Mac app that analyses photos taken below the tree canopy, pointing towards the sky and calculates LAI – photography based LAI.
It utilises several novel techniques that cope with the highly variable nature of actual photos:
- different lighting conditions – leaves can be dark or bright depending whether they are in sun or shadow
- clouds
- variable leaf colour – leaves may be green, red, blue or appear dark
- proportion of leaf to sky may be very variable
- hemispherical or plain photos
It accurately determines:
- foliage from sky
- canopy from non-canopy
All wrapped up in an interface that:
- Is easy to use
- allows batch processing with manual adjustments
- quick
- completely transparently shows its results
I look forward to sharing more about this app in 2019. With time, I’ll use this website to provide a lot more information about LAI and the app.
KerbCoding 