Digital Hemispherical Photography (DHP) is a favoured technique to measure Plant Area Index (PAI) in forests. However, continuous measurements are time and labour-intense. Automatic, low-cost sensors can take potentially over this job.
In recent years, mini-computers like the Raspberry Pi or the Arduino have been designed to fulfil every day, routine tasks such as regulating heating, or to serve as weather stations or private servers. The low-cost, easy-access programming interfaces and strong DIY community have supported this development.
On other hand, measurement of biophysical variables like PAI in forests is still dominated by manual techniques and often expensive sensors. This has hindered the establishment of measurement networks that deliver quality information on a routine basis, as for examples meteorological sensor networks do.
This thesis will deal with the improvement of a previously built prototype sensor with a near-infrared camera and improve the endurance of the sensors system for multi-day measurement campaigns.
- Review literature on PAI measurement principles
- Enhance a prototype sensor-system with new camera
- Adapt measurement protocol and scripts
- Take measurements and compare results with other sensors
- Weiss, M., Baret, F., Smith, G. J., Jonckheere, I., & Coppin, P. (2004). Review of methods for in situ leaf area index (LAI) determination Part II. Estimation of LAI, errors and sampling. Agricultural and Forest Meteorology, 121(1–2), 37–53.
- Electronics & Gadgets enthusiast
- Wiliness for learning new tools and enjoying beautiful forests
Theme(s): Sensing & measuring