The PocketLAI smartphone app: an alternative method for leaf area index estimation

Session A4: Smart and Mobile Devices Used for Environmental Applications

The possibility of adopting the technology implemented in low-costs devices for the monitoring of biophysical processes is being increasingly explored by the scientific community. In the context of environmental studies, leaf area index (LAI) is one of the variables scientists and technicians are more interested in, since directly involved in radiation interception, and in crop response to water availability. An indirect method for leaf area index estimation was recently proposed and implemented in the smartphone app PocketLAI. The application uses the smartphone camera and the accelerometer to acquire images at 57.5° below the canopy while the user is rotating the device along its main axes. Images are automatically processed using a dedicated segmentation algorithm to derive the gap fraction. The PocketLAI was successfully evaluated for paddy rice canopies against data obtained with direct (planimetric) measurements, and results were compared with those provided by a number of commercial instruments. In a following study, PocketLAI was compared with AccuPAR ceptometer for canopies markedly deviating from the ideal assumption behind the simplified model for light transmittance into the canopy implemented in the app (i.e., random distribution of infinitely small leaves). Although a saturation effect was observed for dense canopies with big leaves (maize and giant reed) and a large number of measuring replicates was needed for markedly heterogeneous canopies (natural grassland), the overall positive results support the use of PocketLAI in context characterized by low portability or by limited economic resources. A step forward is here discussed by testing the performances of the app when installed on devices from different price categories and manufacturers, aiming at implementing automatic calibration facilities for entry-level smartphones.