Smart fLAIr: A smartphone application for fast LAI retrieval using Ambient Light Sensors

Abstract

The efficiency of precision agriculture fundamentally depends on the exploration of bio-physical and bio-chemical plant parameters and the assessment of current crop conditions. The leaf area index (LAI) represents one of the most important crop parameters and is defined as the ratio of foliage area to ground area. It is widely-used in agriculture and agronomy as it indicates yield-limiting processes. In this paper, we present Smart fLAIr (fast LAI retrieval), a novel smartphone application for a low-cost in-situ LAI estimation. This estimation is based on the gap fraction analysis, a widespread indirect and non-destructive methodology. For that purpose, Smart fLAIr leverages the smartphone's internal Ambient Light Sensor (ALS). However, in order to improve the gap fraction accuracy, we enhance the ALS by a diffuser cap combined with an optical band-pass filter. Our prototype is implemented on the Android platform with a focus on usability aspects and its practicability. Conducting a comparative analyses with a commercial instrument, we successfully evaluated this prototype for maize canopies. The convincing performance of our approach in terms of accuracy and stability highlights the potential of Smart fLAIr as a valuable alternative for in-situ LAI assessment. © 2016 IEEE.