Mapping <i>Vitis vinifera</i> L. Leaf Area Index Using Side‐View Imagery Continuously Captured by a Smartphone

Background and Aims Leaf area index (LAI) is an important parameter to support vineyard management decisions. However, the common indirect methods for LAI measurement using imagery pose significant challenges, including over‐estimation, impracticality in block‐level LAI mapping, and interaction with non target foliage. Methods and Results This study proposes a method to map the LAI based on side‐view imagery collected continuously by mounting a smartphone on a farm vehicle. The proposed method first estimated the absolute leaf area (LA) for the trunk‐to‐trunk area of each vine based on the Beer–Lambert law and then calculated the LAI by dividing this by the ground surface area. The LAI estimation from the side view was evaluated against the LAI from the traditional bottom–up view imagery and the direct destructive LAI measurements. Data were collected at four different dates during the season from a vineyard in Australia. Results showed a near 1‐to‐1 relationship between the proposed LAI method and the direct LAI measurements with a mean absolute error (MAE) of 0.2, whereas the traditional bottom–up view imagery showed an overestimation error with a MAE of 0.4, suggesting a need to introduce a calibration procedure specific for the vineyard. The R 2 value of the proposed LAI method and LAI from a destructive assessment ranged from 0.75 to 0.94. Conclusions The proposed LAI method demonstrates the capability to robustly and continuously map the vine‐level LAI for the whole block easily and efficiently. Significance of the Study This method offers an easy and inexpensive option for vineyard managers to use maps of LAI to support informed decision making.