Estimating leaf area index (LAI) of Vitis vinifera using indirect methods involves some critical issues, related to its discontinuous and non-homogeneous canopy. This study evaluates the smart app PocketLAI and hemispherical photography in vineyards against destructive LAI measurements. Data were collected during six surveys in an experimental site characterized by a high level of heterogeneity among plants, allowing us to explore a wide range of LAI values. During the last survey, the possibility to combine remote sensing data and in-situ PocketLAI estimates (smart scouting) was evaluated. Results showed a good agreement between PocketLAI data and direct measurements, especially for LAI ranging from 0.13 to 1.41 (R² = 0.94, RRMSE = 17.27%), whereas the accuracy decreased when an outlying value (vineyard LAI = 2.84) was included (R² = 0.77, RRMSE = 43.00%), due to the saturation effect in case of very dense canopies arising from lack of green pruning. The hemispherical photography showed very high values of R², even in presence of the outlying value (R² = 0.94), although it showed a marked and quite constant overestimation error (RRMSE = 99.46%), suggesting the need to introduce a correction factor specific for vineyards. During the smart scouting, PocketLAI showed its reliability to monitor the spatial-temporal variability of vine vigor in cordon-trained systems, and showed a potential for a wide range of applications, also in combination with remote sensing.
Estimating Leaf Area Index (LAI) in Vineyards Using the PocketLAI Smart-App / F. Orlando, E. Movedi, D. Coduto, S.G. Parisi, L. Brancadoro, V. Pagani, T. Guarneri, R. Confalonieri. - In: SENSORS. - ISSN 1424-8220. - 16:12(2016 Dec), pp. 2004.1-2004.12. [10.3390/s16122004]
Estimating Leaf Area Index (LAI) in Vineyards Using the PocketLAI Smart-App
F. Orlando
;E. MovediSecondo
;S.G. Parisi;L. Brancadoro;V. Pagani;T. GuarneriPenultimo
;R. ConfalonieriUltimo
2016
Abstract
Estimating leaf area index (LAI) of Vitis vinifera using indirect methods involves some critical issues, related to its discontinuous and non-homogeneous canopy. This study evaluates the smart app PocketLAI and hemispherical photography in vineyards against destructive LAI measurements. Data were collected during six surveys in an experimental site characterized by a high level of heterogeneity among plants, allowing us to explore a wide range of LAI values. During the last survey, the possibility to combine remote sensing data and in-situ PocketLAI estimates (smart scouting) was evaluated. Results showed a good agreement between PocketLAI data and direct measurements, especially for LAI ranging from 0.13 to 1.41 (R² = 0.94, RRMSE = 17.27%), whereas the accuracy decreased when an outlying value (vineyard LAI = 2.84) was included (R² = 0.77, RRMSE = 43.00%), due to the saturation effect in case of very dense canopies arising from lack of green pruning. The hemispherical photography showed very high values of R², even in presence of the outlying value (R² = 0.94), although it showed a marked and quite constant overestimation error (RRMSE = 99.46%), suggesting the need to introduce a correction factor specific for vineyards. During the smart scouting, PocketLAI showed its reliability to monitor the spatial-temporal variability of vine vigor in cordon-trained systems, and showed a potential for a wide range of applications, also in combination with remote sensing.Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.