Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies in order to assess crop yield. Frequently, plant canopy analyzers (LAI-2000) and digital cameras for hemispherical photography (DHP) are used for indirect effective plant area index (PAI(eff)) estimates. Nevertheless, these instruments are expensive and have the disadvantages of low portability and maintenance. Recently, a smartphone app called PocketLAI was presented and tested for acquiring PAI(eff) measurements. It was used during an entire rice season for indirect PAI(eff) estimations and for deriving reference high-resolution PAI(eff) maps. Ground PAI(eff) values acquired with PocketLAI, LAI-2000, and DHP were well correlated (R-2 = 0.95, RMSE = 0.21 m(2)/m(2) for Licor-2000, and R-2 = 0.94, RMSE = 0.6 m(2)/m(2) for DHP). Complementary data such as phenology and leaf chlorophyll content were acquired to complement seasonal rice plant information provided by PAI(eff). High-resolution PAI(eff) maps, which can be used for the validation of remote sensing products, have been derived using a global transfer function (TF) made of several measuring dates and their associated satellite radiances.

Multitemporal Monitoring of Plant Area Index in the Valencia Rice District with PocketLAI

Boschetti Mirco;Busetto Lorenzo
2016

Abstract

Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies in order to assess crop yield. Frequently, plant canopy analyzers (LAI-2000) and digital cameras for hemispherical photography (DHP) are used for indirect effective plant area index (PAI(eff)) estimates. Nevertheless, these instruments are expensive and have the disadvantages of low portability and maintenance. Recently, a smartphone app called PocketLAI was presented and tested for acquiring PAI(eff) measurements. It was used during an entire rice season for indirect PAI(eff) estimations and for deriving reference high-resolution PAI(eff) maps. Ground PAI(eff) values acquired with PocketLAI, LAI-2000, and DHP were well correlated (R-2 = 0.95, RMSE = 0.21 m(2)/m(2) for Licor-2000, and R-2 = 0.94, RMSE = 0.6 m(2)/m(2) for DHP). Complementary data such as phenology and leaf chlorophyll content were acquired to complement seasonal rice plant information provided by PAI(eff). High-resolution PAI(eff) maps, which can be used for the validation of remote sensing products, have been derived using a global transfer function (TF) made of several measuring dates and their associated satellite radiances.
2016
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
PocketLAI
effective plant area index (PAI(eff))
smartphone
rice
high-resolution map
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/328820
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