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

作者：Campos Taberner Manuel^*; Javier Garcia Haro Franciso; Confalonieri Roberto; Martinez Beatriz; Moreno Alvaro; Sanchez Ruiz Sergio; Amparo Gilabert Maria; Camacho Fernando; Boschetti Mirco; Busetto Lorenzo

来源：Remote Sensing, 2016, 8(3): 202.

DOI：10.3390/rs8030202

• PocketLAI
• effective plant area index (PAI(eff))
• smartphone
• rice
• high-resolution map

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 TF) made of several measuring dates and their associated satellite radiances.

• 出版日期2016-3