Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient

Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or d...

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Main Authors: Carlos Poblete-Echeverría, Sigfredo Fuentes, Samuel Ortega-Farias, Jaime Gonzalez-Talice, Jose Antonio Yuri
Format: Article
Language:English
Published: MDPI AG 2015-01-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/15/2/2860
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author Carlos Poblete-Echeverría
Sigfredo Fuentes
Samuel Ortega-Farias
Jaime Gonzalez-Talice
Jose Antonio Yuri
author_facet Carlos Poblete-Echeverría
Sigfredo Fuentes
Samuel Ortega-Farias
Jaime Gonzalez-Talice
Jose Antonio Yuri
author_sort Carlos Poblete-Echeverría
collection DOAJ
description Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAID), which was compared with LAI estimated by the proposed digital photography method (LAIM). Results showed that the LAIM was able to estimate LAID with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (ff) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.
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spelling doaj.art-161ef7bdfe48428885bd657a6884a9c42022-12-22T04:22:20ZengMDPI AGSensors1424-82202015-01-011522860287210.3390/s150202860s150202860Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction CoefficientCarlos Poblete-Echeverría0Sigfredo Fuentes1Samuel Ortega-Farias2Jaime Gonzalez-Talice3Jose Antonio Yuri4Research and Extension Center for Irrigation and Agroclimatology (CITRA), Universidad de Talca, Talca 3460000, ChileFaculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, VIC 3010, AustraliaResearch and Extension Center for Irrigation and Agroclimatology (CITRA), Universidad de Talca, Talca 3460000, ChileCentro de Pomaceas, Universidad de Talca, Talca 3460000, ChileCentro de Pomaceas, Universidad de Talca, Talca 3460000, ChileLeaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAID), which was compared with LAI estimated by the proposed digital photography method (LAIM). Results showed that the LAIM was able to estimate LAID with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (ff) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.http://www.mdpi.com/1424-8220/15/2/2860light intercepted by the canopygap fractionclumping indexremote sensing
spellingShingle Carlos Poblete-Echeverría
Sigfredo Fuentes
Samuel Ortega-Farias
Jaime Gonzalez-Talice
Jose Antonio Yuri
Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient
Sensors
light intercepted by the canopy
gap fraction
clumping index
remote sensing
title Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient
title_full Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient
title_fullStr Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient
title_full_unstemmed Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient
title_short Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient
title_sort digital cover photography for estimating leaf area index lai in apple trees using a variable light extinction coefficient
topic light intercepted by the canopy
gap fraction
clumping index
remote sensing
url http://www.mdpi.com/1424-8220/15/2/2860
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