Characterizing the Variability of the Structure Parameter in the PROSPECT Leaf Optical Properties Model

Radiative transfer model (RTM) inversion allows for the quantitative estimation of vegetation biochemical composition from satellite sensor data, but large uncertainties associated with inversion make accurate estimation difficult. The leaf structure parameter (<i>N<sub>s</sub><...

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Main Authors: Erik J. Boren, Luigi Boschetti, Dan M. Johnson
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/11/10/1236
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spelling doaj-00776bca84af45e8aa4580477936a58a2020-11-25T01:36:36ZengMDPI AGRemote Sensing2072-42922019-05-011110123610.3390/rs11101236rs11101236Characterizing the Variability of the Structure Parameter in the PROSPECT Leaf Optical Properties ModelErik J. Boren0Luigi Boschetti1Dan M. Johnson2College of Natural Resources, University of Idaho, Moscow, ID 83844 USACollege of Natural Resources, University of Idaho, Moscow, ID 83844 USAWarnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USARadiative transfer model (RTM) inversion allows for the quantitative estimation of vegetation biochemical composition from satellite sensor data, but large uncertainties associated with inversion make accurate estimation difficult. The leaf structure parameter (<i>N<sub>s</sub></i>) is one of the largest sources of uncertainty in inversion of the widely used leaf-level PROSPECT model, since it is the only parameter that cannot be directly measured. In this study, we characterize <i>N<sub>s</sub></i> as a function of phenology by collecting an extensive dataset of leaf measurements from samples of three dicotyledon species (hard red wheat, soft white wheat, and upland rice) and one monocotyledon (soy), grown under controlled conditions over two full growth seasons. A total of 230 samples were collected: measured leaf reflectance and transmittance were used to estimate <i>N<sub>s</sub></i> from each sample. These experimental data were used to investigate whether <i>N<sub>s</sub></i> depends on phenological stages (early/mid/late), and/or irrigation regime (irrigation at 85%, 75%, 60% of the initial saturated tray weight, and pre-/post-irrigation). The results, supported by the extensive experimental data set, indicate a significant difference between <i>N<sub>s</sub></i> estimated on monocotyledon and dicotyledon plants, and a significant difference between <i>N<sub>s</sub></i> estimated at different phenological stages. Different irrigation regimes did not result in significant <i>N<sub>s</sub></i> differences for either monocotyledon or dicotyledon plant types. To our knowledge, this study provides the first systematic record of <i>N<sub>s</sub></i> as a function of phenology for common crop species.https://www.mdpi.com/2072-4292/11/10/1236leaf structure parametermodel inversionPROSPECTradiative transferspectroradiometry
collection DOAJ
language English
format Article
sources DOAJ
author Erik J. Boren
Luigi Boschetti
Dan M. Johnson
spellingShingle Erik J. Boren
Luigi Boschetti
Dan M. Johnson
Characterizing the Variability of the Structure Parameter in the PROSPECT Leaf Optical Properties Model
Remote Sensing
leaf structure parameter
model inversion
PROSPECT
radiative transfer
spectroradiometry
author_facet Erik J. Boren
Luigi Boschetti
Dan M. Johnson
author_sort Erik J. Boren
title Characterizing the Variability of the Structure Parameter in the PROSPECT Leaf Optical Properties Model
title_short Characterizing the Variability of the Structure Parameter in the PROSPECT Leaf Optical Properties Model
title_full Characterizing the Variability of the Structure Parameter in the PROSPECT Leaf Optical Properties Model
title_fullStr Characterizing the Variability of the Structure Parameter in the PROSPECT Leaf Optical Properties Model
title_full_unstemmed Characterizing the Variability of the Structure Parameter in the PROSPECT Leaf Optical Properties Model
title_sort characterizing the variability of the structure parameter in the prospect leaf optical properties model
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2019-05-01
description Radiative transfer model (RTM) inversion allows for the quantitative estimation of vegetation biochemical composition from satellite sensor data, but large uncertainties associated with inversion make accurate estimation difficult. The leaf structure parameter (<i>N<sub>s</sub></i>) is one of the largest sources of uncertainty in inversion of the widely used leaf-level PROSPECT model, since it is the only parameter that cannot be directly measured. In this study, we characterize <i>N<sub>s</sub></i> as a function of phenology by collecting an extensive dataset of leaf measurements from samples of three dicotyledon species (hard red wheat, soft white wheat, and upland rice) and one monocotyledon (soy), grown under controlled conditions over two full growth seasons. A total of 230 samples were collected: measured leaf reflectance and transmittance were used to estimate <i>N<sub>s</sub></i> from each sample. These experimental data were used to investigate whether <i>N<sub>s</sub></i> depends on phenological stages (early/mid/late), and/or irrigation regime (irrigation at 85%, 75%, 60% of the initial saturated tray weight, and pre-/post-irrigation). The results, supported by the extensive experimental data set, indicate a significant difference between <i>N<sub>s</sub></i> estimated on monocotyledon and dicotyledon plants, and a significant difference between <i>N<sub>s</sub></i> estimated at different phenological stages. Different irrigation regimes did not result in significant <i>N<sub>s</sub></i> differences for either monocotyledon or dicotyledon plant types. To our knowledge, this study provides the first systematic record of <i>N<sub>s</sub></i> as a function of phenology for common crop species.
topic leaf structure parameter
model inversion
PROSPECT
radiative transfer
spectroradiometry
url https://www.mdpi.com/2072-4292/11/10/1236
work_keys_str_mv AT erikjboren characterizingthevariabilityofthestructureparameterintheprospectleafopticalpropertiesmodel
AT luigiboschetti characterizingthevariabilityofthestructureparameterintheprospectleafopticalpropertiesmodel
AT danmjohnson characterizingthevariabilityofthestructureparameterintheprospectleafopticalpropertiesmodel
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