Hyperspectral Indices and Model Simulation for Chlorophyll Estimation in Open-Canopy Tree Crops
An investigation of the estimation of leaf biochemistry in open tree crop canopies using high-spatial hyperspectral remote sensing imagery is presented. Hyperspectral optical indices related to leaf chlorophyll content were used to test different radiative transfer modelling assumptions in open canopies where crown, soil and shadow components were separately targeted using 1 m spatial resolution ROSIS hyperspectral imagery. Methods for scaling-up of hyperspectral single-ratio indices such as R750/R710 and combined indices such as MCARI, TCARI and OSAVI were studied to investigate the effects of scene components on indices calculated from pure crown pixels and from aggregated soil, shadow and crown reflectance. Methods were tested on 1-m resolution hyperspectral ROSIS datasets acquired over two olive groves in southern Spain during the HySens 2002 campaign conducted by the German Aerospace Center (DLR). Leaf-level biochemical estimation using 1-m ROSIS data when targeting pure olive tree crowns employed PROSPECT-SAILH radiative transfer simulation. At lower spatial resolution, therefore with significant effects of soil and shadow scene components on the aggregated pixels, a canopy model to account for such scene components had to be used for a more appropriate estimation approach for leaf biochemical concentration. The linked models PROSPECT-SAILH-FLIM improved the estimates of chlorophyll concentration from these open tree canopies, demonstrating that crown-derived relationships between hyperspectral indices and biochemical constituents cannot be readily applied to hyperspectral imagery of lower spatial resolutions due to large soil and shadow effects. Predictive equations built on a MCARI/OSAVI scaled-up index through radiative transfer simulation minimized soil background variations in these open canopies, demonstrating superior performance compared to other single-ratio indices previously shown as good indicators of chlorophyll concentration in closed canopies. The MCARI/OSAVI index was demonstrated to be less affected than TCARI/OSAVI by soil background variations when calculated from the pure crown component even at the typically low LAI orchard and grove canopies.
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Language: | English |
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Elsevier
2004
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Subjects: | Chlorophyll content, Open canopy, Hyperspectral, Remote sensing, Radiative transfer, Olive tree, FLIM, |
Online Access: | http://hdl.handle.net/10261/10241 |
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dig-ias-es-10261-102412016-10-10T11:49:42Z Hyperspectral Indices and Model Simulation for Chlorophyll Estimation in Open-Canopy Tree Crops Zarco-Tejada, Pablo J. Miller, John R. Morales, Arturo Berjón, A. Agüera, Juan Chlorophyll content Open canopy Hyperspectral Remote sensing Radiative transfer Olive tree FLIM An investigation of the estimation of leaf biochemistry in open tree crop canopies using high-spatial hyperspectral remote sensing imagery is presented. Hyperspectral optical indices related to leaf chlorophyll content were used to test different radiative transfer modelling assumptions in open canopies where crown, soil and shadow components were separately targeted using 1 m spatial resolution ROSIS hyperspectral imagery. Methods for scaling-up of hyperspectral single-ratio indices such as R750/R710 and combined indices such as MCARI, TCARI and OSAVI were studied to investigate the effects of scene components on indices calculated from pure crown pixels and from aggregated soil, shadow and crown reflectance. Methods were tested on 1-m resolution hyperspectral ROSIS datasets acquired over two olive groves in southern Spain during the HySens 2002 campaign conducted by the German Aerospace Center (DLR). Leaf-level biochemical estimation using 1-m ROSIS data when targeting pure olive tree crowns employed PROSPECT-SAILH radiative transfer simulation. At lower spatial resolution, therefore with significant effects of soil and shadow scene components on the aggregated pixels, a canopy model to account for such scene components had to be used for a more appropriate estimation approach for leaf biochemical concentration. The linked models PROSPECT-SAILH-FLIM improved the estimates of chlorophyll concentration from these open tree canopies, demonstrating that crown-derived relationships between hyperspectral indices and biochemical constituents cannot be readily applied to hyperspectral imagery of lower spatial resolutions due to large soil and shadow effects. Predictive equations built on a MCARI/OSAVI scaled-up index through radiative transfer simulation minimized soil background variations in these open canopies, demonstrating superior performance compared to other single-ratio indices previously shown as good indicators of chlorophyll concentration in closed canopies. The MCARI/OSAVI index was demonstrated to be less affected than TCARI/OSAVI by soil background variations when calculated from the pure crown component even at the typically low LAI orchard and grove canopies. Financial support from the Spanish Ministry of Science and Technology (MCyT) for this project, support to A. Morales from project CAO 98-004, financial support to P.J. Zarco-Tejada under the MCyT ‘‘Ramón y Cajal’’ Program, as well by the Natural Sciences and Engineering Research Council of Canada to J. Miller are gratefully acknowledged. Peer reviewed 2009-02-03T13:08:18Z 2009-02-03T13:08:18Z 2004 artículo http://purl.org/coar/resource_type/c_6501 Remote Sensing of Environment, 90(4), 463-476 0034-4257 http://hdl.handle.net/10261/10241 10.1016/j.rse.2004.01.017 en http://dx.doi.org/10.1016/j.rse.2004.01.017 none 4085 bytes image/gif Elsevier |
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Chlorophyll content Open canopy Hyperspectral Remote sensing Radiative transfer Olive tree FLIM Chlorophyll content Open canopy Hyperspectral Remote sensing Radiative transfer Olive tree FLIM |
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Chlorophyll content Open canopy Hyperspectral Remote sensing Radiative transfer Olive tree FLIM Chlorophyll content Open canopy Hyperspectral Remote sensing Radiative transfer Olive tree FLIM Zarco-Tejada, Pablo J. Miller, John R. Morales, Arturo Berjón, A. Agüera, Juan Hyperspectral Indices and Model Simulation for Chlorophyll Estimation in Open-Canopy Tree Crops |
description |
An investigation of the estimation of leaf biochemistry in open tree crop canopies using high-spatial hyperspectral remote sensing imagery
is presented. Hyperspectral optical indices related to leaf chlorophyll content were used to test different radiative transfer modelling
assumptions in open canopies where crown, soil and shadow components were separately targeted using 1 m spatial resolution ROSIS
hyperspectral imagery. Methods for scaling-up of hyperspectral single-ratio indices such as R750/R710 and combined indices such as MCARI,
TCARI and OSAVI were studied to investigate the effects of scene components on indices calculated from pure crown pixels and from
aggregated soil, shadow and crown reflectance. Methods were tested on 1-m resolution hyperspectral ROSIS datasets acquired over two olive
groves in southern Spain during the HySens 2002 campaign conducted by the German Aerospace Center (DLR). Leaf-level biochemical
estimation using 1-m ROSIS data when targeting pure olive tree crowns employed PROSPECT-SAILH radiative transfer simulation. At
lower spatial resolution, therefore with significant effects of soil and shadow scene components on the aggregated pixels, a canopy model to
account for such scene components had to be used for a more appropriate estimation approach for leaf biochemical concentration. The linked
models PROSPECT-SAILH-FLIM improved the estimates of chlorophyll concentration from these open tree canopies, demonstrating that
crown-derived relationships between hyperspectral indices and biochemical constituents cannot be readily applied to hyperspectral imagery
of lower spatial resolutions due to large soil and shadow effects. Predictive equations built on a MCARI/OSAVI scaled-up index through
radiative transfer simulation minimized soil background variations in these open canopies, demonstrating superior performance compared to
other single-ratio indices previously shown as good indicators of chlorophyll concentration in closed canopies. The MCARI/OSAVI index
was demonstrated to be less affected than TCARI/OSAVI by soil background variations when calculated from the pure crown component
even at the typically low LAI orchard and grove canopies. |
format |
artículo |
topic_facet |
Chlorophyll content Open canopy Hyperspectral Remote sensing Radiative transfer Olive tree FLIM |
author |
Zarco-Tejada, Pablo J. Miller, John R. Morales, Arturo Berjón, A. Agüera, Juan |
author_facet |
Zarco-Tejada, Pablo J. Miller, John R. Morales, Arturo Berjón, A. Agüera, Juan |
author_sort |
Zarco-Tejada, Pablo J. |
title |
Hyperspectral Indices and Model Simulation for Chlorophyll Estimation in Open-Canopy Tree Crops |
title_short |
Hyperspectral Indices and Model Simulation for Chlorophyll Estimation in Open-Canopy Tree Crops |
title_full |
Hyperspectral Indices and Model Simulation for Chlorophyll Estimation in Open-Canopy Tree Crops |
title_fullStr |
Hyperspectral Indices and Model Simulation for Chlorophyll Estimation in Open-Canopy Tree Crops |
title_full_unstemmed |
Hyperspectral Indices and Model Simulation for Chlorophyll Estimation in Open-Canopy Tree Crops |
title_sort |
hyperspectral indices and model simulation for chlorophyll estimation in open-canopy tree crops |
publisher |
Elsevier |
publishDate |
2004 |
url |
http://hdl.handle.net/10261/10241 |
work_keys_str_mv |
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_version_ |
1777662904925945856 |