Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models

Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models

Airborne Imaging Spectroscopy Workshop, 8 October 2004 - Bruges, Belgium

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Bibliographic Details
Main Authors: Zarco-Tejada, Pablo J., Berjón, A., Miller, John R.
Format: comunicación de congreso biblioteca
Language:English
Published: 2004
Subjects:Crop stress, Water stress, Hyperspectral remote sensing, Vegetation indices, Scaling up,
Online Access:http://hdl.handle.net/10261/10582
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spelling dig-ias-es-10261-105822016-10-10T10:41:17Z Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models Zarco-Tejada, Pablo J. Berjón, A. Miller, John R. Crop stress Water stress Hyperspectral remote sensing Vegetation indices Scaling up Airborne Imaging Spectroscopy Workshop, 8 October 2004 - Bruges, Belgium Progress made on the detection of stress in heterogeneous crop canopies with hyperspectral remote sensing imagery is presented. High-spatial resolution multispectral remote sensing imagery was collected in 2002, 2003 and 2004 over vineyard and olive orchards in Spain. Imagery acquired with the Compact Airborne Spectrographic Imager (CASI) and the Reflective Optics System Imaging Spectrometer (ROSIS) in the visible and near infrared wavelength regions 400-950 nm at 1 m resolution, and with the Airborne Hyperspectral Scanner (AHS) in the reflective and thermal regions at 2 m resolution enabled the study of narrow-band vegetation indices and model simulation for estimation of chlorophyll content for chlorosis detection at the tree and vine level, as well as deriving thermal information function of the stress status. Ground data collection consisted of measurements of crown transmittance with a PCA LAI-2000 and geometrical measurements of crown projected area, height, crown cross-section, and biochemical constituents such as chlorophyll a+b and carotenoids, enabling the estimation of crown leaf area index, crown leaf density, biophysical variables related to the crown intercepted radiation, such as crop yield and canopy fractional cover, as well as crop functioning through chlorophyll content estimation. Leaf and canopy simulation models, such as PROSPECT, SAILH, FLIM, and rowMCRM were used and the scaling up methodology presented. The authors gratefully acknowledge the HySens project support provided through the Access to Research Infrastructures EU Program. Financial support from the Spanish Ministry of Science and Technology (MCyT) for the project AGL2002-04407-C03, and financial support to P.J. Zarco-Tejada under the Ramón y Cajal and Averroes Programs are also acknowledged. Peer reviewed 2009-02-11T11:13:29Z 2009-02-11T11:13:29Z 2004 comunicación de congreso http://purl.org/coar/resource_type/c_5794 http://hdl.handle.net/10261/10582 en open 324430 bytes application/pdf
institution IAS ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-ias-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del IAS España
language English
topic Crop stress
Water stress
Hyperspectral remote sensing
Vegetation indices
Scaling up
Crop stress
Water stress
Hyperspectral remote sensing
Vegetation indices
Scaling up
spellingShingle Crop stress
Water stress
Hyperspectral remote sensing
Vegetation indices
Scaling up
Crop stress
Water stress
Hyperspectral remote sensing
Vegetation indices
Scaling up
Zarco-Tejada, Pablo J.
Berjón, A.
Miller, John R.
Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models
description Airborne Imaging Spectroscopy Workshop, 8 October 2004 - Bruges, Belgium
format comunicación de congreso
topic_facet Crop stress
Water stress
Hyperspectral remote sensing
Vegetation indices
Scaling up
author Zarco-Tejada, Pablo J.
Berjón, A.
Miller, John R.
author_facet Zarco-Tejada, Pablo J.
Berjón, A.
Miller, John R.
author_sort Zarco-Tejada, Pablo J.
title Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models
title_short Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models
title_full Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models
title_fullStr Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models
title_full_unstemmed Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models
title_sort stress detection in crops with hyperspectral remote sensing and physical simulation models
publishDate 2004
url http://hdl.handle.net/10261/10582
work_keys_str_mv AT zarcotejadapabloj stressdetectionincropswithhyperspectralremotesensingandphysicalsimulationmodels
AT berjona stressdetectionincropswithhyperspectralremotesensingandphysicalsimulationmodels
AT millerjohnr stressdetectionincropswithhyperspectralremotesensingandphysicalsimulationmodels
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