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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Spectroscopic remote sensing of plant stress at leaf and canopy levels using the chlorophyll 680 nm absorption feature with continuum removal

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Autor(es):
Sanches, Ieda Del'Arco [1, 2] ; Souza Filho, Carlos Roberto [1] ; Kokaly, Raymond Floyd [3]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Campinas UNICAMP, Inst Geosci, BR-13083970 Campinas, SP - Brazil
[2] Brazilian Natl Inst Space Res INPE, Remote Sensing Div DSR, BR-12227010 Sao Jose Dos Campos, SP - Brazil
[3] US Geol Survey, Denver Fed Ctr, Lakewood, CO 80225 - USA
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING; v. 97, p. 111-122, NOV 2014.
Citações Web of Science: 26
Resumo

This paper explores the use of spectral feature analysis to detect plant stress in visible/near infrared wavelengths. A time series of close range leaf and canopy reflectance data of two plant species grown in hydrocarbon-contaminated soil was acquired with a portable spectrometer. The ProSpecTIR-VS airborne imaging spectrometer was used to obtain far range hyperspectral remote sensing data over the field experiment. Parameters describing the chlorophyll 680 nm absorption feature (depth, width, and area) were derived using continuum removal applied to the spectra. A new index, the Plant Stress Detection Index (PSDI), was calculated using continuum-removed values near the chlorophyll feature centre (680 nm) and on the green-edge (560 and 575 nm). Chlorophyll feature's depth, width and area, the PSDI and a narrow-band normalised difference vegetation index were evaluated for their ability to detect stressed plants. The objective was to analyse how the parameters/indices were affected by increasing degrees of plant stress and to examine their utility as plant stress indicators at the remote sensing level (e.g. airborne sensor). For leaf data, PSDI and the chlorophyll feature area revealed the highest percentage (67-70%) of stressed plants. The PSDI also proved to be the best constraint for detecting the stress in hydrocarbon-impacted plants with field canopy spectra and airborne imaging spectroscopy data. This was particularly true using thresholds based on the ASD canopy data and considering the combination of higher percentage of stressed plants detected (across the thresholds) and fewer false-positives. (C) 2014 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved. (AU)

Processo FAPESP: 11/03416-8 - Utilização de Sensoriamento Remoto Ultra/Hiperespectral para a Detecção Precoce de Alterações Botânicas no Sistema Solo-Vegetação como Indicadores de Pequenos Vazamentos de Hidrocarbonetos Líquidos em Dutos
Beneficiário:Ieda Del'Arco Sanches
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado