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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Haboudane, D. Tremblay, N. Miller, J.R. Vigneault, P. |
| Copyright Year | 2008 |
| Description | Author affiliation: Agric. & Agri-Food Canada, St. Jean sur Richelieu, QC (Tremblay, N.; Vigneault, P.) || Dept. of Earth & Space Sci. & Eng., York Univ., Toronto, ON (Miller, J.R.) || Lab. d'expertise et de Rech. en teledetection et geomatique (LERTG), Univ. du Quebec a Chicoutimi, Chicoutimi, QC (Haboudane, D.) |
| Abstract | This study aims at using forward model simulations and ground-measurements (biophysical and spectral) to estimate chlorophyll concentration from hyperspectral data and imagery. Hence, intensive field campaigns were organized during the growing seasons of 2000, 2004, and 2005 in order to collect ground spectra and corresponding leaf chlorophyll content values, and crop growth status, as well as CASI (Compact Airborne Spectrographic Imager) hyperspectral images. Acquisition dates were planned to coincide with different phenological development stages, to monitor temporal changes in crop biophysical attributes. Field spectral measurements collected were used to test and evaluate several combined indices for chlorophyll determination using hyperspectral imagery. Several index combinations were investigated using both PROSPECT-SAILH canopy simulated spectra and field measured reflectances. The relationships between leaf chlorophyll content and combined optical indices showed similar trends for both PROSPECT-SAILH simulated data and ground measured datasets. The dataset used showed that crop type had a clear influence on the establishment of predictive equations as well as on their validation. In addition to generating different predictive equations, corn and wheat data yielded contrasting agreement between estimated and measured chlorophyll contents even for the same predictive algorithm. Among the set of indices tested in this study, index combinations MCARI/OSAVI, TCI/OSAVI, MTCI/MSAVI, and R-M/MSAVI were found relatively consistent and more stable as estimators of crop chlorophyll content. |
| File Size | 193709 |
| File Format | |
| ISBN | 9781424428076 |
| DOI | 10.1109/IGARSS.2008.4779411 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-07-07 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Hyperspectral sensors Hyperspectral imaging Crops Testing Monitoring Biomedical optical imaging Optical sensors Differential equations Yield estimation Prediction algorithms precision agriculture hyperspectral combined indices chlorophyll estimation chlorophyll content PROSPECT-SAILH crop type effect |
| Content Type | Text |
| Resource Type | Article |
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