| Title | Estimation of crop ground cover and leaf area index (LAI) of wheat using RapidEye satellite data: Prelimary study |
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| Author | Jiali, S; McNairn, H; Schulthess, U; Fernandes, R ; Storie, J |
| Source | 2012 1st International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2012; 6311624, 2012 p. 124-128, https://doi.org/10.1109/Agro-Geoinformatics.2012.6311624 |
| Year | 2012 |
| Alt Series | Natural Resources Canada, Contribution Series 20181152 |
| Publisher | IEEE |
| Document | book |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | geophysics; remote sensing |
| Program | Climate Change
Geoscience |
| Released | 2012 08 01 |
| Abstract | Leaf area index (LAI) is an important indicator of plant growth and biomass accumulation. LAI is often required as an input parameter in many models, especially for crop yield predication and soil
moisture retrieval. With recently due to the increasing demand on large-scale monitoring, optical satellite sensors capable of providing frequent LAI estimation over large coverage are favored. This paper reports the results from a study over an
agriculture site with spring wheat in western Canada using data acquired from RapidEye and in situ measurements using LAI analyzer and hemispherical photos during the 2011 growing season. The prediction of crop ground cover fraction has yield a
coefficient of determination of 0.66. Even better result was achieved for LAI prediction with a coefficient of determination of 0.82. Results suggest that RapdiEye optical satellite data can be a valuable data source for crop ground cover fraction
and LAI retrieval. |
| GEOSCAN ID | 311506 |
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