| Title | Relationship between leaf area index and Landsat Operational Land Imager equivalent reduced simple ratio vegetation index for the Athabasca oil sands region, northern Alberta |
| Download | Downloads |
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| Licence | Please note the adoption of the Open Government Licence - Canada
supersedes any previous licences. |
| Author | Fernandes, R ;
Maloley, M; Canisius, F |
| Source | Geomatics Canada, Open File 39, 2018, 36 pages, https://doi.org/10.4095/308333  Open Access |
| Year | 2018 |
| Publisher | Natural Resources Canada |
| Document | open file |
| Lang. | English |
| Media | on-line; digital |
| File format | pdf |
| Province | Alberta |
| NTS | 74D/13; 74E/04 |
| Area | Athabasca Oil Sands |
| Lat/Long WENS | -112.0000 -111.5000 57.2500 56.7500 |
| Subjects | geophysics; remote sensing; satellite imagery; vegetation; spectral analyses; reflectance; Landsat; Land cover |
| Illustrations | location maps; tables; Landsat images; satellite images; photographs; plots |
| Program | Remote Sensing Science |
| Released | 2018 06 13 |
| Abstract | This document describes the production of a regression relationship between leaf area index and the reduced simple ration vegetation index (RSR) for Landsat Operational Land Imager spectral bands over
the Athabasca Oil Sands region of Alberta. from satellite imagery using standard Canada Centre for Remote Sensing algorithms. 245 Elementary Sampling Units (ESUs) were specified based on a stratification of both land cover and spectral reflectance in
the vicinity of Fort McKay, Alberta, Canada. ESU LAI was estimated using in-situ digital hemispherical photographs acquired during the 2012 and 2013 growing seasons. The estimation used the CCRS Line Transect protocol followed by processing using
CANEYEV6.3 software. Empirical corrections for shoot clumping are documented. In-situ Lai ranged from 0.09 to 6.08. A SPOT 5 satellite image was acquired within two weeks of each of the 2012 and 2013 field campaigns, orthorectified to within 10m (1
standard deviation) and radiometrically normalized to invariant targets in a surface reflectance Landsat OLI image acquired within 1 week of the 2013 SPOT image. The RSR was derived from both normalized SPOT5 images and sampled over each ESU. A
Thiel-Sen linear regression was applied to generate a relationship to predict LAI given RSR across all sampled land cover conditions with a root mean square error of 0.49. |
| Summary | (Plain Language Summary, not published)
This document describes the production of a regression relationship between leaf area index (LAI) and the reduced simple ratio vegetation index (RSR) for
Landsat Operational Land Imager spectral bands over the Athabasca Oil Sands region of Alberta. A total of 245 plots were specified based on a stratification of both land cover and spectral reflectance in the vicinity of Fort McKay, Alberta, Canada.
Plot LAI was estimated using in-situ digital hemispherical photographs acquired during the 2012 and 2013 growing seasons. RSR was derived for each plot from SPOT 5 satellite images calibrated against Landsat OLI images. A linear regression was
applied to generate a relationship to predict LAI given RSR across all sampled land cover conditions with a root mean square error of 0.49. |
| GEOSCAN ID | 308333 |
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