B43C-0576
Improving the frequency of high spatial resolution leaf area index maps using Landsat OLI and Sentinel-2 MSI

Thursday, 17 December 2015
Poster Hall (Moscone South)
Shuang Li1,2, Sangram Ganguly1,3, Jennifer L Dungan1, Gong Zhang1,3, Junchang Ju4, Martin Claverie5 and NASA Earth Exchange (NEX), (1)NASA Ames Research Center, Moffett Field, CA, United States, (2)University Corporation Monterey, Seaside, CA, United States, (3)Bay Area Environmental Research Institute Moffett Field, Moffett Field, CA, United States, (4)Universities Space Research Association Columbia, Columbia, MD, United States, (5)University of Maryland College Park, College Park, MD, United States
Abstract:

The European Space Agency’s Sentinel-2 mission successfully launched the first of two satellites in June, 2015. Sentinel 2A’s MSI instrument is now providing optical data similar to Landsat 8’s OLI imagery and, with its global repeat of 10 days, has the potential to increase the availability of 30m resolution high level products such as leaf area index (LAI). Prior to the launch of S-2A, we simulated MSI imagery using EO-1 Hyperion data and estimated green LAI using an algorithm based on canopy spectral invariants theory. Comparison of the resulting LAI maps resulting from the simulated MSI and corresponding maps derived from OLI data showed a RMSE of 0.1875. Uncertainty bounds on actual MSI data promise to be narrower because of the superior signal-to-noise ratio of MSI. A workflow for the production of LAI and other high level products including data ingest, BRDF correction, cloud masking and atmospheric correction is being developed using the NASA Earth Exchange (NEX) and will improve the capability to examine seasonal changes in canopy LAI.

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