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Proceedings Paper

Using model-data fusion to downscale solar-induced fluorescence data into a higher spatiotemporal resolution
Author(s): Min Chen; Ning Zeng; Ghassem Asrar; Yun Liu
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Paper Abstract

The recent emergence of spaceborne Solar-Induced chlorophyll Fluorescence (SIF) represents a major breakthrough in understanding, monitoring and quantifying global carbon cycle variability and change. However, the existing spaceborne SIF products are typically noisy, coarse and sparse in both time and space coverage, thus are not suitable for regional carbon cycle studies. In this study, we are taking advantage of the complementary characteristics of the Global Ozone Monitoring Experiment (GOME-2) SIF and MODIS observations of terrestrial ecosystems to downscale the coarse-resolution SIF products into finer spatial and temporal resolutions, using an innovative Ensemble Kalman Filter and parameter estimation with Adaptive Spatial Average scheme (ASA-EnKF) data assimilation technique. We used a simplified version of the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE), level-2 GOME-2 ungridded SIF product to develop a high-quality/resolution (i.e., 1km, hourly, gap-free) SIF dataset, over the Western United States. This paper demonstrates some preliminary result of our work.

Paper Details

Date Published: 22 October 2018
PDF: 9 pages
Proc. SPIE 10777, Land Surface and Cryosphere Remote Sensing IV, 107770N (22 October 2018); doi: 10.1117/12.2324582
Show Author Affiliations
Min Chen, Pacific Northwest National Lab. (United States)
Ning Zeng, Univ. of Maryland, College Park (United States)
Ghassem Asrar, Pacific Northwest National Lab. (United States)
Yun Liu, Univ. of Maryland, College Park (United States)
Texas A&M Univ. (United States)


Published in SPIE Proceedings Vol. 10777:
Land Surface and Cryosphere Remote Sensing IV
Mitchell Goldberg; Jing M. Chen; Reza Khanbilvardi, Editor(s)

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