Title: Using thermal time and pixel purity for enhancing biophysical variable time series: an inter-product comparison
Citation: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS vol. 51 no. 4 p. 2119 - 2127
Publication Year: 2013
JRC N°: JRC69916
ISSN: 1545-598X
URI: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6392256
DOI: 10.1109/TGRS.2012.2226731
Type: Articles in periodicals and books
Abstract: This study presents a multi-annual comparison at regional scale of currently available 1 km global leaf area index (LAI) products with crop specific green are index (GAI) retrieved from MODIS 250 m imagery. The crop specific GAI product benefits from extra processing steps of (i) spatial filtering of time series based on pixel purity; (ii) transforming the time scale to thermal time; and (iii) fitting a canopy structural dynamic model (CSDM) to smooth out the signal. In order to perform a rigorous comparison, these steps were also applied to the 1 km LAI products, namely MODIS LAI (MCD15) and CYCLOPES LAI. The results confirm that, for winter wheat, the 250 m GAI product provides a more realistic description of the time course of the biophysical variable in terms of reaching higher values, grasping the variability and providing smoother time series. However, the use of thermal time and pixel purity also improves the temporal consistency and coherence of the 1 km products. Overall, the results of this study suggest that these techniques could be valuable in harmonizing remote sensing data coming from different sources with varying spatial and temporal resolution for enhanced vegetation monitoring.
JRC Directorate:Sustainable Resources

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