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An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS DataAn enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.
Document ID
20120010291
Document Type
Reprint (Version printed in journal)
Authors
Tan, Bin (ERTCorp Laurel, MD)
Morisette, Jeffrey T. (Geological Survey Fort Collins, CO, United States)
Wolfe, Robert E. (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Gao, Feng (ERTCorp Laurel, MD)
Ederer, Gregory A. (Sigma Space Partners, LLC Lanham, MD, United States)
Nightingale, Joanne (Sigma Space Partners, LLC Lanham, MD, United States)
Pedelty, Jeffrey A. (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 26, 2013
Publication Date
June 1, 2012
Publication Information
Publication: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume: 4
Issue: 2
Subject Category
Earth Resources and Remote Sensing
Report/Patent Number
GSFC.JA.00240.2012
Distribution Limits
Public
Copyright
Other