A Qualitative Characterization of Spring Vegetation Phenology Using MODIS Imagery for the Piedmont of North Carolina from 2000 to 2007
Abstract
Recent studies have shown vegetation phenology around the world is being altered by
increased variability in temperatures associated with a warming climate. The onset
of spring and the duration of the growing season in many eastern states has been pushed
forward an average of 2-5 days and lengthened by as much as 10-15 days respectively,
as a response to climatic forcing. Analyzing phenological changes to forest dynamics
is aided by the use of satellite imagery with high temporal and spatial resolution
to accurately estimate the timing of recurrent events associated with the flush of
green vegetation at the beginning of spring in deciduous forests. This study used
daily MODIS images at 250m processed to Normalized Difference in Vegetation Index
(NDVI) for the spring greenup from 2000-2003 and 2007. Of the 792 available images,
20 sites along the Piedmont, coastal plain, and mountains of North Carolina were filtered
(a lowpass Savitsky-Golay convolution filter) to remove atmospheric noise, and used
to estimate relevant phenological parameters. Onset of spring, length of growing season,
rate of green-up, as well as, maximum green-up, were identified using a segmented
regression technique. Over the study period, the Piedmont sites exhibited high variability
in dates of onset among sites ( 5days) and negatively between years (6 days), with
concurrent variability in growing season length. Furthermore, using the NDVI response
in regressions of climate variables at the AmeriFLUX site in Duke Forest from 2001-2003,
showed growing degree-days since last freeze and mean soil temperature as most significantly
in agreement with phenological change. Future studies should focus on acquiring daily
satellite imagery to monitor the changes and variability seen among sites and years
with careful attention given to severe weather anomalies. Creating maps of relevant
climatic variables may provide a more accurate means of predicting phenology and determining
the influence of site-specific environmental variables.
Type
Master's projectSubject
Spring phenologyMODIS-NDVI
Savitsky-Golay
Mean Soil Temperature
Spring phenology response to climate
Remote Sensing
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https://hdl.handle.net/10161/821Citation
Bausch, Adam J. (2008). A Qualitative Characterization of Spring Vegetation Phenology Using MODIS Imagery
for the Piedmont of North Carolina from 2000 to 2007. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/821.Collections
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