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TitleEvaluation of compositing period and AVHRR and MERIS combination for improvement of spring phenology detection in deciduous forests
 
AuthorPouliot, D; Latifovic, R; Fernandes, RORCID logo; Olthof, I
SourceRemote Sensing of Environment vol. 115, issue 1, 2010 p. 158-166, https://doi.org/10.1016/j.rse.2010.08.014
Image
Year2010
Alt SeriesEarth Sciences Sector, Contribution Series 20100081
PublisherElsevier BV
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
ProvinceNova Scotia; Ontario; Quebec; New Brunswick; Newfoundland and Labrador
Lat/Long WENS -82.0000 -48.0000 56.0000 40.0000
Subjectsremote sensing; vegetation; climate; spectral ratios; PlantWatch; AVHRR; MERIS; NDVI; Start of Season (SOS)
Illustrationslocation maps; graphs; plots
ProgramRemote Sensing Science
AbstractAccurate and precise detection of phenology events is needed to assess trends in seasonal vegetation development indicative of climate or other environmental change processes. In this research, detection accuracy of start of season (SOS) phenology for deciduous forest across Eastern Canada was assessed using satellite time series and in situ PlantWatch observations. Several aspects were evaluated regarding performance of phenology information extraction: 1) effect of compositing period, 2) individual performance of the Advanced Very High Resolution Radiometer (AVHRR) and the Medium Resolution Imaging Spectrometer (MERIS) sensors, and 3) performance for these sensors combined. The AVHRR and MERIS sensors were used as they are overlapping operational missions with planned future continuity. Three approaches to utilizing the multi-sensor data were tested: 1) inter-calibrating NDVI data between sensors
and using the multi-sensor data stream to detect SOS, 2) combining independently derived SOS estimatesfrom AVHRR and MERIS based on a weighted average, and 3) combining approaches 1 and 2. Comparison with in situ observations of leaf out and first bloom showed that combining independent SOS estimates from AVHRR and MERIS was better than using the inter-calibrated multi-sensor data. Combining SOS estimatesfrom both sensors reduced error by 1 - 2 days compared to the individual sensor results. Composite periods
from 7 to 11 days produced the best results for leaf out with a mean absolute error (MAE) of 5 days. Results for first bloom were not as good as those for leaf out, producing a MAE of 6.5 days. For first bloom, compositing periods greater than 11 days did not increase error at the same rate as seen for leaf out. However, the larger MAE observed for first bloom may have masked this effect.
GEOSCAN ID285567

 
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