European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset

Vegetation distribution and state have been measured since 1981 by the AVHRR (Advanced Very High Resolution Radiometer) instrument through satellite remote sensing. In this study a correction method is applied to the Pathfinder NDVI (Normalized Difference Vegetation Index) data to create a continuou...

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Published in:International Journal of Remote Sensing
Main Authors: Stockli, R., Vidale, Pier Luigi
Format: Article in Journal/Newspaper
Language:unknown
Published: Taylor & Francis 2004
Subjects:
Online Access:https://centaur.reading.ac.uk/28567/
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spelling ftunivreading:oai:centaur.reading.ac.uk:28567 2024-09-15T18:23:36+00:00 European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset Stockli, R. Vidale, Pier Luigi 2004 https://centaur.reading.ac.uk/28567/ unknown Taylor & Francis Stockli, R. and Vidale, P. L. <https://centaur.reading.ac.uk/view/creators/90000796.html> orcid:0000-0002-1800-8460 (2004) European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset. International Journal of Remote Sensing, 25 (17). pp. 3303-3330. ISSN 0143-1161 doi: https://doi.org/10.1080/01431160310001618149 <https://doi.org/10.1080/01431160310001618149> Article PeerReviewed 2004 ftunivreading https://doi.org/10.1080/01431160310001618149 2024-07-30T14:08:25Z Vegetation distribution and state have been measured since 1981 by the AVHRR (Advanced Very High Resolution Radiometer) instrument through satellite remote sensing. In this study a correction method is applied to the Pathfinder NDVI (Normalized Difference Vegetation Index) data to create a continuous European vegetation phenology dataset of a 10-day temporal and 0.1° spatial resolution; additionally, land surface parameters for use in biosphere–atmosphere modelling are derived. The analysis of time-series from this dataset reveals, for the years 1982–2001, strong seasonal and interannual variability in European land surface vegetation state. Phenological metrics indicate a late and short growing season for the years 1985–1987, in addition to early and prolonged activity in the years 1989, 1990, 1994 and 1995. These variations are in close agreement with findings from phenological measurements at the surface; spring phenology is also shown to correlate particularly well with anomalies in winter temperature and winter North Atlantic Oscillation (NAO) index. Nevertheless, phenological metrics, which display considerable regional differences, could only be determined for vegetation with a seasonal behaviour. Trends in the phenological phases reveal a general shift to earlier (−0.54 days year−1) and prolonged (0.96 days year−1) growing periods which are statistically significant, especially for central Europe. Article in Journal/Newspaper North Atlantic North Atlantic oscillation CentAUR: Central Archive at the University of Reading International Journal of Remote Sensing 25 17 3303 3330
institution Open Polar
collection CentAUR: Central Archive at the University of Reading
op_collection_id ftunivreading
language unknown
description Vegetation distribution and state have been measured since 1981 by the AVHRR (Advanced Very High Resolution Radiometer) instrument through satellite remote sensing. In this study a correction method is applied to the Pathfinder NDVI (Normalized Difference Vegetation Index) data to create a continuous European vegetation phenology dataset of a 10-day temporal and 0.1° spatial resolution; additionally, land surface parameters for use in biosphere–atmosphere modelling are derived. The analysis of time-series from this dataset reveals, for the years 1982–2001, strong seasonal and interannual variability in European land surface vegetation state. Phenological metrics indicate a late and short growing season for the years 1985–1987, in addition to early and prolonged activity in the years 1989, 1990, 1994 and 1995. These variations are in close agreement with findings from phenological measurements at the surface; spring phenology is also shown to correlate particularly well with anomalies in winter temperature and winter North Atlantic Oscillation (NAO) index. Nevertheless, phenological metrics, which display considerable regional differences, could only be determined for vegetation with a seasonal behaviour. Trends in the phenological phases reveal a general shift to earlier (−0.54 days year−1) and prolonged (0.96 days year−1) growing periods which are statistically significant, especially for central Europe.
format Article in Journal/Newspaper
author Stockli, R.
Vidale, Pier Luigi
spellingShingle Stockli, R.
Vidale, Pier Luigi
European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset
author_facet Stockli, R.
Vidale, Pier Luigi
author_sort Stockli, R.
title European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset
title_short European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset
title_full European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset
title_fullStr European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset
title_full_unstemmed European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset
title_sort european plant phenology and climate as seen in a 20-year avhrr land-surface parameter dataset
publisher Taylor & Francis
publishDate 2004
url https://centaur.reading.ac.uk/28567/
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_relation Stockli, R. and Vidale, P. L. <https://centaur.reading.ac.uk/view/creators/90000796.html> orcid:0000-0002-1800-8460 (2004) European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset. International Journal of Remote Sensing, 25 (17). pp. 3303-3330. ISSN 0143-1161 doi: https://doi.org/10.1080/01431160310001618149 <https://doi.org/10.1080/01431160310001618149>
op_doi https://doi.org/10.1080/01431160310001618149
container_title International Journal of Remote Sensing
container_volume 25
container_issue 17
container_start_page 3303
op_container_end_page 3330
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