Remote Sens. 2014, 6(1), 257-284; doi:10.3390/rs6010257
Phenological Metrics Derived over the European Continent from NDVI3g Data and MODIS Time Series
Institute for Surveying, Remote Sensing and Land Information, University of Natural Resources and Life Sciences (BOKU), Peter Jordan Strasse 82, A-1190 Vienna, Austria
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Received: 22 July 2013 / Revised: 21 November 2013 / Accepted: 25 November 2013 / Published: 27 December 2013
(This article belongs to the Special Issue Monitoring Global Vegetation with AVHRR NDVI3g Data (1981-2011))
Abstract
Time series of normalized difference vegetation index (NDVI) are important data sources for environmental monitoring. Continuous efforts are put into their production and updating. The recently released Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g data set is a consistent time series with 1/12° spatial and bi-monthly temporal resolution. It covers the time period from 1981 to 2011. However, it is unclear if vegetation density and phenology derived from GIMMS are comparable to those obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI with 250 m ground resolution. To check the consistency between GIMMS and MODIS data sets, a comparative analysis was performed. For a large European window (40 × 40°), data distribution, spatial and temporal agreement were analyzed, as well as the timing of important phenological events. Overall, only a moderately good agreement of NDVI values was found. Large differences occurred during winter. Large discrepancies were also observed for phenological metrics, in particular the start of season. Information regarding the maximum of season was more consistent. Hence, both data sets should be well inter-calibrated before being used concurrently. View Full-TextKeywords:
MODIS; GIMMS; AVHRR; consistency analysis; Whittaker smoother; phenology; start of season; maximum of season; vegetation density; NDVI
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Atzberger, C.; Klisch, A.; Mattiuzzi, M.; Vuolo, F. Phenological Metrics Derived over the European Continent from NDVI3g Data and MODIS Time Series. Remote Sens. 2014, 6, 257-284.
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