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Li, M; Qu, JJ; Hao, XJ (2010). Investigating phenological changes using MODIS vegetation indices in deciduous broadleaf forest over continental U.S. during 2000-2008. ECOLOGICAL INFORMATICS, 5(5), 410-417.

Vegetation phenology describing the seasonal cycle of plants is currently one of the main concerns in the study of climate change and carbon balance estimation in ecosystems. Remote sensing techniques which can capture canopy reflectance allow vegetation photosynthetic capacity to be assessed In this study, the Normalized Difference Vegetation Index (NDVI). Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) measurements were used to identify onset date of greenness in deciduous broadleaf forest (DBF) over the continental United States from year 2000 to 2008. Onset dates determined by these three indices were compared with North American First Leaf Lilac Phenology Data over the same time period NDVI has a best agreement with the field data among the three vegetation indices Spatial analysis was performed on the onset dates predicted with NDVI Four major conclusions were drawn from this study are 1) onset dates are not only dependent on latitude but also associated with ecoregions and altitudes, 2) onset of greenness moves northward gradually and the average change of onset dates along latitude is about 3 days per degree. Interannual variability of onset dates is greater at higher latitudes (>43 degrees N) than at lower latitudes (<= 43 degrees N), 3) at the same latitude, DBF in mountain area tends to green up latter and coastal forest tends to green up earlier than other ecoregions, and 4) the impact of altitude is more obvious when the range of elevation achieves more than 1000 m. These conclusions provide insight for assessing vegetation indices in determining onset date of greenness at regional scale, and can be exploited to analyze the impacts of climate change on terrestrial ecosystem (C) 2010 Elsevier B V All rights reserved



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