Lag and seasonality considerations in evaluating AVHRR NDVI response to precipitation

Photogrammetric Engineering and Remote Sensing
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Abstract

Assessment of the relationship between the normalized difference vegetation index (NDVI) and precipitation is important in understanding vegetation and climate interaction at a large scale. NDVI response to precipitation, however, is difficult to quantify due to the lag and seasonality effects, which will vary due to vegetation cover type, soils and climate. A time series analysis was performed on biweekly NDVI and precipitation around weather stations in the northern and central U.S. Great Plains. Regression models that incorporate lag and seasonality effects were used to quantify the relationship between NDVI and lagged precipitation in grasslands and croplands. It was found that the time lag was shorter in the early growing season, but longer in the mid- to late-growing season for most locations. The regression models with seasonal adjustment indicate that the relationship between NDVI and precipitation over the entire growing season was strong, with R2 values of 0.69 and 0.72 for grasslands and croplands, respectively. We conclude that vegetation greenness can be predicted using current and antecedent precipitation, if seasonal effects are taken into account.

Publication type Article
Publication Subtype Journal Article
Title Lag and seasonality considerations in evaluating AVHRR NDVI response to precipitation
Series title Photogrammetric Engineering and Remote Sensing
DOI 10.14358/PERS.71.9.1053
Volume 71
Issue 9
Year Published 2005
Language English
Publisher American Society for Photogrammetry and Remote Sensing
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 9 p.
First page 1053
Last page 1061
Online Only (Y/N) N
Additional Online Files (Y/N) N
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