2010
DOI: 10.1016/j.rse.2010.05.005
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The response of African land surface phenology to large scale climate oscillations

Abstract: Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the African continent. Analysis of changes in phenology can provide quantitative information on the effect of climate variability on growing seasons in agricultural regions. Using a robust statistical methodology, we describe the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD),… Show more

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Cited by 130 publications
(82 citation statements)
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“…For example, co-occurrence of positive and negative trends in SOS can be a result of differences in local conditions [50], i.e., topography. Topographical variations can result into microclimate [51,52] and because the air temperature data set we used was created by interpolating sparse point observations [38], it is possible that air temperature has been underestimated or over-estimated at some locations, especially in mountainous areas-hence affecting the magnitude of the temperature trend derived at such pixels. As such, it is possible that some areas did not experience warming as our results suggest.…”
Section: Discussionmentioning
confidence: 99%
“…For example, co-occurrence of positive and negative trends in SOS can be a result of differences in local conditions [50], i.e., topography. Topographical variations can result into microclimate [51,52] and because the air temperature data set we used was created by interpolating sparse point observations [38], it is possible that air temperature has been underestimated or over-estimated at some locations, especially in mountainous areas-hence affecting the magnitude of the temperature trend derived at such pixels. As such, it is possible that some areas did not experience warming as our results suggest.…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, the start of the growing season can also be forecasted using climatic indices [19]. Despite this attractive feature, current knowledge about the relationship between phenology and gross primary production (GPP) in the Sahel is limited.…”
Section: Introductionmentioning
confidence: 99%
“…As temperature is the key factor in determining vegetation phenology, a lot of studies have used temperature based phonological metrics to detect the vegetation phenology [34][35][36][37]. Phenology metrics based upon a traditional thermal method were introduced in this study.…”
Section: Phenology Metrics From Traditional Thermal Methodsmentioning
confidence: 99%
“…The growing season is the most active period in the phenology cycle of non-evergreen vegetation [36]. Generally, there are some different threshold methods which can be used to detect phenology, including the absolute threshold, the dynamic ratio threshold, and the abrupt change method [35].…”
Section: Phenology Metrics Derived From Vegetation Indexmentioning
confidence: 99%