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Assaf Anyamba

Researcher at Goddard Space Flight Center

Publications -  75
Citations -  5438

Assaf Anyamba is an academic researcher from Goddard Space Flight Center. The author has contributed to research in topics: Rift Valley fever & Normalized Difference Vegetation Index. The author has an hindex of 29, co-authored 68 publications receiving 4854 citations. Previous affiliations of Assaf Anyamba include Universities Space Research Association & University of Maryland, Baltimore County.

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Recent trends in vegetation dynamics in the African Sahel and their relationship to climate

TL;DR: In this article, the authors investigated temporal and spatial patterns of vegetation greenness and rainfall variability in the African Sahel and their interrelationships based on analyses of Normalized Difference Vegetation Index (NDVI) time series for the period 1982-2003 and gridded satellite rainfall estimates.
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Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003

TL;DR: In this article, a 23-year time series of Remotely sensed measurements from NOAA-AVHRR expressed as normalized difference vegetation index (NDVI) have been used for long-term studies of Sahel region.
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Climate and Satellite Indicators to Forecast Rift Valley Fever Epidemics in Kenya

TL;DR: Analysis of this record and Pacific and Indian Ocean sea surface temperature anomalies, coupled with satellite normalized difference vegetation index data, shows that prediction of Rift Valley fever outbreaks may be made up to 5 months in advance of outbreaks in East Africa.
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Prediction of a Rift Valley fever outbreak.

TL;DR: A Rift Valley fever risk mapping model using El Niño/Southern Oscillation related climate anomalies predicted areas where outbreaks of RVF in humans and animals were expected and occurred in the Horn of Africa from December 2006 to May 2007, the first prospective prediction of a RVF outbreak.
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Monitoring Global Croplands with Coarse Resolution Earth Observations: The Global Agriculture Monitoring (GLAM) Project

TL;DR: The operational components and new developments of the GLAM monitoring system as well as the future role of earth observations in global agricultural monitoring are discussed.