Title: Analysis of phenologicallly-derived productivity anomalies for food security monitoring
Citation: Proceedings of Temporal Analysis of Satellite Images EARSeL Workshop p. 1-6
Publisher: EARSeL
Publication Year: 2012
JRC N°: JRC71518
URI: http://www.earsel.org/SIG/timeseries/proceedings.php
Type: Articles in periodicals and books
Abstract: For logistical and security reasons, various institutions and organizations monitor vegetation condition in food insecure regions of the world using remote sensing techniques from space. In this study, we outline a method to objectively assess the characteristics of concluded growing seasons on the basis of optical remote sensing data only. A few key phenological indicators, derived from multi-temporal Earth observations, characterize the spatial and temporal evolution of successive growing seasons. These indicators, together with a simplified light use efficiency approach, are used to compute a proxy of the yearly gross primary production. Vegetation condition and the associated risk of food deficit are derived from a comparison of these yearly values with their long-term averages. This approach is exploited here to document the severe 2010-2011 drought in the Horn of Africa.
JRC Directorate:Sustainable Resources

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