Analysis of phenologicallly-derived productivity anomalies for food security monitoring

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.

MERONI Michele;  VERSTRAETE Michel;  REMBOLD Felix;  URBANO Ferdinando;  KAYITAKIRE Francois; 

2013-05-16

EARSeL

JRC71518

http://www.earsel.org/SIG/timeseries/proceedings.php,    https://publications.jrc.ec.europa.eu/repository/handle/JRC71518,