Joining Forces for Food Security – Linking Earth Observation and Crowd-sourcing for improved Decision-support

Friday, 19 December 2014
Markus Enenkel1, Wouter Dorigo1, Linda M See2, Patrick Vinck3 and Andreas Papp4, (1)Vienna University of Technology, Vienna, Austria, (2)IIASA, Laxenburg, Austria, (3)Harvard University, Harvard Humanitarian Initiative, Cambridge, MA, United States, (4)Doctors without Borders, Delegate and Programme Department, Vienna, Austria
Droughts statistically exceed all other natural disasters in complexity, spatio-temporal extent and number of people affected. Triggered by crop failure, food insecurity is a major manifestation of agricultural drought and water scarcity. However, other socio-economic precursors, such as chronically low levels of disaster preparedness, hampered access to food security or a lack of social safety nets are equally important factors. We will present the first results of the SATIDA (Satellite Technologies for Improved Drought-Risk Assessment) project, which advances three complementary developments. First, an existing drought indicator is enhanced by replacing in-situ measurements on rainfall and surface air temperature with satellite-derived datasets. We identify the vegetation status via a new noise-corrected and gap-filled vegetation index. In addition, we introduce a soil moisture component to close the gap between rainfall deficiencies, extreme temperature and the first visible impacts of atmospheric anomalies on vegetation. Second, once calibrated, the index is forced with seasonal forecasts to quantify their uncertainty and added value in the regions of interest. Third, a mobile application is developed to disseminate relevant visualizations to decision-makers in affected areas, to collect additional information about socio-economic conditions and to validate the output of the drought index in real conditions. Involving Doctors without Borders (MSF) as a key user, SATIDA aims at decreasing uncertainties in decision-making via a more holistic risk framework, resulting in longer lead times for disaster logistics in the preparedness phase.