Using Satellite-Based Remote Sensing Data to Assess Millet Price Regimes and Market Performance in Niger (DRAFT)

As a result of the horrific famines of the 1970s and 1980s, the international development community has increasingly turned to early warning systems (EWS) for monitoring food security situations around the world. Emphasis has been placed on monitoring food production systems and markets in Sub-Saharan Africa and the horn of Africa, which historically have faced some of the worst food shortages. Typically, an EWS is composed of three to five monitoring pillars: i) agricultural production monitoring (agro-climatic) and harvest forecasts; ii) market information monitoring (prices, storage, transportation costs, etc..); iii) livelihoods assessments or vulnerability profiles; iv) food and nutrition surveillance; and v) direct food aid monitoring (FAO, 2000). In practice, many of the pillars are difficult to operationalize due to local and international infrastructural, institutional and capacity constraints. For example, detailed market information such as transaction costs are difficult to track, even in the most developed markets. Moreover, because most production systems monitored are highly dependent on local weather and environmental conditions and scant data are available on area planted or yields, many EWS rely heavily on remotely-sensed data, such as NDVI (see Hutchinson, 1991), to make timely harvest forecasts. These projections are analyzed through vulnerability profiles to make food security assessments and predictions