Using Satellite Remote Sensing Data in a Spatially Explicit Price Model: Vegetation Dynamics and Millet Prices
将生长季适宜性信息与西非干旱地区的小米价格整合到一个模型中，生成连续空间价格图，并结合未来1-4个月的遥感植被数据，构建价格变动的先行指标，用于粮食危机早期预警。
Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the world. Here we present a model that integrates information on the suitability of the growing season and millet prices in the dry central and northern areas of West Africa. The model is used to create spatially continuous maps of millet prices. By coupling the model with remote sensing vegetation data estimated one to four months into the future, we create a leading indicator of potential price movements for early warning of food crises. <i></i>