In search of a global model of cultivation: using remote sensing to examine the characteristics and constraints of agricultural production in the developing world

In most developing countries, people are heavily reliant on inexpensive, locally grown food. However, while dependence on cropping crosses national and continental boundaries, the selection of land for cropping has adapted to the available conditions. Recent analyses conducted by the Famine Early Warning System Network (FEWS NET) show that the characteristics of cropped area differ in different countries, indicating that the critical variables influencing the selection of location for the establishment of agriculture also vary. This study looks at a selection of FEWS NET work using high resolution remotely sensed imagery to analyze cropped areas in Afghanistan, Eritrea, Guatemala, Haiti, Mali, Mozambique, South Sudan, Burkina-Faso and Tajikistan. This analysis identifies similarities and differences in the significant factors impacting cropped area in each country. Furthermore, the effectiveness of the application of high-resolution imagery to estimating cultivation is assessed. The results highlight the context-specific nature of cultivation and the effectiveness of very high-resolution satellite imagery for crop estimation. The results also suggest that a single, generally applicable model of cultivation will require complex interactions between economic, governmental and population characteristics in addition to local landscape/geophysical properties.