Human populations are expanding and changing rapidly in many developing countries. Governments need to keep pace with these changes to ensure that resources are planned and delivered appropriately. For example, ensuring that there are enough school places for children. The traditional way that governments plan resource allocations is through the data collected in a national Census. These are huge undertakings as they cover every person within a country and therefore are time consuming and expensive to plan and undertake. This expense often means that census data collection is conducted just once every 10 years in most countries. This means that by the time the results of a new census are published changes in socioeconomic conditions can be seen but often the data do not contain enough information telling us why or how these changes occurred. In developing countries the majority of rural communities rely on natural resources and environmental products for food, fuel, building materials and medicines.Understanding relationships between poverty and the environment have important policy implications for sustainable human development and ecological conservation. Past attempts to study these relationships have been limited by data availability and a resulting focus on small case study examples from single time periods. The USES project examined population-environment relationships using data with unrivaled detail in household level changes in socioeconomic conditions and environmental characteristics. The overall objective of the project was to couple data derived from satellite images with household surveys to explore ways in which we can increase our understanding of population-environment relationships.
The research is important for society because the quality and quantity of data sets such as satellite imagery are becoming increasingly common at cheaper costs. There is increasing evidence that smaller scale changes and characteristics of landscapes that can be detected in satellite imagery could be used to inform policy makers about potential socioeconomic changes in these regions. For example, in some villages, household roof material changes from straw to metal as incomes rise and peoples confidence in their medium term incomes increase. These changes roof material can be detected in fine-grained satellite images. If these changes can be detected automatically from satellite imagery it may be possible to use this information at the government level to indicate a region that is going through a positive socioeconomic change. This would have several benefits to society including reducing the costs of expensive household surveys to monitor changes between census periods (the satellite data would not replace census or household surveys but would supplement the information available to decision makers). The USES project wanted to examine if there was more to be gained by looking at fine-grained data (household level socioeconomic conditions and 2 m spatial resolution satellite imagery which means individual houses and some vehicles can be detected in the imagery).
