Constructing an archive of global environmental data accessible to all;
Developing appropriate image-processing algorithms that produce relevant, processed data layers;
Developing robust predictive models for biodiversity, agriculture, health, poverty, and environmental changes through time;
Linking model outputs to the formulation of environmentally sound policies that are effective at the grass-roots level; and
Producing a monitoring and feedback system that returns quality field data from project areas, to improve the modelling process.
Since human welfare issues involve understanding change over time, archival data (historical maps, aerial photography, pre-satellite era data, and historical satellite data) are key resources that must be preserved. Continued long-term monitoring and archiving of data from current satellite platforms are vital for the same reasons. It would be beneficial for funding considerations and planning of satellite missions to be made with the long term in mind, although funding streams are often not continuous and current project durations tend to be for only one to two years. Workshop participants identified the lack of time series and real-time data from the National Aeronautics and Space Administration (NASA) and other data sources as major barriers to the application of remote sensing technologies to human welfare improvement. Decisions will also have to be made on whether resources are better spent on the collection of more remotely sensed data or on more data analysis.
Potential benefits from the use of remote sensing data and information in food security will be enhanced and made more affordable both by improvements in current technologies and by additional international competition in the development of satellites and sensors, which will increase data availability. Non-satellite technologies for remote sensing could also be advanced, including enhanced aerial photography and the use of unmanned aerial vehicles. Finally, new types of data collection, analysis, and access technologies could be developed to make comparable data for global and regional estimates of the extent of tillage, land use, and land cover change. Because of the growth of urban populations throughout the world and the limited amount of land available for agriculture, agricultural land is a resource that will require careful monitoring and protection.