Capacity Building in NASA Remote Sensing Data for Meteorological and Agricultural Communities in East Africa
Wednesday, 16 December 2015
Poster Hall (Moscone South)
Across the globe, planners and decision makers are hampered by a lack of historic data and scant in situ observations on which to base policy and action plans. Data is often sorely lacking in poorly developed regions such as East Africa where people are vulnerable to a changing climate, extreme weather events, and economies and food security are tied directly to rain fed agriculture or pastoral cultures. NASA global remote sensing observations and research are promising in this regard, as they have great potential to inform policy- and decision-making at global, regional and even local scales the world over, However that potential is not realized as often as it should for a variety of reasons: the data stores are often impenetrable requiring special expertise to “crack the code”, sustainability of observations remains a concern, and research and data are not focused on applications, thus results don’t “fit” in existing tools or are developed for a short-term science objective without long-term use in mind. Although there are good examples of the use of NASA Earth Science research and observations for applications, capacity is lacking and must be built to advance the use of remote sensing for applications and to ease transition of research to the stakeholder. Capacity building is a critical component to transition Earth science research results to stakeholder communities, and is more than traditional training,, it has been described as….”the process of developing and strengthening the skills, instincts, abilities, processes and resources that organizations and communities need to survive, adapt, and thrive in the fast-changing world. Best practices and lessons learned from recent capacity building efforts for Agricultural and Environmental Ministires in East African in support of a NASA-SERVIR Applied Science Project to provide estimates of hydrologic extremes tied to crop yield are described.