SERVIR, spanish for "to serve", - is a regional visualization and monitoring system that integrates Earth observations, forecast models, and in situ data to provide timely environmental decision support products for the general benefit of society. Funded primarily by USAID, and coordinated by NASA and USRA's Science and Technology Institute at Marshall Space Flight Center, SERVIR serves its customers via a network of regional nodes around the world. Besides acting as a platform for the delivery of services and applications, the project also facilitates collaboration and coordination between federal agencies, fosters international partnerships, and supports national governments, universities, NGOs, and the private sector.
The project scope encompasses nine societal benefit areas as defined by the Group on Earth Observations (GEO): agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and weather. SERVIR currently addresses these benefit areas for Central America and the Dominican Republic, East Africa, and the Hindu Kush-Himalayas via regional partnerships in Panama City, Nairobi, and Kathmandu, respectively. Other regional nodes are planned. Within their region, the nodes are also responsible for coordinating with other national and international organizations to deal with matters of climate change, environmental monitoring, disasters, weather, civil protection, and mapping.
SERVIR's geospatial data service has proven especially valuable in times of critical need. Over the past five years, SERVIR has provided analytical products for the monitoring and assessment of nearly 40 natural disasters and environmental threats across the three regions. In order to improve its ability to provide timely information, SERVIR is currently developing its own Earth imaging systems for both orbiting and aerial platforms, as well as designing and implementing in situ instrumentation networks for monitoring vulnerable environments.
Utilizing resources available through SERVIR, scientists use applied remote sensing to map Costa Rica's forest cover.