Protecting Guyana's Mangroves and Communities with NASA Satellites
SERVIR is helping protect biodiversity and human lives in Guyana by working with communities to keep a watchful eye on the health of coastal mangrove forests.
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SERVIR is helping protect biodiversity and human lives in Guyana by working with communities to keep a watchful eye on the health of coastal mangrove forests.
May 22 is World Biodiversity Day, and this year we’re highlighting SERVIR’s commitment to protecting biodiversity in the Amazon Rainforest.
The U.S. Forest Service is hosting webinars to introduce an online training course on Remote Sensing for Forest Cover Change Detection. This activity comes as part of the USAID-funded SilvaCarbon initiative.
Mangrove forests do a lot of heavy lifting to mitigate the effects of coastal flooding. As NASA turns the spotlight on oceans this Earth Day, learn how the joint NASA-USAID SERVIR program is using Earth satellites to support these unique ecosystems that protect 15% of the world’s coasts.
|Stephanie A. Jiménez, Christine Evans, Vanesa Martín, Jacob Ramthun
The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation is the culmination of a two-year collaboration between NASA SERVIR and SilvaCarbon.
According to the World Wildlife Fund, over 2 billion people rely on forests for shelter, livelihoods, water, food, and fuel security. Forests even help renew our air supply, as they take in large amounts of carbon dioxide and release oxygen.
This workshop is the third in a series offered by SERVIR Amazonia focused on using remote sensing to monitor mangroves in Guyana.
The Monitoring and Evaluation of Mangroves in Guyana service brings Synthetic Aperture Radar (SAR) and other remote sensing resources to map the extent and structure of mangrove forests along the coast of Guyana.
Collect Earth Online is a custom built, open-source, satellite image viewing and interpretation system developed by SERVIR, FAO, and other partners as a tool for use in projects that require land cover and/or land use data.