AS Africa registered a significant first, becoming the first continent in the world to complete its digital landuse data, new revelations emerged about its trees outside of key forests in Africa
There are more trees in Africa than initially thought, with the latest study showing there are about 7 billion trees on the continent, not counting the continent’s major woodlands like the Congo rainforest. This is according to a recent study by the Food and Agriculture Organisation (FAO).
NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online webinar series: Earth Observations for Humanitarian Applications. Refugees, internally displaced people (IDPs), and other displaced populations are made more vulnerable to climate change impacts due to their socio-political marginalization. This three-part, intermediate training presents concrete strategies for mapping localized climate conditions with risks faced by refugee and IDP communities around the world.
The training will focus on flood risk assessments and specific challenges for assessing flood risk in refugee and IDP camps; gauging long-term heat stress in refugee camps and the challenges with decision making surrounding heat risk; and monitoring drought effects on agricultural landscapes in refugee settings using Earth observations (EO) to explore the correlations between anomalies in crop productivity and weather-based factors
NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online webinar series: Assessing the Impacts of Fires on Watershed Health. This advanced-level, three-part training will focus on using remote sensing observations for monitoring post-fire impacts on watershed health. Specifically, this training will highlight uses of NASA Earth observations (EO) for pre-fire land cover mapping, watershed delineation and stream mapping, post-fire burn severity mapping, and pre- and post-fire riverine and freshwater water quality.
NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new online introductory webinar series: Fundamentals of Machine Learning for Earth Science. This three-part training, presented in English and Spanish, is open to the public and will provide attendees an overview of machine learning in regards to Earth Science, and how to apply these algorithms and techniques to remote sensing data in a meaningful way. Attendees will also be provided with end-to-end case study examples for generating a simple random forest model for land cover classification from optical remote sensing. We will also present additional case studies to apply the presented workflows using additional NASA data.
A map is a symbolic depiction emphasizing relationships between elements of some space, such as objects, regions, or themes.
