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Earth Observations for Humanitarian Applications

05 Junho 2024 - 19 Junho 2024

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

 

Assessing the Impacts of Fires on Watershed Health

05 Julho 2023 - 12 Julho 2023

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.

Fundamentals of Machine Learning for Earth Science

19 Abril 2023 - 03 Maio 2023

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.