This mini lesson engages students with answering questions on cause and effect relationships by watching a NASA video related to changing forests in the Pacific Northwest from 1984 to 2011.
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Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.
Students will use NASA Satellite data of aerosol optical depth and sulfur dioxide as a tool to find evidence of volcanic activity at Kilauea, HI.
Students identify and classify kinds of land cover (such as vegetation, urban areas, water, and bare soil) in Landsat satellite images of Phoenix, Arizona taken in 1984 and 2018.
Students review a visualization showing a global view of the top-of-atmosphere longwave radiation from January 26 and 27, 2012. They review the supporting text and analyze the data in the visualization to answer questions.
Guided by the 5E model, this lesson allows students to work together to uncover how changes in sea ice extent in the Arctic and Antarctic regions are connected to Earth’s energy budget.
This activity invites students to simulate and observe the different effects on sea level from melting sea-ice.
This story map lesson plan allows students to explore ocean circulation patterns as they relate to the world's ocean garbage patches using NASA ocean currents data. Students will investigate the forces that contribute to ocean circulation patterns, and how debris, especially plastics, travel from land to the garbage patches.
Learners follow adventurous camper, Awenasa, as she travels the United States and attends various camp locations throughout the year. Learners analyze data to find her location among the various campsites using monthly averaged NASA satellite data (Cloud Coverage, Surface (S
Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.