This investigation is part of the NASA: Mission Geography Module "What are the causes and consequences of climate change?" that guides students through explorations in climatic variability and evidence for global climate change.
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This investigation introduces students to the significant environmental changes occurring around the world. The investigation uses NASA satellite images of Brazil to illustrate deforestation as one type of environmental change.
Examine the images to see the projected differences in land use between 1900 and 2100.
This mini lesson focuses on Landsat satellite data and how it is used to detect changes in land use. Students will answer questions based off of a NASA Video that features how Landsat data are interpreted in the forests of the Pacific Northwest, and gives examples of the effects insects and logging have with land management.
This lesson is taken from NASA's Phytopia: Discovery of the Marine Ecosystem written in partnership with Bigelow Laboratory for Ocean Science with funding from the National Science Foundation.
Students use Phytopia: Exploration of the Marine Ecosystem, a computer-based tool, to investigate various phytoplankton species and topics relating to phytoplankton biology.
Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.
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.
This story map allows students to explore the urban heat island effect using land surface temperature and vegetation data in a 5 E-learning cycle. Students investigate the processes that create differences in surface temperatures, as well as how human activities have led to the creation of urban heat islands.
Students will describe how the spread of COVID-19 is affected by population density and explain why patterns in the spread of COVID-19 are happening over time.