Explore using units for calculations with Normalized Difference Vegetation Index (NDVI). NDVI is a ratio of different light wavelength reflectance which can be used to map the density of green vegetation.
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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 compare climographs for two locations to determine the most likely months to expect the emergence of mosquitoes in each location.
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.
In Earth System Science, underling factors affecting observable phenomena can be difficult to identify and describe. The Iceberg Diagram diagram uses the metaphor of an iceberg to demonstrate the idea of visible vs hidden as it relates to Earth science phenomena. This teaching strategy helps students to see beyond the obvious and to develop their awareness of the underlying causes, relationships, and/or conditions that can contribute to phenomenological events. It also provides a framework for digging deeper into phenomena-driven lessons in Earth Science.
Students review the NASA video showing biosphere data over the North Atlantic Ocean as a time series animation displaying a decade of phytoplankton blooms and answer questions.
This story map lesson plan allows students to explore global phytoplankton distribution using chlorophyll concentration data in a 5 E-learning cycle. Students will investigate the processes that allow phytoplankton populations to thrive, as well as how their role in the carbon cycle impacts the other spheres of the Earth System.
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.