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.
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Students use Phytopia: Exploration of the Marine Ecosystem, a computer-based tool, to investigate various phytoplankton species and topics relating to phytoplankton biology.
This mini lesson engages students by watching a NASA video related to plant growth activity around the world using data from the NASA/NOAA Suomi NPP satellite and answering questions on these stability and change relationships.
This story map allows students to explore the formation and impacts of ash and aerosols from volcanic eruptions around the world in a 5 E-learning cycle. They will investigate how ash and aerosols produced from volcanic eruptions are hazardous to the human ecosystem, and will analyze concentrations of aerosols from a volcanic eruption over time.
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
Air, Water, Land, & Life: A Global Perspective
Students learn how to estimate the "energy efficiency" of photosynthesis, or the amount of energy that plants absorb for any given location on Earth. This is the ratio of the amount of energy stored to the amount of light energy absorbed and is used to evaluate and model photosynthesis efficiency.
The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.
The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner determine relationships among variables.