Students will analyze the monthly seasonal chlorophyll concentration images in our global oceans for the four different months of 2017, and then answer the following questions.
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Students will analyze the mapped plot of the historic Ocean Chlorophyll Concentrations at key locations around the world for the period of 1998-2018.
Students analyze and compare satellite data of Ocean Chlorophyll Concentrations with Sea Surface Temperatures, beginning with the North Atlantic region, while answering questions about the global patterns of these phenomenon.
In this interactive, students will explore safe methods for viewing the Sun at home or in the classroom, including using solar eclipse glasses and a pinhole projector. The interactive includes a video that explains how the projector works and how to build one.
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.
Carbon dioxide concentration in the atmosphere is affected by many processes including fires, deforestation, and plant respiration. Students will evaluate a Landsat image to determine the rate of carbon dioxide sequestration in a particular area.
In this story map lesson students will learn how living with a star can teach us about our universe. Through a series of learning activities, students will examine the benefits and hazards of living with a star, describe and/or demonstrate how we use eclipses to study the Sun and its features, and investigate how our Sun may be used to learn about other stars and our universe.
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.
Information from satellites if often used to display information about objects. This information can include how things appear, as well as their contents. Explore how pixel data sequences can be used to create an image and interpret it.
Scientific data are often represented by assigning ranges of numbers to specific colors. The colors are then used to make false color images which allow us to see patterns more easily. Students will make a false-color image using a set of numbers.