The purpose of this activity is for students to create a desktop soil profile based on the biome region of the United States where your school is located.
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The advance-and-retreat cycle of snow cover drastically changes the whiteness and brightness of Earth. Using two maps created using NASA satellite data for 2017, students review the seasonal differences of snow and ice extent and answer questions on their observations.
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 observe seasonal images of Monthly Normalized Difference Vegetation, looking for any changes in vegetation that are occurring throughout the year. They put the images in order based on what they know about seasonal changes.
Students watch a video and answer questions on Dr. Patrick Taylor (Atmospheric Scientist, NASA Langley Research Center) as he discusses the study of clouds and Earth's energy budget by analyzing data from Low Earth Orbit satellites.
Students watch a visualization video and answer questions on the potential of increasing megadroughts in the southwest and central United States from 1950-2095 using models created by soil moisture data.
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, help the learner determine relationships among variables.
The Earth System Satellite, help the learner visualize how different Earth system variables change over time. In this lesson, students will graph six points for a location over one year.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships, identify patterns, and determine relationships among variables.