Students will use NASA Satellite data of aerosol optical depth and sulfur dioxide as a tool to find evidence of volcanic activity at Kilauea, HI.
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Using various visualizations (i.e., images, charts, and graphs), students will explore the energy exchange that occurs when hurricanes extract heat energy from the ocean. This story map is intended to be used with students who have access to a computing device in a 1:1 or 1:2 setting.
Students will analyze and interpret graphs to compare the flow of (shortwave) energy from the Sun toward China over the course of a year on cloudy versus clear days. Students will draw a conclusion and support it with evidence.
This lesson, "Awenasa Goes to Camp!," is a data analysis activity that presents maps of NASA Earth satellite data for a variety of locations across the United States for four unidentified months throughout the year. Each location represents a real science camp th
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
By investigating the data presented in a model that displays extreme summer air temperatures, students explain energy transfer in the Earth system and consider the impact of excessive heat on local communities.
Students construct explanations about Earth’s energy budget by connecting a model with observations from side-by-side animations of the monthly mapped data showing incoming and outgoing shortwave radiation from Earth’s surface.
This lesson walks students through the use of Landsat false-color imagery and identification of different land cover features using these as models.
The Earth System Satellite Images help students observe and analyze global Earth and environmental data, understand the relationship among different environmental variables, and explore how the data change seasonally and over longer timescales.
By matching pie charts with dates between 2002 and 2020, students will predict how air quality has changed over the past two decades. They will then use color-coded Air Quality Index signatures to assess the accuracy of their predictions.