The fires in Greece during the summer of 2007 devastated large tracks of forest and ground cover in this Mediterranean region. Students analyze these data to determine the scale, area, and percentage of the forest impacted by of these fires.
Educational Resources - Search Tool
The Great Smoky Mountains have a unique climate and weather pattern. Students will review a Landsat image and read about the history of the area and why Native Americans called the area “Shaconage.” Then they will answer the questions about what caused the unusual “blue smoke.”
Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.
NASA makes observations and collects data about ozone in the Great Lakes region. Read about the research and analyze related data.
Worldview is a valuable resource in understanding information about the atmosphere. Learn how to access models in order to answer your own questions.
In this 5E’s lesson, students observe maps that show smoke and AOD levels surrounding Fresno, California at the time when the 2020 Creek Fire was burning. Students construct a claim that identifies a relationship between fire-related data and air quality data.
Students will analyze images and data from a variety of NASA sensors and satellites depicting the wildfires of northern Canada to understand the state of the atmosphere at the time. Then they will answer a series of questions.
This lesson contains a card sort activity that challenges students to predict relative albedo values of common surfaces.
Students will observe monthly satellite data of the North Atlantic to identify relationships among key science variables that include sea surface salinity (SS), air temperature at the ocean surface (AT), sea surface temperature (ST), evaporation (EV), precipitation (PT), and evaporation minus pre
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.