In this mini-lesson, students analyze soil moisture quantities associated with Hurricane Harvey around Houston, Texas on August 25, 2017.

In this activity, students explore three indicators of drought are: soil moisture, lack of precipitation, and decreased streamflows. Students investigate each of these parameters develop a sense for the effects of drought on land.

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.

This lesson walks students through the use of Landsat false-color imagery and identification of different land cover features using these as models. Building from an original GLOBE lesson, this resource features Google Slide and Jamboard to assist in both face-to-face and virtual learning.

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.

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 Hurricane Dynamics Implementation Sequence provides a series of lessons and activities for students to learn how hurricanes affect the different spheres within the Earth System by using maps and other geographic representations, tools, and technologies to acquire, process, and report informat

Students investigate the effects of Hurricane Sandy and make a scale model of the storm over the continental United States to assess the area of impact.

Students compare climographs for two locations to determine the most likely months to expect the emergence of mosquitoes in each location.

The purpose of this lesson is for students to compare data displays to determine which best answers the driving question. To do this they will evaluate the spread of the data and what the displays show.