Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.
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The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, identify patterns, and determine relationships among two variables in three months.
This activity was developed by NASA's Global Precipitation Measurement (GPM) team as an introductory experience to a series of lessons about water resources on Earth.
Students will explore the Nitrogen Cycle by modeling the movement of a nitrogen atom as it passes through the cycle. Students will stop in the different reservoirs along the way, answering questions about the processes that brought them to the different reservoirs.
This lesson was based on an activity from UCAR Center for Science Education.
Help learners envision themselves as explorers, scientists, technologists, engineers, and mathematicians as they venture into the summer months. Download the PDF of the two sided document on cardstock and have students imagine and illustrate themselves!
This mini-lesson guides students' observations of soil moisture anomalies (how much the moisture content was above or below the norm) for the continental US in May 2018.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner determine relationships among variables.
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.
The activities in this guide will help students understand variations in environmental parameters by examining connections among different phenomena measured on local, regional and global scales.
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.