Students can interact with NASA data to build a custom visualizations of local, regional, or global plant growth patterns over time, using the Earth System Data Explorer to generate plots of satellite data as they develop models of this phenomenon.
Educational Resources - Search Tool
NASA visualizers take data – numbers, codes – and turn them into animations people can see and quickly understand.
NASA Earth Observations (NEO) strives to make global satellite imagery as accessible as possible. Here you can browse and download imagery of satellite data from NASA's constellation of Earth Observing System satellites.
My NASA Data has recently released several new resources, StoryMaps, for use in educational settings.
The purpose of this activity is to have students use an Earth Systems perspective to identify the various causes associated with changes to Earth's forests as they review Landsat imagery of site locations from around the world.
My NASA Data StoryMaps provide an engaging and interactive way to explore Earth science topics using real NASA data. By integrating storytelling with interactive technology, these resources make complex scientific concepts more accessible and relevant to students.
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.
The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.
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 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.