Explore using units for calculations with Normalized Difference Vegetation Index (NDVI). NDVI is a ratio of different light wavelength reflectance which can be used to map the density of green vegetation.

Students observe seasonal images of Monthly Leaf Area, looking for any changes that are occurring throughout the year.

Explore using units in calculations with the Leaf Area Index (LAI). LAI is a ratio that describes the number of square meters of leaves per square meter of available land surface. Because of the units in the ratio, it is dimensionless.

Use the Data Literacy Cube to guide students’ exploration of mapped data of the Earth System to enrich their observations and inferences.  This is a flexible resource that may be used with a variety of mapped images.  This activity requires a map of Earth data for students to evalu

This mini lesson engages students by watching a NASA video related to plant growth activity around the world using data from the NASA/NOAA Suomi NPP satellite and answering questions on these stability and change relationships.

After learning about the different characteristics of satellite data, students will describe the advantages and disadvantages of using two different satellites to study the Urban Heat Island Effect.  

Explore and connect to biosphere protocols in GLOBE. Each protocol has related Earth System Data Explorer datasets identified, as well.

This investigation introduces students to the significant environmental changes occurring around the world. The investigation uses NASA satellite images of Brazil to illustrate deforestation as one type of environmental change.

Students learn how to estimate the "energy efficiency" of photosynthesis, or the amount of energy that plants absorb for any given location on Earth. This is the ratio of the amount of energy stored to the amount of light energy absorbed and is used to evaluate and model photosynthesis efficiency.

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.