This video provides tips for teachers on helping students make sense of data to help them understand and work with data. It is based on the work of Kristin Hunter-Thomson of Dataspire.org and uses data from the My NASA Data Earth System Data Explorer.
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This lesson walks students through the use of Landsat false-color imagery and identification of different land cover features using these as models.
This activity will help students better understand and practice estimating percent cloud cover.
This investigation is part of the NASA: Mission Geography Module "What are the causes and consequences of climate change?" that guides students through explorations in climatic variability and evidence for global climate change.
Students review Earth System phenomena that are affected by soil moisture. They analyze and evaluate maps of seasonal global surface air temperature and soil moisture data from NASA satellites. Building from their observations, students will select a location in the U.S.
Students analyze map visualizations representing the amount of Sun’s energy received on the Earth as indicated by the amount that is reflected back to space, known as “albedo”.
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 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.
This story map allows students to explore the urban heat island effect using land surface temperature and vegetation data in a 5 E-learning cycle. Students investigate the processes that create differences in surface temperatures, as well as how human activities have led to the creation of urban heat islands.
By matching pie charts with dates between 2002 and 2020, students will predict how air quality has changed over the past two decades. They will then use color-coded Air Quality Index signatures to assess the accuracy of their predictions.