This activity is modified from the USDA/US Forest Services' lesson found in the Natural Inquirer newsletter. The purpose of this hands-on activity is to engage students in a similar process for monitoring forests as NASA scientists use to study the Biosphere, whereby they apply what they know of
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This mini lesson focuses on Landsat satellite data and how it is used to detect changes in land use. Students will answer questions based off of a NASA Video that features how Landsat data are interpreted in the forests of the Pacific Northwest, and gives examples of the effects insects and logging have with land management.
This content has been moved. You can find it under Creation of Urban Heat Islands Story Map link.
To investigate the different rates of heating and cooling of certain materials on earth in order to understand the heating dynamics that take place in the Earth’s atmosphere.
Students analyze and compare satellite data of Ocean Chlorophyll Concentrations with Sea Surface Temperatures, beginning with the North Atlantic region, while answering questions about the global patterns of these phenomenon.
These resources are intended to be used with teachers and students to help model how to apply data literacy skills to analyzing patterns as they relate to stability and change in COVID-19 (and related human geographic) and nitrogen dioxide data.
In this lesson, Observing Earth’s Seasonal Changes, students observe patterns of average snow and ice amounts as they change from one month to another, as well as connect the concepts of the tilt and orbit of the Earth (causing the changing of seasons) with monthly snow/ice data from January 2008
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.
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.