Students will identify and describe the relationship between land cover classification and surface temperature as they relate to the urban heat island effect. Students will also describe patterns between population density and the locations of urban heat islands.
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Students will analyze how surface (skin) temperatures vary across a community and determine what factors contribute to this variation. Students will describe how human activity can affect the local environment.
Students identify patterns and describe the relationship between chlorophyll concentration and incoming shortwave radiation.
This story map lesson plan allows students to explore global phytoplankton distribution using chlorophyll concentration data in a 5 E-learning cycle. Students will investigate the processes that allow phytoplankton populations to thrive, as well as how their role in the carbon cycle impacts the other spheres of the Earth System.
Students interpret a double bar/column chart comparing the number of tropical cyclones in different locations.
This lesson, "Awenasa Goes to Camp!," is a data analysis activity that presents maps of NASA Earth satellite data for a variety of locations across the United States for four unidentified months throughout the year. Each location represents a real science camp th
Learners follow adventurous camper, Awenasa, as she travels the United States and attends various camp locations throughout the year. Learners analyze data to find her location among the various campsites using monthly averaged NASA satellite data (Cloud Coverage, Surface (S
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.
This graphic organizer may be used to help students analyze the processes and components of Earth System phenomena.
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.