In this activity, students explore the Urban Heat Island Effect phenomenon by collecting temperatures of different materials with respect to their locations.  

Students analyze Landsat images of Atlanta, Georgia to explore the relationship between surface temperature and vegetation.

Examine (daytime) surface temperature and solar radiation received at locations found near similar latitudes using NASA Data.

This StoryMap 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. 

In this StoryMap students will learn about the different components of the Earth's Energy Budget, where in the Earth System energy is being absorbed and reflected, and how features of the Earth such as clouds, aerosols, and greenhouse gases, can cause variations in the flow of energy into and out of Earth Systems. In the final section, students make a claim as to why the Earth's Energy Budget is currently out of balance and provide evidence to support their reasoning. 

Explore and connect to the GLOBE Urban protocol bundle. 

Explore and connect to the GLOBE Weather protocol bundle. 

This resource helps to identify and access GLOBE protocols and hands-on learning activities that complement the Urban Heat Island Effect phenomenon. 

GLOBE protocols can be used to collect many types of data to examine urban heat islands and their effects on the environment. Students can use the protocols to collect data and share their data with other GLOBE students around the world. Students can also conduct their own investigations and see how their data related to global patterns by using GLOBE and My NASA Data together.

Students will analyze the monthly seasonal chlorophyll concentration images in our global oceans for the four different months of 2024, and then answer the following questions.

A model analyst develops models to help visualize, observe, and predict complicated data. Model analysis is the process of taking large amounts of data and separate it into a structure that makes it intelligible to the binary process of computers. An analyst also manages the flow of information between different user groups through the use of relational databases.