At the core of scientific visualization is the representation of data graphically - through images, animations, and videos - to improve understanding and develop insight. Data visualizers develop data-driven images, maps, and visualizations from information collected by Earth-observing satellites, airborne missions, and ground measurements. Visualizations allow us to explore data, phenomena and behavior; they are particularly effective for showing large scales of time and space, and "invisible" processes (e.g. flows of energy and matter) as integral parts of the models.

Check out how Dr. James Smith, Research Scientist at Biospheric Sciences Branch at NASA Goddard Space Flight Center researches changes in the Biosphere using remote sensing techniques.

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.

Dr. Tom Loveland is a research geographer at EROS and director of the USGS Land Cover Institute. He has been engaged in research on the use of remote sensing for land use and land cover investigations for over 25 years and has conducted studies that have spanned local to global scales. He was among the first to create continental and global-scale land cover data sets derived from remotely sensed imagery.

Explore and connect to the GLOBE Air Quality protocol bundle. 

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.