Remote sensing scientists use sensors to analyze data and solve regional, national and global concerns. For instance, natural resource management, urban planning, and climate and weather prediction are applications of remote sensing. Many scientists develop new sensor systems, analytical techniques, or new applications for existing systems. 

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Earth is made up of five major parts or subsystems: the Atmosphere, Hydrosphere, Biosphere, Cryosphere, and Geosphere. Each major part is connected to the other parts in a complex web of processes.

My NASA Data has recently released several new resources, StoryMaps, for use in educational settings.

An environmental planner tries to minimize the environmental impacts of housing, industrial, and transportation-related construction projects. Environmental planners help project managers navigate the environmental permitting process where they review a site to investigate potential environmental effects. This includes the effects of natural disasters.

Environmental engineers use the basis of engineering, soil science, biology, and chemistry to develop solutions to problems in the environment. Some of their efforts involve recycling, waste disposal, public health, water and air pollution control. Many are engaged in solving practical, yet global issues such as unsafe drinking water, climate change, and environmental sustainability.

Oceanography covers a wide range of topics, including marine life and ecosystems, ocean circulation, plate tectonics and the geology of the seafloor, and the chemical and physical properties of the ocean.

Scientific data are often represented by assigning ranges of numbers to specific colors. The colors are then used to make false color images which allow us to see patterns more easily. Students will make a false-color image using a set of numbers.

Information from satellites if often used to display information about objects. This information can include how things appear, as well as their contents. Explore how pixel data sequences can be used to create an image and interpret it.

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.