About Remote Sensing Data

Remote sensing is the science of studying things without touching them. You can use remote sensing systems, to study how Earth systems change over time. For example, scientists use, high powered cameras, not unlike the camera in your smartphone, mounted on airplanes and satellites to capture images of the earth as it changes over time. Other sensors such as lidar (light detection and ranging) are used to collect height data which can be used to measure how trees and forests and even development changes over time.

Active vs Passive Remote Sensing

There are two types of remote sensing sensors: active and passive sensors. Passive sensors measure existing energy, often from the sun. The camera in your smartphone or iPad is an example of a passive remote sensing sensor. To capture a picture, this camera records sunlight, reflected off objects. In contract, an active remote sensing sensor creates its own energy source. Lidar (also sometimes referred to as active laser scanning) is an example of an active remote sensing sensor. Lidar systems have a laser on board that emits light that then reflects off of objects, like trees, on the Earth’s surface.

Learn why Earth Data Science skills are important for finding your next job.

Below you will find lessons that cover how to find, download, work with, visualize and analyze remote sensing data including Landsat, MODIS, NAIP and LiDAR in R or Python.