How Remote Sensing Works
Remote sensing is used to collect massive amounts of data on landscapes, infrastructure, and more. But how does it work?
The electromagnetic spectrum and remote sensing
Energy travels in waves, whether it’s kinetic force acting on a solid object or visible light emitting from the sun.
All matter reflects, absorbs, or transfers energy in a unique manner. Advanced sensors can determine a lot about an unknown object by studying its interactions with energy sources.
With the right sensors in place, simple variations in visible light can lend clues about the objects below — for example, the health and growth potential of vegetation photographed from a thousand meters in the sky.
The wavelengths reflected off rocks, vegetation, soil, and manufactured objects are unique from a spectral standpoint. Each can be used to create a fingerprint that identifies an object’s type of matter, its density and chemical composition, and more.
Researchers use high-powered sensors that are uniquely tuned to capture evidence from a number of spectral bands for further analysis. That data could be used to measure a number of things about the terrain below, like the predominant mineral on a hillside, the density and composition of foliage, or the size of a mound of construction refuse.
Light on the visible spectrum is the most commonly studied metric in remote sensing, though ultraviolet radiation and infrared light are valuable for specialty purposes. While some sensors are equipped to document infrared light, most visual documentation systems use aerial photography and photogrammetry
to accumulate data.
How photogrammetric remote sensing works
Remote sensing uses airborne sensors to collect wavelength data from objects on the ground in the form of images, infrared readings, and more.
In one popular method, photogrammetry, source light from the sun bounces off the target, which is collected by sensors on a UAV, manned aircraft, or satellite.
That data is pinned using GPS positioning, and sent to a server for collection and normalization for atmospheric factors, such as humidity, time, date, and more.
From there, that data can be processed using GIS technology to create a measurable 3D survey map. Differences in data over time or variances in color, chemical composition, temperature, or other factors can provide on-the-ground insight from high above.
What is spatial resolution in remote sensing?
Spatial resolution defines the amount of on-the-ground visual data collected in each image pixel. This metric is usually determined by measuring the physical size of a pixel represented in meters, so 100m resolution involves a pixel that documents 100 meters by 100 meters on the ground.
In remote sensing, resolution is a measure of the electromagnetic wave that includes radiometric and temporal components as well. Other common metrics used in remote sensing are:
Spectral resolution, which describes the capacity of a sensor to document color, infrared light, or other electromagnetic wavelengths.
Temporal resolution, which describes the time elapsed between images or data sets.
High-resolution remote sensing will produce visually, spectrally, and spatially rich data sets, complete with robust metadata. In order to ensure the accuracy and quality of your data set, be sure to check the metadata for information on how your data was produced, when, and by whom.