Remote sensing combines science and technology to acquire information about an object, area, or phenomenon by measuring reflected and emitted radiation using a device that's without direct physical contact (typically from satellite or aircraft).
Remote sensing data plays a crucial role at bp by providing a rich data source onto which analysis is performed.
Using computer science techniques including machine learning, artificial intelligence, big data analysis and prediction algorithms features are extracted, changes are detected, forecasts are produced, and invisible phenomena are unmasked. It helps us turn data into information, information into decisions, and decisions into action. Remote sensing improves the safety, efficiency and decision making. For others, the use of imagery is simpler and more obvious, but just as powerful. It provides us with beautiful and recognisable basemaps and real-life references onto which we can display or digitise our data.
In short, it helps us manage, visualise and analyse spatial data in order to solve real world problems.
But how does it work?
To answer this, we need to think about the electromagnetic spectrum.
The Electromagnetic Spectrum
Electromagnetic energy, produced by the vibration of charged particles, travels in waves and spans a broad spectrum from very long radio waves to very short gamma rays.
The human eye can only detect only a small portion of this spectrum called visible light, and we require remote sensing technology to detect all other forms of electromagnetic energy.
Electromagnetic energy has different wavelengths (the distance from wave crest to wave crest) and wave frequencies (the number of peaks passing a fixed point in space per unit time). In remote sensing, it is most common to categorise electromagnetic waves by their wavelength location within the electromagnetic spectrum. Visible light sits in the middle of that range of long to shortwave radiation.
The Earth's atmosphere stops most types of electromagnetic radiation from space from reaching Earth's surface. Some waves are absorbed or scattered by elements in the atmosphere, like water vapor and carbon dioxide, while some wavelengths allow for unimpeded movement through the atmosphere.
The illustration below shows how far into the atmosphere different parts of the EM spectrum can go before being absorbed. Only portions of radio and visible light reach the surface (credit: STScI/JHU/NASA).
When electromagnetic energy is incident on any given earth surface feature, three fundamental energy interactions with the feature are possible: reflection, absorption, and/or transmission. The interrelationship among these mechanisms shows that:
The proportions of energy reflected, absorbed, and transmitted will vary for different earth features, depending on their material type and condition. These differences permit us to distinguish different features in an image.
The wavelength dependency means that, even within a given feature type, the proportion of reflected, absorbed, and transmitted energy will vary at different wavelengths. Thus, two features may be indistinguishable in one spectral range and be very different in another wavelength band.
The primary source of the energy observed by satellites, is the Sun. The amount of the Sun’s energy reflected depends on the roughness of the surface and its albedo, which is how well a surface reflects light instead of absorbing it. Snow, for example, has a very high albedo, reflecting up to 90% of the energy it receives from the Sun, whereas the ocean reflects only about 6%, absorbing the rest. Often, when energy is absorbed, it is reemitted, usually at longer wavelengths. For example, the energy absorbed by the ocean gets re-emitted as infrared radiation.
The reflectance characteristics of earth surface features may be quantified by measuring the portion of incident energy that is reflected. This is measured as a function of wavelength and is called spectral reflectance. This spectral “fingerprint,” acts as a unique identifier just like a human fingerprint.
Remote sensing scientists use this information to identify different Earth features. The spectral characteristics of an object and have a strong influence on the choice of wavelength region(s) of remote sensing data are required for a particular application. And therefore, the number of spectral bands detected by a given sensor, its spectral resolution, determines how much differentiation can be identified between materials.
Watch the video below to explore the basic principles used in remote sensing to record the things that we can't see with our eyes - like the health of plants on the ground. It explains the basic principles of the electromagnetic spectrum, bands and spectral resolution in data and the uses of spectral data to answer science questions (National Ecological Observatory Network, 2015, Mapping the Invisible: Introduction to Spectral Remote Sensing).
For more educational resources, you can use the bp Educational Service to bring real-world science to life with inspiring curriculum-based content for 4 to 19 year olds.