What Are the Different Types of Remote Sensing Sensors?
Remote sensing is a key technology that allows the gathering of information from the Earth's surface without being in physical contact with the studied areas or objects. This technology is an integral part of Geographic Information Systems (GIS), environmental monitoring, agriculture, forestry, urban planning, disaster management, military operations, and observations related to the planet.
Any remote sensing device consists of a remote sensing sensor. The sensor's purpose is to catch and measure the electromagnetic energy that is either reflected, emitted, or scattered by objects found on the surface of the Earth. Generally speaking, the information about the energy that is caught can be processed in order to identify different materials, as well as to track changes in such materials.
Each application utilizes different types of remote sensing devices. Some of the sensors aim at capturing visible imagery, while some sensors are responsible for measuring infrared radiation, microwave signals, and certain narrow spectral bands that are not visible to humans.
This guide provides essential information on the widely used kinds of remote sensing devices, how they work, and the fields of their application.
What Is a Remote Sensing Sensor?
Remote sensing sensors are devices that are able to detect signals in the form of electromagnetic radiation or the like without physical contact.
In terms of specific remote sensing sensor technologies used for measurement, their various functions can be structured as follows:
Detection of sunlight
Detection of heat radiation
Detection of microwaves
Detection of laser beams
Detection of spectral bands
Detection of relief
Detection of atmosphere
Remote sensing sensors can be fixed on different carrier objects, such as:
Satellite
Aeroplane
Land-based system
Spacecraft
Received data is transformed into digital information and processed via remote sensing and geographic information systems software.
How Do Remote Sensing Sensors Work?
Remote sensing sensors operate by sensing the radiant energy that interacts with surfaces or objects.
Passive sensors use energy that comes primarily from naturally occurring sources. Due to their physical and chemical characteristics, surfaces may reflect energy differently. For instance, vegetation reflects large amounts of near-infrared radiation while water tends to absorb most of it.
Active sensors create their own energy and measure the amount of signal reflected off the target. As a result, they are able to gather data without relying on the sun and can carry out observations at night as well.
Here is a simple workflow of remote sensing:
Energy source → Target interaction → Sensor detection → Data collection and transmission → Image processing and analysis
Major Types of Remote Sensing Sensors
Remote sensing sensors can be categorized in a number of ways. One way is by distinguishing between passive and active sensors. Sensors can also be divided according to the parts of the electromagnetic spectrum measured by them.
Optical Sensors
Optical sensors detect electromagnetic radiation mainly in the visible and near-infrared regions of the spectrum.
The technology makes it possible to capture images of the Earth’s surface.
Optical remote sensing systems may contain bands such as
Blue
Green
Red
Near-infrared (NIR)
Shortwave infrared (SWIR)
Multispectral satellite and drone cameras can serve as examples of sensors used in optical remote sensing.
Uses of Optical Sensors
Optical sensors are quite common in:
Land cover mapping
Vegetation monitoring
Urban mapping
Forest monitoring
Water body mapping
Change detection
Environmental assessment
However, traditional optical sensors are influenced by clouds and require adequate lighting.
Multispectral Sensors
Multispectral sensors operate by capturing energy across various spectral bands.
Unlike a normal RGB camera, which captures only red, green, and blue wavelengths, the multispectral sensor can also capture additional wavelengths, for example, the shortwave red.
This implies that the multispectral sensor will be collecting data in Blue plus Green plus Red plus Near-Infrared.
The advantage of having the extra spectral data is that it makes it possible for a user to differentiate the materials that are visually similar in the view.
Applications of Multispectral Sensors.
Multispectral remote sensing technology has important applications in:
Precision agriculture
Crop health monitoring
Land cover classification
Vegetation mapping
Soil analysis
Water quality monitoring
Forestry
Environmental monitoring
Also, it can use multispectral imagery for the calculation of indices such as NDVI.
Hyperspectral Sensors
Hyperspectral sensors are those sensors that are capable of acquiring data in a wider number of narrow spectra.
Though multispectral sensors usually employ a few broad bands, hyperspectral sensors can acquire a few hundred bands.
This allows for the creation of a unique spectral signature for each pixel.
Such a high spectral resolution makes it possible for analysts to discriminate between various materials based on their spectral signatures.
Hyperspectral remote sensing has applications across:
Mineral identification
Crop stress detection
Species classification
Soil characterization
Water quality analysis
Environmental monitoring
Geology mapping
Material identification
Hyperspectral information provides insights that cannot be gained with the help of normal RGB imagers.
Thermal Sensors
Thermal remote sensing sensors are devices that can identify and measure thermal infrared radiation emitted by materials based on their temperatures and emissivity.
Thermal sensors are different from visible light sensors as they rely less on the reflected sun's rays and more on the emitted energy.
Thermal images provide temperature variations that are not detectable in regular photographs, thus being able to show other temperature differences.
The main uses of thermal sensors are:
Wildfire detection
Inspections in industry
Energy analysis of buildings
Monitoring water stress in agriculture
Detection of heat losses
Monitoring volcanic activity
Urban heat island analysis
Inspection of infrastructures
Thermal sensors can be installed on a satellite, airplane, or drone.
Radar Sensors
Radar is a form of remote sensing technology which gives signals in the microwave range to the Earth’s surface to get the reflected signal back.
Because radar derives its electromagnetic signals from itself, it does not rely on light from the sun or time of the day. Some radar signals can penetrate cloudy skies, making it indispensable in the monitoring process where cloudy weather recurs frequently.
One of the most popular radar techniques in remote sensing is Synthetic Aperture Radar (SAR).
Applications of Radar Sensors
The main functions of radar remote sensing involve:
Flood mapping; comparison of ground changes; soil moisture measurements; emergency response activities; sea ice monitoring; agricultural processes; organization of forested areas; supervision of buildings.
The processed information received from SAR can also be analyzed by interferometric methods, including InSAR (Interferometric Synthetic Aperture Radar) for measuring deformation changes in the Earth's surface.
LiDAR Sensors
LiDAR, or Light Detection and Ranging, is a form of active satellite telemetry technology. It involves the sending of laser pulses so as to measure distances from the sensor to objects on the ground.
LiDAR sensor generates laser pulses and estimates the time that passes before a signal reflects from an object to the sensor. Information collected this way can be transformed into three-dimensional data known as point clouds.
LiDAR technology can be used to measure the structure of various elements, including:
Buildings
Trees
Roads
Bridges
Ground
Power lines
Infrastructure
LiDAR Applications
LiDAR technology finds widespread applications, including:
Forestry
3D city modeling
Flood risk analysis
Corridor mapping
Power line inspection
Construction engineering
LiDAR is very important whenever there is a need for precise three-dimensional information about objects and terrain.
Atmospheric Sensors
Several of the sensors used for remote sensing have been specifically developed for the purpose of measuring the characteristics of the atmosphere.
These sensors include those capable of measuring gases, aerosols, clouds, atmospheric temperature, and other atmospheric parameters.
Atmospheric remote sensing can take advantage of several technological options to employ electromagnetic energy in the forms of visible, infrared, microwave, and many others.
Uses of Atmospheric Sensors
Atmospheric sensors support the following applications:
Air quality monitoring
Monitoring of greenhouse gases
Weather forecasting
Climate research
Detection of aerosol presence in the atmosphere
The study of the clouds that constitute part of the atmosphere
Research on atmospheric composition
Active vs. passive remote sensing sensors
Active sensors emit their own source of energy to the target and measure the reflected signal.
Some examples of active remote sensing instruments include:
LiDAR
Radar
SAR
Sonar
Advantages:
Works even without sunlight
Some devices can capture data even through clouds.
Gives information about the characteristics of the surface
Can be used for observations at night
Passive Sensors
Passive sensors use energy that is available naturally, including sun rays or thermal radiation.
Some examples of passive sensors are
RGB camera
Multispectral sensor
Hyperspectral sensor
Thermal sensor
Passive microwave sensor
Advantages:
They can provide good spectral information.
They can help in analyzing materials and vegetation.
They often provide images that are easier to see than others.
How to Choose the Right Remote Sensing Sensor
Choosing the appropriate sensor is based on the needs of the project. Key areas of consideration include:
Spatial Resolution
Spatial resolution indicates the degree of detail about the ground provided by each pixel.
Sensing instruments with high spatial resolution are suitable when mapping small items, buildings, highways, or even individual plants.
Spectral Resolution
Spectral resolution refers to how accurately a sensor can separate various wavelengths.
Generally, hyperspectral instruments give much better spectral resolution than ordinary multispectral sensors.
Temporal Resolution
Temporal resolution means how often the sensor can see the same place. High temporal resolution is significant when doing tasks such as crop monitoring, responding during disasters, or predicting the weather.
Radiometric Resolution
Radiometric resolution is a term that refers to the ability of a sensor to capture variations in energy strength.
Higher levels of this index are beneficial in detecting small differences in the readings.
Weather and Light Conditions
Optical sensors are also greatly affected by the presence of clouds and haze. On the other hand, radar and LiDAR have alternative capabilities under unfavorable weather conditions.
Project Cost and Scope
Satellite imagery is appropriate for large areas, whereas drones are great for local, high-resolution surveys.
Remote Sensing Sensors in GIS
Remote sensing refers to technology in the field of GIS. It is important to note that remote sensing sensors perform certain measurements, while GIS itself allows you to store, analyze, visualize, and integrate these measurements with other spatial data.
Remote sensing could be used in combination with the following datasets:
Vector layers
Digital Elevation Models
GPS/GNSS data
LiDAR point cloud
Road networks
Parcel boundaries
Land-use datasets
Field observations
This combination will make advanced studies possible.
Remote sensing technologies play an important role in acquiring data about different environments such as the surface of the planet, atmosphere, or the deep sea. Various sensor types yield different forms of information, so a proper choice of sensors is crucial when dealing with remote sensing.
For example, optical and multispectral sensors are normally applied to land maps or vegetation studies, and hyperspectral sensors gather information in terms of spectral features of materials. Thermal sensors are relied upon to monitor temperature, radar and SAR allow for active microwave monitoring, and LiDAR is capable of providing three-dimensional measurements.
Proper understanding of these sensor types allows GIS specialists, researchers, surveyors, and Earth observation experts to choose the most appropriate sensor technology for their applications.
As remote sensing technologies develop, it becomes more and more important to combine several types of sensors into one (multisensor or multimode remote sensing) in order to obtain more complete and accurate information.
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