Learning objectives of this topic
- Acquisition characteristics of passive remote sensing
- Need for passive remote sensing
- Passive remote sensing instruments
Daytime dependence
In this topic, we will introduce the first of the two different acquisition strategies that exist to monitor land surfaces across the globe. First, we will take a look at optical and microwave remote sensing techniques that make use of the radiation originating from the sun.
Generally, passive instruments do not send pulses at any wavelength themselves, but solely rely on naturally existent radiation. Unlike active systems, they are not capable of streamlining EM energy of their own to a given target on the Earth’s surface. Passive optical sensors can only acquire data during daytime. Without natural energy, there is nothing that can be reflected across the surface and consequently be ‘bounced’ back to the sensor. Atmospheric effects that affect the amount of daylight that reaches the ground also impact the quality of data acquired by passive sensors.
Types of passive remote sensing instruments
Most passively working sensors utilize multispectral or hyperspectral sensors. What does this mean?
Multispectral
Multispectral (MS) remote sensing instruments record data in multiple spectral bands. The first multispectral satellite in space was the Landsat’s Multispectral Scanner (MSS) back in the late 1970s. Recording in four spectral channels (blue, green, red, near-infrared), these data were of significant value for vegetation analysis in this time. State-of-the-art multispectral sensors like Sentinel-2 are the basis of exploring dynamics across the globe. With 13 spectral bands, high repetition rates and a spatial resolution of up to 10 m, the Sentinel fleet brought non-commercial remote sensing into a new era.
Hyperspectral
Hyperspectral systems outnumber the amount of spectral channels of MS sensors by factors of 10 or even more. The idea is to provide information in many more bands that cover a much smaller portion of the EM spectrum. This leads to more characteristic and distinct spectral responses that can be retrieved for land cover types or use classes. Hyperspectral sensors usually feature narrow bands with widths between 10 – 20 nm that are able to capture small spectral differences, which a multispectral instrument could not sense.
In the video below, more details of the concept of optical remote sensing systems are explained by Dr. Harm Bartholomeus from Wageningen University.
Passive microwave sensors
While commonly used optical sensors work passively, there are also microwave instruments that do not provide their own source of illumination. Most radar sensors are able to produce interpretable data independent of the time of day. This is not the case with passive microwave sensors, which use the naturally available microwave radiation (Earth’s emissions).
The underlying assumption, on which passive microwave remote sensing is based, is that every object that has a finite temperature is constantly radiating energy. This idea has to be true to fit the principle of thermal equilibrium.
As visualized in the figure above there a number of key sources of passive microwave signals that we can measure:
(1) atmospheric emissions,
(2) object emission (depending on surface temperature of a given object),
(3) surface-reflected component and
(4) transmitted subsurface component.
Need for passive microwave remote sensing
Passive remote sensing instruments are of great interest for the monitoring of essential parameters related to hydrologic modeling and observation such as soil moisture estimation, precipitation, ice water content or sea-surface temperature analysis.
Example application: Capturing dynamics in sea ice using the Advanced Microwave Scanning Radiometer 2 (AMSR2), which operates from aboard the Japanese ‘Shizuku’ GCOM-W1 satellite. The passive microwave instrument allows the daily observation of ice-related characteristics in ecosystems that are severely threatened.
List of passive instruments
Below, you can find two animations that present a selection of the most important remote sensing sensors that can be found in the passive remote sensing domain.
Optical sensors
Radar sensors
Sources & further reading
Adão, T., Hruška, J., Pádua, L., Bessa, J., Peres, E., Morais, R. & Sousa J.J. (2017). Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry.
Edmund Optics (2019). Hyperspectral and Multispectral Imaging. <https://www.edmundoptics.de/knowledge-center/application-notes/imaging/hyperspectral-and-multispectral-imaging/>
Elachi, C. & van Zyl, J. (2015²). Introduction to the Physics and Techniques of Remote Sensing. Hoboken, USA: John Wiley & Sons, Inc.
Active RS systems
Learning objectives of this topic
- Fundamental acquisition principles of microwave systems
- Variations of active bands and their use
- Important nomenclature
- Types of scattering and implications on the returned signal
Benefits of active Remote Sensing Systems
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What is an active Remote Sensing System?
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Benefits of active Remote Sensing Systems
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What is an active Remote Sensing System?
Radar satellites are active systems. Find out about their characteristics, and learn how they differ from passive systems.
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What does the term ‘SAR’ mean?
Radar images are very often referred to as SAR images. The acronym SAR stands for Synthetic Aperture Radar and describes an engineering method that is used to achieve higher resolution radar images. Learn how this aperture synthesis works in radar systems in this chapter.
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Radar Imaging geometry
Radar systems have a very unique way of making measurements. Microwave pulses are sent out towards the Earth’s surface and the echoes are recorded back at the sensor.
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Why does the radar need to look to a side?
A radar system primarily makes a measurement of time. The antenna sends out pulsed microwaves and detects the time it takes for the echoes from the target scene to return back to the antenna. If a radar sensor transmits this pulse straight down towards the nadir direction on a flat surface, the distance of all the targets on this surface to the radar antenna would be almost identical. Therefore, the echoes would mostly return simultaneously, and no differentiation of the signals could be made.
By adopting a side-looking geometry and transmitting the pulses obliquely, the radar system is able to resolve distinct targets on the ground by detecting a different time delay for each of the targets, since the time delay is then approximately correlated with distance along the ground (in the range direction).
The nomenclature
Before processing and interpreting radar data, it is important to understand the vocabulary that is used to describe the imaging process. This knowledge will be crucial to understanding what you see in a radar image and how the microwaves interact with the surface.
Nadir
Nadir describes the direction below a particular location. In the context of remote sensing, it refers to the point directly below the satellite/aircraft. To be more precise, it can be defined as the local vertical direction pointing toward the force of gravity at a particular location. The opposite direction to the nadir is the zenith.
Swath
The term ‘swath’ has its roots in farming. It describes the width of a scythe. This analogy has been transferred into remote sensing. In this context, the swath width describes the area (width) on the ground that is covered by the sensor instrument of a satellite or aircraft.
Azimuth
In the context of radar remote sensing, azimuth describes the flight direction or direction of travel of the satellite/aircraft. It can also be referred to as the line of flight.
In an image, azimuth is also known as along-track direction, since it is the relative along-track position of an object within the antenna’s field of view following the radar’s line of flight.
Range
The range direction is the distance between the radar and each illuminated target. It is the dimension of an image perpendicular to the line of flight (azimuth). In radar remote sensing, we differentiate slant range and ground range. Slant range is the distance from the radar toward each target and measured perpendicular to the line of flight. Ground range is the same distance, projected using a geometrical transformation onto a reference surface such as a map.
Incidence Angle
The incidence angle is the angle defined by the incident radar beam and the vertical (normal) to the intercepting surface. In general, reflectivity from distributed scatterers decreases with increasing incidence angle. The incidence angle changes across the radar image swath; it increases from near range to far range.
A change in incidence angle often affects the radar backscattering behaviour of a surface. In the case of satellite radar imagery, the change in the incidence angle for flat terrain across the imaging swath tends to be rather small, usually on the order of several degrees. In the case of an inclined surface, the local incidence angle is defined as the angle between the incident radar beam and a line that is normal to that surface (a vector perpendicular to the surface at a given point).
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Scattering mechanisms
Microwaves interact with objects on the ground. In fact, that is what we are trying to measure with our radar satellites, in order to distinguish the various materials and objects on the ground. To be able to do that and to fully understand the backscatter signal, we have to understand the various types of scattering that can occur on the Earth’s surface.
The concept of scattering mechanisms is at the heart of understanding the signals that are returned to the sensor, after the microwave pulses hit the Earth’s surface. Let’s go through them again to internalise them further. You will need to remember them for the various practical application scenarios in the upcoming lessons.
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The scattering mechanisms in more detail
Specular reflection
If the radar pulse hits a smooth, flat surface (on the scale of the wavelength), most of the energy is scattered away in a specular direction. These areas will appear very dark in the radar image. Typical examples for specular reflection are smooth water surfaces or tarmac (e.g. roads, parking lots).
Surface scattering
A single bounce, or surface scattering, appears when the microwave hits a somewhat rough, homogeneous surface. Parts of the energy are scattered back to the sensor. Which surface is rough and which isn’t is determined by the wavelength, the incidence angle and the spatial resolution of the system. These variables are also referred to as sensor parameters. We will learn more about these parameters in the following topics.
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Double bounce
Double bounce, or dihedral scattering, occurs when the radar pulse hits two relatively smooth surfaces that are perpendicular to each other. The returned signal is particularly strong, due to the multiple transmission of the energy back into the direction of the sensor.
Typical examples where double bounce occurs are buildings and other artificial structures.
Volume scattering
Volume scattering occurs if the radar pulse penetrates into a 3-dimensional body. The energy is scattered multiple times in multiple directions, before parts of it are returned to the sensor.
Classic examples of volume scattering include dry snow surfaces, tree canopies or vegetated fields.
Scatter models
Field scenario
City scenario
Snow scenario
Historic excourse: 30 years after the start of ERS-1, ESA’s first SAR sensor in space.
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Other sources of active imaging – LiDAR
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