A set of three engaging presentations has been recently released by ESA: an introduction to the Earth's magnetic field, why the magnetic field matters and Swarm satellites.
Definitely good educational resources!
The three Swarm mission satellites, namely Swarm A,B and C, follow a near-polar orbit.
Swarm A and B are circling the Earth side-by-side at an altitude of 450 km (LEO) decaying naturally to 300 km during the four years mission, while Swarm C orbit at an altitude of 530 Km (LEO).
This unique configuration enables a quicker sampling of the Earth and allows measurements that help us to distinguish between the effect of different source of magnetism.
Copyright: European Space Agency (ESA)
The magnitude-9 earthquake that hit Japan on March 11 2011 was felt by GOCE.
The earthquake produced infrasound, sound waves lower in frequency than the normal limit of human hearing, causing changes in air density detected by the satellite.
Copyright ESA/IRAP/CNES/TU Delft/HTG/Planetary Visions
Floods are usually accompanied by cloudy skies making it difficult to monitor them from space. Using radar technology, the new Copernicus Sentinel-1 satellite is able to 'see' through clouds and rainfall to map emergency-stricken regions.
Copyright ESA / DLR
SMOS (Soil Moisture and Ocean Salinity) was launched on November 2, 2009. This satellite is able to measure soil moisture and ocean salinity globally. SMOS has mapped Earth’s wet and dry soils, helping us to understand the water cycle and supporting water resource management. Global ocean salinity data from SMOS has given us new insight into how rivers and runoff from land are dispersed by ocean currents. Surpassing expectations, SMOS data are also being used to monitor Arctic sea ice extent and thickness, providing daily coverage of the Arctic Ocean. In addition, the satellite can track hurricanes, such as last year’s Hurricane Sandy that devastated parts of the US east coast.
The map, generated using SMOS data, shows the soil moisture values across central Europe on 31 May and 2 June 2013. The blues indicate wetter soils and the yellow and orange colours indicate dryer soils. For example, a value of 0.50 means that there is 500 litres of water in one cubic metre of soil. Heavy rainfall has led to disastrous flooding in Germany, Austria, the Czech Republic and Slovakia.
Replay of the Swarm liftoff on a Rockot launcher from the Plesetsk cosmodrome in northern Russia at 12:02 GMT (13:02 CET) on 22 November 2013.
The three-satellite Swarm mission aims to provide new information on the sources of the magnetic fieldinside Earth. This includes understanding how the magnetic field is related to the motion of molten iron in the outer core, how the conductivity of the mantle is related to its composition and how the crust has been magnetised over geological timescales.
It will also investigate how the magnetic field relates to Earth’s environment through the radiation beltsand their near-Earth effects, including the solar wind energy input into the upper atmosphere.
This ESA application tracks in real-time the position of the selected satellite and predicts when and where the satellite will be visible from the user's actual position.
This application is a remarkable tool for education, scientists and general public to get an insight into what the CryoSat mission is about.
The mission is described through a variety of materials (text, images, photos, videos and news). The content specific toolbar allows access to different supporting archives, the ESA Media Library and YouTube.
It provides information on the current satellite position relatively to the Earth and the user current geographical location.
The application allows also interactive inspection of the CryoSat 3D model, zooming in and out to highlight details. By selecting any of the sensors on the satellite payload, the user can display detailed technical characteristics.
Moreover it is possible to download selected satellite's products or get information on the altimetric data.
Copyright ESA / DLR
After 4 years and 8 months orbiting Earth, the GOCE mission came to an end on 11 November 2013.
Catastrophic events are widespread. Remote sensing found an important application in prevention, mitigation and management of natural disasters.
Given the limited accessibility to the affected areas, satellite data provide us appropriate knowledge of the region, allowing us to organize better prevention plans, through the assessment and determination of risk areas, and plans for implementation and management of quick and appropriate relief.
Sensors used in thermal remote sensing detect infrared radiation emitted from the Earth's surface considered as a blackbody. All materials at temperatures above Absolute zero (0 K, -273°C) continuously emit electromagnetic radiation. A blackbody spectrum is determined by the temperature alone. The Earth (surface temperature 300 K) has its emission peak in the infrared.
As optical systems, thermal systems may be distinguished according to the spectral sampling (multispectral and hyperspectral). The intensity of the thermal radiation emitted is lower than the intensity of the reflected solar radiation. The consequence is that the width of individual spectral bands is broader comparing with optical sensors.
Thermal infrared remote sensing is used for measurements of the Earth's land and sea surface temperature, for detection of forest fires and geological applications.
Active microwave sensors generate their own radiation in the microwave region of the electromagnetic spectrum. The emitted radiation is sent to the surface and then is reflected back and received by the sensor. SAR (Synthetic Aperture Radar), microwave scatterometer, radar altimeters are examples of active sensors.
Passive microwave sensors receive the microwave radiation emitted from the object. All objects emit very small amounts of microwave energy. Microwave radiometers and scanners are examples of passive sensors.
In optical remote sensing the source of energy is the Sun. The sensors measure the electromagnetic radiation reflected from the target in the following bands:
- Portion Visible (Reflective)
- Near Infrared (Reflective)
- Middle Infrared (Reflective)
- Far Infrared (Thermal, Emissive )
Optical systems may be distinguished according to the spectral sampling (number of spectral bands used in the process):
- Panchromatic: measured in one spectral band
- Multispectral: measured in 2-10 spectral bands
- Hyperspectral: measured in 10-200 typically contiguous spectral bands
The narrower the bands i.e. a smaller wavelength range, the more precise will be the survey. But in this way the instrument will collect less specific energy, increasing at the same time the "noise" associated with the information.
In the resultant image we are able to identify objects by their spectral signature, i.e. their response to the different wavelengths.
The solar radiation spectrum is an excellent approximation of a blackbody spectrum.
A blackbody is a theoretical object that absorbs all radiation incident upon it and radiates it as a continuous spectrum. A blackbody is at constant temperature and its spectrum is determined by the temperature alone. By temperature we mean the surface temperature. Hotter objects emit more total energy at all the wavelengths.
We have seen that the electromagnetic radiation travels from the Sun to the Earth (target) and then to the sensors trough the atmosphere. The atmospheric constituents cause absorption and scattering of radiation.
When you are comparing emission and absorption spectra you refer to the spectral lines generated by a transparent gas in the foreground of a blackbody. If the transparent gas is colder than the blackbody the lines will appear dark, i.e. absorption lines. If the transparent gas is warmer the lines will appear in emission.
Absorption reduces the solar radiation within the absorption bands of the gases. In remote sensing we want to minimize this effect, considering wavelength regions outside the main absorption bands of the gases in the atmosphere.
Applications of optical remote sensing include meteorology, oceanography, global vegetation monitoring, atmospheric composition, land cover and changes maps, disaster monitoring, cartography and hydrology. We will go soon trough practical examples.
Most commonly we refer to remote sensing as the imagery information obtained from sensors housed on satellite platforms .
Satellite sensors record the various waves emitted/reflected from/to the Earth's surface.
A sensor is a device that detects a signal and it is part of a data acquisition system. A signal is a form of energy and we can classify signals according to the energy they detect.
A sensor is a type of transducer ( it converts a signal in one form of energy to another form of energy). The output signal of the sensor may be described in terms of amplitude, frequency and phase.
So a sensor detects electromagnetic energy that travels through space at the speed of light.
The signal is in fact proportional to the electromagnetic energy that reaches the sensor. The sensors capture the reflected or emitted energy from the surface and convert it to an electrical signal. The radiation is reflected, absorbed and emitted in varying proportions depending on the characteristics of the surface and the wavelength. The atmosphere, as the energy travels through it, absorbs, distributes, and modifies both the incident radiation and the one directed towards the sensor.
We use the signal received by the sensor to manufacture images. Sensors are divided into:
- Imaging sensors (Scanning Radiometer, SLAR and SAR)
- Non-imaging sensors (radar altimeter, weather, atmospheric sounder)
We can get information measuring the emitted or reflected electromagnetic radiation of distant objects in certain bands (infrared, visible light, microwaves) of the electromagnetic spectrum.
The electromagnetic spectrum is the range of all possible frequencies of electromagnetic waves and is divided into seven regions (or bands) depending on the wavelength.
Digital sensors acquire these regions with different spectral, geometric, radiometric and temporal resolutions.
- Spectral resolution - the number of bands detected and their width: the greater the number of bands, the lower their width, the greater will be the ability to identify objects according to the proportion of incident light that a given surface is able to reflect .
- Geometric resolution: the minimum area on the ground that an instrument can view from a given height at a given time and is represented by the size of the surface element recognizable in a recorded image.
- Temporal resolution: the time period between two successive shots of the same area.
- Radiometric resolution: the minimum signal difference that the sensor is able to distinguish (i.e. How sensitive is the sensor in recording small differences in reflected or emitted energy).
There are passive and active remote sensing sensors. A passive instrument is one that detects electromagnetic radiation reflected or emitted from natural sources (the Sun is an example). Signal logging occurs only when the Sun illuminates the Earth.
Active sensors emit radiation directed towards the object (LIDAR, RADAR). The sensor record and measure the radiation reflected from the object.
We gather information from sensors mounted on orbiting satellites. The digital data acquired by satellites are transmitted to ground stations. These digital data, once processed, will give us images.
We can classify the satellite imaging systems according to the spectral regions used in data acquisition systems:
- Ultraviolet and Visible
- Visible and Reflective Infrared
- Thermal Infrared
The sensor, as we have seen, measure the electromagnetic radiation reflected or emitted in certain bands of the electromagnetic spectrum. On an image these bands are displayed using the primary colors (red, green, blue) so that people can look at them.
The digital images resulting from the sensing process are records of the amount of light that stroke the sensor. Data transmitted to the ground are affected by errors of various types.
A digital image is made up of pixels (picture elements). In our context a pixel represents the smallest discernible area element on the Earth's surface and it can be addressed by its physical coordinates. The location of each pixel must be identified exactly. Geometric errors (i.e. errors due to the rotation of the Earth, to track movement simultaneously on the ground during a cycle of satellite observation, etc...) do not allow the exact identification of that position. These errors are compensated by suitable computerized correction programs.
A pixel has also an intensity value, the average measured quantity (reflected, emitted and scattered electromagnetic radiation). This value is stored as a digital number.
Coded numbers about a generic pixel are not always properly relevant energy levels at various wavelengths, due to the radiometric errors. A cause of error is the spread of radiant energy in the atmosphere, which decreases the contrast of images. This error is correct trough a procedure known as removal of haze.
The second most common cause of error is due to the radiometric sensors. The "answer" of the instrument may be different in spite of equal reflectance levels. By reflectance we mean the incident light that a surface is able to reflect. The data that they provide must therefore be calibrated at each detection cycle.